BACKGROUND: Maternal exposure to air pollution during pregnancy is associated with adverse birth outcomes, although less is known for wildfire smoke. This systematic review evaluated the association between maternal exposure to wildfire smoke during pregnancy and the risk of perinatal, obstetric, and early childhood health outcomes. METHODS: We searched CINAHL Complete, Ovid/EMBASE, Ovid/MEDLINE, ProQuest, PubMed, Scopus, Web of Science, and Google Scholar to identify relevant epidemiological observational studies indexed through September 2023. The screening of titles, abstracts, and full-texts, data extraction, and risk of bias assessment was performed by pairs of independent reviewers. RESULTS: Our systematic search yielded 28,549 records. After duplicate removal, we screened 14,009 studies, identifying 31 for inclusion in the present review. Data extraction highlighted high methodological heterogeneity between studies, including a lack of geographic variation. Approximately 56.5% and 16% originated in the United States and Brazil, respectively, and fewer in other countries. Among the studies, wildfire smoke exposure during pregnancy was assessed using distance of residence from wildfire-affected areas (n = 15), measurement of air pollutant concentration during wildfires (n = 11), number of wildfire records (n = 3), aerosol index (n = 1), and geographic hot spots (n = 1). Pooled meta-analysis for birthweight and low birthweight were inconclusive, likely due to low number of methodologically homogenous studies. However, the reviewed studies provided suggestive evidence for an increased risk of birthweight reduction, low birthweight, preterm birth, and other adverse health outcomes. CONCLUSIONS: This review identified 31 studies evaluating the impacts of maternal wildfire smoke exposure on maternal, infant, and child health. Although we found suggestive evidence of harm from exposure to wildfire smoke during pregnancy, more methodologically homogenous studies are required to enable future meta-analysis with greater statistical power to more accurately evaluate the association between maternal wildfire smoke and adverse birth outcomes and other health outcomes.
China is now confronting the intertwined challenges of air pollution and climate change. Given the high synergies between air pollution abatement and climate change mitigation, the Chinese government is actively promoting synergetic control of these two issues. The Synergetic Roadmap project was launched in 2021 to track and analyze the progress of synergetic control in China by developing and monitoring key indicators. The Synergetic Roadmap 2022 report is the first annual update, featuring 20 indicators across five aspects: synergetic governance system and practices, progress in structural transition, air pollution and associated weather-climate interactions, sources, sinks, and mitigation pathway of atmospheric composition, and health impacts and benefits of coordinated control. Compared to the comprehensive review presented in the 2021 report, the Synergetic Roadmap 2022 report places particular emphasis on progress in 2021 with highlights on actions in key sectors and the relevant milestones. These milestones include the proportion of non-fossil power generation capacity surpassing coal-fired capacity for the first time, a decline in the production of crude steel and cement after years of growth, and the surging penetration of electric vehicles. Additionally, in 2022, China issued the first national policy that synergizes abatements of pollution and carbon emissions, marking a new era for China’s pollution-carbon co-control. These changes highlight China’s efforts to reshape its energy, economic, and transportation structures to meet the demand for synergetic control and sustainable development. Consequently, the country has witnessed a slowdown in carbon emission growth, improved air quality, and increased health benefits in recent years.
This article presents the initiation and implementation of a systematic scientific and political cooperation in the Arctic related to environmental pollution and climate change, with a special focus on the role of the Arctic Monitoring and Assessment Programme (AMAP). The AMAP initiative has coordinated monitoring and assessments of environmental pollution across countries and parameters for the entire Arctic region. Starting from a first scientific assessment in 1998, AMAP’s work has been fundamental in recognizing, understanding and addressing environmental and human health issues in the Arctic, including those of persistent organic pollutants (POPs), mercury, radioactivity, oil, acidification and climate change. These scientific results have contributed at local and international levels to define and take measures towards reducing the pollution not only in the Arctic, but of the whole globe, especially the contaminant exposure of indigenous and local communities with a traditional lifestyle. The results related to climate change have documented the rapid changes in the Arctic and the strong feedback between the Arctic and the rest of the world. The lessons learned from the work in the Arctic can be beneficial for other regions where contaminants may accumulate and affect local and indigenous peoples living in a traditional way, e.g. in the Himalayas. Global cooperation is indispensable in reducing the long -range transported pollution in the Arctic.(c) 2023 The Authors. Published by Elsevier B.V. on behalf of Chinese Society for Environmental Sciences, Harbin Institute of Technology, Chinese Research Academy of Environmental Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
A case-crossover study among 511,767 cardiovascular disease (CVD) deaths in Jiangsu province, China, during 2015-2021 was conducted to assess the association of exposure to ambient ozone (O(3)) and heat wave with CVD mortality and explore their possible interactions. Heat wave was defined as extreme high temperature for at least two consecutive days. Grid-level heat waves were defined by multiple combinations of apparent temperature thresholds and durations. Residential O(3) and heat wave exposures were assessed using grid data sets (spatial resolution: 1 km × 1 km for O(3); 0.0625° × 0.0625° for heat wave). Conditional logistic regression models were applied for exposure-response analyses and evaluation of additive interactions. Under different heat wave definitions, the odds ratios (ORs) of CVD mortality associated with medium-level and high-level O(3) exposures ranged from 1.029 to 1.107 compared with low-level O(3), while the ORs for heat wave exposure ranged from 1.14 to 1.65. Significant synergistic effects on CVD mortality were observed for the O(3) and heat wave exposures, which were generally greater with higher levels of the O(3) exposure, higher temperature thresholds, and longer durations of heat wave exposure. Up to 5.8% of the CVD deaths were attributable to O(3) and heat wave. Women and older adults were more vulnerable to the exposure to O(3) and heat wave exposure. Exposure to both O(3) and heat wave was significantly associated with an increased odds of CVD mortality, and O(3) and heat wave can interact synergistically to trigger CVD deaths.
The global temperature has been increasing resulting in climate change. This negatively impacts planetary health that disproportionately affects the most vulnerable among us, especially children. Extreme weather events, such as hurricanes, tornadoes, wildfires, flooding, and heatwaves, are becoming more frequent and severe, posing a significant threat to our patients’ health, safety, and security. Concurrently, shifts in environmental exposures, including air pollution, allergens, pathogenic vectors, and microplastics, further exacerbate the risks faced by children. In this paper, we provide an overview of pediatric illnesses that are becoming more prevalent and severe because of extreme weather events, global temperature increases, and shifts in environmental exposures. As members of pediatric health care teams, it is crucial for pediatric radiologists to be knowledgeable about the impacts of climate change on our patients, and continue to advocate for safe, healthier environments for our patients.
PURPOSE OF REVIEW: The upper and lower airways are inter-related despite serving different functions and can no longer be considered separately. Rhinologists are becoming increasingly aware of the role the lower airway plays in optimizing outcomes for their patients. This review highlights recent developments in pulmonology that impact rhinologic conditions. RECENT FINDINGS: The unified airway concept now supports the multidisciplinary management of respiratory and rhinologic pathologies. Biomarkers, biologics and the concept of treatable traits have permitted the development of personalized and precise treatment of the entire respiratory tract. The concept of corticosteroid stewardship, the introduction of steroid sparing agents for the treatment of respiratory diseases and the development of biomarkers, now forces us to be more considerate and precise with oral corticosteroid (OCS) prescribing and to consider reduction regimens. Finally, current research on climate change and vaping will allow us to better educate and prepare our patients to improve adherence and avoid exacerbations to maintain optimal global respiratory health. SUMMARY: The inter-relatedness of the upper and lower airway has encouraged a multidisciplinary focus in respiratory medicine. More research is required to improve the precision respiratory medicine model, particularly in the realm of biomarkers and endotyping. These developments must also consider the impact of climate change, pollution and toxins for us to provide optimum care for our patients.
As wildfire activity continues to increase throughout much of the western US, questions remain about how to effectively communicate wildfire smoke risk to harder-to-reach groups, including rural populations. Standard public health strategies rely largely on risk assessment and communication informed by available air quality data. However, rural populations can be difficult to reach through traditional communication channels and air quality monitoring to inform messaging can be absent or scarce. As efforts increase to expand air quality monitoring into rural regions, there is a need to identify and affirm the most effective content and communication channels for motivating protective action. We used a mental models approach to identify wildfire smoke risk information needs and preferred communication channels in three rural counties in northern Nevada. Participants revealed a substantial knowledge base with opportunities for enhancement related to the range of potential physical and mental health impacts, vulnerable groups, and exposure mitigation strategies. Preferred communication channels were varied but almost exclusively local. The mental models approach also uncovered important barriers to exposure mitigation as well as potential areas of future research. Insights gained from this study will be used to inform targeted wildfire smoke risk communication for rural Nevada counties and may serve to motivate similar studies in other rural regions. Identifying similarities and differences in information needs and preferred communication channels can help inform understanding of how and why to tailor wildfire smoke risk communication. Any new messaging developed from such studies should be evaluated to ensure its effectiveness.
Climate change may affect the quality of the indoor environment through heat and mass transfer between indoors and outdoors: first by a direct response to global warming itself and related extreme weather phenomena and second by indirect actions taken to reduce greenhouse gas emissions that can lead to increased concentrations of indoor air contaminants. Therefore, both indoor and outdoor air pollution contribute to poor indoor air quality in this context. Exposures to high concentrations of these pollutants contribute to inflammatory respiratory diseases. Climate change adaptation and mitigation measures could minimize these risks and bring associated health benefits.
There is mounting evidence that climate change is having a significant influence on exacerbations of airway disease. We herein explore the physical factors of carbon dioxide, temperature increases, and humidity on intensifying allergen and fungal growth, and worsening air quality. The direct influence of these factors on promoting allergic rhinitis, chronic rhinosinusitis, and allergic fungal rhinosinusitis is reviewed.
We review current knowledge on the trends and drivers of global wildfire activity, advances in the measurement of wildfire smoke exposure, and evidence on the health effects of this exposure. We describe methodological issues in estimating the causal effects of wildfire smoke exposures on health and quantify their importance, emphasizing the role of nonlinear and lagged effects. We conduct a systematic review and meta-analysis of the health effects of wildfire smoke exposure, finding positive impacts on all-cause mortality and respiratory hospitalizations but less consistent evidence on cardiovascular morbidity. We conclude by highlighting priority areas for future research, including leveraging recently developed spatially and temporally resolved wildfire-specific ambient air pollution data to improve estimates of the health effects of wildfire smoke exposure.
Few studies have delved into the effects of heatwaves on sleep duration loss among older adults. Our study examined correlations between heatwave exposure and sleep duration reductions in this demographic. Utilizing data of 7,240 older adults drawn from the China Health and Retirement Longitudinal Study (CHARLS) from 2015 to 2018, we assessed sleep duration differences between the baseline year (2015) and follow-up year (2018). Absolute reductions in sleep duration were defined as differences of ≥ 1, 1.5, or 2 h. Changes in sleep duration were categorized based on cut-offs of 5 and 8 h, including excessive decrease, moderate to short and persistent short sleep duration types. 12 heatwave definitions combining four thresholds (90th, 92.5th, 95th, and 97.5th percentiles of daily minimum temperature) and three durations (≥2, ≥3 and ≥ 4 days) were used. Heatwave exposure was determined by the difference in the number of 12 preceding months’ heatwave days or events in 2015 and the number of 12 preceding months’ heatwave days or events in 2018. The results showed that increased heatwave events (defined as ≥ P90th percentile & lasting three days) were associated with a higher likelihood of ≥ 1-hour sleep reduction and persistent short sleep duration. An increase in heatwave event (defined as ≥ P95th percentile & lasting three days) was linked to shifts from moderate to short sleep duration. For the association between an absolute reduction in sleep duration and heatwave exposure, while higher thresholds signified greater sleep reduction risks, the effect estimates of longer durations were not uniformly consistent. We observed that air pollution and green space modified the relationship between heatwaves and sleep duration. Females, urban residents, and individuals with chronic diseases were identified as vulnerable populations. This study found that increased heatwave exposure was associated with a higher risk of sleep duration loss in older adults.
Understanding the spatiotemporal distribution and behavior of Polycyclic Aromatic Hydrocarbons (PAHs) in the context of climate change and human activities is essential for effective environmental management and public health protection. This study utilized an integrated simulation system that combines land-use, hydrological, and multimedia fugacity models to predict the concentrations, transportation, and degradation of 16 priority-controlled PAHs across six environmental compartments (air, water, soil, sediment, vegetation, and impermeable surfaces) within one of the world’s prominent urban agglomerations, the Yangtze River Delta Urban Agglomeration (YRDUA), under future Shared Socio-economic Pathways (SSP)-Representative Concentration Pathways (RCP) scenarios. Incremental lifetime carcinogenic risk for adults and children exposed to PAHs were also evaluated. The results show a declining trend in PAHs concentrations and associated health risks during the 21st century. Land use types, hydrological characteristics, population, and GDP, have significant correlations with the fate of PAHs. The primary removal for PAHs is determined to be driven by advection through air and water. PAHs covering on impermeable surfaces pose a relatively higher health risk compared to those in other environmental media. This study offers valuable insights into PAHs pollution in the YRDUA, aiming to ensure public health safety, with the potential for application in other urban areas.
Wildland fire smoke risks are not uniformly distributed across people and places, and the most vulnerable communities are often disproportionately impacted. This study develops a county level community health vulnerability index (CHVI) for the Contiguous United States (CONUS) using three major vulnerability components: adaptive capacity, sensitivity, and exposure at the national and regional level. We first calculated sensitivity and adaptive capacity sub-indices using nine sensitivity and twenty adaptive capacity variables. These sub-indices were then combined with an exposure sub-index, which is based on the Community Multiscale Air Quality data (2008-2018), to develop CHVI. Finally, we conducted several analyses with the derived indices to: 1) explore associations between the level of fine particulate matter from wildland fires (fire-PM(2.5)) and the sub-indices/CHVI; 2) measure the impact of fire-PM(2.5) on the increase in the annual number of days with 12-35 μg/m(3) (moderate) and >35 μg/m(3) (at or above unhealthy for sensitive groups) based on the US EPA Air Quality Index categories, and 3) calculate population size in different deciles of the sub-indices/CHVI. This study has three main findings. First, we showed that the counties with higher daily fire-PM(2.5) concentration tend to have lower adaptive capacity and higher sensitivity and vulnerability. Relatedly, the counties at high risk tended to experience a greater increase in the annual number of days with 12-35 μg/m(3) and >35 μg/m(3) than their counterparts. Second, we found that 16.1, 12.0, and 17.6 million people out of 332 million in CONUS reside in the counties in the lowest adaptive capacity decile, highest sensitivity decile, and highest vulnerability decile, respectively. Third, we identified that the US Northwest, California, and Southern regions tended to have higher vulnerability than others. Accurately identifying a community’s vulnerability to wildfire smoke can help individuals, researchers, and policymakers better understand, prepare for, and respond to future wildland fire events.
Airborne microorganisms and biological matter (bioaerosols) play a key role in global biogeochemical cycling, human and crop health trends, and climate patterns. Their presence in the atmosphere is controlled by three main stages: emission, transport, and deposition. Aerial survival rates of bioaerosols are increased through adaptations such as ultra-violet radiation and desiccation resistance or association with particulate matter. Current research into modern concerns such as climate change, global gene transfer, and pathogenicity often neglects to consider atmospheric involvement. This comprehensive review outlines the transpiring of bioaerosols across taxa in the atmosphere, with significant focus on their interactions with environmental elements including abiotic factors (e.g., atmospheric composition, water cycle, and pollution) and events (e.g., dust storms, hurricanes, and wildfires). The aim of this review is to increase understanding and shed light on needed research regarding the interplay between global atmospheric phenomena and the aeromicrobiome. The abundantly documented bacteria and fungi are discussed in context of their cycling and human health impacts. Gaps in knowledge regarding airborne viral community, the challenges and importance of studying their composition, concentrations and survival in the air are addressed, along with understudied plant pathogenic oomycetes, and archaea cycling. Key methodologies in sampling, collection, and processing are described to provide an up-to-date picture of ameliorations in the field. We propose optimization to microbiological methods, commonly used in soil and water analysis, that adjust them to the context of aerobiology, along with other directions towards novel and necessary advancements. This review offers new perspectives into aeromicrobiology and calls for advancements in global-scale bioremediation, insights into ecology, climate change impacts, and pathogenicity transmittance.
Exposure to pollen and fungal spores can trigger asthma/allergic symptoms and affect health. Rising temperatures from climate change have been associated with earlier seasons and increasing intensity for some pollen, with weaker evidence for fungal spores. It is unclear whether climate change has resulted in changes in the exposure-response function between temperature and pollen/fungal spore concentrations over time. This study examined associations between temperature and pollen/fungal spores in different time periods and assessed potential adaptation using the longest pollen/fungal spore dataset in existence (52 years). Daily concentrations of pollen (birch and grass) and fungal spores (Cladosporium, Alternaria, Sporobolomyces and Tilletiopsis) collected between April and October from Derby (1970-2005) and Leicester (2006-2021), UK, were analysed. Cumulative seasonal concentrations (seasonal integral) and start-of-season were calculated and linked to seasonal mean temperatures (Tmeans) using generalized additive models. Daily concentrations were evaluated against daily Tmean with distributed lagged nonlinear models. Models were adjusted for precipitation, relative humidity, long-term trend and location. Seasonal and daily analyses were respectively stratified into two periods (1970-1995, 1997-2021) and five decades. Warmer seasonal Tmeans were associated with higher seasonal integral for birch, Cladosporium and Alternaria, as well as earlier start-of-season for birch, grass and Cladosporium. There were indications of changing associations with temperature in the recent decades. A warmer January was associated with higher seasonal integral for grass in 1997-2021, but not in 1970-1995. In 2000-2021, daily concentrations of birch pollen tended to remain at higher levels, vs. decrease during 1990s, when Tmean was between 13 and 15 °C. Our study suggests higher temperatures experienced in recent decades are associated with higher overall abundance of some pollen/fungal spores, which may increase future disease burdens of allergies. The changing responses of some pollen to higher temperatures over time may indicate adaptation to increasing temperatures and should be considered in climate change mitigation and adaptation planning.
PURPOSE OF REVIEW: The consequences of climate change, including heat and extreme weather events impact kidney function in adults and children. The impacts of climate change on kidney development during gestation and thereby on kidney function later in life have been poorly described. Clinical evidence is summarized to highlight possible associations between climate change and nephron mass. RECENT FINDINGS: Pregnant women are vulnerable to the effects of climate change, being less able to thermoregulate, more sensitive to the effects of dehydration, and more susceptible to infections. Exposure to heat, wildfire smoke, drought, floods and climate-related infections are associated with low birth weight, preterm birth and preeclampsia. These factors are associated with reduced nephron numbers, kidney dysfunction and higher blood pressures in offspring in later life. Exposure to air pollution is associated with higher blood pressures in children and has variable effects on estimated glomerular filtration rate. SUMMARY: Climate change has important impacts on pregnant women and their unborn children. Being born too small or too soon is associated with life-time risk of kidney disease. Climate change may therefore have a dual effect of impacting fetal kidney development and contributing to cumulative postnatal kidney injury. The impact on population kidney health of future generations may be significant.
PURPOSE OF REVIEW: The purpose of this review is to summarize the current literature regarding youth suicidality (suicidal ideation, suicidal behavior, and completed suicide) in the context of disasters. RECENT FINDINGS: There are fewer studies that examine the effect of disasters on suicidality specifically in children and youth than studies that focus on adults or general population. Numerous studies have reported on the effect of disasters on youth mental health in general without zeroing in on suicide risk. Some variables that have shown to increase suicide risk in children and youth after disasters include female gender, age at the time of disaster exposure, dependence on adults, attachments to places and caregivers, family functioning, and vulnerability to mistreatment. Several studies have demonstrated that youth suicidality fluctuates in response to disasters, at times increasing immediately post-disaster and at other times decreasing immediately post-disaster followed by an increase later. Exposure to natural disasters (e.g., earthquakes, typhoons, hurricanes, wildfires, and extremes of temperature and humidity), man-made disasters (e.g., armed conflict, global warming, and pollution), and unique disasters (e.g., the COVID-19 pandemic) have had significant impact on suicidality in children and adolescents. Although there are several promising interventions to mitigate the post-disaster suicide risk among youth, there is no consensus on a single intervention that is superior to others. More research is needed to study youth suicide risk in the context of disasters and develop culturally appropriate and evidence-based interventions.
In Canada, Indigenous populations are disproportionately threatened by wildfire smoke and the associated adverse health impacts. This paper presents the results of a narrative review of 51 academic and related resources which explored protective action decision making during wildfire smoke events within Indigenous communities in Canada. A search of scholarly articles and other relevant sources yielded resources which were subject to thematic analysis and described in order to present a narrative review of current knowledge and gaps in research. A small and growing literature provides insights into protective actions taken by the general population during wildfire smoke events, but very little is known about protective actions taken by Indigenous peoples in Canada during wildfire smoke events. This lack of understanding hinders the capacity of decision makers to improve emergency management and minimize community health impacts of wildfire smoke.
Wildfire smoke is associated with short-term respiratory outcomes including asthma exacerbation in children. As investigations into developmental wildfire smoke exposure on children’s longer-term respiratory health are sparse, we investigated associations between developmental wildfire smoke exposure and first use of respiratory medications. Prescription claims from IBM MarketScan Commercial Claims and Encounters database were linked with wildfire smoke plume data from NASA satellites based on Metropolitan Statistical Area (MSA). A retrospective cohort of live infants (2010-2016) born into MSAs in six western states (U.S.A.), having prescription insurance, and whose birthdate was estimable from claims data was constructed (N = 184,703); of these, gestational age was estimated for 113,154 infants. The residential MSA, gestational age, and birthdate were used to estimate average weekly smoke exposure days (smoke-day) for each developmental period: three trimesters, and two sequential 12-week periods post-birth. Medications treating respiratory tract inflammation were classified using active ingredient and mode of administration into three categories:: ‘upper respiratory’, ‘lower respiratory’, ‘systemic anti-inflammatory’. To evaluate associations between wildfire smoke exposure and medication usage, Cox models associating smoke-days with first observed prescription of each medication category were adjusted for infant sex, birth-season, and birthyear with a random intercept for MSA. Smoke exposure during postnatal periods was associated with earlier first use of upper respiratory medications (1-12 weeks: hazard ratio (HR) = 1.094 per 1-day increase in average weekly smoke-day, 95%CI: (1.005,1.191); 13-24 weeks: HR = 1.108, 95%CI: (1.016,1.209)). Protective associations were observed during gestational windows for both lower respiratory and systemic anti-inflammatory medications; it is possible that these associations may be a consequence of live-birth bias. These findings suggest wildfire smoke exposure during early postnatal developmental periods impact subsequent early life respiratory health.
OBJECTIVE: To evaluate the association of short-term exposure to overall fine particulate matter of <2.5 μm (PM(2.5) ) and wildfire-specific PM(2.5) with emergency department (ED) visits for headache. Studies have reported associations between PM(2.5) exposure and headache risk. As climate change drives longer and more intense wildfire seasons, wildfire PM(2.5) may contribute to more frequent headaches. METHODS: Our study included adult Californian members (aged ≥18 years) of a large de-identified commercial and Medicare Advantage claims database from 2006 to 2020. We identified ED visits for primary headache disorders (subtypes: tension-type headache, migraine headache, cluster headache, and "other" primary headache). Claims included member age, sex, and residential zip code. We linked daily overall and wildfire-specific PM(2.5) to residential zip code and conducted a time-stratified case-crossover analysis considering 7-day average PM(2.5) concentrations, first for primary headache disorders combined, and then by headache subtype. RESULTS: Among 9898 unique individuals we identified 13,623 ED encounters for primary headache disorders. Migraine was the most frequently diagnosed headache (N = 5534/13,623 [47.6%]) followed by "other" primary headache (N = 6489/13,623 [40.6%]). For all primary headache ED diagnoses, we observed an association of 7-day average wildfire PM(2.5) (odds ratio [OR] 1.17, 95% confidence interval [CI] 0.95-1.44 per 10 μg/m(3) increase) and by subtype we observed increased odds of ED visits associated with 7-day average wildfire PM(2.5) for tension-type headache (OR 1.42, 95% CI 0.91-2.22), "other" primary headache (OR 1.40, 95% CI 0.96-2.05), and cluster headache (OR 1.29, 95% CI 0.71-2.35), although these findings were not statistically significant under traditional null hypothesis testing. Overall PM(2.5) was associated with tension-type headache (OR 1.29, 95% CI 1.03-1.62), but not migraine, cluster, or "other" primary headaches. CONCLUSIONS: Although imprecise, these results suggest short-term wildfire PM(2.5) exposure may be associated with ED visits for headache. Patients, healthcare providers, and systems may need to respond to increased headache-related healthcare needs in the wake of wildfires and on poor air quality days.
Wildfires are increasing in prevalence in western North America due to changing climate conditions. A growing number of studies examine the impact of wildfire smoke on morbidity; however, few evaluate these impacts using syndromic surveillance data that cover many emergency departments (EDs). We used syndromic surveillance data to explore the effect of wildfire smoke exposure on all-cause respiratory and cardiovascular ED visits in Washington state. Using a time-stratified case crossover design, we observed an increased odds of asthma visits immediately after and in all five days following initial exposure (lag 0 OR: 1.13; 95% CI: 1.10, 1.17; lag 1-5 ORs all 1.05 or greater with a lower CI of 1.02 or higher), and an increased odds of respiratory visits in all five days following initial exposure (lag 1 OR: 1.02; 95% CI: 1.00, 1.03; lag 2-5 ORs and lower CIs were all at least as large) comparing wildfire smoke to non-wildfire smoke days. We observed mixed results for cardiovascular visits, with evidence of increased odds emerging only several days following initial exposure. We also found increased odds across all visit categories for a 10 μg m(-3) increase in smoke-impacted PM(2.5). In stratified analyses, we observed elevated odds for respiratory visits among ages 19-64, for asthma visits among ages 5-64, and mixed risk estimates for cardiovascular visits by age group. This study provides evidence of an increased risk of respiratory ED visits immediately following initial wildfire smoke exposure, and increased risk of cardiovascular ED visits several days following initial exposure. These increased risks are seen particularly among children and younger to middle-aged adults.
Exposure to fine particles in wildfire smoke is deleterious for human health and can increase cases of cardio-respiratory illnesses and related hospitalizations. Neighborhood-level risk factors can increase susceptibility to environmental hazards, such as air pollution from smoke, and the same exposure can lead to different health effects across populations. While the San Diego-Tijuana border can be exposed to the same wildfire smoke event, socio-demographic differences may drive differential effects on population health. We used the October 2007 wildfires, one the most devastating wildfire events in Southern California that brought smoke to the entire region, as a natural experiment to understand the differential effect of wildfire smoke on both sides of the border. We applied synthetic control methods to evaluate the effects of wildfire smoke on cardio-respiratory hospitalizations in the Municipality of Tijuana and San Diego County separately. During the study period (October 11th- October 26th, 2007), 2009 hospital admissions for cardio-respiratory diseases occurred in San Diego County while 37 hospital admissions were reported in the Municipality of Tijuana. The number of cases in Tijuana was much lower than San Diego, and a precise effect of wildfire smoke was detected in San Diego but not in Tijuana. However, social drivers can increase susceptibility to environmental hazards; the poverty rate in Tijuana is more than three times that of San Diego. Socio-demographics are important in modulating the effects of wildfire smoke and can be potentially useful in developing a concerted regional effort to protect populations on both sides of the border from the adverse health effects of wildfire smoke.
OBJECTIVES: This study aimed to evaluate the performance of a low-cost smoke sampling platform relative to environmental and occupational exposure monitoring methods in a rural agricultural region in central Washington state. METHODS: We co-located the Thingy AQ sampling platform alongside cyclone-based gravimetric samplers, a nephelometer, and an environmental beta attenuation mass (E-BAM) monitor during August and September of 2020. Ambient particulate matter concentrations were collected during a smoke and non-smoke period and measurements were compared across sampling methods. RESULTS: We found reasonable agreement between observations from two particle sensors within the Thingy AQ platform and the nephelometer and E-BAM measurements throughout the study period, though the measurement range of the sensors was greater during the smoke period compared to the non-smoke period. Occupational gravimetric sampling methods did not correlate with PM(2.5) data collected during smoke periods, likely due to their capture of larger particle sizes than those typically measured by PM(2.5) ambient air quality instruments during wildfire events. CONCLUSION: Data collected before and during an intense wildfire smoke episode in September 2020 indicated that the low-cost smoke sampling platform provides a strategy to increase access to real-time air quality information in rural areas where regulatory monitoring networks are sparse if sensor performance characteristics under wildfire smoke conditions are understood. Improving access to spatially resolved air quality information could help agricultural employers protect both worker and crop health as wildfire smoke exposure increases due to the impacts of climate change. Such information can also assist employers with meeting new workplace wildfire smoke health and safety rules.
Pacific Northwest wildfires are expected to increase in frequency and scale, with more communities exposed to smoke. We explored the environmental justice context for wildfire smoke impact to young children in urban communities in the Pacific Northwest with a focus on Seattle, Washington. We found substantial evidence that young children are vulnerable during wildfire smoke events due to a residential building stock that was primarily built before meaningful energy codes were enacted, along with low air conditioning rates; both contribute to a high transfer of air pollutants indoors from the outdoor environment. While our results are limited to PM2.5, we suggest that preventing injustices at child care settings during wildfire smoke events depends primarily on access to real-time information, use of that information to reduce exposure, and the strategies used by policy actors to make these adaptation options available and affordable for vulnerable communities. To date, adaptation during wildfire smoke events relies on voluntary efforts which may not be effective public health remedies in general, and particularly for vulnerable communities. Licensed child care settings could provide feasible and just risk management options for urban communities in the Pacific Northwest.
Globally, wildfires have seen remarkable increase in duration and size and have become a health hazard. In addition to vegetation and habitat destruction, rapid release of smoke, dust and gaseous pollutants in the atmosphere contributes to its short and long-term detrimental effects. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has emerged as a public health concern worldwide that primarily target lungs and respiratory tract, akin to air pollutants. Studies from our lab and others have demonstrated association between air pollution and COVID-19 infection and mortality rates. However, current knowledge on the impact of wildfire-mediated sudden outburst of air pollutants on COVID-19 is limited. In this study, we examined the association of air pollutants and COVID-19 during wildfires burned during August-October 2020 in California, United States. We observed an increase in the tropospheric pollutants including aerosols (particulate matter [PM]), carbon monoxide (CO) and nitrogen dioxide (NO(2)) by approximately 150%, 100% and 20%, respectively, in 2020 compared to the 2019. Except ozone (O(3)), similar proportion of increment was noticed during the peak wildfire period (August 16 – September 15, 2020) in the ground PM(2.5), CO, and NO(2) levels at Fresno, Los Angeles, Sacramento, San Diego and San Francisco, cities with largest active wildfire area. We identified three different spikes in the concentrations of PM(2.5), and CO for the cities examined clearly suggesting wildfire-induced surge in air pollution. Fresno and Sacramento showed increment in the ground PM(2.5), CO and NO(2) levels, while San Diego recorded highest change rate in NO(2) levels. Interestingly, we observed a similar pattern of higher COVID-19 cases and mortalities in the cities with adverse air pollution caused by wildfires. These findings provide a logical rationale to strategize public health policies for future impact of COVID-19 on humans residing in geographic locations susceptible to sudden increase in local air pollution.
BACKGROUND: Wildfire-related fine particulate matter (PM(2.5)) has many adverse health impacts, but its impacts on human epigenome are unknown. We aimed to evaluate the associations between long-term exposure to wildfire-related PM(2.5) and blood DNA methylation, and whether the associations differ from those with non-wildfire-related PM(2.5). METHODS: We studied 479 Australian women comprising 132 twin pairs and 215 of their sisters. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on 3-year (year of blood collection and previous two years) average wildfire-related and non-wildfire-related PM(2.5) at 0.01°×0.01° spatial resolution were created by combining information from satellite observations, chemical transport models, and ground-based observations. Exposure data were linked to each participant’s home address, assuming the address did not change during the exposure window. For DNA methylation of each cytosine-guanine dinucleotide (CpG), and for global DNA methylation represented by the average of all measured CpGs or CpGs in repetitive elements, we evaluated their associations with wildfire- or non-wildfire-related PM(2.5) using a within-sibship analysis controlling for factors shared between siblings and other important covariates. Differentially methylated regions (DMRs) were defined by comb-p and DMRcate. RESULTS: The 3-year average wildfire-related PM(2.5) (range: 0.3 to 7.6 µg/m(3)(,) mean: 1.6 µg/m(3)) was negatively, but not significantly (p-values greater than 0.05) associated with all seven global DNA methylation measures. There were 26 CpGs and 33 DMRs associated with wildfire-related PM(2.5) (Bonferroni adjusted p-value < 0.05) mapped to 47 genes enriched for pathways related to inflammatory regulation and platelet activation. These genes have been related to many human diseases or phenotypes e.g., cancer, mental disorders, diabetes, obesity, asthma, blood pressure. These CpGs, DMRs and enriched pathways did not overlap with the 1 CpG and 7 DMRs associated with non-wildfire-related PM(2.5). CONCLUSIONS: Long-term exposure to wildfire-related PM(2.5) was associated with various blood DNA methylation signatures in Australian women, and these were distinct from those associated with non-wildfire-related PM(2.5).
BACKGROUND: Wildfire imposes a high mortality burden on Brazil. However, there is a limited assessment of the health economic losses attributable to wildfire-related fine particulate matter (PM(2.5)). METHODS: We collected daily time-series data on all-cause, cardiovascular, and respiratory mortality from 510 immediate regions in Brazil during 2000-2016. The chemical transport model GEOS-Chem driven with Global Fire Emissions Database (GFED), in combination with ground monitored data and machine learning was used to estimate wildfire-related PM(2.5) data at a resolution of 0.25° × 0.25°. A time-series design was applied in each immediate region to assess the association between economic losses due to mortality and wildfire-related PM(2.5) and the estimates were pooled at the national level using a random-effect meta-analysis. We used a meta-regression model to explore the modification effect of GDP and its sectors (agriculture, industry, and service) on economic losses. RESULTS: During 2000-2016, a total of US$81.08 billion economic losses (US$5.07 billion per year) due to mortality were attributable to wildfire-related PM(2.5) in Brazil, accounting for 0.68% of economic losses and equivalent to approximately 0.14% of Brazil’s GDP. The attributable fraction (AF) of economic losses due to wildfire-related PM(2.5) was positively associated with the proportion of GDP from agriculture, while negatively associated with the proportion of GDP from service. CONCLUSION: Substantial economic losses due to mortality were associated with wildfires, which could be influenced by the agriculture and services share of GDP per capita. Our estimates of the economic losses of mortality could be used to determine optimal levels of investment and resources to mitigate the adverse health impacts of wildfires.
Rationale: Wildfires are a growing source of pollution including particulate matter ⩽2.5 μm in aerodynamic diameter (PM(2.5)), but associated trends in health burden are not well characterized. Objectives: We investigated trends and disparities in PM(2.5)-related cardiorespiratory health burden (asthma, chronic obstructive pulmonary disease, and all-cause respiratory and cardiovascular emergency department [ED] visits and hospital admissions) for all days and wildfire smoke-affected days across California from 2008 to 2016. Methods: Using residential Zone Improvement Plan code and daily PM(2.5) exposures, we estimated overall and subgroup-specific (age, gender, race and ethnicity) associations with cardiorespiratory outcomes. Health burden trends and disparities were evaluated on the basis of relative risk, attributable number, and attributable fraction by demographic and geographic factors and over time. Measurements and Main Results: PM(2.5)-attributed burden steadily decreased, whereas the fraction attributed to wildfire smoke varied by fire season intensity, constituting up to 15% of the annual PM(2.5)-burden. The highest relative risk and PM(2.5)-attributed burden (92 per 100,000 people) was observed for respiratory ED visits, accounting for 2.2% of the respiratory annual burden. Disparities in overall morbidity in the oldest age, Black, and “other” race groups were also reflected in PM(2.5)-attributed burden, whereas Asian populations had the highest risk rate in respiratory outcomes and thus the largest fraction of the total burden attributed to the exposure. In contrast, high wildfire PM(2.5)-attributed burden rates in rural, central, and northern California populations occurred because of differential exposure. Conclusions: In California, wildfires’ impact on air quality offset the public health gains achieved through reductions in nonsmoke PM(2.5). Disproportionate effects could be attributed to differences in subpopulation susceptibility, relative risk, and differential exposure.
Wildfires are relevant sources of PM emissions and can have an important impact on air pollution and human health. In this study, we examine the impact of wildfire PM emissions on the Piemonte (Italy) air quality regional monitoring network using a Generalized Additive Mixed Model. The model is implemented with daily PM10 and PM2.5 concentrations sampled for 8 consecutive years at each monitoring site as the response variable. Meteorological data retrieved from the ERA5 dataset and the observed burned area data stored in the Carabinieri Forest Service national database are used in the model as explanatory variables. Spline functions for predictive variables and smooths for multiple meteorological variables’ interactions improved the model performance and reduced uncertainty levels. The model estimates are in good agreement with the observed PM data: adjusted R-2 range was 0.63-0.80. GAMMs showed rather satisfactory results in order to capture the wildfires contribution: some severe PM pollution episodes in the study area due to wildfire air emissions caused peak daily levels up to 87.3 mu g/m(3) at the Vercelli PM10 site (IT1533A) and up to 67.7 mu g/m(3) at the Settimo Torinese PM2.5 site (IT1130A).
Wildfire activity is increasing in the continental U.S. and can be linked to climate change effects, including rising temperatures and more frequent drought conditions. Wildfire emissions and large fire frequency have increased in the western U.S., impacting human health and ecosystems. We linked 15 years (2006-2020) of particulate matter (PM(2.5)) chemical speciation data with smoke plume analysis to identify PM(2.5)-associated nutrients elevated in air samples on smoke-impacted days. Most macro- and micro-nutrients analyzed (phosphorus, calcium, potassium, sodium, silicon, aluminum, iron, manganese, and magnesium) were significantly elevated on smoke days across all years analyzed. The largest percent increase was observed for phosphorus. With the exception of ammonium, all other nutrients (nitrate, copper, and zinc), although not statistically significant, had higher median values across all years on smoke vs. non-smoke days. Not surprisingly, there was high variation between smoke impacted days, with some nutrients episodically elevated >10 000% during select fire events. Beyond nutrients, we also explored instances where algal blooms occurred in multiple lakes downwind from high-nutrient fires. In these cases, remotely sensed cyanobacteria indices in downwind lakes increased two to seven days following the occurrence of wildfire smoke above the lake. This suggests that elevated nutrients in wildfire smoke may contribute to downwind algal blooms. Since cyanobacteria blooms can be associated with the production of cyanotoxins and wildfire activity is increasing due to climate change, this finding has implications for drinking water reservoirs in the western United States, and for lake ecology, particularly alpine lakes with otherwise limited nutrient inputs.
Due in part to climate change, wildfire activity is increasing, with the potential for greater public health impact from smoke in downwind communities. Studies examining the health effects of wildfire smoke have focused primarily on fine particulate matter (PM(2.5)), but there is a need to better characterize other constituents, such as hazardous air pollutants (HAPs). HAPs are chemicals known or suspected to cause cancer or other serious health effects that are regulated by the United States (US) Environmental Protection Agency. Here, we analyzed concentrations of 21 HAPs in wildfire smoke from 2006 to 2020 at 309 monitors across the western US. Additionally, we examined HAP concentrations measured in a major population center (San Jose, CA) affected by multiple fires from 2017 to 2020. We found that concentrations of select HAPs, namely acetaldehyde, acrolein, chloroform, formaldehyde, manganese, and tetrachloroethylene, were all significantly elevated on smoke-impacted versus nonsmoke days (P < 0.05). The largest median increase on smoke-impacted days was observed for formaldehyde, 1.3 μg/m(3) (43%) higher than that on nonsmoke days. Acetaldehyde increased 0.73 μg/m(3) (36%), and acrolein increased 0.14 μg/m(3) (34%). By better characterizing these chemicals in wildfire smoke, we anticipate that this research will aid efforts to reduce exposures in downwind communities.
Climate change favors weather conditions conducive to wildland fires. The intensity and frequency of forest fires are increasing, and fire seasons are lengthening. Exposure of human populations to smoke emitted by these fires increases, thereby contributing to airborne pollution through the emission of gas and particulate matter (PM). The adverse health outcomes associated with wildland fire exposure represent an important burden on the economies and health systems of societies. Even though cardiovascular diseases (CVDs) are the main of cause of the global burden of diseases attributable to PM exposure, it remains difficult to show reliable associations between exposure to wildland fire smoke and cardiovascular disease risk in population-based studies. Optimal health requires a resilient and adaptable network of small blood vessels, namely, the microvasculature. Often alterations of this microvasculature precede the occurrence of adverse health outcomes, including CVD. Biomarkers of microvascular health could then represent possible markers for the early detection of poor cardiovascular outcomes. This review aims to synthesize the current literature to gauge whether assessing the microvasculature can better estimate the cardiovascular impact of wildland fires.
People using electricity-dependent durable medical equipment (DME) may be vulnerable to health effects from wildfire smoke, residence near wildfires, or residence in evacuation zones. To our knowledge, no studies have examined their healthcare utilization during wildfires. METHODS: We obtained 2016-2020 counts of residential Zip Code Tabulation Area (ZCTA) level outpatient, emergency department (ED), and inpatient visits made by DME-using Kaiser Permanente Southern California members 45+. We linked counts to daily ZCTA-level wildfire particulate matter (PM) 2.5 and wildfire boundary and evacuation data from the 2018 Woolsey and 2019 Getty wildfires. We estimated the association of lagged (up to 7 days) wildfire PM 2.5 and residence near a fire or in an evacuation zone and healthcare visit frequency with negative binomial and difference-in-differences models. RESULTS: Among 236,732 DME users, 10 µg/m 3 increases in wildfire PM 2.5 concentration were associated with the reduced rate (RR = 0.96; 95% confidence interval [CI] = 0.94, 0.99) of all-cause outpatient visits 1 day after exposure and increased rate on 4 of 5 subsequent days (RR range 1.03-1.12). Woolsey Fire proximity (<20 km) was associated with reduced all-cause outpatient visits, whereas evacuation and proximity were associated with increased inpatient cardiorespiratory visits (proximity RR = 1.45; 95% CI = 0.99, 2.12, evacuation RR = 1.72; 95% CI = 1.00, 2.96). Neither Getty Fire proximity nor evacuation was associated with healthcare visit frequency. CONCLUSIONS: Our results support the hypothesis that wildfire smoke or proximity interrupts DME users' routine outpatient care, via sheltering in place. However, wildfire exposures were also associated with increased urgent healthcare utilization in this vulnerable group.
Wildfires, which have been occurring increasingly in the era of climate change, emit massive amounts of particulate matter (PM) into the atmosphere, strongly affecting air quality and public health. Biomass burning aerosols may contain environmentally persistent free radicals (EPFRs, such as semiquinone radicals) and redox-active compounds that can generate reactive oxygen species (ROS, including center dot OH, superoxide and organic radicals) in the aqueous phase. However, there is a lack of data on EPFRs and ROS associated with size-segregated wildfire PM, which limits our understanding of their climate and health impacts. We collected size-segregated ambient PM in Southern California during two wildfire events to measure EPFRs and ROS using electron paramagnetic resonance spectroscopy. EPFRs are likely associated with soot particles as they are predominantly observed in submicron particles (PM1, aerodynamic diameter <= 1 mu m). Upon extraction in water, wildfire PM mainly generates center dot OH (28-49%) and carbon-centered radicals (similar to 50%) with minor contributions from superoxide and oxygen-centered organic radicals (2-15%). Oxidative potential measured with the dithiothreitol assay (OP-DTT) is found to be high in wildfire PM1, exhibiting little correlation with the radical forms of ROS (r(2) <= 0.02). These results are in stark contrast with PM collected at highway and urban sites, which generates predominantly center dot OH (84-88%) that correlates well with OP-DTT (r(2) similar to 0.6). We also found that PM generated by flaming combustion generates more radicals with higher OP-DTT compared to those by smoldering or pyrolysis.
The paper analyses biometeorological conditions in Lublin based on the Universal Thermal Climate Index (UTCI), and air quality based on the Common Air Quality Index (CAQI). The used data were obtained from the database of IMGW-PIB and RDEM, and cover the period 2015-2021. The most frequently occurring biometeorological conditions were classified as no thermal stress. They were observed with a frequency of 34.3%. Conditions unfavourable for the human organism accounted for 65.7% in total, including those belonging to thermal stress classes related to cold stress (52.3%), and heat stress (13.4%). In the analysed years, 75.5% of cases were with very low and low air pollution. High and very high air pollution usually occurred during biometeorological conditions related to cold stress (from slight cold stress to strong cold stress). During extreme thermal phenomena, such as a cold wave (January 2007) and hot wave (August 2015), unfavourable biometeorological conditions were accompanied by low aerosanitary conditions (low air quality). In the analysed period, and particularly in recent years, an improvement in air quality has been observed, potentially associated with limited mobility of people during the COVID-19 pandemic.
Particulate pollution has become a major issue in developing countries including Pakistan. Aerosols are causing severe impacts on climate and human health. To understand the effects of aerosols on the environment and human health, we must first understand their optical and physical properties. In this paper, we used ozone monitoring instrument (OMI) retrieved ultraviolet aerosol index (UVAI) to analyze spatial and temporal distribution, annual and seasonal trends of absorbing aerosols, and their relationship with meteorological parameters (e.g., temperature, relative humidity, and wind speed) over Pakistan from October 2004 to December 2021. Significant spatiotemporal changes in UVAI values were found with high values in southern and central regions and low values in northern regions of Pakistan. The mean UVAI over Pakistan showed an increasing trend of 2.89% year(-1). Seasonally, UVAI increases at the rate of 3.97% winter(-1), 3.24% autumn(-1), 0.81% summer(-1), and 0.71% spring(-1). A strong positive correlation of UVAI with precipitation and temperature (~ 0.6) is observed in the central and southern regions of Pakistan. A negative and positive correlation of -0.3223 and 0.4284 of UVAI with CO(2) emissions and primary industry is observed in Pakistan, respectively. We also found potential sources of aerosols over major cities of Pakistan using the Hybrid Single Particle Langrangian Integrated Trajectory (HYSPLIT) model. It determines that the dominant aerosols over Karachi are natural aerosols like sea salt and dust particles and anthropogenic aerosols are dominant over Lahore. Moreover, the natural and anthropogenic factors influencing absorbing aerosols are also discussed herein. Considering the outcomes of this study different methods would be used to reduce the concentration of particulate pollution like afforestation, efficient fuel energy consumption, promotion of public transport networks, etc.
OBJECTIVES: (i) To analyze trends and gaps in evidence of health effects on pollutants and extreme temperatures by evidence mapping; (ii) to conduct a cross-sectional survey on the use of the Grades of Recommendations Assessment Development and Evaluation (GRADE) in systematic reviews or meta-analyses (SR/MAs) of health effects on pollutants and extreme temperatures. STUDY DESIGN AND SETTING: PubMed, Embase, the Cochrane Library, Web of Science, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) were searched until July 7, 2022. SR/MAs investigated health effects of pollutants and extreme temperatures were included. RESULTS: Out of 22,658 studies, 312 SR/MAs were included in evidence mapping, and the effects of pollutants on cancer and congenital malformations were new research hotspots. Among 16 SR/MAs involving 108 outcomes that were rated using GRADE, the certainty of evidence was mostly downgraded for inconsistency (50, 42.7%), imprecision (33, 28.2%), and risk of bias (24, 20.5%). In contrast, concentration-response gradient (26, 65.0%) was the main upgrade factor. CONCLUSION: GRADE is not widely used in SR/MAs of health effects on pollutants and extreme temperatures. The certainty of evidence is generally low, mainly because of the serious inconsistency or imprecision. Use of the GRADE in SR/MAs of health effects on pollutants and extreme temperatures should strengthen.
Forest fire activity has been increasing in California. Satellite imagery data along with ground level measurements of PM2.5 have been previously used to determine the presence and level of smoke. In this study, emergency room visits for asthma are explored for the impacts of wildland smoke over the entire state of California for the years 2008-2015. Smoke events included extreme high-intensity fire and smoke along with low and moderate smoke events. The presence of wildland fire smoke detected by remote sensing significantly increased fine particulate matter (PM2.5) and significantly increased the odds of exceeding expected concentrations of PM2.5 at ground level. Smoke observed above a monitoring site increases the chance of PM2.5 exceeding 35 mu g m(-3) (odds ratio 114 (87-150) when high levels of smoke are detected). The strength of association of an asthma emergency room visit is increased with higher PM2.5 concentrations. The odds ratios (OR) are highest for asthma hospital visits when daily mean PM2.5 concentrations experienced exceed 35 mu g m(-3) for multiple days (OR 1.38 (1.21-1.57) with 3 days). Nonetheless, on days with wildland fire smoke, the association of an emergency room visit for asthma due to PM2.5 is not observed. Further study is needed to confirm these findings and determine if this is a product of smoke avoidance and reduction of personal exposure during smoke episodes.
Climate change and air pollution are two interconnected global challenges that have profound impacts on human health. In Africa, a continent known for its rich biodiversity and diverse ecosystems, the adverse effects of climate change and air pollution are particularly concerning. This review study examines the implications of air pollution and climate change for human health and well-being in Africa. It explores the intersection of these two factors and their impact on various health outcomes, including cardiovascular disease, respiratory disorders, mental health, and vulnerable populations such as children and the elderly. The study highlights the disproportionate effects of air pollution on vulnerable groups and emphasizes the need for targeted interventions and policies to protect their health. Furthermore, it discusses the role of climate change in exacerbating air pollution and the potential long-term consequences for public health in Africa. The review also addresses the importance of considering temperature and precipitation changes as modifiers of the health effects of air pollution. By synthesizing existing research, this study aims to shed light on complex relationships and highlight the key findings, knowledge gaps, and potential solutions for mitigating the impacts of climate change and air pollution on human health in the region. The insights gained from this review can inform evidence-based policies and interventions to mitigate the adverse effects on human health and promote sustainable development in Africa.
Environmental stressors including high temperature and air pollution cause health problems. However, understanding how the combined exposure to heat and air pollution affects both physical and mental health remains insufficient due to the complexity of such effects mingling with human society, urban and natural environments. Our study roots in the Social Ecological Theory and employs a tri-environmental conceptual framework (i.e., across social, built and natural environment) to examine how the combined exposure to heat and air pollution affect self-reported physical and mental health via, for the first time, the fine-grained nationwide investigation in Australia and highlight how such effects vary across inter- and intra-urban areas. We conducted an ecological study to explore the importance of heat and air quality to physical and mental health by considering 48 tri-environmental confounders through the global and local random forest regression models, as advanced machine learning methods with the advantage of revealing the spatial heterogeneity of variables. Our key findings are threefold. First, the social and built environmental factors are important to physical and mental health in both urban and rural areas, and even more important than exposure to heat and air pollution. Second, the relationship between temperature and air quality and health follows a V-shape, reflecting people’s different adaptation and tolerance to temperature and air quality. Third, the important roles that heat and air pollution play in physical and mental health are most obvious in the inner-city and near inner-city areas of the major capital cities, as well as in the industrial zones in peri-urban regions and in Darwin city with a low-latitude. We draw several policy implications to minimise the inter- and intra-urban differences in healthcare access and service distribution to populations with different sensitivity to heat and air quality across urban and rural areas. Our conceptual framework can also be applied to examine the relationship between other environmental problems and health outcomes in the era of a warming climate.
Forest fires are extreme natural/artificial events releasing polycyclic aromatic hydrocarbons (PAHs), which are carcinogenic. Most of the released PAHs are trapped in burnt ash, a part of which is transported and settle on different mediums like soil and water. After strong rainfall events, PAHs enter into surface water bodies through surface runoff, thereby deteriorating water quality. Changes in PAHs levels during the post-fire duration and human health risks due to PAHs released from forest fires need attention. This study aim to explain the trends and patterns of PAHs and health risks due to exposure to soil and water contaminated with PAHs. Forest fires release a higher percentage of low molecular weight PAHs (LMW PAHs) than high molecular weight PAHs (HMW PAHs). Ash and burnt soils contain a higher percentage of LMW PAHs since biomass burning releases huge amounts of LMW PAHs. Whereas, sediments contain a higher percentage of HMW PAHs since most of the LMW PAHs are already degraded. HMW PAHs were causing higher risk to humans (both cancer and non-cancer) due to their higher oxidation potential. Exposure to water contaminated by PAHs resulted in higher health risks for both BaP equivalent and a mixture of PAHs. Exposure to sediment produced the highest health risk due to a higher percentage of HMW PAHs, followed by surface water, burnt soil, ash, and unburnt soil. Cancer and non-cancer risk due to dermal exposure was more elevated than oral exposure. The mixture of PAHs in sediment produced a higher average dermal risk for children (2.21E+00 for cancer and 7.69E+03 for non-cancer risk) and oral cancer risk for adults (7.11E-03). However, exposure to BaP equivalent in sediment produced higher oral non-cancer risk (7.01E+02) for children. Thus, effective PAHs monitoring is required in both soil and surface water mediums for ensuring proper treatment in water supply systems.
Wildfires are a significant cause of exposure to ambient air pollution in the United States and other settings. Although indoor air pollution is a known contributor to tuberculosis reactivation and progression, it is unclear whether ambient pollution exposures, including wildfire smoke, similarly increase risk. Objectives: To determine whether tuberculosis diagnosis was associated with recent exposure to acute outdoor air pollution events, including those caused by wildfire smoke. Methods: We conducted a case-crossover analysis of 6,238 patients aged ⩾15 years diagnosed with active tuberculosis disease between 2014 and 2019 in 8 California counties. Using geocoded address data, we characterized individuals’ daily exposure to <2.5 μm-diameter particulate matter (PM(2.5)) during counterfactual risk periods 3-6 months before tuberculosis diagnosis (hazard period) and the same time 1 year previously (control period). We compared the frequency of residential PM(2.5) exposures exceeding 35 μg/m(3) (PM(2.5) events) overall and for wildfire-associated and nonwildfire events during individuals' hazard and control periods. Measurements and Main Results: In total, 3,139 patients experienced 1 or more PM(2.5) events during the hazard period, including 671 experiencing 1 or more wildfire-associated events. Adjusted odds of tuberculosis diagnosis increased by 5% (95% confidence interval, 3-6%) with each PM(2.5) event experienced over the 6-month observation period. Each wildfire-associated PM(2.5) event was associated with 23% (19-28%) higher odds of tuberculosis diagnosis in this time window, whereas no association was apparent for nonwildfire-associated events. Conclusions: Residential exposure to wildfire-associated ambient air pollution is associated with an increased risk of active tuberculosis diagnosis.
Droughts reduce hydropower production and heatwaves increase electricity demand, forcing power system operators to rely more on fossil fuel power plants. However, less is known about how droughts and heat waves impact the county level distribution of health damages from power plant emissions. Using California as a case study, we simulate emissions from power plants under a 500-year synthetic weather ensemble. We find that human health damages are highest in hot, dry years. Counties with a majority of people of color and counties with high pollution burden (which are somewhat overlapping) are disproportionately impacted by increased emissions from power plants during droughts and heat waves. Taxing power plant operations based on each plant’s contribution to health damages significantly reduces average exposure. However, emissions taxes do not reduce air pollution damages on the worst polluting days, because supply scarcity (caused by severe heat waves) forces system operators to use every power plant available to avoid causing a blackout.
The atmosphere is a major route for microbial intercontinental dispersal, including harmful microorganisms, antibiotic resistance genes, and allergens, with strong implications in ecosystem functioning and global health. Long-distance dispersal is facilitated by air movement at higher altitudes in the free troposphere and is affected by anthropogenic forcing, climate change, and by the general atmospheric circulation, mainly in the intertropical convergence zone. The survival of microorganisms during atmospheric transport and their remote invasive potential are fundamental questions, but data are scarce. Extreme atmospheric conditions represent a challenge to survival that requires specific adaptive strategies, and recovery of air samples from the high altitudes relevant to study harmful microorganisms can be challenging. In this paper, we highlight the scope of the problem, identify challenges and knowledge gaps, and offer a roadmap for improved understanding of intercontinental microbial dispersal and their outcomes. Greater understanding of long-distance dispersal requires research focus on local factors that affect emissions, coupled with conditions influencing transport and survival at high altitudes, and eventual deposition at sink locations.
Climate change is a defining challenge for today’s society and its consequences pose a great threat to humanity. Cities are major contributors to climate change, accounting for over 70% of global greenhouse gas emissions. With urbanization occurring at a rapid rate worldwide, cities will play a key role in mitigating emissions and addressing climate change. Greenhouse gas emissions are strongly interlinked with air quality as they share emission sources. Consequently, there is a great opportunity to develop policies which maximize the co-benefits of emissions reductions on air quality and health. As such, a narrative meta-review is conducted to highlight state-of-the-art monitoring and modelling tools which can inform and monitor progress towards greenhouse gas emission and air pollution reduction targets. Urban greenspace will play an important role in the transition to net-zero as it promotes sustainable and active transport modes. Therefore, we explore advancements in urban greenspace quantification methods which can aid strategic developments. There is great potential to harness technological advancements to better understand the impact of greenhouse gas reduction strategies on air quality and subsequently inform the optimal design of these strategies going forward. An integrated approach to greenhouse gas emission and air pollution reduction will create sustainable, net-zero and healthy future cities.
Environmental risks are a substantial factor in the current burden of disease, and their role is likely to increase in the future. Model-based scenario analysis is used extensively in environmental sciences to explore the potential effects of human activities on the environment. In this Review, we examine the literature on scenarios modelling environmental effects on health to identify the most relevant findings, common methods used, and important research gaps. Health outcomes and measures related to climate change (n=106) and air pollution (n=30) were most frequently studied. Studies examining future disease burden due to changes or policies related to dietary risks were much less common (n=10). Only a few studies assessed more than two environmental risks (n=3), even though risks can accumulate and interact with each other. Studies predominantly covered high-income countries and Asia. Sociodemographic, vulnerability, and health-system changes were rarely accounted for; thus, assessing the full effect of future environmental changes in an integrative way is not yet possible. We recommend that future models incorporate a broader set of determinants of health to more adequately capture their effect, as well as the effect of mitigation and adaptation efforts.
It is increasingly recognized that strong geographic variations in cardiovascular risk cannot be explained using traditional cardiovascular risk factors alone. Indeed, it is highly unlikely that heredity and classic risk factors such as hypertension, diabetes, dyslipidemia, and tobacco use can explain the tenfold variation observed in cardiovascular mortality among men in Russia and those in Switzerland. Since the advent of industrialization and resultant changes to our climate, it is now clear that environmental stressors also influence cardiovascular health and our thinking around cardiovascular risk prediction is in need of aparadigm shift. Herein, we review the basis for this shift in our understanding of the interplay of environmental factors with cardiovascular health. We illustrate how air pollution, hyperprocessed foods, the amount of green space, and population activity levels are now considered the 4 major environmental determinants of cardiovascular health and provide a framework for how these considerations might be incorporated into clinical risk assessment. We also outline the clinical and socioeconomic effects of the environment on cardiovascular health and review key recommendations from major medical societies.
As the climate continues to change, suicide is becoming more frequent. In this study, absolute humidity (AH) was included for the first time and Wuhu, a typical subtropical city along the Yangtze River, was taken as the research object to explore the impact of suicide death risk on meteorological factors. The daily meteorological factors and suicide mortality data of Wuhu city from 2014 to 2020 were collected. Guided by structural equation model (SEM), a time series analysis method combining distributed lag nonlinear model (DLNM) and generalized additive model (GAM) was adopted. To investigate the correlation among different populations, we stratified age and gender at different meteorological levels. A total of 1259 suicide deaths were collected in Wuhu. The results indicated that exceedingly low and low levels of AH short-term exposure increased suicide mortality, with the maximum effect occurring at lag 14 for both levels of exposure, when the relative risk (RR) was 1.131 (95% CI: 1.030, 1.242) and 1.065 (95% CI: 1.006, 1.127), respectively. Exposure to exceedingly high and exceedingly low levels of temperature mean (T mean) also increased suicide mortality, with maximum RR values of 1.132 (lag 14, 95% CI: 1.015, 1.263) and 1.203 (lag 0, 95% CI: 1.079, 1.340), sequentially. As for diurnal temperature range (DTR), low-level exposure decreased the risk of suicide, while high-level exposure increased this risk, with RR values of 0.955 (lag 0, 95% CI: 0.920, 0.991, minimum) and 1.060 (lag 0, 95% CI: 1.018, 1.104, maximum), sequentially. Stratified analysis showed that AH and DTR increased the suicide death risk in male and elderly people, while the risk effect of T mean have no effect on young people only. In summary, male and elderly people appear to be more vulnerable to adverse weather effects.
Heat and tropospheric ozone have acute impacts on rates of premature death. Warm temperatures affect the photochemical processes in ozone formation, suggesting ozone as a mediator of the acute health effect of heat on mortality. We assembled a summertime daily time-series data set of 15 French urban areas during 2000-2015 to decompose the acute total effect of heat waves on mortality into natural direct and indirect effects using a regression-based product method under the potential outcomes framework. For each area, we estimated the effect of heat waves on mortality using a quasi-Poisson model with adjustment for covariates such as lagged nitrogen dioxide concentration, and we modeled ozone with a linear regression of heat waves and the same set of covariates. We pooled estimates across areas using random-effects models. We also provide R software code (R Foundation for Statistical Computing, Vienna, Austria) with which to reproduce or replicate our analysis. Most areas demonstrated evidence of mediation by ozone, with the pooled relative risks for natural indirect effects being 1.03 (95% confidence interval (CI): 1.02, 1.05), 1.03 (95% CI: 1.01, 1.04), and 1.04 (95% CI: 1.00, 1.07) for nonaccidental, cardiovascular, and respiratory mortality, respectively. We found evidence of a mediation effect by ozone in the association between heat waves and mortality in France which varied by geographic location and cause of mortality.
BACKGROUND: Pregnancy loss, a major health issue that affects human sustainability, has been linked to short-term exposure to ground-surface ozone (O(3)). However, the association is inconsistent, possibly because of the co-occurrence of O(3) and heat episodes, as increased temperature is a risk factor for pregnancy loss. To explain this inconsistency, the effect of O(3) on pregnancy loss needs to be examined jointly with that of high temperature. METHODS: A total of 247,305 pregnancy losses during the warm season were extracted from fetal death certificates from the 386 counties in contiguous United States from 1989 to 2005. We assessed environmental exposure based on the daily maximum 8 h average of O(3) from Air Quality System monitors and the 24 h average temperature from the North American Regional Reanalysis product. We conducted a bidirectional, time-stratified case-crossover study of the association between pregnancy loss and exposures to O(3) and temperature and their multiplicative interaction. The main time window for the exposure assessment was the day of case occurrence and the preceding 3 days. To estimate the association, we used conditional logistic regression with adjustment for relative humidity, height of the planetary boundary layer, and holidays. Sensitivity analyses were performed on the lagged structure, nonlinearity, and between-subpopulation heterogeneity of the estimated joint effect. RESULTS: The joint effect was first estimated by the regression against categorical exposure by tertile. Compared to the low-low exposure group (O(3) ≤ 78 μg/m(3) and temperature ≤ 18 °C), the odds of pregnancy loss was significantly higher by 6.0 % (95 % confidence interval [CI] 2.4-9.7 %), 9.8 % (6.1-13.8 %), and 7.5 % (4.7-10.3 %) in the high-low (>104 μg/m(3) and ≤18 °C), low-high (≤78 μg/m(3) and >23 °C), and high-high (>104 μg/m(3) and >23 °C) groups. The model of linear exposure and the multiplicative interaction yielded similar results. Each increment of 10 μg/m(3) in O(3) and 1 °C in temperature was associated with a 3.0 % (2.0 %-4.0 %) and 3.9 % (3.5 %-4.3 %), respectively, increase in the odds of pregnancy loss. A decrease in odds of 0.2 % (0.1 %-0.2 %) was associated with the temperature × O(3) interaction. The finding of an antagonistic interaction between temperature and O(3) was confirmed by models parametrizing the joint exposure as alternative nonlinear terms (i.e., a two-dimensional spline term or a varying-coefficient term) and was robust to a variety of exposure lags and stratifications. Therefore, the marginal effect of O(3) was estimated to vary by climate zone. A significant association between O(3) and pregnancy loss was observed in the northern, but not southern, United States. CONCLUSION: Joint exposure to O(3) and high temperature can increase the risk for pregnancy loss. The adverse effect of O(3) is potentially modified by ambient temperature. In high-latitude cities, controlling for O(3) pollution could protect maternal health.
INTRODUCTION: Urban ozone pollution in China is becoming increasingly serious. Climate warming, high temperatures, and ozone pollution all have significant impacts on human health. However, the synergistic effects of high temperatures and ozone pollution in summer on human health are rarely studied. China is at a critical stage of environmental pollution control. Assessing the health impact of high temperatures and ozone exposure on the number of deaths from circulatory diseases is of great significance for formulating ozone-related prevention and control policies. METHODS: This study uses daily data on deaths from circulatory system diseases in Shijiazhuang from June to August during the summer of 2013-2016, as well as concurrent meteorological data and concentration of O(3) and PM(2.5) pollution data. The generalized additive model (GAM) with Poisson distribution, smooth curve threshold effect, and saturation effect method is used to control for confounding effects. RESULTS: The study evaluates the impact of short-term exposure to temperature and ozone on deaths from circulatory system diseases and the synergistic effect after controlling for confounding factors. The results show that the impact of temperature and ozone on deaths from circulatory system diseases in Shijiazhuang is nonlinear, with a temperature threshold of 27.5°C and an ozone concentration threshold of 100 μg/m(3). With an increase of temperature by 1°C, the risk of deaths for total population, men and women are 6.8%, 4.6% and 9.3%, respectively. The increase in temperature and ozone concentration has a greater impact on women; in men, the increase has a lag effect of 2 to 3 days, but the lag did not affect women. DISCUSSION: In conclusion, high temperatures and high ozone concentration have synergistic enhancement effects on circulatory system diseases. Prevention and scientific management strategies of circulatory system diseases in high temperatures and high ozone environments should be strengthened.
Volatile organic compound (VOC) emissions have attracted wide attention due to their impacts on atmospheric quality and public health. However, most studies reviewed certain aspects of natural VOCs (NVOCs) or anthropogenic VOCs (AVOCs) rather than comprehensively quantifying the hotspots and evolution trends of AVOCs and NVOCs. We combined the bibliometric method with the evolution tree and Markov chain to identify research focus and uncover the trends in VOC emission sources. This study found that research mainly focused on VOC emission characteristics, effects on air quality and health, and VOC emissions under climate change. More studies concerned on AVOCs than on NVOCs, and AVOC emissions have shifted with a decreasing proportion of transport emissions and an increasing share of solvent utilization in countries with high emissions and publications (China and the USA). Research on AVOCs is imperative to develop efficient and economical abatement techniques specific to solvent sources or BTEX species to mitigate the detrimental effects. Research on NVOCs originating from human sources risen due to their application in medicine, while studies on sources sensitive to climate change grew slowly, including plants, biomass burning, microbes, soil and oceans. Research on the long-term responses of NVOCs derived from various sources to climate warming is warranted to explore the evolution of emissions and the feedback on global climate. It is worthwhile to establish an emission inventory with all kinds of sources, accurate estimation, high spatial and temporal resolution to capture the emission trends in the synergy of industrialization and climate change as well as to simulate the effects on air quality. We review VOC emissions from both anthropogenic and natural sources under climate change and their effects on atmospheric quality and health to point out the research directions for the comprehensive control of global VOCs and mitigation of O(3) pollution.
Background Because of global climate change, extreme flood events are expected to increase in quantity and intensity in the upcoming decades. In catchments affected by ore mining, flooding leads to the deposition of fine sediments enriched in trace metal(loid)s. Depending on their concentration, trace metal(loid)s can be a health hazard. Therefore, exposure of the local population to flood sediments, either by ingestion (covering direct ingestion and consuming food grown on these sediments) or via inhalation of dried sediments contributing to atmospheric particulate matter, is of concern. Results The extreme flood of July 2021 deposited large amounts of sediment across the town of Eschweiler (western Germany), with the inundation area exceeding previously mapped extreme flood limits (HQ(extreme)). These sediments are rich in fine material (with the < 63 mu m fraction making up 32% to 96%), which either can stick to the skin and be ingested or inhaled. They are moderately to heavily enriched in Zn > Cu > Pb > Cd > Sn compared to local background concentrations. The concentrations of Zn, Pb, Cd, Cu, and As in flood sediments exceed international trigger action values. A simple assessment of inhalation and ingestion by humans reveals that the tolerable daily intake is exceeded for Pb. Despite the enrichment of other trace elements like Zn, Cu, Cd, and Sn, they presumably do not pose a risk to human well-being. However, exposure to high dust concentrations may be a health risk. Conclusions In conclusion, flood sediments, especially in catchments impacted by mining, may pose a risk to the affected public. Hence, we propose to (I) improve the flood mapping by incorporating potential pollution sources; (II) extend warning messages to incorporate specific guidance; (III) use appropriate clean-up strategies in the aftermath of such flooding events; (IV) provide medical support, and ( V) clue the public and medical professionals in on this topic accordingly.
Allergic disease is still a serious global public health problem, affecting 30-40% of world population. The rapid increase in prevalence indicates gene-by-environment interaction, in which epigenetics may be the underlying mechanism. We reviewed recent epidemiological studies about the association between prenatal exposure to air pollution and childhood allergies. On the other hand, we reviewed the evidence that maternal exposure to air pollution caused epigenetic alterations that changed the gene expression or transcription in offspring. We further discussed the challenges of the global warming and COVID-19 to the childhood allergies especially in developing countries and suggested the opportunities to prevention or control by early intervention, immunotherapy, and epigenetic therapy.
The occurrence of wildfires in Indonesia is prevalent during drought seasons. Multiple toxic pollutants emitted from wildfires have deleterious effects on pregnant women. However, the evidence for these on pregnant women was underreported. The study conducted 24-h monitoring of fine particulate matter (PM(2.5)) concentrations indoors and outdoors in 9 low-income homes in Palangka Raya during the 2019 wildfire season and 6 low-income homes during the 2019 non-wildfire season. A hundred and seventy pregnant women had their PM exposure assessed between July and October 2019 using personal monitors. It was observed that outdoor air pollutant levels were greater than those found indoors without indoor sources. The findings indicate that indoor PM(2.5) concentrations were modestly increased by 1.2 times higher than outdoor, suggesting that buildings only partially protected people from exposure during wildfires. The concentrations of PM(2.5) were found to be comparatively higher indoors in residential buildings with wood material than in brick houses. The study findings indicate that 8 out of 12 brick houses exhibited a notable RI/O(24 h) of less than 1 during the wildfires, whereas all I/O(24 h) ratios during the non-wildfire season were >1, suggesting the influence of indoor sources. Based on the estimation of daily PM(2.5) dose, pregnant women received around 21% of their total daily dose during sedentary activity involving cooking. The present research offers empirical support for the view that indoor air quality in low-income households is affected by a complex combination of factors, including wildfire smoke, air tightness, and occupant behaviour. Also, this situation is more likely a potential risk to pregnant women being exposed to wildfire smoke.
This study investigates the impact of environmental factors on human health, including harmful substances, extreme temperatures, and air quality. The health status of the population in regions where many industries operate also depends on meteorological factors. The purpose of the study is to characterize and determine the influence of environmental factors (humidity, temperature, wind) and industries, including metal mining and processing regions, on the health of people in the Aktobe region, Republic of Kazakhstan. The study used general theoretical methods to analyze and systematize the results of the meteorological service of the Aktobe region and the experiments conducted by the branch of the National Centre of Expertise of the Committee of Sanitary and Epidemiological Control of the Ministry of Healthcare of the Republic of Kazakhstan for the Aktobe region in 2020 and 2021. Statistical data on the amount of chromium, lead, and nickel in the blood, and the morbidity rate of the population were analyzed. The study’s findings indicate that residents in the Aktobe region experience hypothermia during winter at temperatures between -12 °C and -15 °C and humidity of 81%, and in summer overheating occurs at temperatures between +19.6 °C and +22.5 °C with humidity of 77%. These extreme temperature conditions disrupt the body’s heat exchange with the environment, affecting the respiratory and circulatory systems. Moreover, the predominantly windless conditions in the region affect the atmosphere’s self-cleaning ability, resulting in high levels of air pollution throughout the year. The findings can inform strategies to improve public health and prevent diseases in industrial regions. Integr Environ Assess Manag 2023;00:1-10. © 2023 SETAC.
With the increasing severity of the malignant tumors situation worldwide, the impacts of climate on them are receiving increasing attention. In this study, for the first time, all-malignant tumors were used as the dependent variable and absolute humidity (AH) was innovatively introduced into the independent variable to investigate the relationship between all-malignant tumors and meteorological factors. A total of 42,188 cases of malignant tumor deaths and meteorological factors in Wuhu City were collected over a 7-year (2014-2020) period. The analysis method combines distributed lagged nonlinear modeling (DLNM) as well as generalized additive modeling (GAM), with prior pre-analysis using structural equation modeling (SEM). The results showed that AH, temperature mean (T mean) and diurnal temperature range (DTR) all increased the malignant tumors mortality risk. Exposure to low and exceedingly low AH increases the malignant tumors mortality risk with maximum RR values of 1.008 (95% CI: 1.001, 1.015, lag 3) and 1.016 (95% CI: 1.001, 1.032, lag 1), respectively. In addition, low and exceedingly low T mean exposures also increased the risk of malignant tumors mortality, the maximum RR was 1.020 (95% CI: 1.006, 1.034) for low T mean and 1.035 (95% CI: 1.014, 1.058) for exceedingly low T mean. As for DTR, all four levels (exceedingly low, low, high, exceedingly high, from low to high) of exposure increased the risk of death from malignant tumors, from exceedingly low to exceedingly high maximum RR values of 1.018 (95% CI: 1.004, 1.032), 1.011 (95% CI: 1.005, 1.017), 1.006 (95% CI: 1.001, 1.012) and 1.019 (95% CI: 1.007, 1.031), respectively. The results of the stratified analysis suggested that female appear to be more sensitive to humidity, while male require additional attention to reduce exposure to high level of DTR.
Particulate pollution from forest fire smoke threatens the health of communities by increasing the occurrence of respiratory illnesses. Wind drives both fire behaviour and smoke dispersal. Understanding regional wind patterns would assist in effectively managing smoke risk. Sydney, Australia is prone to smoke pollution because it has a large population close to fire-prone eucalypt forests. Here we use the self-organising maps (SOM) technique to identify sixteen unique wind classes for the Sydney region from days with active fires, including identifying sea breeze occurrence. We explored differences in PM(2.5) levels between classes and between hazard reduction burning (HRB) and wildfire days. For HRB days, classes with the highest PM(2.5) mostly had a sea breeze, whereas better air quality days usually had winds aligned across the region (e.g. all westerly). The wind class with the most HRB days had low wind speeds and a sea breeze and was among the worst wind classes for air quality. For wildfire days, days with a sea breeze were also generally of poor air quality but many classes had at least some poor air quality days, most of which were during the 2019-2020 east coast wildfires in New South Wales. Some poor air quality days occurred in wind classes that sent strong plumes directly over air quality stations, spread smoke over a wide area or transported smoke from outside the region. The classes identified may be useful in scheduling HRBs, for example, identifying days with low pollution risk to conduct an HRB, or for assisting in understanding pollution risk and sending health warnings during HRBs and wildfires. Further development of the approach may allow the creation of multi-day classifications for fire managers to plan HRB ignitions over several days to ensure better smoke dispersal. Further research could incorporate other weather predictors or focus on other regions.
As a destructive and economic disaster in the world, drought shows an increasing trend under the continuous global climate change and adverse health effects have been reported. The interactive effects between drought and air pollutants, which may also be harmful to respiratory systems, remain to be discussed. We built the generalized additive model (GAM) and distributed lag nonlinear model (DLNM) to estimate the effects of drought and air pollutants on daily upper respiratory infections (URTI) outpatient visits among children under 6 in three cities of Gansu province. The Standardized Precipitation Index (SPI) based on monthly precipitation (SPI-1) was used as an indicator of drought. A non-stratified model was established to explore the interaction effect of SPI-1 and air pollutants. We illustrated the number of daily pediatric URTI outpatient visits increased with the decrease in SPI-1. The interactive effects between air pollutants and the number of daily pediatric URTIs were significant. According to the non-stratified model, we revealed highly polluted and drought environments had the most significant impact on URTI in children. The occurrence of drought and air pollutants increased URTI in children and exhibited a significant interactive effect.
Exposure to extreme temperatures or fine particles is associated with adverse health outcomes but their interactive effects remain unclear. We aimed to explore the interactions of extreme temperatures and PM(2.5) pollution on mortalities. Based on the daily mortality data collected during 2015-2019 in Jiangsu Province, China, we conducted generalized linear models with distributed lag non-linear model to estimate the regional-level effects of cold/hot extremes and PM(2.5) pollution. The relative excess risk due to interaction (RERI) was evaluated to represent the interaction. The relative risks (RRs) and cumulative relative risks (CRRs) of total and cause-specific mortalities associated with hot extremes were significantly stronger (p < 0.05) than those related to cold extremes across Jiangsu. We identified significantly higher interactions between hot extremes and PM(2.5) pollution, with the RERI range of 0.00-1.15. The interactions peaked on ischaemic heart disease (RERI = 1.13 [95%CI: 0.85, 1.41]) in middle Jiangsu. For respiratory mortality, RERIs were higher in females and the less educated. The interaction pattern remained consistent when defining the extremes/pollution with different thresholds. This study provides a comprehensive picture of the interactions between extreme temperatures and PM(2.5) pollution on total and cause-specific mortalities. The projected interactions call for public health actions to face the twin challenges, especially the co-appearance of hot extremes and PM pollution.
This paper explores the relationship between human health and energy technologies, with a focus on how energy technology needs to adapt to new health challenges. The authors examine how a clean, affordable, and reliable energy infrastructure is critical for mitigating the impact of future pandemics. They also look at how increasing the proportion of solar and wind energy can create a near-zero emission energy system that is independent of fuel supply and its associated environmental problems. However, to ensure system resilience, significant investments in energy storage and smart control systems are necessary. For instance, the pandemic led to around 5% increase in US residential sector electricity consumption share in 2020 compared to 2019 due to stay-at-home orders, which could impact grid reliability and resiliency. This work also highlights the importance of designing energy -efficient and low-cost cooling and heating technologies for residential buildings to protect vulnerable populations from the health consequences of rising temperatures due to climate change. Additionally, the growing number of refugees worldwide and the need for efficient portable power sources in refugee camps are also addressed. The authors demonstrate how pandemics like COVID-19 can have far-reaching effects on energy technologies, from household energy use to large energy companies, and result in energy insecurity and decreased quality of life for many. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
INTRODUCTION: Drivers of Transportation Network Companies (TNC) are an essential workforce that is affected by extreme weather events and high exposure risk to airborne infectious diseases due to their proximity with customers. The purpose of this study was to understand TNC drivers’ professional experience during the COVID-19 pandemic and their opinions about climate change and the development of future pandemics. METHODS: Open- and closed-ended responses were collected during TNC rides and analyzed with content analysis and descriptive statistics. RESULTS: We found more participants believed in the COVID-19 pandemic compared to participants who believed in climate change. Overall, participants were less concerned about COVID-19 than climate change. However, several participants felt that the pandemic had a positive impact on the climate system, specifically by reducing air pollution from traffic. Few participants felt that climate change could lead to the development of future pandemics. CONCLUSIONS: The TNC essential workforce could be integral for identifying transportation and public health sectors solutions for addressing the occupational health needs of an essential workforce, and response to climate change and pandemics.
Forest fires cause many environmental impacts, including air pollution. Brazil is a very fire-prone region where few studies have investigated the impact of wildfires on air quality and health. We proposed to test two hypotheses in this study: i) the wildfires in Brazil have increased the levels of air pollution and posed a health hazard in 2003-2018, and ii) the magnitude of this phenomenon depends on the type of land use and land cover (e.g., forest area, agricultural area, etc.). Satellite and ensemble models derived data were used as input in our analyses. Wildfire events were retrieved from Fire Information for Resource Management System (FIRMS), provided by NASA; air pollution data from the Copernicus Atmosphere Monitoring Service (CAMS); meteorological variables from the ERA-Interim model; and land use/cover data were derived from pixel-based classification of Landsat satellite images by MapBiomas. We used a framework that infers the “wildfire penalty” by accounting for differences in linear pollutant annual trends (β) between two models to test these hypotheses. The first model was adjusted for Wildfire-related Land Use activities (WLU), considered as an adjusted model. In the second model, defined as an unadjusted model, we removed the wildfire variable (WLU). Both models were controlled by meteorological variables. We used a generalized additive approach to fit these two models. To estimate mortality associated with wildfire penalties, we applied health impact function. Our findings suggest that wildfire events between 2003 and 2018 have increased the levels of air pollution and posed a significant health hazard in Brazil, supporting our first hypothesis. For example, in the Pampa biome, we estimated an annual wildfire penalty of 0.005 μg/m(3) (95%CI: 0.001; 0.009) on PM(2.5). Our results also confirm the second hypothesis. We observed that the greatest impact of wildfires on PM(2.5) concentrations occurred in soybean areas in the Amazon biome. During the 16 years of the study period, wildfires originating from soybean areas in the Amazon biome were associated with a total penalty of 0.64 μg/m(3) (95%CI: 0.32; 0.96) on PM(2.5), causing an estimated 3872 (95%CI: 2560; 5168) excess deaths. Sugarcane crops were also a driver of deforestation-related wildfires in Brazil, mainly in Cerrado and Atlantic Forest biomes. Our findings suggest that between 2003 and 2018, fires originating from sugarcane crops were associated with a total penalty of 0.134 μg/m(3) (95%CI: 0.037; 0.232) on PM(2.5) in Atlantic Forest biome, resulting in an estimated 7600 (95%CI: 4400; 10,800) excess deaths during the study period, and 0.096 μg/m(3) (95%CI: 0.048; 0.144) on PM(2.5) in Cerrado biome, resulting in an estimated 1632 (95%CI: 1152; 2112) excess deaths during the study period. Considering that the wildfire penalties observed during our study period may continue to be a challenge in the future, this study should be of interest to policymakers to prepare future strategies related to forest protection, land use management, agricultural activities, environmental health, climate change, and sources of air pollution.
A synergistic pathway is regarded as a critical measure for tackling the intertwined challenges of climate change and air pollution in China. However, there is as yet no indicator that can comprehensively reflect such synergistic effects; hence, existing studies lack a consistent framework for comparison. Here, we introduce a new synergistic indicator defined as the pollutant generation per gross domestic product (GDP) and adopt an integrated analysis framework by linking the logarithmic mean Divisia index (LMDI) method, response surface model (RSM), and global exposure mortality model (GEMM) to evaluate the synergistic effects of carbon mitigation on both air pollutant reduction and public health in China. The results show that synergistic effects played an increasingly important role in the emissions mitigation of SO2, NOx, and primary particulate matter with an aerodynamic diameter no greater than 2.5 mu m (PM2.5), and the synergistic mitigation of pollutants respectively increase from 3.1, 1.4, and 0.3 Mt during the 11th Five-Year Plan (FYP) (2006-2010) to 5.6, 3.7, and 1.9 Mt during the 12th FYP (2011-2015). Against the non-control scenario, synergistic effects alone contributed to a 15% reduction in annual mean PM2.5 con-centration, resulting in the prevention of 0.29 million (95% confidential interval: 0.28-0.30) PM2.5- attributable excess deaths in 2015. Synergistic benefits to air quality improvement and public health were remarkable in the developed and population-dense eastern provinces and municipalities. With the processes of urbanization and carbon neutrality in the future, synergistic effects are expected to con-tinue to increase. Realizing climate targets in advance in developed regions would concurrently bring strong synergistic effects to air quality and public health.(c) 2022 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The quantification of PM(2.5) concentrations solely stemming from both wildfire and prescribed burns (hereafter referred to as ‘fire’) is viable using the Community Multiscale Air Quality (CMAQ), although CMAQ outputs are subject to biases and uncertainties. To reduce the biases in CMAQ-based outputs, we propose a two-stage calibration strategy that improves the accuracy of CMAQ-based fire PM(2.5) estimates. First, we calibrated CMAQ-based non-fire PM(2.5) to ground PM(2.5) observations retrieved during non-fire days using an ensemble-based model. We estimated fire PM(2.5) concentrations in the second stage by multiplying the calibrated non-fire PM(2.5) obtained from the first stage by location- and time-specific conversion ratios. In a case study, we estimated fire PM(2.5) during the Washington 2016 fire season using the proposed calibration approach. The calibrated PM(2.5) better agreed with ground PM(2.5) observations with a 10-fold cross-validated (CV) R(2) of 0.79 compared to CMAQ-based PM(2.5) estimates with R(2) of 0.12. In the health effect analysis, we found significant associations between calibrated fire PM(2.5) and cardio-respiratory hospitalizations across the fire season: relative risk (RR) for cardiovascular disease = 1.074, 95% confidence interval (CI) = 1.021-1.130 in October; RR = 1.191, 95% CI = 1.099-1.291 in November; RR for respiratory disease = 1.078, 95% CI = 1.005-1.157 in October; RR = 1.153, 95% CI = 1.045-1.272 in November. However, the results were inconsistent when non-calibrated PM(2.5) was used in the analysis. We found that calibration affected health effect assessments in the present study, but further research is needed to confirm our findings.
Background and Objective: Poor air quality can be harmful to human well-being. There are a variety of respiratory disorders associated with toxins present within the atmosphere, such as bronchitis and asthma, which eventually lead to heart or lung complications over time. Fine particles like particulate matter 2.5 (PM 2.5) accumulate in the small airways of the lung. These irritants can cause epigenetic modifications in gene regulation, leading to changes responsible for both benign and malignant lung diseases. In this review we will discuss known associations between environmental factors and pulmonary complications, consider preventative measures and offer further areas for future investigation. This review presents a summary of the literature outlining the current work done on air quality and its effects on lung-related illnesses. We discuss regional differences in air quality and consider the causes, such as manufacturing, traffic density, increase in fuel usage and natural events. We further explore disparities based on geography, race, and other social determinants.Methods: A comprehensive literature review was performed using keywords related to air quality, pollution and lung disease within the PubMed database as well as MEDLINE and Google Scholar. The search strategy is shown in Table 1.Key Content and Findings: The Clean Air Act of 1970 marked an essential transition for air quality improvement. The legislation led to decreased emissions and control measures to address atmosphere contamination. Despite these actions, poor atmospheric conditions still persist today and have become an ongoing issue. These poor conditions affect individuals living in metropolitan areas more significantly than suburban or rural areas. Pollution from industrial operations and transportation vehicles have led to increased emission outputs recently. Climate change further aggravates air quality problems by raising pollutant and allergen concentrations. The detrimental consequences of poor air quality include increased incidence of disease processes like asthma, chronic obstructive pulmonary disease (COPD) and lung cancer. To keep up with the well-being of people globally, it is important that actions be taken to battle contamination in the climate so its impact on public health can be limited.Conclusions: Poor air quality and recent worsening of industrial emissions have had a negative impact on lung-related illnesses. Future mitigation strategies should be taken to reduce pollution and treat diseases earlier in their course. Some of these strategies include more reliance on alternative energy sources, creation of mass transit systems and increased rates of recycling.
The impacts of climate change and air pollution on respiratory diseases present significant global health challenges. This review aims to investigate the effects of the interactions between these challenges focusing on respiratory diseases. Climate change is predicted to increase the frequency and intensity of extreme weather events amplifying air pollution levels and exacerbating respiratory diseases. Air pollution levels are projected to rise due to ongoing economic growth and population expansion in many areas worldwide, resulting in a greater burden of respiratory diseases. This is especially true among vulnerable populations like children, older adults, and those with pre-existing respiratory disorders. These challenges induce inflammation, create oxidative stress, and impair the immune system function of the lungs. Consequently, public health measures are required to mitigate the effects of climate change and air pollution on respiratory health. The review proposes that reducing greenhouse gas emissions contribute to slowing down climate change and lessening the severity of extreme weather events. Enhancing air quality through regulatory and technological innovations also helps reduce the morbidity of respiratory diseases. Moreover, policies and interventions aimed at improving healthcare access and social support can assist in decreasing the vulnerability of populations to the adverse health effects of air pollution and climate change. In conclusion, there is an urgent need for continuous research, establishment of policies, and public health efforts to tackle the complex and multi-dimensional challenges of climate change, air pollution, and respiratory health. Practical and comprehensive interventions can protect respiratory health and enhance public health outcomes for all.
PURPOSE OF REVIEW: With increasing industrialization, exposure to ambient and wildfire air pollution is projected to increase, necessitating further research to elucidate the complex relationship between exposure and sinonasal disease. This review aims to summarize the role of ambient and wildfire air pollution in chronic rhinosinusitis (CRS) and olfactory dysfunction and provide a perspective on gaps in the literature. RECENT FINDINGS: Based on an emerging body of evidence, exposure to ambient air pollutants is correlated with the development of chronic rhinosinusitis in healthy individuals and increased symptom severity in CRS patients. Studies have also found a robust relationship between long-term exposure to ambient air pollutants and olfactory dysfunction. Ambient air pollution exposure is increasingly recognized to impact the development and sequelae of sinonasal pathophysiology. Given the rising number of wildfire events and worsening impacts of climate change, further study of the impact of wildfire-related air pollution is a crucial emerging field.
INTRODUCTION: The associations between non-optimal ambient temperature, air pollution and SARS-CoV-2 infection and post COVID-19 condition (PCC) remain constrained in current understanding. We conducted a retrospective analysis to explore how ambient temperature affected SARS-CoV-2 infection in individuals who later developed PCC compared to those who did not. We investigated if these associations were modified by air pollution. METHODS: We conducted a bidirectional time-stratified case-crossover study among individuals who tested positive for SARS-CoV-2 between May 2021 and June 2022. We included 6302 infections, with 2850 PCC cases. We used conditional logistic regression and distributed lag non-linear models to obtain odds ratios (OR) and 95% confidence intervals (CI) for non-optimal temperatures relative to the period median temperature (10.6 °C) on lags 0 to 5. For effect modification, daily average PM(2.5) concentrations were categorized using the period median concentration (8.8 μg/m(3)). Z-tests were used to compare the results by PCC status and PM(2.5). RESULTS: Non-optimal cold temperatures increased the cumulative odds of infection (OR = 1.93; 95%CI:1.67-2.23, OR = 3.53; 95%CI:2.72-4.58, for moderate and extreme cold, respectively), with the strongest associations observed for non-PCC cases. Non-optimal heat temperatures decreased the odds of infection except for moderate heat among PCC cases (OR = 1.32; 95%CI:0.89-1.96). When PM(2.5) was >8.8 μg/m(3), the associations with cold were stronger, and moderate heat doubled the odds of infection with later development of PCC (OR = 2.18; 95%CI:1.01-4.69). When PM(2.5) was ≤8.8 μg/m(3), exposure to non-optimal temperatures reduced the odds of infection. CONCLUSION: Exposure to cold increases SARS-CoV2 risk, especially on days with moderate to high air pollution. Heated temperatures and moderate to high air pollution during infection may cause PCC. These findings stress the need for mitigation and adaptation strategies for climate change to reduce increasing trends in the frequency of weather extremes that have consequences on air pollution concentrations.
The association between heatwaves and cognitive impairment in older adults, especially the joint effect of air pollution and green space on this association, remains unknown. The present cohort study used data from waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) from 2008 to 2018. Heatwaves were defined as having daily maximum temperature ≥ 92.5th, 95th and 97.5th percentile that continued at least two, three and four days, measured as the one-year heatwave days prior to the participants’ incident cognitive impairment. Data on the annual average air pollutant concentrations of fine particulate matter (PM(2.5)) and ozone (O(3)) as well as green space exposure (according to the Normalized Difference Vegetation Index (NDVI)) were collected. Time-varying Cox proportional hazards models were constructed to examine the independent effect of heatwaves on cognitive impairment and the combined effect of heatwaves, air pollution, and green space on cognitive impairment. Potential multiplicative interactions were examined by adding a product term of air pollutants and NDVI with heatwaves in the models. The relative excess risk due to interaction (RERI) was calculated to reflect additive interactions. We found that heatwave exposure was associated with higher risks of cognitive impairment, with hazard ratios (HRs) and 95 % confidence intervals (CIs) ranging from 1.035 (95 % CI: 1.016-1.055) to 1.058 (95 % CI: 1.040-1.075). We observed a positive interaction of PM(2.5) concentrations, O(3) concentrations, lack of green space, and heatwave exposure on a multiplicative scale (HRs for product terms >1). Furthermore, we found a synergistic interaction of PM(2.5) concentrations, O(3), lack of green space, and heatwave exposure on an additive scale, with RERIs >0. These results suggest that extreme heat exposure may be a potential risk factor for cognitive impairment in older adults. Additionally, coexposure to air pollution and lack of green space exacerbated the adverse effects of heatwaves on cognitive function.
To review the recent literature on the effects of wildfire smoke (WFS) exposure on asthma and allergic disease, and on potential mechanisms of disease. RECENT FINDINGS: Spatiotemporal modeling and increased ground-level monitoring data are allowing a more detailed picture of the health effects of WFS exposure to emerge, especially with regard to asthma. There is also epidemiologic and some experimental evidence to suggest that WFS exposure increases allergic predisposition and upper airway or sinonasal disease, though much of the literature in this area is focused more generally on PM(2.5) and is not specific for WFS. Experimental evidence for mechanisms includes disruption of epithelial integrity with downstream effects on inflammatory or immune pathways, but experimental models to date have not consistently reflected human disease in this area. Exposure to WFS has an acute detrimental effect on asthma. Potential mechanisms are suggested by in vitro and animal studies.
Promoting energy efficiency is crucial for reducing energy consumption, yet its impact on human health remains discussed. This study examines the relationship between household energy efficiency, ambient air pollution, climate change, and mortality risk from chronic respiratory diseases. The study collected observational data in six major cities in Taiwan from 2008 to 2020. The energy efficiency level was determined using the input demand function derived from the stochastic frontier analysis (SFA). Subsequently, analysis was conducted employing a dynamic panel data model and a pooled mean group estimator. The study’s findings indicate that enhancing household energy efficiency decreases the mortality rate associated with chronic respiratory
The allocation of resources towards the development and enhancement of urban parks offers an effective strategy for promoting and improving the health and well-being of urban populations. Investments in urban parks can result in a multitude of health benefits. The increased usage of greenspace by park users has been linked to positive physical and mental health outcomes. Additionally, the expansion of greenspace in urban areas can mitigate harmful impacts from air pollutants, heat, noise, and climate-related health risks. While the health benefits attributed to urban parks and greenspaces are well documented, few studies have measured the economic value of these benefits. This study applied a novel ecohealth economic valuation framework to quantify and estimate the potential economic value of health benefits attributed to the development of a proposed park in the downtown core of Peterborough, Canada. The results indicated that development of the small urban park will result in annual benefits of CAD 133,000 per year, including CAD 109,877 in the avoided economic burden of physical inactivity, CAD 23,084 in health savings associated with improved mental health, and CAD 127 in health savings attributed to better air quality. When including the economic value of higher life satisfaction, the economic benefit is more than CAD 4 million per year. The study demonstrates the value of developing and enhancing urban parks as a strategy to improve population health and well-being, and as a means of cost savings to the medical system.
Iraq is one of the regions most affected by climate change around the world. These multidimensional effects of climate and pollution must be taken into consideration when estimating both climate and air pollution-related impacts, in order to develop appropriate health policies and measures to address both current and future climate and pollution challenges. The study was conducted in the Iraqi governorate of Salah al-Din, during the fall, winter and spring seasons of the year 2021-2022, with the aim of evaluating the level of pollutants in the atmospheric air for three regions: Abotuama rural area, Baiji oil refinery and the city of Tikrit. The concentrations of each of the toxic gases were measured: SO2, NO, NO2, HCL, HF, TVOC, CO2 and CO, as well as temperatures. Significant differences were found between the study locations and seasons for all the variables that were tested, as Baiji refinery recorded the highest concentrations of SO2, NO, NO2, HCL, FH and TVOC at 3.5 ppm, 10.78 ppm, 7.475 ppm, 13.1 ppm, 0.8 mg m-3 and 15.25 ppm, respectively. The site of Tikrit recorded the highest concentrations of CO2 and CO, which were 1016 ppm and 29.85 mg m-3, respectively. While the spring season recorded the highest concentrations of SO2, HCL, TVOC and CO compounds, followed by the winter season of NO2, FH and TVOC compounds, the temperature rates were identical in the three study sites and during the fall, winter and spring seasons, reaching 30.25, 12.5 and 31 & DEG;C during the three seasons, respectively. The results of analyzing the relationship between temperature and pollutant concentrations showed that SO2, NO, HCl, and CO increase in hot seasons, while NO2, HF, TVOC, and CO2 pollutant concentrations increase during cold seasons.
Evidence suggests an association between air pollutant exposure and worse outcomes for respiratory viral diseases, like COVID-19. However, does breathing polluted air over many years affect the susceptibility to SARS-CoV-2 infection or severity of COVID-19 disease, and how intense are these effects? As climate change intensifies, air pollutant levels may rise, which might further affect the burden of respiratory viral diseases. We assessed the effect of increasing exposure to PM2.5 (particulate matter = 2.5 microns in diameter) on SARS-CoV-2 susceptibility or COVID-19 severity and projected the impact on infections and hospitalisations over two years. Simulations in a hypothetical, representative population show that if exposure affects severity, then hospital admissions are projected to increase by 5-10% for a one-unit exposure increase. However, if exposure affects susceptibility, then infections would increase with the potential for onward transmission and hospital admissions could increase by over 60%. Implications of this study highlight the importance of considering this potential additional health and health system burden as part of strategic planning to mitigate and respond to changing air pollution levels. It is also important to better understand at which point PM2.5 exposure affects SARS-CoV-2 infection through to COVID-19 disease progression, to enable improved protection and better support of those most vulnerable.
Elevated surface concentrations of ozone and fine particulate matter (PM(2.5)) can lead to poor air quality and detrimental impacts on human health. These pollutants are also termed Near-Term Climate Forcers (NTCFs) as they can also influence the Earth’s radiative balance on timescales shorter than long-lived greenhouse gases. Here we use the Earth system model, UKESM1, to simulate the change in surface ozone and PM(2.5) concentrations from different NTCF mitigation scenarios, conducted as part of the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). These are then combined with relative risk estimates and projected changes in population demographics, to estimate the mortality burden attributable to long-term exposure to ambient air pollution. Scenarios that involve the strong mitigation of air pollutant emissions yield large future benefits to human health (25%), particularly across Asia for black carbon (7%), when compared to the future reference pathway. However, if anthropogenic emissions follow the reference pathway, then impacts to human health worsen over South Asia in the short term (11%) and across Africa (20%) in the longer term. Future climate change impacts on air pollutants can offset some of the health benefits achieved by emission mitigation measures over Europe for PM(2.5) and East Asia for ozone. In addition, differences in the future chemical environment over regions are important considerations for mitigation measures to achieve the largest benefit to human health. Future policy measures to mitigate climate warming need to also consider the impact on air quality and human health across different regions to achieve the maximum co-benefits.
BACKGROUND: Tuberculosis (TB) is a severe public health problem globally. Previous studies have revealed insufficient and inconsistent associations between air pollutants, meteorological factors and TB cases. Yet few studies have examined the associations between air pollutants, meteorological factors and TB cases in Beijing. OBJECTIVE: The purpose of this study was to explore the impact of air pollutants and meteorological factors on TB in Beijing, and to provide novel insights into public health managers to formulate control strategies of TB. METHODS: Data on the daily case of TB in Beijing during 2014-2020 were obtained from Chinese tuberculosis information management system. Concurrent data on the daily PM(10), PM(2.5), SO(2), NO(2), CO and O(3), were obtained from the online publication platform of the Chinese National Environmental Monitoring Center. Daily average temperature, average wind speed, relative humidity, sunshine duration and total precipitation were collected from the China Meteorological Science Data Sharing Service System. A distributed lag non-linear model was fitted to identify the non-linear exposure-response relationship and the lag effects between air pollutions, meteorological factors and TB cases in Beijing. RESULTS: In the single-factor model, the excess risk (ER) of TB was significantly positively associated with every 10 μg/m(3) increase in NO(2) in lag 1 week (ER: 1.3%; 95% confidence interval [CI]: 0.4%, 2.3%) and every 0.1 m/s increase in average wind speed in lag 5 weeks (ER: 0.3%; 95% CI: 0.1%, 0.5%), and was negatively associated with every 10 μg/m(3) increase in O(3) in lag 1 week (ER: -1.2%; 95% CI: -1.8%, -0.5%), every 5 °C increase in average temperature (ER: -1.7%; 95% CI: -2.9%, -0.4%) and every 10% increase in average relative humidity (ER: -0.4%; 95% CI: -0.8%, -0.1%) in lag 10 weeks, respectively. In the multi-factor model, the lag effects between TB cases and air pollutants, meteorological factors were similar. The subgroup analysis suggests that the effects of NO(2), O(3), average wind speed and relative humidity on TB were greater in male or labor age subgroup, while the effect of CO was greater in the elderly. In addition, no significant associations were found between PM(2.5), SO(2,) sunshine duration and TB cases. CONCLUSION: Our findings provide a better understanding of air pollutants and meteorological factors driving tuberculosis occurrence in Beijing, which enhances the capacity of public health manager to target early warning and disease control policy-making.
The associations of air pollution and meteorological factors with the outpatient visits of urticaria remain poorly studied. This study aimed to assess the association between air pollution, meteorological factors, and daily outpatient visits for urticaria in Shijiazhuang, China, during 2014-2019. Daily recordings of air pollutant concentrations, meteorological data, and outpatient visits data for urticaria were collected during the 6 years. Descriptive research methods were used to describe the distribution characteristics and demographic features of urticaria. A combination of the generalized linear regression model (GLM) and distribution lag nonlinear model (DLNM) was used to evaluate the lag association between environmental factors and daily outpatient visits for urticaria. Stratified analyses by gender (male; female) and age (< 18 years; 18-39 years; > 39 years) were further conducted. The dose-response relationship between daily urticaria visits and CO, NO(2), O(3), temperature, and relative humidity was nonlinear. High concentrations of CO, NO(2), O(3), and high temperatures increased the risk of urticaria outpatient visits. The maximum cumulative association of high concentrations of CO, NO(2), and O(3) was lag 0-14 days (CO: RR = 1.10, 95%CI: 1.06, 1.31; NO(2): RR = 1.09, 95%CI: 1.01, 1.08; O(3): RR = 1.16, 95%CI: 1.08, 1.25), and high temperatures was lag 0-7 days (RR = 1.27, 95%CI: 1.14, 1.41). Low concentrations of NO(2), O(3), and high humidity, on the other hand, act as protective factors for urticaria outpatient. The maximum cumulative association of low concentrations of NO(2) was the 0-day lag (RR = 0.97, 95%CI: 0.95, 0.99), O(3) was lag 0-5 days (RR = 0.94, 95%CI: 0.88, 0.99), and high humidity was lag 0-10 days (RR = 0.93, 95%CI: 0.89, 0.98). Stratified analyses showed that the risk of urticaria outpatient visits was higher for the males and in the < 18 years age group. In conclusion, we found that the development of urticaria in Shijiazhuang has a distinct seasonal and cyclical nature. Air pollutants and meteorological factors had varying degrees of influence on the risk of urticaria outpatient visits. This study provides indirect evidence for a link between air pollution, meteorological factors, and urticaria outpatient visits.
Wildfires constitute a growing source of extremely high levels of particulate matter that is less than 2.5 microns in diameter (PM2.5). Recently, toxicologic and epidemiologic studies have shown that PM2.5 generated from wildfires may have a greater health burden than PM2.5 generated from other pollutant sources. This study examined the impact of PM2.5 on hospitalizations for respiratory diseases in California between 2006 and 2019 using a health impact assessment approach that considers differential concentration-response functions (CRF) for PM2.5 from wildfire and non-wildfire sources of emissions. We quantified the burden of respiratory hospitalizations related to PM2.5 exposure at the zip code level through two different approaches: (a) naïve (considering the same CRF for all PM2.5 emissions) and (b) nuanced (considering different CRFs for PM2.5 from wildfires and from other sources). We conducted a Geographically Weighted Regression to analyze spatially varying relationships between the delta (i.e., the difference between the naïve and nuanced approaches) and the Centers for Disease Control and Prevention’s Social Vulnerability Index (SVI). A higher attributable number of respiratory hospitalizations was found when accounting for the larger health burden of wildfire PM2.5. We found that, between 2006 and 2019, the number of hospitalizations attributable to PM2.5 may have been underestimated by approximately 13% as a result of not accounting for the higher CRF of wildfire-related PM2.5 throughout California. This underestimation was higher in northern California and areas with higher SVI rankings. The relationship between delta and SVI varied spatially across California. These findings can be useful for updating future air pollution guideline recommendations.
BACKGROUND: In 2020, the American West faced two competing challenges: the COVID-19 pandemic and the worst wildfire season on record. Several studies have investigated the impact of wildfire smoke (WFS) on COVID-19 morbidity and mortality, but little is known about how these two public health challenges impact mortality risk for other causes. OBJECTIVES: Using a time-series design, we evaluated how daily risk of mortality due to WFS exposure differed for periods before and during the COVID-19 pandemic. METHODS: Our study included daily data for 11 counties in the Front Range region of Colorado (2010-2020). We assessed WFS exposure using data from the National Oceanic and Atmospheric Administration and used mortality counts from the Colorado Department of Public Health and Environment. We estimated the interaction between WFS and the pandemic (an indicator variable) on mortality risk using generalized additive models adjusted for year, day of week, fine particulate matter, ozone, temperature, and a smoothed term for day of year. RESULTS: WFS impacted the study area on 10% of county-days. We observed a positive association between the presence of WFS and all-cause mortality risk (incidence rate ratio (IRR) = 1.03, 95%CI: 1.01-1.04 for same-day exposures) during the period before the pandemic; however, WFS exposure during the pandemic resulted in decreased risk of all-cause mortality (IRR = 0.90, 95%CI: 0.87-0.93 for same-day exposures). DISCUSSION: We hypothesize that mitigation efforts during the first year of the pandemic, e.g., mask mandates, along with high ambient WFS levels encouraged health behaviors that reduced exposure to WFS and reduced risk of all-cause mortality. Our results suggest a need to examine how associations between WFS and mortality are impacted by pandemic-related factors and that there may be lessons from the pandemic that could be translated into health-protective policies during future wildfire events.
The Harmattan, a dry, northeasterly trade wind, transports large quantities of Saharan dust over the Sahelian region during the dry season (December-March). Studies have shown that bacterial meningitis outbreaks in Sahelian regions show hyper-endemic to endemic levels during high-dust months. We examine the (a) seasonality and intraseasonal variability of dust, climate, and meningitis and the (b) quantitative relationships between various dust proxies with meningitis lags of 0-10 weeks in Senegal from 2012 to 2017. The results show that the onset of the meningitis season occurs in February, roughly 2 months after the dusty season has begun. The meningitis season peaks at the beginning of April, when northeasterly wind speeds and particulate matter (PM) are relatively high, and the meningitis season ends near the end of June, when temperature and humidity rise and northeasterly wind speeds decline. Furthermore, we find that Senegal’s relatively high humidity year-round may help slow the transmission of the infection, contributing to a lower disease incidence than landlocked countries in the meningitis belt. Lastly, our results suggest the desert dust may have a significant impact on the onset to the peak of the meningitis season in Senegal, particularly at the 0-2 and 10-week lag, whether that be directly through biological processes or indirectly through changes in human behavior. PM and visibility, however, are not in phase with aerosol optical depth throughout the year and consequently show different relationships with meningitis. This study further exemplifies the critical need for more PM, meteorological, and meningitis measurements in West Africa to further resolve these relationships.
It is well recognized that carbon dioxide and air pollutants share similar emission sources so that synergetic policies on climate change mitigation and air pollution control can lead to remarkable co-benefits on greenhouse gas reduction, air quality improvement, and improved health. In the context of carbon peak, carbon neutrality, and clean air policies, this perspective tracks and analyzes the process of the synergetic governance of air pollution and climate change in China by developing and monitoring 18 indicators. The 18 indicators cover the following five aspects: air pollution and associated weather-climate conditions, progress in structural transition, sources, inks, and mitigation pathway of atmospheric composition, health impacts and benefits of coordinated control, and synergetic governance system and practices. By tracking the progress in each indicator, this perspective presents the major accomplishment of coordinated control, identifies the emerging challenges toward the synergetic governance, and provides policy recommendations for designing a synergetic roadmap of Carbon Neutrality and Clean Air for China.
Environmental risk factors that have an impact on the ocular surface were reviewed and associations with age and sex, race/ethnicity, geographical area, seasonality, prevalence and possible interactions between risk factors are reviewed. Environmental factors can be (a) climate-related: temperature, humidity, wind speed, altitude, dew point, ultraviolet light, and allergen or (b) outdoor and indoor pollution: gases, particulate matter, and other sources of airborne pollutants. Temperature affects ocular surface homeostasis directly and indirectly, precipitating ocular surface diseases and/or symptoms, including trachoma. Humidity is negatively associated with dry eye disease. There is little data on wind speed and dewpoint. High altitude and ultraviolet light exposure are associated with pterygium, ocular surface degenerations and neoplastic disease. Pollution is associated with dry eye disease and conjunctivitis. Primary Sjögren syndrome is associated with exposure to chemical solvents. Living within a potential zone of active volcanic eruption is associated with eye irritation. Indoor pollution, “sick” building or house can also be associated with eye irritation. Most ocular surface conditions are multifactorial, and several environmental factors may contribute to specific diseases. A systematic review was conducted to answer the following research question: “What are the associations between outdoor environment pollution and signs or symptoms of dry eye disease in humans?” Dry eye disease is associated with air pollution (from NO(2)) and soil pollution (from chromium), but not from air pollution from CO or PM(10). Future research should adequately account for confounders, follow up over time, and report results separately for ocular surface findings, including signs and symptoms.
Current practices in the U.S. health care industry drive climate change. This review summarizes the vast research on the negative health effects of the climate crisis on patients as relevant to obstetrics and gynecology. We further propose solutions to decarbonize operating rooms, labor and delivery units, and nurseries and neonatal intensive care units through evidence-based reduction in our single-use supply, energy, and water, as well as anesthetic gases and appropriate waste sorting.
In this study, we leverage multiple linear regression and quantile regression combined with a novel deep learning tool (SHapley Additive exPlanations) to isolate the impact of meteorology on surface ozone pollution and to assess the effectiveness of emission reduction measures across the Contiguous United States (US) during the latest climate period (1991-2020). The findings demonstrate that all regions except the Northern Rockies and the Southwest experienced decreasing trends in median values during the warm season, with rural stations in the Southeast and urban stations in the Northeast experiencing the greatest declines of-1.29 +/- 0.07 and-0.85 +/- 0.08 ppb.a- 1, respectively. Similar to the original data, the median values of adjusted MDA8 (Maximum Daily 8-h Average) ozone show negative trends in all regions except for Southwest urban stations, with the highest recorded in rural stations of the Southeast (-1.13 +/- 0.05 ppb.a- 1) and urban stations of the Northeast (-0.79 +/- 0.06 ppb.a- 1). In addition, the 95th percentile values of original and adjusted MDA8 ozone decreased in all regions in which Northeast urban stations had the greatest reduction (original: 3.53 +/- 0.29 ppb.a- 1, adjusted: 2.96 +/- 0.27 ppb.a- 1). Our results suggest that meteorological inter-annual variability reduces the ozone burden during the warm season in the eastern US and southern California; at the same time, it contributes to increased ozone pollution in the central US, Southwest, and northern California, indicating that efforts to reduce air pollution may be hindered by climate change. Our analysis of the impact of short-term exposure to ozone on health shows that the South was the most positively impacted by emission control policies implemented after 2000, and the Northeast had the highest number of prevented deaths (30.45 deaths prevented/million people) resulting from respiratory diseases. The results of this study should benefit air quality managers and policy -makers, particularly in their efforts to update ozone mitigation strategies.
BACKGROUND: There is emerging evidence that air pollution exposure increases the risk of developing liver cancer. To date, there have been four epidemiologic studies conducted in the United States, Taiwan, and Europe showing generally consistent positive associations between ambient exposure to air pollutants, including particulate matter <2.5 μm in aerodynamic diameter (PM(2.5)) and nitrogen dioxide (NO(2)), and liver cancer risk. There are several research gaps and thus valuable opportunities for future work to continue building on this expanding body of literature. The objectives of this paper are to narratively synthesize existing epidemiologic literature on the association between air pollution exposure and liver cancer incidence and describe future research directions to advance the science of understanding the role of air pollution exposure in liver cancer development. FUTURE RESEARCH DIRECTIONS: include 1) accounting for potential confounding by established risk factors for the predominant histological subtype, hepatocellular carcinoma (HCC); 2) examination of incident primary liver cancer outcomes with consideration of potential differential associations according to histology; 3) air pollution exposure assessments considering early-life and/or historical exposures, residential histories, residual confounding from other sources of air pollution (e.g., tobacco smoking), and integration of geospatial ambient exposure modeling with novel biomarker technologies; 4) examination of air pollution mixtures experienced in the exposome; 5) consideration of increased opportunities for exposure to outdoor air pollution due to climate change (e.g., wildfires); and 6) consideration of modifying factors for air pollution exposure, such as socioeconomic status, that may contribute to disparities in liver cancer incidence. CONCLUSIONS: In light of mounting evidence demonstrating that higher levels of air pollution exposure increase the risk for developing liver cancer, methodological considerations primarily concerning residual confounding and improved exposure assessment are warranted to robustly demonstrate an independent association for air pollution as a hepatocarcinogen.
Due to global warming, an increased number of open fires is becoming a major contributor to PM(2.5) pollution and thus a threat to public health. However, the burden of stillbirths attributable to fire-sourced PM(2.5) is unknown. In low- and middle-income countries (LMICs), there is a co-occurrence of high baseline stillbirth rates and frequent firestorms, which may lead to a geographic disparity. Across 54 LMICs, we conducted a self-matched case-control study, making stillbirths comparable to the corresponding livebirths in terms of time-invariant characteristics (e.g., genetics) and duration of gestational exposure. We established a joint-exposure-response function (JERF) by simultaneously associating stillbirth with fire- and non-fire-sourced PM(2.5) concentrations, which were estimated by fusing multi-source data, such as chemical transport model simulations and satellite observations. During 2000-2014, 35,590 pregnancies were selected from multiple Demographic and Health Surveys. In each mother, a case of stillbirth was compared to her livebirth(s) based on gestational exposure to fire-sourced PM(2.5). We further applied the JERF to assess stillbirths attributable to fire-sourced PM(2.5) in 136 non-Western countries. The disparity was evaluated using the Gini index. The risk of stillbirth increased by 17.4% (95% confidence interval [CI]: 1.6-35.7%) per 10 μg/m(3) increase in fire-sourced PM(2.5). In 2014, referring to a minimum-risk exposure level of 10 μg/m(3), total and fire-sourced PM(2.5) contributed to 922,860 (95% CI: 578,451-1,183,720) and 49,951 (95% CI: 3,634-92,629) stillbirths, of which 10% were clustered within the 6.4% and 0.6% highest-exposure pregnancies, respectively. The Gini index of stillbirths attributable to fire-sourced PM(2.5) was 0.65, much higher than for total PM(2.5) (0.28). Protecting pregnant women against PM(2.5) exposure during wildfires is critical to avoid stillbirths, as the burden of fire-associated stillbirths leads to a geographic disparity in maternal health.
There is worldwide concern about how climate change -which involves rising temperatures- may increase the risk of contracting and developing diseases, reducing the quality of life. This study provides new research that takes into account parameters such as land surface temperature (LST), surface urban heat island (SUHI), urban hotspot (UHS), air pollution (SO(2), NO(2), CO, O(3) and aerosols), the normalized difference vegetation index (NDVI), the normalized difference building index (NDBI) and the proportion of vegetation (PV) that allows evaluating environmental quality and establishes mitigation measures in future urban developments that could improve the quality of life of a given population. With the help of Sentinel 3 and 5P satellite images, we studied these variables in the context of Granada (Spain) during the year 2021 to assess how they may affect the risk of developing diseases (stomach, colorectal, lung, prostate and bladder cancer, dementia, cerebrovascular disease, liver disease and suicide). The results, corroborated by the statistical analysis using the Data Panel technique, indicate that the variables LST, SUHI and daytime UHS, NO(2), SO(2) and NDBI have important positive correlations above 99% (p value: 0.000) with an excess risk of developing these diseases. Hence, the importance of this study for the formulation of healthy policies in cities and future research that minimizes the excess risk of diseases.
The disastrous impact of climate change is already being felt around the globe. Climate change is affected by increasing discharges of greenhouse gases. Pakistan’s metropolitan air pollution is among the utmost severe in the world and it bases main reparations on economic activities and affects human health. This study has been designed for the analysis of ambient air quality in different Karachi areas. The surveys have been done based on seasonal variation i.e., pre and post-monsoon from four industrial zones viz. S.I.T.E area, North Karachi industrial area, Korangi industrial area, and Landhi industrial area in the year 2019. These zones are com-prised of the industrial, residential, and commercial sectors, so heavy traffic and dense populations affect these zones. In this study, HAZ-SCANNER (HIM-6000) apparatus was used for data collection of Ambient air pollutants like nitrogen oxides (NOx), carbon monoxide (CO), and sulphur dioxide (SO2), particulate matters (TSPM, PM10, and PM2.5). For spatial-temporal analysis of ambient air quality GIS interpolation (IDW) technique has been used. It is observed that in post-monsoon, the intensity of particulate matters (TSPM, PM10 & PM2.5), CO, and NO2 values in sampling sites are less to moderate than the values of pre-monsoon due to the seasonal monsoon effects. While North Karachi is at the least risk because of having a small number of scale industries pre-sent. The PM10 & PM2.5 levels average about 2-3 fold greater than the SEPA standards. High levels of ambient air pollutants cause severe health problems and chronic diseases on human health. Therefore, the implementation of rules and regulations regarding ambient air pollutants should be more active.& COPY;2023 L & H Scientific Publishing, LLC. All rights reserved.
BACKGROUND: Wildfires cause significant physical and mental ill-health. How physical and mental symptoms interact following wildfire smoke exposure is unclear, particularly in the context of repeated exposures. In this cross-sectional study we investigated how posttraumatic stress and general psychological distress associated with somatic symptoms in a community exposed to multiple smoke events. METHODS: A random weighted sample of 709 adults exposed to smoke during the 2014 Hazelwood coal mine fire in south-eastern Australia completed a survey in 2020. The survey coincided with the Black Summer wildfires that caused a similar period of smoke haze in the region. Participants self-reported somatic symptoms (PHQ-15) and mine fire-related posttraumatic stress (IES-R) experienced over the previous week, general psychological distress (K10) experienced over the previous four weeks, lifetime health diagnoses and demographic information. Associations between posttraumatic stress, general psychological distress, and each PHQ-15 somatic symptom were analysed using ordinal logistic regression models. RESULTS: Overall, 36.2% of participants reported moderate- or high-level somatic symptomology. The most frequent somatic symptoms were fatigue, limb pain, trouble sleeping, back pain, headaches, and shortness of breath. After controlling for confounding factors, general psychological distress and posttraumatic stress were independently associated with all somatic symptoms (except menstrual problems in females for posttraumatic stress). CONCLUSIONS: Results highlight the high prevalence of somatic symptoms and their association with general psychological distress and posttraumatic stress within a community in the midst of a second large-scale smoke event. It is essential that healthcare providers and public health authorities consider the interconnections of these conditions when supporting communities affected by climate-related disasters.
Wildfire is a major disturbance agent in Arctic boreal and tundra ecosystems that emits large quantities of atmospheric pollutants, including PM(2.5). Under the substantial Arctic warming which is two to three times of global average, wildfire regimes in the high northern latitude regions are expected to intensify. This imposes a considerable threat to the health of the people residing in the Arctic regions. Alaska, as the northernmost state of the US, has a sizable rural population whose access to healthcare is greatly limited by a lack of transportation and telecommunication infrastructure and low accessibility. Unfortunately, there are only a few air quality monitoring stations across the state of Alaska, and the air quality of most remote Alaskan communities is not being systematically monitored, which hinders our understanding of the relationship between wildfire emissions and human health within these communities. Models simulating the dispersion of pollutants emitted by wildfires can be extremely valuable for providing spatially comprehensive air quality estimates in areas such as Alaska where the monitoring station network is sparse. In this study, we established a methodological framework that is based on an integration of the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, the Wildland Fire Emissions Inventory System (WFEIS), and the Arctic-Boreal Vulnerability Experiment (ABoVE) Wildfire Date of Burning (WDoB) dataset, an Arctic-oriented fire product. Through our framework, daily gridded surface-level PM(2.5) concentrations for the entire state of Alaska between 2001 and 2015 for which wildfires are responsible can be estimated. This product reveals the spatio-temporal patterns of the impacts of wildfires on the regional air quality in Alaska, which, in turn, offers a direct line of evidence indicating that wildfire is the dominant driver of PM(2.5) concentrations over Alaska during the fire season. Additionally, it provides critical data inputs for research on understanding how wildfires affect human health which creates the basis for the development of effective and efficient mitigation efforts.
Introduction: Along with climate changes, we see an increase in allergic symptoms and the number of pollen-allergic patients in many countries. Increased allergic symptoms are associated with an elevated ozone exposure which may be linked by impaired epithelial barrier function. This study aimed to quantify the clinical effect of ozone and pollen double exposure (DE). We tested whether ozone impairs barrier-related skin physiology and mucosal functions under double exposure with pollen ozone in grass pollen-allergic patients versus healthy controls. Methods: This case-control study included 8 grass pollen-allergic patients and 8 non-allergic healthy subjects exposed to grass pollen and ozone in the GA(2)LEN pollen chamber, comparing shorter and longer DE duration. Non-invasive skin physiological parameters were assessed, including stratum corneum hydration, skin redness, surface pH, and basal transepidermal water loss (TEWL) as a parameter for epidermal barrier function. The subjects’ general well-being, bronchial, nasal, and ocular symptoms were documented. Results: Skin physiology tests revealed that DE in allergic patients deteriorates the epidermal barrier function, increases the surface pH and skin redness. DE significantly induced nasal secretion in pollen-allergic versus healthy subjects, which was more pronounced with longer DE. The general well-being was significantly impaired under DE versus pollen or ozone alone, with a negative influence of DE-duration. No relevant bronchial symptoms were recorded. Conclusion: Skin physiology and nasal mucosal symptoms and are negatively affected by ozone and grass pollen DE in allergic patients. The negative effects showed, in some parameters, a dose(time)-response relationship. The surface pH can be regarded as a possible modulatory mechanism.
Lung cancer risk from exposure to ambient polycyclic aromatic hydrocarbons (PAHs) is expected to change significantly by 2050 compared to 2008 due to changes in climate and emissions. Integrating a global atmospheric chemistry model, a lung cancer risk model, and plausible future emissions trajectories of PAHs, we assess how global PAHs and their associated lung cancer risk will likely change in the future. Benzo(a)pyrene (BaP) is used as an indicator of cancer risk from PAH mixtures. From 2008 to 2050, the population-weighted global average BaP concentrations under all RCPs consistently exceeded the WHO-recommended limits, primarily attributed to residential biofuel use. Peaks in PAH-associated incremental lifetime cancer risk shift from East Asia (4 x 10(-5)) in 2008 to South Asia (mostly India, 2-4 x 10(-5)) and Africa (1-2 x 10(-5)) by 2050. In the developing regions of Africa and South Asia, PAH-associated lung cancer risk increased by 30-64% from 2008 to 2050, due to increasing residential energy demand in households for cooking, heating, and lighting, the continued use of traditional biomass use, increases in agricultural waste burning, and forest fires, accompanied by rapid population growth in these regions. Due to more stringent air quality policies in developed countries, their PAH lung cancer risk substantially decreased by similar to 80% from 2008 to 2050. Climate change is likely to have minor effects on PAH lung cancer risk compared to the impact of emissions. Future policies, therefore, need to consider efficient combustion technologies that reduce air pollutant emissions, including incomplete combustion products such as PAH.
Atopic dermatitis (AD) is one of the leading burdens of skin disease in children globally. Meteorological factors are involved in the onset and development of AD. Several studies have examined the effects of meteorological factors on AD, but their results are inconsistent, and the understanding of the link between AD and meteorological factors remains inadequate. In this study, a total of 19,702 children aged 0 to 14 visited the outpatient clinic for AD from 2015 to 2019 in Lanzhou, China. A distributed lag nonlinear model (DLNM) applies to evaluate effects of meteorological factors on childhood AD in Lanzhou, China, and further explored age and gender differences. It was found that extremely high or low temperatures, extremely high diurnal temperature range (DTR), extremely low relative humidity (RH), and extremely high wind speed (WS) increased the risk of outpatient visits for childhood AD. Effects of extremely high DTR and extremely high WS were more intense, with maximum cumulative risks of 2.248 (95% CI 1.798, 2.811) and 3.834 (95% CI 3.086, 4.759) at lag 0-21, respectively. Furthermore, the combination of low temperature and low RH can also contribute to the higher risk of childhood AD. For extreme temperatures, children aged 7-14 years were more vulnerable. For extremely low RH, extremely high DTR and WS, boys and children aged 0-3 years were more vulnerable. Public health departments should strengthen publicity and education about how meteorological factors affect childhood AD and develop sex- and age-specific preventative measures.
Hemorrhagic stroke (HS) is associated with severe morbidity and high mortality. Identifying the trigger factors for HS is critical for disease prevention. This study aimed to assess the associations between short-term environmental triggers (STETs) and HS risk. We systematically searched six databases for articles published up to September 9, 2022. Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using random-effect models to evaluate the associations between STETs and the risk of HS. Heterogeneity was assessed using Cochran Q and I(2) tests. A total of 63 studies were included for analysis. Of these, 40 focused on air pollutants and 23 on meteorological factors. Pooling results showed that exposure to particulate matter 2.5 (PM(2.5;) OR, 1.003 per 10 μg/m(3); 95% CI, 1.001-1.007), sulfur dioxide (SO(2;) OR, 1.022 per 10 ppb; 95% CI, 1.005-1.040), and nitrogen dioxide (NO(2;) OR, 1.026 per 10 ppb; 95% CI, 1.004-1.047) was associated with an increase in HS risk. Moreover, exposure to PM(2.5) (OR, 1.018 per 10 μg/m(3); 95% CI, 1.009-1.027) and SO(2) (OR, 1.102 per 10 ppb; 95% CI, 1.010-1.204) was positively associated with the risk of intracerebral hemorrhage. In addition, extreme temperature, high pressures, high and low relative humidity were potentially associated with HS risk. Targeted preventive measures to limit the effect of these air pollutants and extreme meteorological factors should be taken to reduce the HS disease burden. Further studies are warranted to verify these findings.
While some studies report a possible association between heat waves and kidney disease and kidney-related conditions, there still is no consistent scientific consensus on the matter or on the role played by other variables, such as air pollution and relative humidity. Ecological retrospective time series study 01-01-2013 to 31-12-2018). Dependent variables: daily emergency hospitalisations due to kidney disease (KD), acute kidney injury (AKI), lithiasis (L), dysnatraemia (DY) and hypovolaemia (HPV). Independent variables: maximum and minimum daily temperature (Tmax, Tmin, °C), and daily relative humidity (RH, %). Other variables were also calculated, such as the daily temperature for risk of kidney disease (Theat, °C) and low daily hazardous relative humidity (HRH%). As variables of air pollution, we used the daily mean concentrations of PM(10), PM(2.5), NO(2) and O(3) in μg/m3. Based on these, we then calculated their daily excesses over World Health Organisation (WHO) guideline levels ((h)PM(10), (h)PM(2.5), (h)NO(2) and (h)O(3) respectively). Poisson family generalised linear models (GLMs) (link = log) were used to calculate relative risks (RRs), and attributable risks and attributable admissions. In the models, we controlled for the covariates included: seasonalities, trend, autoregressive component, day of the week, month and year. A statistically significant association was found between Theat and all the dependent variables analysed. The greatest AKI disease burden was attributable to Theat (2.2 % (1.7, 2.6) of attributable hospital admissions), followed by (h)NO(2) (1.7 % (0.9, 3.4)) and HRH (0.8 (0.6, 1.1)). In the case of hypovolaemia and dysnatraemia, the greatest disease burden again corresponded to Theat, with 6.9 % (6.2, 7.6) and 5.7 (4.8, 6.6) of attributable hospital admissions respectively. Episodes of extreme heat exacerbate daily emergency hospital admissions due to kidney disease and kidney-related conditions; and attributable risks are likewise seen for low relative humidity and high ozone levels.
BACKGROUND: Few studies investigated the impact of particulate matter (PM(2.5)) on some symptom exacerbations that are not perceived as severe enough to search for medical assistance. We aimed to study the association of short-term daily total PM(2.5) exposure with work loss due to sickness among adults living in California. METHODS: We included 44,544 adult respondents in the workforce from 2015 to 2018 California Health Interview Survey data. Daily total PM(2.5) concentrations were linked to respondents’ home addresses from continuous spatial surfaces of PM(2.5) generated by a geostatistical surfacing algorithm. We estimated the effect of a 2-week average of daily total PM(2.5) exposure on work loss using logistic regression models. RESULTS: About 1.69% (weighted percentage) of adult respondents reported work loss in the week before the survey interview. The odds ratio of work loss was 1.45 (odds ratio [OR] = 1.45, 95% confidence interval [CI]: 1.03, 2.03) when a 2-week average of daily total PM(2.5) exposure was higher than 12 µg/m(3). The OR for work loss was 1.05 (95% CI: 0.98, 1.13) for each 2.56ug/m(3) increase in the 2-week average of daily total PM(2.5) exposure, and became stronger among those who were highly exposed to wildfire smoke (OR = 1.06, 95% CI: 1.00, 1.13), compared to those with lower wildfire smoke exposure (OR = 1.04, 95% CI: 0.79, 1.39). CONCLUSIONS: Our findings suggest that short-term ambient PM(2.5) exposure is positively associated with work loss due to sickness and the association was stronger among those with higher wildfire smoke exposure. It also indicated that the current federal and state PM(2.5) standards (annual average of 12 µg/m(3)) could be further strengthened to protect the health of the citizens of California.
BACKGROUND AND OBJECTIVES: Chronic conditions and multimorbidity are increasing worldwide. Yet, understanding the relationship between climate change, air pollution, and longitudinal changes in multimorbidity is limited. Here, we examined the effects of sociodemographic and environmental risk factors in multimorbidity among adults aged 45+ and compared the rural-urban disparities in multimorbidity. RESEARCH DESIGN AND METHODS: Data on the number of chronic conditions (up to 14), sociodemographic, and environmental factors were collected in 4 waves of the China Health and Retirement Longitudinal Study (2011-2018), linked with the full-coverage particulate matter 2.5 (PM(2.5)) concentration data set (2000-2018) and temperature records (2000-2018). Air pollution was assessed by the moving average of PM(2.5) concentrations in 1, 2, 3, 4, and 5 years; temperature was measured by 1-, 2-, 3-, 4-, and 5-year moving average and their corresponding coefficients of variation. We used the growth curve modeling approach to examine the relationship between climate change, air pollution, and multimorbidity, and conducted a set of stratified analyses to study the rural-urban disparities in multimorbidity related to temperature and PM(2.5) exposure. RESULTS: We found the higher PM(2.5) concentrations and rising temperature were associated with higher multimorbidity, especially in the longer period. Stratified analyses further show the rural-urban disparity in multimorbidity: Rural respondents have a higher prevalence of multimorbidity related to rising temperature, whereas PM(2.5)-related multimorbidity is more severe among urban ones. We also found temperature is more harmful to multimorbidity than PM(2.5) exposure, but PM(2.5) exposure or temperature is not associated with the rate of multimorbidity increase with age. DISCUSSION AND IMPLICATIONS: Our findings indicate that there is a significant relationship between climate change, air pollution, and multimorbidity, but this relationship is not equally distributed in the rural-urban settings in China. The findings highlight the importance of planning interventions and policies to deal with rising temperature and air pollution, especially for rural individuals.
BACKGROUND: During wildfire smoke episodes, school and childcare facility staff and those who support them rely upon air quality data to inform activity decisions. Where ambient regulatory monitor data is sparse, low-cost sensors can help inform local outdoor activity decisions, and provide indoor air quality data. However, there is no established protocol for air quality decision-makers to use sensor data for schools and childcare facilities. To develop practical, effective toolkits to guide the use of sensors in school and childcare settings, it is essential to understand the perspectives of the potential end-users of such toolkit materials. METHODS: We conducted 15 semi-structured interviews with school, childcare, local health jurisdiction, air quality, and school district personnel regarding sensor use for wildfire smoke response. Interviews included sharing PM(2.5) data collected at schools during wildfire smoke. Interviews were transcribed and transcripts were coded using a codebook developed both a priori and amended as additional themes emerged. RESULTS: Three major themes were identified by organizing complementary codes together: (1) Low-cost sensors are useful despite data quality limitations, (2) Low-cost sensor data can inform decision-making to protect children in school and childcare settings, and (3) There are feasibility and public perception-related barriers to using low-cost sensors. CONCLUSIONS: Interview responses provided practical implications for toolkit development, including demonstrating a need for toolkits that allow a variety of sensor preferences. In addition, participants expected to have a wide range of available time for monitoring, budget for sensors, and decision-making types. Finally, interview responses revealed a need for toolkits to address sensor uses outside of activity decisions, especially assessment of ventilation and filtration.
BACKGROUND: Climate change legislation will require dramatic increases in the energy efficiency of school buildings across the UK by 2050, which has the potential to affect air quality in schools. We assessed how different strategies for improving the energy efficiency of school buildings in England and Wales may affect asthma incidence and associated healthcare utilization costs in the future. METHODS: Indoor concentrations of traffic-related NO(2) were modelled inside school buildings representing 13 climate regions in England and Wales using a building physics school stock model. We used a health impact assessment model to quantify the resulting burden of childhood asthma incidence by combining regional health and population data with exposure-response functions from a recent high-quality systematic review/meta-analysis. We compared the effects of four energy efficiency interventions consisting of combinations of retrofit and operational strategies aiming to improve indoor air quality and thermal comfort on asthma incidence and associated hospitalization costs. RESULTS: The highest childhood asthma incidence was found in the Thames Valley region (including London), in particular in older school buildings, while the lowest concentrations and health burdens were in the newest schools in Wales. Interventions consisting of only operational improvements or combinations of retrofit and operational strategies resulted in reductions in childhood asthma incidence (547 and 676 per annum regional average, respectively) and hospital utilization costs (£52,050 and £64,310 per annum regional average, respectively. Interventions that improved energy efficiency without operational measures resulted in higher childhood asthma incidence and hospital costs. CONCLUSION: The effect of school energy efficiency retrofit on NO(2) exposure and asthma incidence in schoolchildren depends critically on the use of appropriate building operation strategies. The findings from this study make several contributions to fill the knowledge gap about the impact of retrofitting schools on exposure to air pollutants and their effects on children’s health.
Very few researches have concentrated on a variety of time scales to evaluate the association between temperature variation (TV) and childhood asthma (CA), and the evidence for the interaction of air pollutants on this association is lacking. In this study, we aim to estimate the relative risks (RRs) of CA due to TV by following metrics: diurnal temperature range (DTR), temperature changes between neighboring days (TCN), and temperature variability (TV(0-t)); to quantify the seasonal attributable fraction (AF) and number (AN) of CA due to TV; to examine the interactive effects of the TV and air pollutants on CA in different seasons. We mainly applied distributed lagged nonlinear model (DLNM) and conditional Poisson models to evaluate the associations between TV and outpatient visits for CA during 2014-2019 in Lanzhou, China. Additionally, the bivariate response surface model was used to examine the interplay effect of air pollutants. We found that in warm season, the risks of DTR maximum at lag5 (RR = 1.073, 95% CI: 1.017-1.133); TCN showed protective effect. In cold season, the risks of DTR peaked at lag8 (RR = 1.063, 95% CI: 1.027-1.100); the risks of TCN maximum at lag0 (RR = 1.058 95% CI: 1.009-1.109); the estimation of total cases maximized at TV(0-4) in cold season (RR = 1.039 at TV(0-3), 95% CI: 1.001, 1.077) and was the lowest at TV(0-1) in warm season (RR = 0.999, 95% CI: 0.969, 1.030). In addition, the response surface model graphically pictured ambient air pollutants enhanced the DTR/TV(0-4)-CA effect for girls. In conclusion, the RRs of CA are markedly increased by TV exposure, particularly during the colder months. A combined evaluation of DTR, TCN, TV(0-5)∼TV(0-6), NO(2), SO(2), and PM(2.5) should be used to identify the adverse effects of TV on CA.
Climate change has both direct and indirect effects on human health, and some populations are more vulnerable to these effects than others. Viral respiratory infections are most common illnesses in humans, with estimated 17 billion incident infections globally in 2019. Anthropogenic drivers of climate change, chiefly the emission of greenhouse gases and toxic pollutants from burning of fossil fuels, and the consequential changes in temperature, precipitation, and frequency of extreme weather events have been linked with increased susceptibility to viral respiratory infections. Air pollutants like nitrogen dioxide, particulate matter, diesel exhaust particles, and ozone have been shown to impact susceptibility and immune responses to viral infections through various mechanisms, including exaggerated or impaired innate and adaptive immune responses, disruption of the airway epithelial barrier, altered cell surface receptor expression, and impaired cytotoxic function. An estimated 90% of the world’s population is exposed to air pollution, making this a topic with high relevance to human health. This review summarizes the available epidemiologic and experimental evidence for an association between climate change, air pollution, and viral respiratory infection.
Due to rapid urbanization, Delhi experiences frequent pollution events, and the particulate matter load exceeds the prescribed limit often. This study analyzes nanoparticles (10 to 1090 nm) during different emission scenarios, seasonal and meteorological conditions in two phases: April to June 2021 (Period I) and October to November 2021 (Period II). Period I experienced around 31% less concentration of particles (similar to 2.4 x 10(4) cm(-3)) due to lockdown restrictions and, on the other hand, particle concentration increased by 35% compared to normal conditions due to the sudden rise in firework emissions in Period II. Except for the post-Diwali phase (10(4) cm(-3) to 10(5) cm(-3)), the concentrations lie between 10(3) cm(-3) and 10(5) cm(-3). The Aitken modes contribute 10 to 30% of total concentration in both periods. Particles in nucleation and accumulation modes contribute 30 to 40%, 20 to 30%, 15 to 25%, and 35 to 50% in Periods I and II, respectively. Number concentration-based studies are essential for estimating the potential impacts on human health due to air pollution. The study provides information regarding vehicle emission-based particle concentration under various emission scenarios in urban cities, which is crucial for estimation of emissions, health impact assessment, future policy formulation and strategy measures.
Air pollution may be involved in spreading dengue fever (DF) besides rainfalls and warmer temperatures. While particulate matter (PM), especially those with diameter of 10 μm (PM10) or 2.5 μm or less (PM25), and NO2 increase the risk of coronavirus 2 infection, their roles in triggering DF remain unclear. We explored if air pollution factors predict DF incidence in addition to the classic climate factors. Public databases and DF records of two southern cities in Taiwan were used in regression analyses. Month order, PM10 minimum, PM2.5 minimum, and precipitation days were retained in the enter mode model, and SO2 minimum, O3 maximum, and CO minimum were retained in the stepwise forward mode model in addition to month order, PM10 minimum, PM2.5 minimum, and precipitation days. While PM2.5 minimum showed a negative contribution to the monthly DF incidence, other variables showed the opposite effects. The sustain of month order, PM10 minimum, PM2.5 minimum, and precipitation days in both regression models confirms the role of classic climate factors and illustrates a potential biological role of the air pollutants in the life cycle of mosquito vectors and dengue virus and possibly human immune status. Future DF prevention should concern the contribution of air pollution besides the classic climate factors.
OBJECTIVE: Climate and environmental change is a well-known factor causing bronchial asthma in children. After the outbreak of coronavirus disease (COVID-19), climate and environmental changes have occurred. The present study investigated the relationship between climate changes (meteorological and environmental factors) and the number of hospitalizations for pediatric bronchial asthma in Suzhou before and after the COVID-19 pandemic. METHODS: From 2017 to 2021, data on daily inpatients diagnosed with bronchial asthma at Children’s Hospital of Soochow University were collected. Suzhou Meteorological and Environmental Protection Bureau provided daily meteorological and environmental data. To assess the relationship between bronchial asthma-related hospitalizations and meteorological and environmental factors, partial correlation and multiple stepwise regression analyses were used. To estimate the effects of meteorological and environmental variables on the development of bronchial asthma in children, the autoregressive integrated moving average (ARIMA) model was used. RESULTS: After the COVID-19 outbreak, both the rate of acute exacerbation of bronchial asthma and the infection rate of pathogenic respiratory syncytial virus decreased, whereas the proportion of school-aged children and the infection rate of human rhinovirus increased. After the pandemic, the incidence of an acute asthma attack was negatively correlated with monthly mean temperature and positively correlated with PM(2.5). Stepwise regression analysis showed that monthly mean temperature and O(3) were independent covariates (risk factors) for the rate of acute asthma exacerbations. The ARIMA (1, 0, 0) (0, 0, 0) 12 model can be used to predict temperature changes associated with bronchial asthma. CONCLUSION: Meteorological and environmental factors are related to bronchial asthma development in children. The influence of meteorological and environmental factors on bronchial asthma may be helpful in predicting the incidence and attack rates.
California plans to substantially increase the use of prescribed fire to reduce risk of catastrophic wildfires. Although for a beneficial purpose, prescribed fire smoke may still pose a health concern, especially among sensitive populations. We sought to understand community health experience, adaptive capacity, and attitudes regarding wildland and prescribed fire smoke to inform public health guidance. We conducted a cross-sectional survey of medically vulnerable persons in a rural, high fire risk county (N = 106, 76% > 65 years) regarding wildfire and prescribed smoke health effects; health protective actions; information needs; and support for fire management policies. Qualitative comments were reviewed for context and emerging themes. More than half (58%) of participants reported health impacts from wildfire smoke; 26% experienced impacts from prescribed fire smoke. Participants expressed strong support for prescribed fire, although also concerns about safety and smoke. Respondents reported taking actions to reduce smoke exposure (average 5 actions taken per person), but many (47%) lacked confidence that they could successfully protect their health. Persons who were satisfied with the information received tended to be more confident in their ability to protect their health compared to those who were not satisfied (61% vs. 35%). More information was desired on many topics, including notifications about prescribed fire, health protection and exposure reduction. As California expands use of prescribed fire, the need for effective health protective communication regarding smoke is increasingly vital. We recommend seeking solutions that strengthen community resilience and address equity for vulnerable populations.
Wildfires are a significant source of organic aerosol during summer, with major impacts on air quality and climate. However, studies in Europe suggest a surprisingly low (less than 10%) contribution of biomass burning organic aerosol to average summertime fine particulate matter levels. In this study we combine field measurements and atmospheric chemical transport modeling, to demonstrate that the contribution of wildfires to fine particle levels in Europe during summer is seriously underestimated. Our work suggests that the corresponding contribution has been underestimated by a factor of 4-7 and that wildfires were responsible for approximately half of the total OA in Europe during July 2022. This discrepancy with previous work is due to the rapid physicochemical transformation of these emissions to secondary oxidized organic aerosol with an accompanying loss of its organic chemical fingerprints. These atmospheric reactions lead to a regionally distributed background organic aerosol that is responsible for a significant fraction of the health-related impacts caused by fine particles in Europe and probably in other continents. These adverse health effects can occur hundreds or even thousands of kilometers away from the fires. We estimate that wildfire emissions are responsible for 15-22% of the deaths in Europe due to exposure to fine particulate matter during summer.
BACKGROUND: Previous studies have shown that carbon monoxide (CO) poisoning occurs mostly in winter and is associated with severe cold weather (e.g., ice storms, temperature drops). However, according to previous studies, the impact of low temperature on health has a delayed effect, and the existing research cannot fully reveal the delayed effect of cold waves on CO poisoning. OBJECTIVES: The purpose of this study is to analyze the temporal distribution of CO poisoning in Jinan and to explore the acute effect of cold waves on CO poisoning. METHODS: We collected emergency call data for CO poisoning in Jinan from 2013 to 2020 and used a time-stratified case-crossover design combined with a conditional logistic regression model to evaluate the impact of the cold wave day and lag 0-8 days on CO poisoning. In addition, 10 definitions of a cold wave were considered to evaluate the impact of different temperature thresholds and durations. RESULTS: During the study period, a total of 1,387 cases of CO poisoning in Jinan used the emergency call system, and more than 85% occurred in cold months. Our findings suggest that cold waves are associated with an increased risk of CO poisoning in Jinan. When P01, P05, and P10 (P01, P05, and P10 refer to the 1st, 5th, and 10th percentiles of the lowest temperature, respectively) were used as temperature thresholds for cold waves, the most significant effects (the maximum OR value, which refers to the risk of CO poisoning on cold wave days compared to other days) were 2.53 (95% CI:1.54, 4.16), 2.06 (95% CI:1.57, 2.7), and 1.49 (95% CI:1.27, 1.74), respectively. CONCLUSION: Cold waves are associated with an increased risk of CO poisoning, and the risk increases with lower temperature thresholds and longer cold wave durations. Cold wave warnings should be issued and corresponding protective policies should be formulated to reduce the potential risk of CO poisoning.
Emissions from wildfires worsen air quality and can adversely impact human health. This study utilized the fire inventory from NCAR (FINN) as wildfire emissions, and performed air quality modeling of April-October 2012, 2013, and 2014 using the U.S. Environmental Protection Agency CMAQ model under two cases: with and without wildfire emissions. This study then assessed the health impacts and economic values attributable to PM(2.5) from fires. Results indicated that wildfires could lead annually to 4000 cases of premature mortality in the U.S., corresponding to $36 billion losses. Regions with high concentrations of fire-induced PM(2.5) were in the west (e.g., Idaho, Montana, and northern California) and Southeast (e.g., Alabama, Georgia). Metropolitan areas located near fire sources, exhibited large health burdens, such as Los Angeles (119 premature deaths, corresponding to $1.07 billion), Atlanta (76, $0.69 billion), and Houston (65, $0.58 billion). Regions in the downwind of western fires, although experiencing relatively low values of fire-induced PM(2.5), showed notable health burdens due to their large population, such as metropolitan areas of New York (86, $0.78 billion), Chicago (60, $0.54 billion), and Pittsburgh (32, $0.29 billion). Results suggest that impacts from wildfires are substantial, and to mitigate these impacts, better forest management and more resilient infrastructure would be needed.
Globally Ambrosia species (Asteraceae), commonly called ragweed, are recognized to be one of the most problematic groups of invasive weeds and one of the main allergenic genus. Climate and land-use change and air pollution are expected to promote ragweed spread, increase airborne ragweed pollen concentrations (the source of allergens), extend the pollen season, and promote longdistance transport of pollen or sub-pollen particles containing allergens. The allergenicity of pollen itself is going to increase. Likely, all these factors will have meaningful effects in the exacerbation of the sensitization to ragweed pollen and the severity of allergy symptoms. Globally the major health concern regards A. artemisiifolia, because of its very wide global distribution and highly invasive behavior. Together with A. artemisiifolia, also A. trifida and A. psilostachya are species of health concern distributed across different continents, widespread and invasive in several regions. The present review summarizes the characteristics of these species and gives an overview of factors contributing to their allergenicity.
Rapidly changing wildfire regimes across the Western United States have driven more frequent and severe wildfires, resulting in wide-ranging societal threats from wildfires and wildfire-generated smoke. However, common measures of fire severity focus on what is burned, disregarding the societal impacts of smoke generated from each fire. We combine satellite-derived fire scars, air parcel trajectories from individual fires, and predicted smoke PM2.5 to link source fires to resulting smoke PM2.5 and health impacts experienced by populations in the contiguous United States from April 2006 to 2020. We quantify fire-specific accumulated smoke exposure based on the cumulative population exposed to smoke PM2.5 over the duration of a fire and estimate excess asthma-related emergency department (ED) visits as a result of this exposure. We find that excess asthma visits attributable to each fire are only moderately correlated with common measures of wildfire severity, including burned area, structures destroyed, and suppression cost. Additionally, while recent California fires contributed nearly half of the country’s smoke-related excess asthma ED visits during our study period, the most severe individual fire was the 2007 Bugaboo fire in the Southeast. We estimate that a majority of smoke PM2.5 comes from sources outside the local jurisdictions where the smoke is experienced, with 87% coming from fires in other counties and 60% from fires in other states. Our approach could enable broad-scale assessment of whether specific fire characteristics affect smoke toxicity or impact, inform cost-effectiveness assessments for allocation of suppression resources, and help clarify the growing transboundary nature of local air quality.
Non-optimal temperatures are associated with premature deaths globally. However, the evidence is limited in low- and middle-income countries, and the productivity losses due to non-optimal temperatures have not been quantified. We aimed to estimate the work-related impacts and economic losses attributable to non-optimal temperatures in Brazil. We collected daily mortality data from 510 immediate regions in Brazil during 2000 and 2019. A two-stage time-series analysis was applied to evaluate the association between non-optimum temperatures and the Productivity-Adjusted Life-Years (PALYs) lost. The temperature-PALYs association was fitted for each location in the first stage and then we applied meta-analyses to obtain the national estimations. The attributable fraction (AF) of PALY lost due to ambient temperatures and the corresponding economic costs were calculated for different subgroups of the working-age population. A total of 3,629,661 of PALYs lost were attributed to non-optimal temperatures during 2000-2019 in Brazil, corresponding to 2.90 % (95 % CI: 1.82 %, 3.95 %) of the total PALYs lost. Non-optimal temperatures have led to US$104.86 billion (95 % CI: 65.95, 142.70) of economic costs related to PALYs lost and the economic burden was more substantial in males and the population aged 15-44 years. Higher risks of extreme cold temperatures were observed in the South region in Brazil while extreme hot temperatures were observed in the Central West and Northeast regions. In conclusion, non-optimal temperatures are associated with considerable labour losses as well as economic costs in Brazil. Tailored policies and adaptation strategies should be proposed to mitigate the impacts of non-optimal temperatures on the labour supply in a changing climate.
Smoke from wildfires presents one of the greatest threats to air quality, public health, and ecosystems in the United States, especially in the West. Here we quantify the efficacy of prescribed burning as an intervention for mitigating smoke exposure downwind of wildfires across the West during the 2018 and 2020 fire seasons. Using the adjoint of the GEOS-Chem chemical transport model, we calculate the sensitivities of population-weighted smoke concentrations in receptor regions, including states and rural environmental justice communities, to fire emissions upwind of the receptors. We find that the population-weighted smoke exposure across the West during the September 2020 fires was 44 mu g/m(3) but would have been 20%-30% greater had these wildfires occurred in October or November. We further simulate a set of prescribed burn scenarios and find that controlled burning interventions in northern California and the Pacific Northwest could have reduced the population-weighted smoke exposure across the western United States by 21 mu g/m(3) in September 2020, while doing so in all other states would have reduced smoke exposure by only 1.5 mu g/m(3). Satellite records of large, prescribed burns (>1,000 acres, or 4 km(2)) reveal that northern California and western Oregon conducted only seven such prescribed fires over a 6-year period (2015-2020), even though these regions have a disproportionate impact on smoke exposure for rural environmental justice communities and population centers across the West. Our analysis suggests that prioritizing northern California and the Pacific Northwest for prescribed burns might mitigate future smoke exposure.
BACKGROUND: Exposure to wildfire smoke has been linked with a range of health outcomes. However, to date, evidence is limited for the association between wildfire-specific PM(2.5), a primary emission of wildfire smoke, and adverse birth outcomes. OBJECTIVE: We aimed to estimate the risk and burden of preterm birth/term low birth weight, associated with maternal exposure to wildfire-specific PM(2.5). METHODS: A total of 330,884 birth records with maternal information were collected from the New South Wales Australia from 2015 to 2019, covering 523 residential communities. Daily wildfire-specific PM(2.5) at a 0.25° × 0.25° (≈ 25 km × 25 km) resolution was estimated by a machine learning method combining 3-D chemical transport model (GEOS-Chem) and reanalysis meteorological data. Cox proportional hazards models were implemented to evaluate the association between wildfire-specific PM(2.5) and preterm birth/term low birth weight. Number and fraction of preterm birth/term low birth weight attributable to wildfire-specific PM(2.5) during pregnancy were calculated. RESULTS: Per one interquartile-range rise in wildfire-specific PM(2.5) was found to be associated with 6.9% (HR: 1.069, 95% CI: 1.058-1.081) increased risk of preterm birth and 3.6% (HR: 1.036, 95% CI: 1.014-1.058) higher risk of term low birth weight. The most susceptible gestational window was the 2nd trimester for preterm birth whereas the 1st for term low birth weight. We estimated that 14.30% preterm births and 8.04% term low birth weight cases were attributable to maternal exposure to wildfire-specific PM(2.5) during the whole pregnancy. Male infants and mothers aged ≥ 40, experiencing temperature extremes or living in the inner region, and concepted during spring had higher risks of preterm birth/term low birth weight associated with wildfire-specific PM(2.5). Comparatively, mothers with advanced age have a higher risk of preterm birth while younger mothers were more likely to deliver term newborns with low birth weight, when being exposed to wildfire-specific PM(2.5). Pregnancy-induced hypertension enhanced the risk of preterm birth associated with wildfire-specific PM(2.5). CONCLUSIONS: This study strengthened robust evidence on the enhanced risk of preterm birth/term low birth weight associated with maternal exposure to wildfire-specific PM(2.5). In light of higher frequency and intensity of wildfire occurrences globally, more special attention should be paid to pregnant women by policy makers.
Due to climate change, landscape fires account for an increasing proportion of air pollution emissions, and their impacts on primary and pharmaceutical care are little understood. OBJECTIVES: To evaluate associations between exposure in two early life periods to severe levels of PM(2.5) from a mine fire, background PM(2.5), and primary and pharmaceutical care. METHODS: We linked records of births, general practitioner (GP) presentations and prescription dispensing for children born in the Latrobe Valley, Australia, 2012-2014, where a severe mine fire occurred in February-March 2014 in an area with otherwise low levels of ambient PM(2.5). We assigned modelled exposure estimates for fire-related (cumulative over the fire and peak 24-hour average) and annual ambient PM(2.5) to residential address. Associations with GP presentations and dispensing of prescribed medications in the first two years of life (exposure in utero) and in the two years post-fire (exposure in infancy) were estimated using two-pollutant quasi-Poisson regression models. RESULTS: Exposure in utero to fire-related PM(2.5) was associated with an increase in systemic steroid dispensing (Cumulative: IRR = 1.11, 95%CI = 1.00-1.24 per 240 μg/m(3); Peak: IRR = 1.15, 95%CI = 1.00-1.32 per 45 μg/m(3)), while exposure in infancy was associated with antibiotic dispensing (Cumulative: IRR = 1.05, 95%CI = 1.00-1.09; Peak: IRR = 1.06, 95%CI = 1.00-1.12). Exposure in infancy to ambient PM(2.5), despite relatively low levels from a global perspective (Median = 6.1 μg/m(3)), was associated with an increase in antibiotics (IRR = 1.10, 95%CI = 1.01-1.19 per 1.4 μg/m(3)) and in GP presentations (IRR = 1.05, 95%CI = 1.00-1.11), independently from exposure to the fire. We also observed differences in associations between sexes with GP presentations (stronger in girls) and steroid skin cream dispensing (stronger in boys). DISCUSSION: Severe medium-term concentrations of PM(2.5) were linked with increased pharmaceutical treatment for infections, while chronic low levels were associated with increased prescriptions dispensed for infections and primary care usage. Our findings also indicated differences between sexes.
In recent years, with the repeated occurrence of extreme weather and the continuous increase of air pollution, the incidence of weather-related diseases has increased yearly. Air pollution and extreme temperature threaten sensitive groups’ lives, among which air pollution is most closely related to respiratory diseases. Owing to the skewed attention, timely intervention is necessary to better predict and warn the occurrence of death from respiratory diseases. In this paper, according to the existing research, based on a number of environmental monitoring data, the regression model is established by integrating the machine learning methods XGBoost, support vector machine (SVM), and generalized additive model (GAM) model. The distributed lag nonlinear model (DLNM) is used to set the warning threshold to transform the data and establish the warning model. According to the DLNM model, the cumulative lag effect of meteorological factors is explored. There is a cumulative lag effect between air temperature and PM2.5, which reaches the maximum when the lag is 3 days and 5 days, respectively. If the low temperature and high environmental pollutants (PM2.5) continue to influence for a long time, the death risk of respiratory diseases will continue to rise, and the early warning model based on DLNM has better performance.
In the summer of 2018, Sweden experienced widespread wildfires, particularly in the region of Jamtland Harjedalen during the final weeks of July. We previously conducted an epidemiological study and investigated acute respiratory health effects in eight municipalities relation to the wildfire air pollution. In this study, we aimed to estimate the potential health impacts under less favorable conditions with different locations of the major fires. Our scenarios focused on the most intense plume from the 2018 wildfire episode affecting the largest municipality, which is the region’s only city. Combining modeled PM2.5 concentrations, gridded population data, and exposure-response functions, we assessed the relative increase in acute health effects. The cumulative population-weighted 24 h PM2.5 exposure during the nine highest-level days reached 207 mu g/m(3) days for 63,227 inhabitants. We observed a small number of excess cases, particularly in emergency unit visits for asthma, with 13 additional cases compared to the normal 12. Overall, our scenario-based health impact assessment indicates minor effects on the studied endpoints due to factors such as the relatively small population, limited exposure period, and moderate increase in exposure compared to similar assessments. Nonetheless, considering the expected rise in fire potential due to global warming and the long-range transport of wildfire smoke, raising awareness of the potential health risks in this region is important.
The degradation of air quality, an environmental consequence of anthropogenic activities, poses a challenge to human health. However, the corresponding control measures incur additional costs. This study presents an analysis of the health and socioeconomic benefits of air quality control measures and climate change mitigation. Multidisciplinary modelling was used for PM2.5 and ozone distribution to analyze the co-benefits of end-of-pipe measures and electrification as well as their period-specific impacts on human health and the economy. The results indicated that the long-term impacts of end-of-pipe technologies and electrification in Japan’s residential, building, and transportation sectors could reduce premature deaths, caused by PM2.5 and ozone pollution, by 65,500 annually from 2010 to 2050. These technologies could save a per capita work hour loss of 3.64 h and avoid an economic loss of 5.43 billion USD by 2050. This study predicted climate actions would enable western Japan to benefit from PM2.5 control measures, whereas the entire country would benefit from ozone pollution reduction.
Pollen grains are among the main causes of respiratory allergies worldwide and hence they are routinely monitored in urban environments. However, their sources can be located farther, outside cities’ borders. So, the fundamental question remains as to how frequent longer-range pollen transport incidents are and if they may actually comprise high-risk allergy cases. The aim was to study the pollen exposure on a high-altitude location where only scarce vegetation exists, by biomonitoring airborne pollen and symptoms of grass pollen allergic individuals, locally. The research was carried out in 2016 in the alpine research station UFS, located at 2650 m height, on the Zugspitze Mountain in Bavaria, Germany. Airborne pollen was monitored by use of portable Hirst-type volumetric traps. As a case study, grass pollen-allergic human volunteers were registering their symptoms daily during the peak of the grass pollen season in 2016, during a 2-week stay on Zugspitze, 13-24 June. The possible origin of some pollen types was identified using back trajectory model HYSPLIT for 27 air mass backward trajectories up to 24 h. We found that episodes of high aeroallergen concentrations may occur even at such a high-altitude location. More than 1000 pollen grains m(-3) of air were measured on the UFS within only 4 days. It was confirmed that the locally detected bioaerosols originated from at least Switzerland, and up to northwest France, even eastern American Continent, because of frequent long-distance transport. Such far-transported pollen may explain the observed allergic symptoms in sensitized individuals at a remarkable rate of 87 % during the study period. Long-distance transport of aeroallergens can cause allergic symptoms in sensitized individuals, as evidenced in a sparse-vegetation, low-exposure, ‘low-risk’ alpine environment. We strongly suggest that we need cross-border pollen monitoring to investigate long-distance pollen transport, as its occurrence seems both frequent and clinically relevant.
Allergic rhinitis (AR) is a highly prevalent respiratory condition that carries a heavy burden and can have a significant impact on patient quality of life. AR is caused by seasonal or perennial exposure to outdoor pollens and molds as well as indoor allergic triggers. In this review article, we discuss the factors associated with the development of AR throughout the year and the fact that patients with AR need continuous treatment rather than seasonal treatment. Conventionally, AR has been mainly categorized into seasonal AR and perennial AR, but these classes do not seem to be well-adapted. Climate changes, temperature changes, and high carbon dioxide (CO(2)) concentration affect the growth of plants and increase the length of pollen seasons and pollen allergenicity. Air pollution aggravates allergic sensitization symptoms in AR sensitized individuals. Due to increased air pollution and indefinite pollen seasons AR symptoms are present throughout the year. Patients with AR often need continuous treatment, which should be considered while making the strategy for treating allergic rhinitis sufferers. Management of AR involves avoiding the allergen, medications for symptomatic relief, anti-inflammatory therapies, and allergy immunotherapy. Although the first-generation H(1)-antihistamines reduce AR symptoms, they cause sedation and impair cognitive functions; thus, second-generation antihistamines (ie, levocetirizine, loratadine, bilastine, fexofenadine) are preferred. The efficacy and safety of fexofenadine for the treatment of seasonal allergic rhinitis (SAR) symptoms have been demonstrated by numerous clinical studies, irrespective of the season and underlying allergen. In this review, we discuss the allergic rhinitis classification, the role of climate change, air pollution, and factors contributing to year-round symptoms in patients with AR and the need for continuous pharmacological treatment for management.
In recent years, evidence of the synergistic effects of pollen and viruses on respiratory health has begun to accumulate. Pollen exposure is a known risk factor for the incidence and severity of respiratory viral infections. However, recent evidence suggests that pollen exposure may also inhibit or weaken viral infections. A comprehensive summary has not been made and a consensus on the synergistic health effects has not been reached. It is highly possible that climate change will increase the significance of pollen exposure as a cause of respiratory problems and, at the same time, affect the risk of infectious disease outbreaks. It is important to accurately assess how these two factors affect human health separately and concurrently. In this review article, for the first time, the data from previous studies are combined and reviewed and potential research gaps concerning the synergistic effects of pollen and viral exposure are identified.
Air pollution is among the leading environmental threats to health around the world today, particularly in the context of sports and exercise. With the effects of air pollution, pollution episodes (eg, wildfire conflagrations) and climate change becoming increasingly apparent to the general population, so have their impacts on sport and exercise. As such, there has been growing interest in the sporting community (ie, athletes, coaches, and sports science and medicine team members) in practical personal-level actions to reduce the exposure to and risk of air pollution. Limited evidence suggests the following strategies may be employed: minimising all exposures by time and distance, monitoring air pollution conditions for locations of interest, limiting outdoor exercise, using acclimation protocols, wearing N95 face masks and using antioxidant supplementation. The overarching purpose of this position statement by the Canadian Academy of Sport and Exercise Medicine and the Canadian Society for Exercise Physiology is to detail the current state of evidence and provide recommendations on implementing these personal strategies in preventing and mitigating the adverse health and performance effects of air pollution exposure during exercise while recognising the limited evidence base.
Shipping is the cornerstone of international trade and thus a critical economic sector. However, ships predominantly use fossil fuels for propulsion and electricity generation, which emit greenhouse gases such as carbon dioxide and methane, and air pollutants such as particulate matter, sulfur oxides, nitrogen oxides, and volatile organic compounds. The availability of Automatic Information System (AIS) data has helped to improve the emission inventories of air pollutants from ship stacks. Recent laboratory, shipborne, satellite and modeling studies provided convincing evidence that ship-emitted air pollutants have significant impacts on atmospheric chemistry, clouds, and ocean biogeochemistry. The need to improve air quality to protect human health and to mitigate climate change has driven a series of regulations at international, national, and local levels, leading to rapid energy and technology transitions. This resulted in major changes in air emissions from shipping with implications on their environmental impacts, but observational studies remain limited. Growth in shipping in polar areas is expected to have distinct impacts on these pristine and sensitive environments. The transition to more sustainable shipping is also expected to cause further changes in fuels and technologies, and thus in air emissions. However, major uncertainties remain on how future shipping emissions may affect atmospheric composition, clouds, climate, and ocean biogeochemistry, under the rapidly changing policy (e.g., targeting decarbonization), socioeconomic, and climate contexts.
PURPOSE OF REVIEW: As the incidence of allergic conditions has increased in recent decades, the effects of climate change have been implicated. There is also increased knowledge on the effects of other physical influences, such as scratching and Staphylococcus aureus . The skin barrier is the first line of defense to the external environment, so understanding the ways that these factors influence skin barrier dysfunction is important. RECENT FINDINGS: Although the impact on environmental exposures has been well studied in asthma and other allergic disorders, there is now more literature on the effects of temperature, air pollution, and detergents on the skin barrier. Factors that cause skin barrier dysfunction include extreme temperatures, air pollution (including greenhouse gases and particulate matter), wildfire smoke, pollen, scratching, S. aureus, and detergents. SUMMARY: Understanding the ways that external insults affect the skin barrier is important to further understand the mechanisms in order to inform the medical community on treatment and prevention measures for atopic conditions.
BACKGROUND: Ragweed is an invasive plant in Europe, causing hay fever and asthma in allergic patients. Climate change is predicted to increase expansion and allergenicity. Elevated NO(2) induced upregulation of a new allergen in ragweed pollen, an enolase, Amb a 12. OBJECTIVE: of this study was producing ragweed enolase as a recombinant protein and characterizing its physicochemical and immunological features. METHODS: Amb a 12 was designed for E. coli and insect cell expression. Physicochemical features were determined by mass spectrometry, circular dichroism measurements and enzymatic activity assay. Immunological characteristics were determined in ELISA, in a mediator release assay and by investigation of association with clinical symptoms. Common allergen sources were screened for similar proteins. RESULTS: Ragweed enolase was produced as a 48 kDa protein forming oligomers in both expression systems, showing differences in secondary structure content and enzymatic activity depending on expression system. IgE frequency and allergenicity were low regardless of expression system. Enolase-specific serum bound to similar sized molecules in mugwort, timothy grass and birch pollen, as well as food allergen sources, while highest IgE inhibition was achieved with peach pulp extract. CONCLUSIONS: Amb a 12 had high sequence similarity and comparable IgE frequency to enolase allergens from different sources. 50 kDa proteins were found in other pollen and food allergen sources, suggesting that enolases might be pan-allergens in pollen and plant foods.
Epidemiological and toxicological studies have confirmed that exposure to atmospheric particulate matter (PM) could affect our cardiovascular and respiratory systems. Recent studies have shown that PM can penetrate the skin and cause skin inflammation, but the evidence is limited and contradictory. As the largest outermost surface of the human body, the skin is constantly exposed to the environment. The aim of this study was to assess the relationship between PM and inflammatory skin diseases. Most epidemiological studies have provided positive evidence for outdoor, indoor, and wildfire PM and inflammatory skin diseases. The effects of PM exposure during pregnancy and inflammatory skin diseases in offspring are heterogeneous. Skin barrier dysfunction, Oxidative stress, and inflammation may play a critical role in the underlying mechanisms. Finally, we summarize some interventions to alleviate PM-induced inflammatory skin diseases, which may contribute to public health welfare. Overall, PM is related to inflammatory skin diseases via skin barrier dysfunction, oxidative stress, and inflammation. Appropriate government interventions are beneficial.
Ground level ozone is a potent respiratory toxicant with decades of accumulated data demonstrating respiratory harms to children. Despite the ubiquity of ozone in the United States, impacting both urban and rural communities, the associated harms of exposure to this important air pollutant are often infrequently or inadequately covered during medical training including pulmonary specialization. Thus, many providers caring for children’s respiratory health may have limited knowledge of the harms which may result in reduced discussion of ozone pollution during clinical encounters. Further, the current US air quality standard for ozone does not adequately protect children. In this nonsystematic review, we present basic background information for healthcare providers caring for children’s respiratory health, review the US process for setting air quality standards, discuss the respiratory harms of ozone for healthy children and those with underlying respiratory disease, highlight the urgent need for a more protective ozone standard to adequately protect children’s respiratory health, review impacts of climate change on ozone levels, and provide information for discussion in clinical encounters.
Reducing PM2.5-related premature mortality is essential for health-related sustainable development. China, one of the most populated and PM2.5 polluted developing countries in the world, is striving to be in the vanguard for meeting this target. However, the global chemical transport methods for future PM2.5 projections are difficult to use and computationally expensive and may import measurement uncertainty into regional exposure assessments, thus bringing challenges to policy making. Here, we proposed an integrated PM2.5 projection model framework based on regional land use, emission, climate and population simulations. The ambient PM2.5 exposure and associated premature mortality to 2100 in China at a scale of 10 x 10 km were projected and compared under different development pathways. Ambient PM2.5 exposure is expected to peak in recent decades (2030-2060) with mean values ranging from 32.72 to 35.11 mu g/m(3) for different pathways, while associated premature mortality are projected to decrease (2273.9-778.59) (in thousands) over time (2030-2100). The change in the emission scenario with significant CH4 and NMVOC increases could lead to the greatest increase in average PM2.5 exposure (4.03 mu g/m(3)), while the decrease (-0.90 mu g/m(3)) was linked to BC, SO2, CH4, and NMVOC decreases. Meanwhile, premature deaths decrease (15-226,424) for most projection periods when land use, emissions, and population data were separately replaced with RCP2.6-SSP1 data. Land use impacts in socioeconomic change scenarios could be moderate in certain regions. Therefore, the sustainable development pathway of the RCP2.6-SSP1 scenario should be prioritized in China for future development considering both environmental protection and health sustainability. Plain Language Summary Reducing PM2.5 exposure and the related health burden is one of the primary tasks for sustainable environmental and health development. China has made great efforts to meet this challenge, but the influence duration and future trend are not clear. We projected the future PM2.5 exposure and associated health burden to 2100 in China for four common development pathways and develop sensitivity analyses by replacing land use, emissions, and population data separately. We found that ambient PM2.5 exposure and associated premature mortality for the pathway with low radiative forcing levels and sustainable socioeconomic development were the lowest for most projection periods in common pathways and sensitivity analyses. This illustrates that the sustainable development pathway for both climate and socioeconomic factors should be a top priority for China.
How a nuclear power phase-out may affect air pollution, climate and health in the future is up for debate. Here the authors assess impacts of a nuclear phase-out in the United States on ground-level ozone and fine particulate matter (PM2.5). We explore how nuclear shut-downs in the United States could affect air pollution, climate and health with existing and alternative grid infrastructure. We develop a dispatch model to estimate emissions of CO2, NOx and SO2 from each electricity-generating unit, feeding these emissions into a chemical transport model to calculate effects on ground-level ozone and fine particulate matter (PM2.5). Our scenario of removing nuclear power results in compensation by coal, gas and oil, resulting in increases in PM2.5 and ozone that lead to an extra 5,200 annual mortalities. Changes in CO2 emissions lead to an order of magnitude higher mortalities throughout the twenty-first century, incurring US$11-180 billion of damages from 1 year of emissions. A scenario exploring simultaneous closures of nuclear and coal plants redistributes health impacts and a scenario with increased penetration of renewables reduces health impacts. Inequities in exposure to pollution are persistent across all scenarios-Black or African American people are exposed to the highest relative levels of pollution.
In recent years, the environmental impacts of climate change have become increasingly evident. Extreme meteorological events are influenced by climate change, which also alter the magnitude and pattern of precipitations and winds. Climate change can have a particularly negative impact on respiratory health, which can lead to the emergence of asthma and allergic respiratory illnesses. Pollen is one of the main components of the atmospheric bioaerosol and is able to induce allergic symptoms in certain subjects. Climate change affects the onset, length, and severity of the pollen season, with effects on pollen allergy. Higher levels of carbon dioxide (CO2) can lead to enhanced photosynthesis and a higher pollen production in plants. Pollen grains can also interact with air pollutants and be affected by thunderstorms and other extreme events, exacerbating the insurgence of respiratory diseases such as allergic rhinitis and asthma. The consequences of climate change might also favor the spreading of pandemics, such as the COVID-19 one.
This article employs new materialist theory to the accounts of women who were pregnant, giving birth or parenting new-borns during the Australian bushfires of 2019/2020. As feminist scholars we are concerned with the inequitable responsibility accorded to women during this time to limit their (un)born children’s exposure to smoke. Drawing on Barad’s (2007) relational ontology we trace how (non)human phenomena like ‘smoke’, ‘public health advice’ and discourses of ‘the good mother’ work intra-actively to establish conditions of possibility in relation to mother’s agency and responsibility in this crisis. Via in-depth interviews with 25 women, we discovered these coagulating forces meant many experienced feelings of ‘powerlessness’ and subsequent ‘guilt’ at their inability to prevent smoke inhalation for their (un)born children. To challenge this burden of responsibility, we (re)configure conventional notions of ‘agency’ and ‘responsibility’ within a new materialist frame. When agency is understood as an intra-active becoming and response-ability as preceding the subject, responsibility for the air shifts to a recognition that everyone/thing is complicit in the world’s differential becoming. We extend this thinking to consider human response-ability and agency in relation to the climate change that has been attributed to causing the fires.
The EU, seeking to be a global leader in the fight against climate change, is moving ahead with ambitious policies to mitigate greenhouse gases emissions. In this context, the Fit for 55 package (FF55) is a set of proposals to revise and update EU legislation, to ensure that policies are in line with the climate goals of cutting emissions by at least 55% by 2030. Whilst these policies are designed for climate purposes, they will have positive side-effects (co-benefits) on air quality. Separately, additional policies are also in place to reduce emissions of related air pollutants and to improve air quality concentrations on EU territory. In this work, through a modelling study, we analyse the benefits of these policies via the health benefits arising from the resulting reductions in yearly average PM2.5 concentrations. Results are analysed by assessing and comparing morbidity and mortality impacts as computed using both the HRAPIE (Health risks of air pollution in Europe, WHO, as implemented in the CaRBonH model) and the GBD (Global Burden of Disease, as implemented in FASST-GBD model) approaches. Even when considering the uncertainty and variability in the results obtained using the two approaches, it is clear that EU policies can bring health and economic benefit in EU, with several Billions of Euro of benefits both in terms of morbidity and mortality indicators.
Climate change and exposure to environmental pollutants play a key role in the onset and aggravation of allergic diseases. As different climate-dependent patterns of molecular immunoglobulin E (IgE) reactivity have been regionally described, we sought to investigate the evolving allergen exposome in distinctive allergic phenotypes and subtropical weather conditions through a Precision Allergy Molecular Diagnosis (PAMD@) model. Concurrent sensitization to several house dust mites (HDM) and storage mite molecules were broadly dominant in the investigated cohort, followed by the major cat allergen Fel d 1, and regardless of the basal allergic disease. Although a complex repertoire of allergens was recognized, a steadily increasing number of IgE binding molecules was associated with the complexity of the underlying atopic disease. Besides the highly prevalent IgE responses to major HDM allergens, Der p 21, Der p 5, and Der p 7 also showed up as serodominant molecules, especially in subjects bothered by asthma and atopic dermatitis. The accurate characterization of the external exposome at the molecular level and their putative role as clinically relevant allergens is essential to elucidate the phenotypic diversity of atopic disease in terms of personalized diagnosis and therapy.
Indoor heat and air pollution pose concurrent threats to human health and wellbeing, and their effects are more pronounced for vulnerable individuals. This study investigates exposures to summertime indoor overheating and airborne particulate matter (PM2.5) experienced by low-income seniors and explores the potential of natural ventilation on maintaining good indoor thermal conditions and air quality (IAQ). Environmental and behavioural monitoring and a series of interviews were conducted during summer 2017 in 24 senior apartments on three public housing sites in NJ, USA (1930s’ low-rise, 1960s’ high-rise and LEED-certified 2010s’ mid-rise). All sites had high exposures to overheating and PM2.5 concentrations during heat waves and on regular summer days, but with substantial between-site and between-apartment variability. Overheating was higher in the 30s’ low-rise site, while pollutant levels were higher in the 60s’ high-rise. Mixed linear models indicated a thermal and air quality trade-off with window opening (WO), especially in some ‘smoking’ units from the older sites, but also improved both thermal and PM2.5 concentration conditions in 20% of the apartments. Findings suggest that with warmer future summers, greater focus is needed on the interdependencies among (1) thermal and IAQ outcomes and (2) technological and behavioural dimensions of efforts to improve comfort for vulnerable occupants.
Due to a combination of lifestyle risk factors, the burden of cardiovascular disease (CVD) has been increasing in China, affecting an estimated 330 million people. Environmental risk factors can exacerbate these risks or independently contribute to CVD. Ozone is an overlooked and invisible risk factor, and it plays a significant role in the development of CVD. Our study provides a novel quantification of the ozone-attributable CVD mortality burden based on daily maximum 8-h average ozone concentration during May to October (6mDMA8) in Chinese adults in 2050, projected under Shared Socioeconomic Pathways 585 and 126, and using the updated WHO air quality guideline level. The study also considers the contributions made by changes in ozone exposure, population aging, population size, and baseline death rates of CVD between 2019 and 2050. While adopting a sustainable and green pathway (SSP 126) can reduce the projected magnitude of premature CVD deaths to 359,200 in 2050, it may not be sufficient to reduce the CVD mortality burden significantly. Therefore, it is crucial to implement strategies for stricter ozone control and reducing the baseline death rate of CVD to mitigate the impacts of ozone on Chinese adults.
The smoke produced by wildfires can travel great distances and lead to respiratory and/or cardiovascular health impacts through inhalation. Individuals can reduce exposure by implementing smoke mitigation measures in their homes and beyond. In this article, we examine household level survey data (n = 543) on wildfire smoke mitigation in response to the September 2020 wildfires that occurred in the state of Oregon (and beyond). The air quality was hazardous for about 10 days in many affected regions. This study assessed the implementation of six commonly referenced approaches to reducing exposure to smoke: staying indoors; keeping doors and windows closed, turning on HVAC; using air purifiers; replacing air filters, and wearing face masks. We found high levels of implementation of staying indoors and keeping doors and windows closed; however, statistical analysis of socioeconomic demographics suggests that respondents vary in the implementation of the other measures. Income, number of exposure days, and access to information on smoke mitigation were positively associated with the implementation. Given the importance of information access for implementation for three of the measures, we also present data on how different age groups prefer to be contacted about air quality and smoke mitigation. For example, participants above 65 years of age prefer local TV as opposed to social media, whereas text messages were favored by all age groups. These survey results will help to inform the design of campaigns to engage community members differentially and potentially affect best communication practices and other assistance/preparation for smoke mitigation across demographics.
As the global population becomes more concentrated in urban environments, higher numbers of people will be exposed to urban air pollution. The environmental and human health benefits of green roofs are widely recognized. The aim of this paper is to promote green roofs as an effective passive technique for pollution mitigation and adaptation to climate change. During the heating season, the ambient concentrations of PM1, PM2.5, and PM10 were measured above a green roof and a reference roof on a school building, located in New Belgrade, the second-most populous municipality and business center of Serbia’s largest city. The percent reduction of PM10, PM2.5 and PM1, in January 2020, above the green roof compared to the reference roof was 7%, 16.6%, and 17.6%, respectively. The results show that lightweight green roof improve air quality in terms of PM concentrations for all months considered. In this paper, correlation analysis and the use of Pearson’s coefficient were used in the process of analysis to determine the relationship between PM10, PM2.5, PM1, and ambient parameters: relative humidity, ambient temperature, and wind speed. It was found that the statistical correlation expressed by the Pearson coefficient between all PM particles and wind speed was statistically significant in all observed months except September. Also, the degree of significance of the correlation between PM particles and humidity and temperature of ambient air varies by month.
INTRODUCTION: The complex interplay of multiple environmental factors and cardiovascular has scarcely been studied. Within the EXPANSE project, we evaluated the association between long-term exposure to multiple environmental indices and stroke incidence across Europe. METHODS: Participants from three traditional adult cohorts (Germany, Netherlands and Sweden) and four administrative cohorts (Catalonia [region Spain], Rome [city-wide], Greece and Sweden [nationwide]) were followed until incident stroke, death, migration, loss of follow-up or study end. We estimated exposures at residential addresses from different exposure domains: air pollution (nitrogen dioxide (NO(2)), particulate matter < 2.5 μm (PM(2.5)), black carbon (BC), ozone), built environment (green/blue spaces, impervious surfaces) and meteorology (seasonal mean and standard deviation of temperatures). Associations between environmental exposures and stroke were estimated in single and multiple-exposure Cox proportional hazard models, and Principal Component (PC) Analyses derived prototypes for specific exposures domains. We carried out random effects meta-analyses by cohort type. RESULTS: In over 15 million participants, increased levels of NO(2) and BC were associated with increased higher stroke incidence in both cohort types. Increased Normalized Difference Vegetation Index (NDVI) was associated with a lower stroke incidence in both cohort types, whereas an increase in impervious surface was associated with an increase in stroke incidence. The first PC of the air pollution domain (PM(2.5), NO(2) and BC) was associated with an increase in stroke incidence. For the built environment, higher levels of NDVI and lower levels of impervious surfaces were associated with a protective effect [%change in HR per 1 unit = -2.0 (95 %CI, -5.9;2.0) and -1.1(95 %CI, -2.0; -0.3) for traditional adult and administrative cohorts, respectively]. No clear patterns were observed for distance to blue spaces or temperature parameters. CONCLUSIONS: We observed increased HRs for stroke with exposure to PM(2.5), NO(2) and BC, lower levels of greenness and higher impervious surface in single and combined exposure models.
Emissions generated by wildfires are a growing threat to human health and are characterized by a unique chemical composition that is tightly dependent on geographic factors such as fuel type. Long noncoding RNAs (lncRNAs) are a class of RNA molecules proven to be critical to many biological processes, and their condition-specific expression patterns are emerging as prominent prognostic and diagnostic biomarkers for human disease. We utilized a new air-liquid interface (ALI) direct exposure system that we designed and validated in house to expose immortalized human tracheobronchial epithelial cells (AALE) to two unique wildfire smokes representative of geographic regions (Sierra Forest and Great Basin). We conducted an RNAseq analysis on the exposed cell cultures and proved through both principal component and differential expression analysis that each smoke has a unique effect on the LncRNA expression profiles of the exposed cells when compared to the control samples. Our study proves that there is a link between the geographic origin of wildfire smoke and the resulting LncRNA expression profile in exposed lung cells and also serves as a proof of concept for the in-house designed ALI exposure system. Our study serves as an introduction to the scientific community of how unique expression patterns of LncRNAs in patients with wildfire smoke-related disease can be utilized as prognostic and diagnostic tools, as the current roles of LncRNA expression profiles in wildfire smoke-related disease, other than this study, are completely uncharted.
Accentuated by climate change, catastrophic wildfires are a growing, distributed global public health risk from inhalation of smoke and dust. Underrecognized, however, are the health threats arising from fire-altered toxic metals natural to soils and plants. Here, we demonstrate that high temperatures during California wildfires catalyzed widespread transformation of chromium to its carcinogenic form in soil and ash, as hexavalent chromium, particularly in areas with metal-rich geologies (e.g., serpentinite). In wildfire ash, we observed dangerous levels (327-13,100 µg kg(-1)) of reactive hexavalent chromium in wind-dispersible particulates. Relatively dry post-fire weather contributed to the persistence of elevated hexavalent chromium in surficial soil layers for up to ten months post-fire. The geographic distribution of metal-rich soils and fire incidents illustrate the broad global threat of wildfire smoke- and dust-born metals to populations. Our findings provide new insights into why wildfire smoke exposure appears to be more hazardous to humans than pollution from other sources.
Background: Pollen is a key source of aeroallergens responsible for allergic rhinitis, conjunctivitis, and asthma. Objective: The goal of this scoping review was to summarize current available literature on the factors that affect pollen counts, allergenicity, and thresholds that induce symptoms in individuals who were sensitized. Methods: Several databases showed no published articles with a similar scope as of January 2022. A search of these data bases yielded 373 articles for assessment. These were then reviewed for relevance, and articles were selected to demonstrate the breadth of available data on pollen counts, allergenicity, and thresholds that induce symptoms in individuals who were sensitized. Additional articles were identified through examination of bibliographies of search-identified articles. Results: Several environmental factors have shown a correlation with pollen counts and allergen load, including the distance from the source, wind characteristics, pollen size, terrain, urban environments, air composition (particulate matter, CO₂ levels, ozone, NO₂), and weather conditions (humidity, thunderstorms, precipitation). Pollen thresholds at which symptoms were induced varied by study, pollen type, symptom, disease, and location. In addition, there was heterogeneity in study designs, threshold definition, and outcome measures. Conclusion: This scoping review demonstrates the plethora of variables that influence the relationship between pollen and the symptoms of allergic diseases. Analysis of the available data sheds light on the complex interaction between environmental and biologic factors that affect pollen’s role in allergic diseases and provides guidance on multiple areas for further investigation.
Airborne fungal spores and pollen (aerospora), synergistic with air pollution, are key triggers of allergic respiratory diseases. Effective diagnosis and treatment requires up-to-date location-specific knowledge on the temporal variability of aerospora types and levels. Johannesburg is the largest city in South Africa and has grown substantially in three decades, with changes in ground cover, population density and air pollution, yet until now, no continuous aerospora sampling has occurred. We present a daily two-year (August 2019-July 2021) aerospora assemblage for Johannesburg and explore temporal characteristics of 13 dominant aerospora in relation to daily meteorological variables (pressure, rainfall, relative humidity, temperature and wind characteristics). February-July, July-September and January-July represent high-risk periods for fungal spores [(Alternaria alternata (Fries. ex Keissler), Ascospores, Aspergillus niger (Van Tieghem), Penicillium chrysogenum (Thom), Cladosporium graminum (Corda), Epicoccum nigrum (Link), Helminthosporium solani (Durieu and Montagne) Nigrospora sphaerica (Saccardo ex. Mason), Smuts Ustilago nuda (Jensen ex. Rostrup) and Torula herbarum (Link)], trees (Cupressus, Morus and Platanus) and grass (Poaceae), respectively. Using a generalised additive model, results show that daily meteorological characteristics explained 7-32% of daily aerospora variability, with the largest effect on tree pollen. Rainfall, relative humidity and temperature influenced daily fungal spore and Poaceae counts, with moderate/low rainfall (< 20 mm), higher/mid-ranging relative humidity (similar to 40-60%) and temperatures of similar to 15-20 degrees C associated with higher counts during high-risk periods. Rainfall predominantly influenced tree counts during high-risk periods, with higher counts occurring on low rainfall (<10 mm) days. These results update the aerospora profile of Johannesburg, South Africa, providing important information to inform allergy care.
Atmospheric fine particulate matter (PM(2.5)) is a human health risk factor, but its ambient concentration depends on both precursor emissions and meteorology. While emission reductions are used to set PM(2.5)-related health policies, the effect of meteorology is often overlooked. To explore this aspect, we examined PM(2.5) interannual variability (IAV) associated with meteorological parameters using the long-term simulation from the Community Earth System Model (CESM1), a global climate-chemistry model, with fixed emissions. The results are subsequently contrasted with the MERRA-2 reanalysis dataset, which inherently considers emission and meteorology effects. Over continental East Asia, the CESM1 domain-average PM(2.5) IAV is 6.7 %, mainly attributed to humidity, precipitation, and ventilation variation. The grid-cell PM(2.5) IAVs over southern East China are larger, up to 12 % due to the more substantial influence of El Niño-induced meteorological anomalies. Under such climate extreme, sub-regional PM(2.5) concentration may occasionally exceed WHO air quality guideline levels despite the compliance of the long-term mean. The simulated PM(2.5) IAV over continental East Asia is ~25 % of that derived from the MERRA-2 data, which highlights the influence of both emission and meteorology-driven variations and trends inherent in the latter. Although emission-driven variability is significant to PM(2.5) IAV, in remote areas downwind of major source regions in East Asia, North America, and Western Europe, the MERRA-2 data revealed that meteorological variations contributed more to PM(2.5) IAV than emission variations. Thus, when setting policies for complying with the WHO PM(2.5)-related air quality guideline levels, the highest annual PM(2.5) associated with climate extremes should be considered instead of that based on average climate conditions.
BACKGROUND: An increasing number of systematic reviews (SRs) in the environmental field have been published in recent years as a result of the global concern about the health impacts of air pollution and temperature. However, no study has assessed and compared the methodological and reporting quality of SRs on the health effects of air pollutants and extreme temperatures. This study aims to assess and compare the methodological and reporting quality of SRs on the health effects of ambient air pollutants and extreme temperatures. METHODS: PubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Library, Web of Science, and Epistemonikos databases were searched. Two researchers screened the literature and extracted information independently. The methodological quality of the SRs was assessed through A Measurement Tool to Assess Systematic Reviews 2 (AMSTAR 2). The reporting quality was assessed through Preferred Reporting Items of Systematic reviews and Meta-Analyses (PRISMA). RESULTS: We identified 405 SRs (286 for air pollution, 108 for temperature, and 11 for the synergistic effects). The methodological and reporting quality of the included SRs were suboptimal, with major deficiencies in protocol registration. The methodological quality of SRs of air pollutants was better than that of temperature, especially in terms of satisfactory explanations for any heterogeneity (69.6% v. 45.4%). The reporting quality of SRs of air pollution was better than temperature, however, adherence to the reporting of the assessment results of risk of bias in all SRs (53.5% v. 34.3%) was inadequate. CONCLUSIONS: Methodological and reporting quality of SRs on the health effect of air pollutants were higher than those of temperatures. However, deficiencies in protocol registration and the assessment of risk of bias remain an issue for both pollutants and temperatures. In addition, developing a risk-of-bias assessment tool applicable to the temperature field may improve the quality of SRs.
Climate change is considered the greatest threat to global health. Greenhouse gases as well as global surface temperatures have increased causing more frequent and intense heat and cold waves, wildfires, floods, drought, altered rainfall patterns, hurricanes, thunderstorms, air pollution, and windstorms. These extreme weather events have direct and indirect effects on the immune system, leading to allergic disease due to exposure to pollen, molds, and other environmental pollutants. In this review, we will focus on immune mechanisms associated with allergy and asthma-related health risks induced by climate change events. We will review current understanding of the molecular and cellular mechanisms by which the changing environment mediates these effects.
Climate change is suspected to cause adverse health effects, and increased ozone concentration is one of the proposed pathways. We examined the mediation of ozone on the association between temperature and daily mortality and estimated excess mortality due to climate change. METHODS: Daily mean temperature, 8-hour maximum ozone concentration, and daily number of non-accidental deaths from 7 metropolitan cities in Korea (Seoul, Busan, Daegu, Incheon, Daejeon, Gwangju, and Ulsan) between January 1, 2006 and December 31, 2019 were analyzed. A mediation analysis using a linear regression model for temperature and ozone and a Poisson regression model for temperature and mortality adjusting for ozone was conducted on days with temperature higher than or lower than city specific minimum mortality temperature. We calculated excess mortality due to direct and indirect effects of daily temperature exceeding average daily temperature from 1960 to 1990. RESULTS: The daily mean temperature from 2006 to the end of 2019 was 1.15 ± 2.94 °C higher than the average daily temperature from 1960 to 1990. The pooled relative risk (for a 1 °C increment) of indirect effects through increased ozone were 1.0002 [95% confidence interval (CI): 0.9999, 1.0004] and 1.0003 (95% CI: 1.0002, 1.0005) in days with higher than or lower than minimum mortality temperature, respectively. The numbers of excess deaths during the study period were 2072.5 (95% CI: 1957.1, 2186.5) due to direct effects in days with higher than minimal mortality temperature, and 94.6 (95% CI: 84.3, 101.7) and 268.5 (95% CI: 258.4, 289.1) due to indirect effects in days with higher than and lower than minimal mortality temperature, respectively. CONCLUSION: We observed a mediating effect of ozone between temperature and daily mortality. There has been excess deaths due direct effect of temperature and indirect effects through ozone.
Macrosomia has increased rapidly worldwide in the past few decades, with a huge impact on health. However, the effect of PM(2.5) and extreme high-temperature (EHT) on macrosomia has been ignored. OBJECTIVE: This study aimed to explore the association between maternal exposure to EHT, PM(2.5) and macrosomia based on the Seventh Demographic and Health Survey (DHS) in 14 countries of Africa. METHODS: The study included detailed demographic information on 106 382 births and maternal. Satellite inversion models estimated monthly mean PM(2.5) and mean surface temperature of 2 m (SMT(2m) ). Macrosomia was defined as the birth weight ≥ 4000 g. We used a Cox proportional risk regression model to estimate the association between PM(2.5) , EHT and macrosomia. We further explored the susceptibility of exposure to EHT and PM(2.5) at different pregnancy periods to macrosomia, and plotted the expose-response curve between PM(2.5) and macrosomia risk using a restricted cubic spline function. In addition, the Interplot model was used to investigate the interaction between EHT and PM(2.5) on macrosomia. Finally, some potential confounding factors were analysed by stratification. RESULTS: There was the positive association between EHT, PM(2.5) and macrosomia, and the risk of macrosomia with the increase in concentrations of PM(2.5) without clear threshold. Meanwhile, EHT and PM(2.5) had a higher effect on macrosomia in middle/later and early/middle stages of pregnancy, respectively. There was a significant interaction between EHT and PM(2.5) on macrosomia. CONCLUSIONS: Maternal exposure to EHT, PM(2.5) during pregnancy was associated with an increased risk of macrosomia in Africa.
Rising levels of Environmental Air Pollution (EAP) caused by wildfires and traffic emissions impact Indoor Air Quality (IAQ) by penetrating buildings through air conditioning intakes and door and window openings. Exposure to fine Particulate Matter (PM2.5) causes building occupant discomfort and significant health issues. Hence, it is vital to continuously monitor the PM2.5 exposure level and the general IAQ of buildings. This study uses Internet of Things (IoT) sensors to investigate the temporal and spatial correlations between indoor and outdoor PM2.5 concentrations in a university building in Sydney, Australia, over five months. Sensor measurements are used to determine the Indoor to Outdoor (I/O) ratio and Exceedance Index (E-index). The study timeline included impacts associated with Hazard Reduction Burning (HRB) and localized peak traffic flow. The findings reveal that the closest indoor area to the building entrance exceeded double the World Health Organization (WHO) PM2.5 recommended threshold for more than 80% of the study period. Results also confirm a negative correlation between the distance from ground level and indoor PM2.5 exposure. An hourly analysis shows that the PM2.5 concentrations in Winter increase overnight. During HRB in Winter, the I/O ratios increased by up to 200% on average during regular HVAC operating hours. Localized outdoor readings were also compared with the nearest regional air quality monitoring station (RAQMS). Those results indicate that the average PM2.5 for the local outdoor sensor was approximately 2.5 times higher than the nearest RAQMS, confirming that regional stations may not be reliable references for localized PM2.5 concentrations.
Health risk resulting from non-optimal temperature exposure, referred to as “systematic risk”, has been a sustainable-development challenge in the context of global warming. Previous studies have recognized interactions between and among system components while assessing the vulnerability to climate change, but have left open the question of indicator directional interactions. The question is important, not least because indicator directional association analysis provides guidance to address climate risks by revealing the key nodes and pathways. The purpose of this work was to assess health vulnerability to short-term summer heat exposure based on a directional interaction network. Bayesian network model and network analysis were used to conduct a directional interaction network. Using indicator directional associations as weights, a weighted technique for the order of preference by similarity to ideal solution method was then proposed to assess heat-related health vulnerability. Finally, hotspots and coping strategies were explored based on the directional interaction network and health vulnerability assessments. The results showed that (1) indicator directional interactions were revealed in the health vulnerability framework, and the interactions differed between northern and southern China; (2) there was a dramatic spatial imbalance of health vulnerability in China, with the Beijing-Tianjin-Hebei Region and the Yangtze River Basin identified as hotspots; (3) particulate matter and ozone were recognized as priority indicators in the most vulnerable cities of northern China, while summer heat exposure level and variation were priority indicators in southern China; and (4) adaptive capacity could alter the extent of risk; thus, mitigation and adaptation should be implemented in an integrated way. Our study has important implications for strengthening the theoretical basis for the vulnerability assessment framework by providing indicator directional associations and for guiding policy design in dealing with heat-related health vulnerability in China.
Extreme heat events pose a significant threat to population health that is amplified by climate change. Traditionally, statistical models have been used to model heat-health relationships, but they do not consider potential interactions between temperature-related and air pollution predictors. Artificial intelligence (AI) methods, which have gained popularity for health applications in recent years, can account for these complex and non-linear interactions, but have been underutilized in modelling heat-related health impacts. In this paper, six machine and deep learning models were considered to model the heat-mortality relationship in Montreal (Canada) and compared to three statistical models commonly used in the field. Decision Tree (DT), Random Forest (RF), Gradient Boosting Machine (GBM), Single- and Multi-Layer Perceptrons (SLP and MLP), Long Short-Term Memory (LSTM), Generalized Linear and Additive Models (GLM and GAM), and Distributed Lag Non-Linear Model (DLNM) were employed. Heat exposure was characterized by air temperature, relative humidity and wind speed, while air pollution was also included in the models using five pollutants. The results confirmed that air temperature at lags of up to 3 days was the most important variable for the heat-mortality relationship in all models. NO(2) concentration and relative humidity (at lags 1 to 3 days) were also particularly important. Ensemble tree-based methods (GBM and RF) outperformed other approaches to model daily mortality during summer months based on three performance criteria. However, a partial validation during two recent major heatwaves highlighted that non-linear statistical models (GAM and DLNM) and simpler decision tree may more closely reproduce the spike of mortality observed during such events. Hence, both machine learning and statistical models are relevant for modelling heat-health relationships depending on the end user goal. Such extensive comparative analysis should be extended to other health outcomes and regions.
BACKGROUND: Tuberculosis (TB) is a public health problem worldwide, and the influence of meteorological and air pollutants on the incidence of tuberculosis have been attracting interest from researchers. It is of great importance to use machine learning to build a prediction model of tuberculosis incidence influenced by meteorological and air pollutants for timely and applicable measures of both prevention and control. METHODS: The data of daily TB notifications, meteorological factors and air pollutants in Changde City, Hunan Province ranging from 2010 to 2021 were collected. Spearman rank correlation analysis was conducted to analyze the correlation between the daily TB notifications and the meteorological factors or air pollutants. Based on the correlation analysis results, machine learning methods, including support vector regression, random forest regression and a BP neural network model, were utilized to construct the incidence prediction model of tuberculosis. RMSE, MAE and MAPE were performed to evaluate the constructed model for selecting the best prediction model. RESULTS: (1) From the year 2010 to 2021, the overall incidence of tuberculosis in Changde City showed a downward trend. (2) The daily TB notifications was positively correlated with average temperature (r = 0.231), maximum temperature (r = 0.194), minimum temperature (r = 0.165), sunshine duration (r = 0.329), PM(2.5) (r = 0.097), PM(10) (r = 0.215) and O(3) (r = 0.084) (p < 0.05). However, there was a significant negative correlation between the daily TB notifications and mean air pressure (r = -0.119), precipitation (r = -0.063), relative humidity (r = -0.084), CO (r = -0.038) and SO(2) (r = -0.034) (p < 0.05). (3) The random forest regression model had the best fitting effect, while the BP neural network model exhibited the best prediction. (4) The validation set of the BP neural network model, including average daily temperature, sunshine hours and PM(10), showed the lowest root mean square error, mean absolute error and mean absolute percentage error, followed by support vector regression. CONCLUSIONS: The prediction trend of the BP neural network model, including average daily temperature, sunshine hours and PM(10), successfully mimics the actual incidence, and the peak incidence highly coincides with the actual aggregation time, with a high accuracy and a minimum error. Taken together, these data suggest that the BP neural network model can predict the incidence trend of tuberculosis in Changde City.
Conjunctivitis is a common multifactorial inflammatory ocular surface disease characterized by symptoms such as congestion, edema, and increased secretion of conjunctival tissue, and the potential effects of meteorological factors as well as extreme meteorological factors on conjunctivitis and their lagging effects have not been fully evaluated. We obtained the electronic case information of 59,731 outpatients with conjunctivitis from the Ophthalmology Department of the First Affiliated Hospital of Xinjiang Medical University (Urumqi, Xinjiang, China) for the period from January 1, 2013, to December 31, 2020. Meteorological data for daily mean temperature (°C), daily relative humidity (%), daily average wind speed (m/s), and atmospheric pressure (hPa) were obtained from the China Meteorological Data Sharing Service. The air pollutant data were obtained from 11 standard urban background fixed air quality monitors. A time-series analysis design and a quasi-Poisson generalized linear regression model combined with a distributed lagged nonlinear model (DLNM) were used to fit the effects of exposure to different meteorological factors and extreme weather on conjunctivitis outpatient visits. Subgroup analyses were performed on gender, age and season, and type of conjunctivitis. Univariate and multifactorial model results indicated that each 10-unit increase in mean temperature and relative humidity was associated with an increased risk of conjunctivitis outpatient visits, while each 10-unit increase in atmospheric pressure was associated with a decreased risk. The results of the extreme weather analysis suggested that extremely low levels of atmospheric pressure and relative humidity as well as extreme levels of temperature were associated with an increased risk of outpatient conjunctivitis visits, and extreme wind speeds were associated with a decreased risk. The results of the subgroup analysis suggested gender, age, and seasonal differences. We conducted the first large sample size time-series analysis in the large city furthest from the ocean in the world and confirmed for the first time that elevated mean temperature and extreme low levels of relative humidity in Urumqi were risk factors for local conjunctivitis outpatient visits, while elevated atmospheric pressure and extreme low levels of wind speed were protective factors, and there were lagged effects of temperature and atmospheric pressure. Multicenter studies with larger sample sizes are needed.
Background: Cervical, endometrial, and ovarian cancers are three major gynecological cancers (GCs) leading to heavy disease burden and high mortality among women worldwide, which are associated with environmental exposure. However, the role of air pollution and temperature on GCs remains unclear.Objective: To assess the combined effects of short-term, medium-term, and long-term exposure to ambient air pollution and temperature indicators on GCs in women.Methods: A case-control study was conducted in XiangYa Hospital from 2010 to 2018 at Changsha, China. A standard questionnaire was designed to collect the health status and personal factors of 305 cases with GCs including cervical, endometrial, and ovarian cancers and 399 healthy women as control group. Personal expo-sure to ambient air pollution (PM10, SO2, and NO2), temperature, and diurnal temperature variation (DTV) during past one year, past five years, and past ten years was calculated by inverse distance weighted (IDW) method based on each subject’s home address. Multiple logistic regression model was used to analyse the relationship of GCs with outdoor air pollution and temperature indicators.Results: Exposure to NO2 during past five years and past ten years was significantly associated with GCs, with adjusted ORs (95% CI) of 1.40 (1.02-1.91) and 1.41 (1.03-1.93). Furthermore, an increase in temperature during past ten years was related with GCs, with OR (95% CI) = 1.95 (1.16-3.25). We strikingly found that high temperature increased the effect of long-term exposure to PM10 and NO2 during past ten years on GCs, while low DTV elevated GCs risk of air pollution exposure. Sensitivity analysis suggests that some specific subjects were more susceptible to the effect of air pollution and temperature indicators on GCs.Conclusion: Relatively long-term exposure to traffic-related air pollution (NO2) and increased temperature played important roles in the development of women’s GCs. There may be interactions between air pollution and temperature indicators on GCs.
BACKGROUND: Long-term improvements in air quality and public health in the continental USA were disrupted over the past decade by increased fire emissions that potentially offset the decrease in anthropogenic emissions. This study aims to estimate trends in black carbon and PM(2·5) concentrations and their attributable mortality burden across the USA. METHODS: In this study, we derived daily concentrations of PM(2·5) and its highly toxic black carbon component at a 1-km resolution in the USA from 2000 to 2020 via deep learning that integrated big data from satellites, models, and surface observations. We estimated the annual PM(2·5)-attributable and black carbon-attributable mortality burden at each 1-km(2) grid using concentration-response functions collected from a national cohort study and a meta-analysis study, respectively. We investigated the spatiotemporal linear-regressed trends in PM(2·5) and black carbon pollution and their associated premature deaths from 2000 to 2020, and the impact of wildfires on air quality and public health. FINDINGS: Our results showed that PM(2·5) and black carbon estimates are reliable, with sample-based cross-validated coefficients of determination of 0·82 and 0·80, respectively, for daily estimates (0·97 and 0·95 for monthly estimates). Both PM(2·5) and black carbon in the USA showed significantly decreasing trends overall during 2000 to 2020 (22% decrease for PM(2·5) and 11% decrease for black carbon), leading to a reduction of around 4200 premature deaths per year (95% CI 2960-5050). However, since 2010, the decreasing trends of fine particles and premature deaths have reversed to increase in the western USA (55% increase in PM(2·5), 86% increase in black carbon, and increase of 670 premature deaths [460-810]), while remaining mostly unchanged in the eastern USA. The western USA showed large interannual fluctuations that were attributable to the increasing incidence of wildfires. Furthermore, the black carbon-to-PM(2·5) mass ratio increased annually by 2·4% across the USA, mainly due to increasing wildfire emissions in the western USA and more rapid reductions of other components in the eastern USA, suggesting a potential increase in the relative toxicity of PM(2·5). 100% of populated areas in the USA have experienced at least one day of PM(2·5) pollution exceeding the daily air quality guideline level of 15 μg/m(3) during 2000-2020, with 99% experiencing at least 7 days and 85% experiencing at least 30 days. The recent widespread wildfires have greatly increased the daily exposure risks in the western USA, and have also impacted the midwestern USA due to the long-range transport of smoke. INTERPRETATION: Wildfires have become increasingly intensive and frequent in the western USA, resulting in a significant increase in smoke-related emissions in populated areas. This increase is likely to have contributed to a decline in air quality and an increase in attributable mortality. Reducing fire risk via effective policies besides mitigation of climate warming, such as wildfire prevention and management, forest restoration, and new revenue generation, could substantially improve air quality and public health in the coming decades. FUNDING: National Aeronautics and Space Administration (NASA) Applied Science programme, NASA MODIS maintenance programme, NASA MAIA satellite mission programme, NASA GMAO core fund, National Oceanic and Atmospheric Administration (NOAA) GEO-XO project, NOAA Atmospheric Chemistry, Carbon Cycle, and Climate (AC4) programme, and NOAA Educational Partnership Program with Minority Serving Institutions.
Heat waves and air pollution extremes exert compounding effects on human health and food security and may worsen under future climate change. On the basis of reconstructed daily O(3) levels in China and meteorological reanalysis, we found that the interannual variability of the frequency of summertime co-occurrence of heat wave and O(3) pollution in China is regulated mainly by a combination of springtime warming in the western Pacific Ocean, western Indian Ocean, and Ross Sea. These sea surface temperature anomalies impose influences on precipitation, radiation, etc., to modulate the co-occurrence, which were also confirmed with coupled chemistry-climate numerical experiments. We thus built a multivariable regression model to predict co-occurrence a season in advance, and correlation coefficient could reach 0.81 (P < 0.01) for the North China Plain. Our results provide useful information for the government to take actions in advance to mitigate damage from these synergistic costressors.
BACKGROUND: Study results are inconclusive regarding how access to greenspace differs by sociodemographic status potentially due to lack of consideration of varying dimensions of greenspace. OBJECTIVE: We investigated how provision of greenspace by sociodemographic status varies by greenspace metrics reflecting coverage and accessibility of greenspace. METHODS: We used vegetation levels measured by Enhanced Vegetation Index (EVI), percent of greenspace, percent tree cover, percent tree cover along walkable roads, and percent of people living ≤500 m of a park entrance (park accessibility). We considered data for 2008-2013 in Census block groups in 3 US regions: New Haven, Connecticut; Baltimore, Maryland; and Durham, North Carolina. We examined geographical distribution of greenspace metrics and their associations with indicators of income, education, linguistic isolation, race/ethnicity, and age. We used logistic regression to examine associations between these greenspace metrics and age-standardized mortality controlling for sociodemographic indicators. RESULTS: Which region had the highest greenspace depended on the greenspace metric used. An interquartile range (33.6%) increase in low-income persons was associated with a 6.2% (95% CI: 3.1, 9.3) increase in park accessibility, whereas it was associated with 0.03 (95% CI: -0.035, -0.025) to 7.3% (95% CI: -8.7, -5.9) decreases in other greenspace metrics. A 15.5% increase in the lower-education population was associated with a 2.1% increase (95% CI: -0.3%, 4.6%) in park accessibility but decreases with other greenspace metrics (0.02 to 5.0%). These results were consistent across the 3 study areas. The odds of mortality rate more than the 75th percentile rate were inversely associated with all greenspace metrics except for annual average EVI (OR 1.27, 95% CI: 0.43, 3.79) and park accessibility (OR 1.40, 95% CI: 0.52, 3.75). SIGNIFICANCE: Environmental justice concerns regarding greenspace differ by the form of natural resources, and pathways of health benefits can differ by form of greenspace and socioeconomic status within communities. IMPACT STATEMENT: Comparisons of exposure to greenspace between different greenspace metrics should be incorporated in decision-making within local contexts.
There has been an insurgence of allergic respiratory diseases such as asthma and rhinitis in industrialized countries in the last few decades as a result of the interaction between air pollutants and pollen, which has become a global and dramatic health problem. Air pollutants such as nitrogen dioxide, sulfur dioxide, ozone, and carbon dioxide affect the physical, chemical and biological properties of pollen such as the pollen content, production, and allergenicity, exacerbating symptoms in vulnerable subjects. When investigating these interactions and their effects, the environmental impact of climate change, weather variables and urbanization should be taken into account as well as the pollen species, type of pollutant, conditions of exposure, and individual susceptibility. Up to 25% of asthma adult cases are work-related, because several categories of workers in different sectors are exposed to aeroallergens and outdoor air pollutants. Thus, in this study, we evaluated the significant impacts of occupational allergies on worker’s health and quality of life. In summary, to assess the effect of interactions between air pollutants and pollen on public and occupational health, all the factors that play a role in this context will be investigated, including environmental factors, individual susceptibility in relation to pollen species, type of pollutants, and conditions of exposure.
Ambient wildfire smoke in the American West has worsened considerably in recent decades, while the number of individuals recreating outdoors has simultaneously surged. Wildfire smoke poses a serious risk to human health, especially during long periods of exposure and during exercise. As such, evaluating whether people modify recreation in response to smoke is important to understanding the public health implications of these trends. Here we aggregate data on black carbon, a major component of wildfire smoke, and recreational visitation in 32 US national parks from 1980 to 2019 to examine how visitors respond to wildfire smoke. We hypothesize that visitor response may exhibit a threshold effect where ambient smoke reduces visitation after a critical level, but not before. We develop a series of breakpoint models to test this hypothesis. The results of these models are mixed, but overall show little to no effect of ambient smoke on visitation to the 32 parks tested, even when allowing for critical thresholds at the extreme upper ranges of smoke exposure. This indicates that wildfire smoke does not greatly alter park attendance. This finding suggests that management actions to protect visitor health during smoke events may be warranted.
The indoor air quality (IAQ) was investigated in 15 Passive Houses in the heating and non-heating seasons between 2019 and 2021 in Hungary. The concentrations of volatile organic compounds (VOCs), aldehydes, ozone, nitrogen dioxide, PM2.5 mass, carbon dioxide, bacteria, fungi, and pollen were measured together with the monitoring of temperature, relative humidity and air change rate (ACR). The IAQ varied considerably among the investigated buildings. Significant seasonal differences were obtained for all physical parameters (temperature, relative humidity, ACR), certain VOCs (benzene, alpha-pinene, limonene), acetaldehyde, and airborne fungi. Considerable health concern was associated with the indoor concentrations of PM2.5 mass and nitrogen dioxide in many cases based on the evaluation of IAQ in relation to potential adverse health effects, while the peak con-centrations of other pollutants (e.g. trichloroethylene, alpha-pinene, certain aldehydes, fungi) were also of concern in a couple of cases. The median indoor/outdoor concentration ratios of benzene, PM2.5 mass, nitrogen dioxide, ozone and fungi indicated that these pollutants are mainly of outdoor origin, while the other VOCs, aldehydes and bacteria showed higher concentration indoors. Overheating, the lack of proper particle filters in the me-chanical ventilation system, and low ACR and relative humidity were identified as frequent problems related to the building characteristics. The emissions from building materials and furniture, the proximity of construction works and unpaved roads, and the allergenic vegetation might considerably influence IAQ. The results highlight that risk reduction measures are needed to create healthier indoor environment in the Passive Houses.
Low quality in a museum’s internal microclimate can induce both the deterioration of the exhibit collections, as well as affecting the health of visitors, employees and restorers. Starting from this premise, the present study aims to study the perception of visitors and employees of Darvas-La Roche Museum House (Romania) in relation to the air quality in the exhibition spaces. Their opinions were analyzed based on a questionnaire comprising 11 items aimed at understanding the influence of the indoor environment on the health of individuals, the degree of disturbance induced by the indoor air, if they experienced symptoms of illness after visiting the museum, etc. The obtained data were analyzed statistically in the SPSS 28 program, using tests such as coefficient, analysis of variance (ANOVA) and model summary, in order to obtain correlations between the sets of variables. The results obtained indicate that the majority of respondents perceived the indoor air quality as good, but there were also exceptions (approximately 20% of the respondents), which indicated different symptoms induced by the indoor air. Most of those (%) affected stated that they had pre-existing conditions, wear contact lenses or are smokers. In their case, the statistical-mathematical analyses indicated strong correlations between the ailments they suffer from and the appearance of certain discomforts (caused by too low or too high temperature, dust or dry air, etc.) and disease symptoms (nasal congestion, eye and skin irritations, coughs, migraines, frequent colds, etc.).
Understanding the costs and benefits of climate change mitigation and adaptation options is crucial to justify and prioritize future decarbonization pathways to achieve net zero. Here, we quantified the co-benefits of decarbonization for air quality and public health under scenarios that aim to limit end-of-century warming to 2 degrees C and 1.5 degrees C. We estimated the mortality burden attributable to ambient PM2.5 exposure using population attributable fractions of relative risk, incorporating projected changes in population demographics. We found that implementation of decarbonization scenarios could produce substantial global reductions in population exposure to PM2.5 pollution and associated premature mortality, with maximum health benefits achieved in Asia around mid-century. The stringent 1.5oC-compliant decarbonization scenario (SSP1-1.9) could reduce the PM2.5-attributable mortality burden by 29% in 2050 relative to a middle-of-the-road scenario (SSP2-4.5), averting around 2.9 M annual deaths worldwide. While all income groups were found to benefit from improved air quality through a combination of decarbonization and air pollution controls, the smallest health benefits are experienced by the low-income population. The disparity in PM2.5 exposure across income groups is projected to reduce by 2100, but a 30% disparity between high- and low-income groups persists even in the strongest mitigation scenario. Further, without additional and targeted air quality measures, low- and lower-middle-income populations (predominantly in Africa and Asia) will continue to experience PM2.5 exposures that are over three times the World Health Organization Air Quality Guideline. Implementation of decarbonization strategies to mitigate future climate change can provide additional benefits or “co-benefits” through improved air quality and public health. Quantifying these benefits and how they manifest across different world regions and income groups is essential to incentivize climate action. In this work we have quantified the air pollution health co-benefits for three different possible future scenarios: one “middle-of-the-road” scenario and two decarbonization scenarios. We found that by following a future decarbonization pathway instead of a “middle-of-the-road” pathway, can generate substantial air quality and public health benefits worldwide, particularly in Asia around 2050. While all income groups were found to benefit from improved air quality through decarbonization, the smallest health benefits are experienced by the low-income population. Inequalities in air pollution exposure between the lower-income and high-income groups were found to reduce rapidly under a decarbonization pathway, but persist through to 2100 even under the strongest mitigation. Further, without additional and targeted air quality measures, low- and lower-middle-income populations (predominantly in Africa and Asia) will continue to experience air pollution levels that exceed the World Health Organization Air Quality Guideline. Decarbonization has the potential to generate substantial health co-benefits by averting millions of premature deaths associated with PM2.5 exposure across all income groupsThe low-income population is predicted to experience the smallest health benefits of decarbonization and continue to be exposed to PM2.5 concentrations that are over three times that of the World Health Organization Air Quality GuidelineUnder a decarbonization future pathway, the global socioeconomic disparity in PM2.5 exposure reduces but persists at around 30% by the end of the century
Exposure to climate hazards is increasing, and the experiences of frontline communities warrant meaningful and urgent attention towards how to mitigate, manage, and adapt to hazards. We report results from a community-engaged pilot (November 2021-June 2022) of N = 30 participants in four frontline communities of the San Francisco Bay Area, California, USA. The study region is an area where low-income, non-English-speaking residents are inequitably exposed and vulnerable to wildfire smoke, extreme heat, and other climate hazards. Building from a yearslong partnership of researchers, community organizations, and community members, we report the feasibility of a project piloting (1) instruments to monitor indoor air quality, temperature, and participant sleep health, and (2) interventions to improve indoor air quality and support protective behaviors. Data collection included experience-based survey data (via in-person administered surveys and a smartphone application) and interviews about heat and air quality, as well as data from an air monitoring protocol. Results cover the prevalence of hazard exposure and protective actions among participants. We discuss throughout methods for conducting and evaluating a community-engaged pilot, particularly by using a community ambassador program. Implications include the feasibility of community-engaged research projects, including discussion of resources required to accomplish this work.
The purpose of this study is to explore the associations among dry eye disease (DED), air pollution, and meteorological conditions in the cold region of a northeastern Chinese metropolis (i.e., Changchun). Data on ambient air pollutants and meteorological parameters as well as diagnosed DED outpatients during 2015-2021 were collected. The associations between DED and environmental factors were analysed at multiple time scales using various statistical methods (i.e., correlation, regression and machine learning). Among the 10,809 DED patients (21,617 eyes) studied, 64.60% were female and 35.40% were male. A higher frequency of DED was observed in March and April, followed by January, August and October. Individual and multiple factor models showed the positive importance of particles with aerodynamic diameters <10 μm (PM(10)), carbon monoxide (CO), and ozone (O(3)) among normal air pollutants and air pressure (AP), air temperature (AT) and wind speed (WS) among normal meteorological parameters. Air pollutants (PM(10), nitrogen dioxide: NO(2)) and meteorological parameters (AT, AP) have combined impacts on DED occurrence. For the first time, we further explored the associations of detailed components of atmospheric particles and DED, suggesting potential emission sources, including spring dust from bare soil and roads and precursor pollutants of summer O(3) formation from vehicles and industry in Northeast China. Our results revealed the quantitative associations among air pollutants, meteorological conditions and DED outpatients in cold regions, highlighting the importance of coordinated policies in air pollution control and climate change mitigation.
China faces increasing health risks from climate change. The structure and function of the eye and vision were affected by extreme heat and cold. The study aimed to evaluate the impacts of heatwaves and cold spells on glaucoma. A national cross-sectional study of the Rural Epidemiology for Glaucoma (REG-China) was conducted in ten provinces of China, and 36,081 adults aged 40 years or more were included. Glaucoma signs were assessed via a standard examination. A total of 15 heatwave definitions, based on intensity (95th to 99th percentiles of temperature distribution) and duration (≥2 days, 3 days, and 4 days), were used to quantify heatwave effects, and 6 cold spell definitions were defined based on threshold temperature percentile (5th and 10th) and duration (3 days, 5 days, and 9 days). Multivariable-adjusted logistic regression models paired with interaction analysis were performed to investigate the impacts of heatwaves and cold spells on glaucoma, and the dose-response relationships were assessed using a restricted cubic spline (RCS) model. Subgroup analysis was conducted stratified by gender, age, smoking status, occupation, and family history of glaucoma. The overall prevalence of glaucoma was 2.1% (95% CI 1.94-2.25%). Higher heatwaves were significantly correlated with higher OR of glaucoma, with the OR (95% CI) ranging from 1.014 (1.009, 1.018) to 1.090 (1.065, 1.115) by different definitions. Glaucoma was affected by heatwaves more strongly than by cold spells. The effects of both heatwaves and cold spells were higher in males than females and in smokers than nonsmokers. These results of the present study evoked the attention of prospective research to elucidate the relationship between extreme temperatures and eye diseases.
Climate change and air pollution are closely interlinked since carbon dioxide and air pollutants are co-emitted from fossil fuel combustion. Net Zero (NZ) policies aiming to reduce carbon emissions will likely bring co-benefits in air quality and associated health. However, it is unknown whether regional NZ policies alone will be sufficient to reduce air pollutant levels to meet the latest 2021 World Health Organisation (WHO) guidelines. Here, we carried out high resolution air quality modelling for in the West Midlands region, a typical metropolitan area in the UK, to quantify the effects of different NZ policies on air quality. Results show that NZ policies will significantly improve air quality in the West Midlands, with up to 6 μg m(-3) (21%) reduction in annual mean NO(2) (mostly through the electrification of vehicle fleet, EV) and up to 1.4 μg m(-3) (12%) reduction in annual mean PM(2.5) projected for 2030 relative to levels under a “business as usual” (BAU) scenario. Under BAU, 2030 PM(2.5) concentrations in most wards would be below 10 μg m(-3) whilst under the Net Zero scenario, those in all wards would be below 10 μg m(-3). This means that the ward averages in the West Midlands would meet the UK PM(2.5) of 10 μg m(-3)target a decade early under the Net Zero scenario. However, no ward-level-averaged annual mean PM(2.)concentrations meet the 2021 WHO Air Quality guideline level of 5 μg m(-3) under any scenario. Similarly for NO(2) only 18 wards (8% of the region’s population) are predicted to have NO(2) concentrations below the 2021 WHO guideline level (10 μg m(-3)). Decarbonisation policies linked to Net Zero deliver substantial regional air quality benefits, but are not in isolation sufficient to deliver clean air with air pollutant levels low enough to meet the 2021 WHO guidelines.
BACKGROUND: The number of reported cases of Legionnaires’ disease (LD) has risen markedly in Switzerland (6.5/100,000 inhabitants in 2021) and abroad over the last decade. Legionella, the causative agent of LD, are ubiquitous in the environment. Therefore, environmental changes can affect the incidence of LD, for example by increasing bacterial concentrations in the environment or by facilitating transmission. OBJECTIVES: The aim of this study is to understand the environmental determinants, in particular weather conditions, for the regional and seasonal distribution of LD in Switzerland. METHODS: We conducted a series of analyses based on the Swiss LD notification data from 2017 to 2021. First, we used a descriptive and hotspot analysis to map LD cases and identify regional clusters. Second, we applied an ecological model to identify environmental determinants on case frequency at the district level. Third, we applied a case-crossover design using distributed lag non-linear models to identify short-term associations between seven weather variables and LD occurrence. Lastly, we performed a sensitivity analysis for the case-crossover design including NO(2) levels available for the year 2019. RESULTS: Canton Ticino in southern Switzerland was identified as a hotspot in the cluster analysis, with a standardised notification rate of 14.3 cases/100,000 inhabitants (CI: 12.6, 16.0). The strongest association with LD frequency in the ecological model was found for large-scale factors such as weather and air pollution. The case-crossover study confirmed the strong association of elevated daily mean temperature (OR 2.83; CI: 1.70, 4.70) and mean daily vapour pressure (OR: 1.52, CI: 1.15, 2.01) 6-14 days before LD occurrence. DISCUSSION: Our analyses showed an influence of weather with a specific temporal pattern before the onset of LD, which may provide insights into the effect mechanism. The relationship between air pollution and LD and the interplay with weather should be further investigated.
Wildfires are increasing yearly in number and severity as a part of the evolving climate crisis. These fires are a significant source of air pollution, a common driver of flares in cardiorespiratory disease, including asthma, which is the most common chronic disease of childhood. Poorly controlled asthma leads to significant societal costs through morbidity, mortality, lost school and work time and healthcare utilization. This retrospective cohort study set in Calgary, Canada evaluates the relationship between asthma exacerbations during wildfire smoke events and equivalent low-pollution periods in a pediatric asthma population. Air pollution was based on daily average levels of PM(2.5). Wildfire smoke events were determined by combining information from provincial databases and local monitors. Exposures were assumed using postal codes in the health record at the time of emergency department visits. Provincial claims data identified 27,501 asthma exacerbations in 57,375 children with asthma between 2010 to 2021. Wildfire smoke days demonstrated an increase in asthma exacerbations over the baseline (incidence rate ratio: 1.13; 95% CI: 1.02-1.24); this was not seen with air pollution in general. Increased rates of asthma exacerbations were also noted yearly in September. Asthma exacerbations were significantly decreased during periods of COVID-19 healthcare precautions.
Studies on the health effects of heat are particularly limited in Texas, a U.S. state in the top 10 highest number of annual heat-related deaths per capita from 2018 to 2020. This study assessed the effects of heat on all-cause and cause-specific mortality in 12 metropolitan statistical areas (MSAs) across Texas from 1990 to 2011. METHODS: First, we determined the heat thresholds for each MSA above which the relation between temperature and mortality is linear. We then conducted a distributed lag non-linear model for each MSA, followed by a random effects meta-analysis to estimate the pooled effects for all MSAs. We repeated this process for each mortality cause and age group to achieve the effect estimates. RESULTS: We found a 1 °C temperature increase above the heat threshold is associated with an increase in the relative risk of all-cause mortality of 0.60% (95%CI [0.39%, 0.82%]) and 1.10% (95%CI [0.65%, 1.56%]) for adults older than 75. For each MSA, the relative risk of mortality for a 1 °C temperature increase above the heat threshold ranges from 0.10% (95%CI [0.09%, 0.10%]) to 1.29% (95%CI [1.26%, 1.32%]). Moreover, elevated temperatures showed a slight decrease in cardiovascular mortality (0.37%, 95%CI [-0.35%, 1.09%]) and respiratory disease (1.97%, 95%CI [-0.11%, 4.08%]), however this effect was not considered statistically significant.. CONCLUSION: Our study found that high temperatures can significantly impact all-cause mortality in Texas, and effect estimates differ by MSA, age group, and cause of death. Our findings generate critical information on the impact of heat on mortality in Texas, providing insights for policymakers on resource allocation and strategic intervention to reduce heat-related health effects.
In this study, we estimated the future emission inventory of primary air pollutants in Japan in 2050 after introducing low-carbon technology based on the results of the socio-economic model provided by the Japanese government. The results suggested that introducing net-zero carbon technology would contribute to a 50-60 % decrease in primary NOx, SO2, and CO emissions and a similar to 30 % decrease in primary emissions of volatile organic compounds (VOCs) and PM2.5. The estimated emission inventory and future meteorological conditions in 2050 were applied as inputs to a chemical transport model. A scenario involving the application of future reduction strategies with relatively moderate global warming (RCP4.5) was evaluated. The results showed that the concentration of tropospheric ozone (O3) was highly reduced compared with that in 2015 after applying net-zero carbon reduction strategies. On the other hand, the fine particulate matter (PM2.5) concentration under the 2050 scenario was expected to be equal or higher because of the growth in secondary aerosol formation caused by the increase in short-wave radiation. Finally, the premature mortal-ity change from 2015 to 2050 was analyzed, and the change in air quality contributed by net-zero carbon technology will contribute to a similar to 4000 decrease in premature deaths in Japan.
The UK is legally committed to reduce its greenhouse gas emissions to net zero by 2050. We aimed to understand the potential impact on population health of two pathways for achieving this target through the integrated effects of six actions in four sectors. METHODS: In this multisectoral modelling study we assessed the impact on population health in England and Wales of six policy actions relating to electricity generation, transport, home energy, active travel, and diets relative to a baseline scenario in which climate actions, exposures, and behaviours were held constant at 2020 levels under two scenarios: the UK Climate Change Committee’s Balanced Pathway of technological and behavioural measures; and its Widespread Engagement Pathway, which assumes more substantial changes to consumer behaviours. We quantified the impacts of each policy action on mortality using a life table comprising all exposures, behaviours, and health outcomes in a single model. FINDINGS: Both scenarios are predicted to result in substantial reductions in mortality by 2050. The Widespread Engagement Pathway achieves a slightly greater reduction in outdoor fine particulate matter air pollution of 3·2 μg/m(3) (33%) and, under assumptions of appropriate ventilation, a greater improvement in indoor air pollution (a decrease in indoor-generated fine particulate matter from 9·4 μg/m(3) to 4·6 μg/m(3)) and winter temperatures (increasing from 17·8°C to 18·1°C), as well as appreciably greater changes in levels of active travel (27% increase in metabolic equivalent hours per week of walking and cycling) by 2050. Additionally, the greater reduction in red meat consumption (50% compared with 35% under the Balanced Pathway) by 2050 results in greater consumption of fruits (17-18 g/day), vegetables (22-23 g/day), and legumes (5-7 g/day). Combined actions under the Balanced Pathway result in more than 2 million cumulative life-years gained over 2021-50; the estimated gain under the Widespread Engagement Pathway is greater, corresponding to nearly 2·5 million life-years gained by 2050 and 13·7 million life-years gained by 2100. INTERPRETATION: Reaching net zero greenhouse gas emissions is likely to lead to substantial benefits for public health in England and Wales, with the cumulative net benefits being correspondingly greater with a pathway that entails faster and more ambitious changes, especially in physical activity and diets. FUNDING: National Institute for Health Research and the Wellcome Trust.
BACKGROUND: Allergic diseases, especially inhalation allergies, have reached epidemic levels and environmental factors play an important role in their development. Climate change influences the occurrence, frequency, and severity of allergic diseases. METHODS: The contents of this article were selected by the authors and developed section by section according to their expertise and the current state of knowledge. The sections were then discussed and agreed upon amongst all authors. RESULTS: The article highlights direct and indirect effects of climate change on allergies. It goes into detail about the connections between climate change and (new) pollen allergens as well as (new) occupational inhalation allergens, explains the effects of climate change on the clinical picture of atopic dermatitis, discusses the connections between air pollutants and allergies, and provides information about the phenomenon of thunderstorm asthma. CONCLUSIONS: There is a need for action in the field of pollen and fungal spore monitoring, allergy and sensitisation monitoring, urban planning from an allergological perspective, and changes in the working environment, among others.
BACKGROUND: The impacts of air pollutants on health range from short-term health impairments to hospital admissions and deaths. Climate change is leading to an increase in air pollution. METHODS: This article addresses, based on selected literature, the relationship between climate change and air pollutants, the health effects of air pollutants and their modification by air temperature, with a focus on Germany. RESULTS: Poor air quality increases the risk of many diseases. Climate change is causing, among other things, more periods of extreme heat with simultaneously increased concentrations of air pollutants. The interactions between air temperature and air pollutants, as well as their combined effects on human health, have not yet been sufficiently studied. Limit, target, and guideline values are of particular importance for health protection. CONCLUSIONS: Measures to reduce air pollutants and greenhouse gases must be more strictly implemented. An essential step towards improving air quality is setting stricter air quality limit values in Europe. Prevention and adaptation measures should be accelerated in Germany, as they contribute to climate-resilient and sustainable healthcare systems.
Climate change may affect mental health. We conducted an umbrella review of meta-analyses examining the association between mental health and climate events related to climate change, pollution and green spaces. We searched major bibliographic databases and included meta-analyses with at least five primary studies. Results were summarized narratively. We included 24 meta-analyses on mental health and climate events (n = 13), pollution (n = 11), and green spaces (n = 2) (two meta-analyses provided data on two categories). The quality was suboptimal. According to AMSTAR-2, the overall confidence in the results was high for none of the studies, for three it was moderate, and for the other studies the confidence was low to critically low. The meta-analyses on climate events suggested an increased prevalence of symptoms of post-traumatic stress, depression, and anxiety associated with the exposure to various types of climate events, although the effect sizes differed considerably across study and not all were significant. The meta-analyses on pollution suggested that there may be a small but significant association between PM(2.5), PM(10), NO(2), SO(2), CO and mental health, especially depression and suicide, as well as autism spectrum disorders after exposure during pregnancy, but the resulting effect sizes varied considerably. Serious methodological flaws make it difficult to draw credible conclusions. We found reasonable evidence for an association between climate events and mental health and some evidence for an association between pollution and mental disorders. More high-quality research is needed to verify these associations.
OBJECTIVE: It is known that the inhalation of air pollutants adversely affects human health. These air pollutants originated from natural sources such as desert storms or human activities including traffic, power generating, domestic heating, etc. This study aimed to investigate the impacts of desert dust storms, particulate matter ≤10 μm (PM(10)) and daily maximum temperature (MT) on mortality and emergency department (ED) visits due to stroke in the city of Gaziantep, Southeast Turkey. METHOD: The data on mortality and ED visits due to stroke were retrospectively recruited from January 1, 2009, to March 31, 2014, in Gaziantep City Centre. RESULTS: PM(10) levels did not affect ED visits or mortality due to stroke; however, MT increased both ED visits [adjusted odds ratio (OR) = 1.002, 95% confidence interval (CI) = 1.001-1.003] and mortality (OR = 1.006, 95% CI = 0.997-1.014) due to stroke in women. The presence of desert storms increased ED visits due to stroke in the total population (OR = 1.219, 95% CI = 1.199-1.240), and all subgroups. It was observed that desert dust storms did not have an increasing effect on mortality. CONCLUSION: Our findings suggest that MT and desert dust storms can induce morbidity and mortality due to stroke.
The potential critical windows for extreme ambient temperature, air pollution exposure and small for gestational age (SGA) are still unclear, and no study has explored their joint effects on SGA. In a national multi-center prospective cohort, we included 179,761 pairs of mother-infant from 16 counties of 8 provinces in China during 2014-2018. Daily averaged temperature and PM(2.5) concentration were matched to the maternal residential address to estimate personal exposure. Extreme temperature exposures were categorized by a series of percentile in each meteorological and geographic division for the entire pregnancy, each trimester and gestational week (GA-week). Generalized linear mixed models (GLMMs) and distributed lag nonlinear models (DLNMs) were used to estimate the whole pregnancy-, trimester-specific, and weekly-specific associations of extreme temperature and PM(2.5) exposures with SGA. Combined effects were evaluated with the relative excess risk due to interaction (RERI) and proportion attributable to interaction (AP). We observed that by referring to temperature at the 41st – 50th percentile, heat (>90th percentile) exposure during 13th – 29th GA-weeks was associated with SGA; odds ratio (OR) and 95 % confidence intervals (CI) was 1.16 (1.06, 1.28). For cold (<=10th percentile), inverse associations were observed during the 1st - 8th GA-weeks. PM(2.5) exposure during the 2nd - 5th and 19th - 27th GA-weeks was associated with SGA, with the strongest association in the 2nd GA-week (OR = 1.0017, 95 %CI: 1.0001, 1.0034, for a 10 μg/m(3) increase). No interactive effects between ambient temperature and PM(2.5) on SGA were observed. Our findings suggest the weekly susceptibility windows for heat and PM(2.5) exposure were primarily the gestational weeks within the 2nd trimester, therefore, corresponding protective measures should be conveyed to pregnant women during routine prenatal visits to reduce exposures.
The production and quality of human life have been impacted by the extreme heat wave events caused by global warming and urbanization. This study analyzed the prevention of air pollution and the strategies of emission reduction based on decision trees (DT), random forests (RF), and extreme random trees (ERT). Additionally, we quantitatively investigated the contribution rate of atmospheric particulate pollutants and greenhouse gases to urban heat wave occurrences by combining numerical models and big data mining technology. This study focuses on changes in the urban environment and climate. The main findings of this study are as follows. The average concentrations of PM(2.5) in the northeast of Beijing-Tianjin-Hebei in 2020 were 7.4%, 0.9%, and 9.6% lower than those in the corresponding years of 2017, 2018, and 2019, respectively. The carbon emissions in the Beijing-Tianjin-Hebei region showed an increasing trend during the previous 4 years, which was consistent with the spatial distribution of PM(2.5). In 2020, there were fewer urban heat waves, which was attributable to a reduction of 75.7% in emissions and an improvement of 24.3% in the prevention and management of air pollution. These results suggest that the government and environmental protection agencies need to pay attention to changes in the urban environment and climate to diminish the negative effects of heatwaves on the health and economic growth of the urban population.
This study aims to determine the reasons for the increase in the frequency of sand and dust storms in the Middle East and to identify their sources and mitigate them. A set of climatic data from 60 years (1960-2022) was analyzed. Sand storms in Iraq are a silty sand mature arkose composed of 72.7% sand, 25.1% silt, and 2.19% clay; the clay fraction in dust storms constitutes 70%, with a small amount of silt (20.6%) and sand (9.4%). Dust and sand storms (%) are composed of quartz (49.2, 67.1), feldspar (4.9, 20.9), calcite (38, 5), gypsum (4.8, 0.4), dolomite (0.8, 1.0), and heavy minerals (3.2, 6.6). Increasing temperatures in Iraq, by an average of 2 degrees C for sixty years, have contributed to an increase in the number of dust storms from 75 to 200 times annually. North African storms affect the Middle East, with a monthly average exceeding 300 g/m(3) in peak dust seasons. To reduce the negative impacts on public health, property, and infrastructure, the study suggests solutions to mitigate them, including reducing carbon dioxide gas emissions to prevent the expansion of drought and the afforestation of the desert with plants adapted to drought using advanced techniques and avoiding land overuse.
Ambient air pollution, and especially particulate matter (PM) air pollution <2.5 μm in diameter (PM(2.5)), has clearly emerged as an important yet often overlooked risk factor for atherosclerosis and ischemic heart disease (IHD). In this review, we examine the available evidence demonstrating how acute and chronic PM(2.5) exposure clinically translates into a heightened coronary atherosclerotic burden and an increased risk of acute ischemic coronary events. Moreover, we provide insights into the pathophysiologic mechanisms underlying PM(2.5)-mediated atherosclerosis, focusing on the specific biological mechanism through which PM(2.5) exerts its detrimental effects. Further, we discuss about the possible mechanisms that explain the recent findings reporting a strong association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, increased PM(2.5) exposure, and morbidity and mortality from IHD. We also address the possible mitigation strategies that should be implemented to reduce the impact of PM(2.5) on cardiovascular morbidity and mortality, and underscoring the strong need of clinical trials demonstrating the efficacy of specific interventions (including both PM(2.5) reduction and/or specific drugs) in reducing the incidence of IHD. Finally, we introduce the emerging concept of the exposome, highlighting the close relationship between PM(2.5) and other environmental exposures (i.e.: traffic noise and climate change) in terms of common underlying pathophysiologic mechanisms and possible mitigation strategies.
Composite dust samples were collected on a monthly basis over a full year from Doha, Qatar. Inductively Coupled Plasma Mass Spectrometry (ICPMS) was used for the determination of total concentrations of Na, K, Mg, Ca, Li, Be, B, V, Cr, Fe, Mn, Co, Ni, Cu, Zn, As, Se, Sr, Cd, Ba, Al, Pb, Ag, TI, U, Sb, Si, Sn, Mo and Bi. A combined approach, merging conventional sampling and analysis with subsequent numerical calculations of the risk of exposure to toxic elements, was employed. For assessment of the health risks associated with the regular exposure to dust, the exposure routes related to the dermal contact and inhalation were considered. Our results indicate that the total non-carcinogenic health risk through exposure to different elements (Hazardous Quotients, HQ’s) that are contained in the dust are quite low (well below unity) for both dermal contact and inhalation routes in all months of the year, i.e., there is no risk to the human health. There is no clear explanation for the seasonal variation of metals in the dust in the Qatar area. Several elements in the dust collected in the sum-mertime have higher concentration than in the wintertime. This could be due to the weather conditions and natural depositions. However, the content of several elements (Pb, Zn, Cu, Sn and Li) showed elevation in the wintertime. For dermal exposure, the dominant contribution to the Hazardous Index (HI) comes from thallium (Tl) while for inhalation exposure several comparable contributions are related to Mn, Sb, Si, Ni, and Co. Long -term monitoring strategies are still needed for detailed research on dust pollutants and potential risks.
BACKGROUND: Studies which analyse the joint effect of acoustic or chemical air pollution variables and different meteorological variables on neuroendocrine disease are practically nonexistent. This study therefore sought to analyse the impact of air pollutants and environmental meteorological variables on daily unscheduled admissions due to endocrine and metabolic diseases in the Madrid Region from January 01, 2013 to December 31, 2018. MATERIAL AND METHODS: We conducted a longitudinal, retrospective, ecological study of daily time series analysed by Poisson regression, with emergency neuroendocrine-disease admissions in the Madrid Region as the dependent variable. The independent variables were: mean daily concentrations of PM(10), PM(2.5), NO(2) and O(3); acoustic pollution; maximum and minimum daily temperatures; hours of sunlight; relative humidity; wind speed; and air pressure above sea level. Estimators of the statistically significant variables were used to calculate the relative risks (RRs). RESULTS: A statistically significant association was found between the increase in temperatures in heat waves, RR: 1.123 95% CI (1.001-1.018), and the number of emergency admissions, making it the main risk factor. An association between a decrease in sunlight and an increase in hospital admissions, RR: 1.005 95% CI (1.002 1.008), was likewise observed. Similarly, ozone, in the form of mean daily concentrations in excess of 44 μg/m(3), had an impact on admissions due to neuroendocrine disease, RR: 1.010 95% CI (1.007-1.035). The breakdown by sex showed that in the case of women, NO(2) was also a risk factor, RR: 1.021 95% CI (1.007-1.035). CONCLUSION: The results obtained in this study serve to identify risk factors for this disease, such as extreme temperatures in heat waves, O(3) or NO(2). The robust association found between the decrease in sunlight and increase in hospital admissions due to neuroendocrine disease serves to spotlight an environmental factor which has received scant attention in public health until now.
Windblown dust events, including dust storms and smaller blowing dust events, pose severe risks to public health and transportation safety. In the United States, the statistics of fatalities caused by dust events remains elusive. We developed a new dataset by merging dust Analysis Reporting System (FARS). There was a total of 232 deaths from windblown dust events from 2007 to 2017. This number is much larger than that reported by the NOAA Natural Hazard Statistics, which assigns some dust fatalities to high winds and thunderstorms (similar to 45%) and does not include many events in FARS. Dust fatalities are most frequent over the Southwest, consistent with the spatial distribution of dust storm occurrences. Other high-risk regions include the Colorado Plateau, Columbia Plateau in Washington and Oregon, the High Plains where the disastrous “Dust Bowl” occurred, and the Corn Belt where blowing dust from croplands presents a driving hazard. All six most deadly dust wrecks (three deaths or more) involved semi trucks and five of them were caused by dust storms along Interstate 10. There exist two “hotspots” for dust fatalities: 1) the “Deadliest 10 Miles” between Phoenix and Tucson, Arizona, and 2) Lordsburg Playa in New Mexico, where active dust mitigation projects have been managed by state transportation agencies. In most years, dust events caused comparable life losses to that from other weather hazards such as hurricanes, thunderstorms, lightning, and wildfires. This work presents new evidence that dust is an underappreciated weather hazard.
Air pollution is a growing concern in India, and its adverse health effects are well documented. Climate change is likely to exacerbate this problem by altering weather patterns and increasing the frequency and severity of extreme events. This paper examines the potential impact of climate change on ambient air pollution in India and its implications for policy design. Our analysis reveals that pollution in India is highly sensitive to variation in weather, particularly in the densely populated Indus-Gangetic Plain. Using our estimated relationship between weather and pollution, we predict that changing weather patterns will increase average PM2.5 concentrations by 3.1 mu g/m3, leading to a loss of 364 million years of life expectancy. To address this challenge, we propose an emissions fee calibrated to be highest in regions most vulnerable to persistently high levels of pollution and most sensitive to future deterioration in air quality due to climate change.
Air pollution and global temperature change are expected to affect infectious diseases. Air pollution usually causes inflammatory response and disrupts immune defense system, while temperature mainly exacerbates the effect of vectors on humans. Yet to date overview of systematic reviews assessing the exposure risk of air pollutants and temperature on infectious diseases is unavailable. This article aims to fill this research gap. PubMed, Embase, the Cochrane Library, Web of Science, and the Cumulative Index to Nursing and Allied Health Literature were searched. Systematic reviews and meta-analyses investigated the exposure risk of pollutants or temperature on infectious diseases were included. Two investigators screened literature, extracted data and performed the risk of bias assessments independently. A total of 23 articles met the inclusion criteria, which 3 (13%) were “low” quality and 20 (87%) were “critically low” quality. COVID-19 morbidity was associated with long-term exposure PM(2.5) (RR = 1.056 per 1 [Formula: see text], 95% CI: 1.039-1.072) and NO(2) (RR = 1.042 per 1 [Formula: see text], 95% CI: 1.017-1.068). In addition, for each 1 °C increase in temperature, the morbidity risk of dengue increased 13% (RR = 1.130 per 1 °C, 95% CI: 1.120-1.150), infectious diarrhea increased 8% (RR = 1.080 per 1 °C, 95% CI: 1.050-1.200), and hand, foot and mouth disease (HFMD) increased 5% (RR = 1.050 per 1 °C, 95% CI: 1.020-1.080). In conclusion, PM(2.5) and NO(2) increased the risk of COVID-19 and temperatures were associated with dengue, infectious diarrhoea and HFMD morbidity. Moreover, the exposure risk of temperature on COVID-19 was recommended to be further explored.
The climate change leads to periods of extreme events (i.e. reduction of cold seasons, heat waves, overheating, urban heat island among others) that affect the performance of residential and tertiary buildings with high occupancy (i.e. hospitals, schools, commercial centres, offices etc). However, most of low-carbon policies do not consider the ventilation as a mitigation measure. In fact, a lack of studies on natural ventilation (NV) and mixedmode (MM) strategies was detected, especially for warm regions or areas with hot and humid climates. This paper aims to carry out a bibliometric analysis from 1928 to 2023, to observe the evolution of the topic. After identifying the main research clusters (thermal comfort, energy efficiency, indoor air quality and simulation tools) by science mapping, the most relevant publications of the last 20 years were assessed (2003-2023). The results of this study revealed that only 1.51 % of the scientific documents in 95 years corresponded to an extensive literature review, although epidemic or disease outbreaks led to peaks of production in this topic. This emphasizes the importance of observing what was done and how was implemented over the years. Regarding the clusters, some relevant aspects can be highlighted: (i) non-homogeneity of studies on NV or MM related to building type; (ii) interregional projects should be drawn up to check the effectiveness of NV and MM, especially when other architectural techniques are adopted (i.e. solar chimneys, window wall ratio -WWR-, thermally activated building structures -TABS- etc); (iii) the optimization of simulation tools should be based on the incorporation of BIM and generative design for NV and MM.
Research on sense of place suggests that people’s understandings of themselves and others is closely tied to the feelings they have about the place where they reside. Solastalgia expands on this sociological concept by considering the impacts on the various benefits derived from place when a landscape is changed through acute or chronic environmental disruptions. As such, climate-related disasters affect both tangible and intangible goods. Using 24 qualitative interviews with residents of Paradise, California several months after a wildfire destroyed their town, this exploratory study examines three ways in which the solastalgia experience is socially constructed. This occurs through disruptions to coping resources found in the natural world, embeddedness of history in place, and the experience of “homesickness” for a changed landscape.
The Jazmurian basin in Iran is an area affected by climate change and desertification where aerosols and dust storms are common. The aim of this work was to determine the human and ecological risks from atmospheric particles during dust storms in different cities in the Jazmurian basin. For this purpose, the dust samples were collected from Jiroft, Roodbar Jonoob, Ghaleh Ganj, Kahnooj and Iranshahr cities, which are located around the Jazmurian playa in southeast of Iran. Satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products and the Aerosol Optical Depth (AOD) were used to detect aerosol loading in the atmosphere. Moreover, the trace element composition of the collected particles was determined and used to evaluate human and ecological impact assessment using US EPA human health risk assessment and ReCiPe 2016 endpoint hierarchist impact assessment method incorporated in the OpenLCA 1.10.3 software. The human health risk assessment of the particles revealed high non-carcinogenic risks for children from exposure to nickel and manganese and carcinogenic risks in both adults and children due to hexavalent chromium, arsenic and cobalt during dust storm events. Terrestrial ecotoxicity was found to have the largest ecological impact on ecosystems with copper, nickel and zinc exhibiting the largest contributions.
RATIONALE: Air pollution and extreme temperature and humidity are risk factors for lung dysfunction, but their interactions are not clearly understood. OBJECTIVES: To assess the impact of exposure to air pollutants and meteorological factors on lung function, and the contribution of their interaction to the overall effect. METHODS: The peak expiratory flow rates of 135 participants were repeatedly measured during up to four visits. Two weeks before each visit, the concentrations of gaseous pollutants and 19 fine particle components, and the temperature and relative humidity, were continuously monitored in the community where they lived. A Bayesian Kernel machine regression model was used to explore the non-linear exposure-response relationships of the peak expiratory flow rate with pollutant exposure and meteorological factors, and their interactions. MEASUREMENTS AND MAIN RESULTS: Increased temperature and relative humidity could exacerbate pollutant-associated decline in the peak expiratory flow rate, although their associations with lung dysfunction disappeared after adjustment for pollutant exposure. For example, declines of peak expiratory flow rate associated with interquartile range increase of 3-day cadmium exposure were -0.03 and -0.07 units, when temperature was at 0.1 and 19.5 °C, respectively. Decreased temperature were associated with declines of peak expiratory flow rate after adjustment for pollutant exposure, and had interaction with pollutant exposure on lung dysfunction. CONCLUSIONS: High temperature, low temperature, and high humidity were all high-risk factors for lung dysfunction, and their interactions with pollutant levels contributed greatly to the overall effects.
Evidence on the potential interactive effects of heat and ambient air pollution on cause-specific mortality is inconclusive and limited to selected locations. OBJECTIVES: We investigated the effects of heat on cardiovascular and respiratory mortality and its modification by air pollution during summer months (six consecutive hottest months) in 482 locations across 24 countries. METHODS: Location-specific daily death counts and exposure data (e.g., particulate matter with diameters ≤ 2.5 µm [PM(2.5)]) were obtained from 2000 to 2018. We used location-specific confounder-adjusted Quasi-Poisson regression with a tensor product between air temperature and the air pollutant. We extracted heat effects at low, medium, and high levels of pollutants, defined as the 5th, 50th, and 95th percentile of the location-specific pollutant concentrations. Country-specific and overall estimates were derived using a random-effects multilevel meta-analytical model. RESULTS: Heat was associated with increased cardiorespiratory mortality. Moreover, the heat effects were modified by elevated levels of all air pollutants in most locations, with stronger effects for respiratory than cardiovascular mortality. For example, the percent increase in respiratory mortality per increase in the 2-day average summer temperature from the 75th to the 99th percentile was 7.7% (95% Confidence Interval [CI] 7.6-7.7), 11.3% (95%CI 11.2-11.3), and 14.3% (95% CI 14.1-14.5) at low, medium, and high levels of PM(2.5), respectively. Similarly, cardiovascular mortality increased by 1.6 (95%CI 1.5-1.6), 5.1 (95%CI 5.1-5.2), and 8.7 (95%CI 8.7-8.8) at low, medium, and high levels of O(3), respectively. DISCUSSION: We observed considerable modification of the heat effects on cardiovascular and respiratory mortality by elevated levels of air pollutants. Therefore, mitigation measures following the new WHO Air Quality Guidelines are crucial to enhance better health and promote sustainable development.
PURPOSE OF REVIEW: Wildfire smoke is associated with human health, becoming an increasing public health concern. However, a comprehensive synthesis of the current evidence on the health impacts of ambient wildfire smoke on children and adolescents, an exceptionally vulnerable population, is lacking. We conduct a systematic review of peer-reviewed epidemiological studies on the association between wildfire smoke and health of children and adolescents. RECENT FINDINGS: We searched for studies available in MEDLINE, EMBASE, and Scopus from database inception up to October 11, 2022. Of 4926 studies initially identified, 59 studies from 14 countries were ultimately eligible. Over 33.3% of the studies were conducted in the USA, and two focused on multi-countries. The exposure assessment of wildfire smoke was heterogenous, with wildfire-specific particulate matters with diameters ≤ 2.5 µm (PM(2.5), 22.0%) and all-source (22.0%) PM(2.5) during wildfire period most frequently used. Over half of studies (50.6%) focused on respiratory-related morbidities/mortalities. Wildfire smoke exposure was consistently associated with enhanced risks of adverse health outcomes in children/adolescents. Meta-analysis results presented a pooled relative risk (RR) of 1.04 (95% confidence interval [CI], 0.96-1.12) for all-cause respiratory morbidity, 1.11 (95% Ci: 0.93-1.32) for asthma, 0.93 (95% CI, 0.85-1.03) for bronchitis, and 1.13 (95% CI, 1.05-1.23) for upper respiratory infection, whilst - 21.71 g for birth weight (95% CI, - 32.92 to - 10.50) per 10 µg/m(3) increment in wildfire-specific PM(2.5)/all-source PM(2.5) during wildfire event. The majority of studies found that wildfire smoke was associated with multiple adverse health outcomes among children and adolescents, with respiratory morbidities of significant concern. In-utero exposure to wildfire smoke may increase the risk of adverse birth outcomes and have long-term impacts on height. Higher maternal baseline exposure to wildfire smoke and poor family-level baseline birthweight respectively elevated risks in preterm birth and low birth weight associated with wildfire smoke. More studies in low- and middle-income countries and focusing on extremely young children are needed. Despite technological progress, wildfire smoke exposure measurements remain uncertain, demanding improved methodologies to have more precise assessment of wildfire smoke levels and thus quantify the corresponding health impacts and guide public mitigation actions.
AimClimate change and air pollution exposures are global issues impacting human health. This scoping review aims to synthesize evidence on the health-related impacts of climate change and air pollution exposures on immigrant and refugee populations younger than 18 and 65 years and older, and to determine if the impacts are influenced by age, immigrant category, gender, and/or geographical location.Subject and methodsDatabases were searched from inception to July 2022 and included PROSPERO, OVID Medline, OVID EMBASE, Wiley Cochrane Library (CDSR and Central), Proquest Dissertations and Theses Global and SCOPUS. All time frames, languages, and geographic locations were included. Types of evidence sources included were reviews (e.g. scoping, systematic, clinical), books, and descriptive (e.g., ecological) and analytical (e.g. case-control, cross-sectional and cohort) studies.ResultsThree studies fit the criteria. All used secondary data sources, different study designs and analysis approaches and defined immigrants, refugees, and exposures differently. Only climate change exposures (excessive temperatures) were explored, with mortality and respiratory syncytial virus outcomes. Two articles found that foreign-born and non-US citizens 65 years and older were similarly or less susceptible compared to native-born, but younger individuals were more susceptible. The other found that higher temperatures were associated with higher respiratory syncytial virus incidence in refugee children younger than 5 years old. If stratification was done, only sex, age, race, ethnicity, and place of birth were examined.ConclusionsImmigrants and refugees are understudied in the literature and often excluded. Additional research is needed to determine other exposures and health outcomes for immigrant and refugee populations.
PURPOSE: Climate change is considered to be the greatest threat to human health in the 21st century, and its effects are accelerating. Extensive research has clearly demonstrated its increasing impact across the continuum of health conditions. Despite this, there has been limited attention to the ramifications of climate change on hearing loss and hearing disorders. This lack of consideration is somewhat surprising as the environment itself and its changing nature have a substantial effect on hearing. METHOD: Tackling climate change could be the greatest global health opportunity of the 21st century. To address this issue, this tutorial provides a general introduction to climate change and its three major elements (pollution, infectious diseases, and extreme weather events) and their effects on health. The substantial consequences of climate change for the incidence, development, and exacerbation of hearing loss and disorders are clearly described and detailed. CONCLUSIONS: The challenge of responding to this very real and escalating threat to hearing requires a combination of prevention, advocacy, and education. These three roles place audiologists in the perfect position to take action on the far-reaching effects of climate change on hearing loss and disorders. To respond to this challenge and to fulfill these roles, several strategies, ranging from the individual level to the global level, are delineated for audiologists to incorporate into their practice.
PM(2.5) emissions from heavy-duty diesel trucks (HDDTs) have a significant impact on air quality, human health, and climate change, and seriously threaten the UN Sustainable Development Goals. Globally, a series of emission control measures have been implemented to reduce pollution emissions from HDDTs. Current studies assessing the impact of these measures on air quality and human health have mainly used coarse-grained emission data as input to dispersion model, resulting in the inability to capture the spatiotemporal variability of pollutant concentrations and tending to increase the uncertainty of health impact assessment results. In this study, we quantified the impact of pollution control policies for HDDTs in Beijing on PM(2.5) concentrations, human health, and economic losses by integrating policy scenario analysis, pollution dispersion simulation, public health impact and economic benefit assessment models, supported by high spatiotemporal resolution emission data from HDDTs. The results show that PM(2.5) concentrations from HDDTs exhibit significant spatial aggregation characteristics, with the intensity of aggregation at night being about twice as high as that during the day. The emission hotspots are mainly concentrated in the sixth, fifth and fourth rings and major highways. Compared to the “business as usual” scenario in 2018, the current policy of updating the fuel standard to China VI and the emission standard to China 6 can reduce PM(2.5) concentrations by 96.72%, thereby avoiding 612 premature deaths, which is equivalent to obtaining economic benefits of 1.65 billion CNY. This study further emphasizes the importance of high spatiotemporal resolution emission data during traffic dispersion modeling. The results can help improve the understanding of the effectiveness of emission reduction measures for HDDTs from a health benefit perspective.
Climate change and its respective environmental impacts, such as dying lakes, is widely acknowledged. Studies on the impact of shrinking hyper-saline lakes suggest severe negative consequences for the health of the affected population. The primary aim was to investigate the relationship between changes in the water level of the hyper-saline Lake Urmia, along with the associated salt release, and the prevalence of hypertension and the general state of health of the local population in Shabestar County north of the lake. Moreover, we sought to map the vulnerability of the local population to the health risks associated with salt-dust scatter using multiple environmental and demographic characteristics. We applied a spatiotemporal analysis of the environmental parameters of Lake Urmia and the health of the local population. We analyzed health survey data from local health care centers and a national STEPS study in Shabestar County, Iran. We used a time-series of remote sensing images to monitor the trend of occurrence and extent of salt-dust storms between 2012 and 2020. To evaluate the impacts of lake drought on the health of the residences, we investigated the spatiotemporal correlation of the lake drought and the state of health of local residents. We applied a GIScience multiple decision analysis to identify areas affected by salt-dust particles and related these to the health status of the residents. According to our results, the lake drought has significantly contributed to the increasing cases of hypertension in local patients. The number of hypertensive patients has increased from 2.09% in 2012 to 19.5% in 2019 before decreasing slightly to 16.05% in 2020. Detailed results showed that adults, and particularly females, were affected most by the effects of the salt-dust scatter in the residential areas close to the lake. The results of this study provide critical insights into the environmental impacts of the Lake Urmia drought on the human health of the residents. Based on the results we suggest that detailed socioeconomic studies might be required for a comprehensive analysis of the human health issues in this area. Nonetheless, the proposed methods can be applied to monitor the environmental impacts of climate change on human health.
BACKGROUND: Given the increasing prevalence of wildfires worldwide, understanding the effects of wildfire air pollutants on human health-particularly in specific immunologic pathways-is crucial. Exposure to air pollutants is associated with cardiorespiratory disease; however, immune and epithelial barrier alterations require further investigation. OBJECTIVE: We sought to determine the impact of wildfire smoke exposure on the immune system and epithelial barriers by using proteomics and immune cell phenotyping. METHODS: A San Francisco Bay area cohort (n = 15; age 30 ± 10 years) provided blood samples before (October 2019 to March 2020; air quality index = 37) and during (August 2020; air quality index = 80) a major wildfire. Exposure samples were collected 11 days (range, 10-12 days) after continuous exposure to wildfire smoke. We determined alterations in 506 proteins, including zonulin family peptide (ZFP); immune cell phenotypes by cytometry by time of flight (CyTOF); and their interrelationship using a correlation matrix. RESULTS: Targeted proteomic analyses (n = 15) revealed a decrease of spondin-2 and an increase of granzymes A, B, and H, killer cell immunoglobulin-like receptor 3DL1, IL-16, nibrin, poly(ADP-ribose) polymerase 1, C1q TNF-related protein, fibroblast growth factor 19, and von Willebrand factor after 11 days’ average continuous exposure to smoke from a large wildfire (P < .05). We also observed a large correlation cluster between immune regulation pathways (IL-16, granzymes A, B, and H, and killer cell immunoglobulin-like receptor 3DL1), DNA repair [poly(ADP-ribose) 1, nibrin], and natural killer cells. We did not observe changes in ZFP levels suggesting a change in epithelial barriers. However, ZFP was associated with immune cell phenotypes (naive CD4(+), T(H)2 cells). CONCLUSION: We observed functional changes in critical immune cells and their proteins during wildfire smoke exposure. Future studies in larger cohorts or in firefighters exposed to wildfire smoke should further assess immune changes and intervention targets.
Ambient fine particulate matter (PM(2.5)) has severe adverse health impacts, making it crucial to reduce PM(2.5) exposure for public health. Meteorological and emissions factors, which considerably affect the PM(2.5) concentrations in the atmosphere, vary substantially under different climate change scenarios. In this work, global PM(2.5) concentrations from 2021 to 2100 were generated by combining the deep learning technique, reanalysis data, emission data, and bias-corrected CMIP6 future climate scenario data. Based on the estimated PM(2.5) concentrations, the future premature mortality burden was assessed using the Global Exposure Mortality Model. Our results reveal that SSP3-7.0 scenario is associated with the highest PM(2.5) exposure, with a global concentration of 34.5 μg/m(3) in 2100, while SSP1-2.6 scenario has the lowest exposure, with an estimated of 15.7 μg/m(3) in 2100. PM(2.5)-related deaths for individuals under 75 years will decrease by 16.3 and 10.5% under SSP1-2.6 and SSP5-8.5, respectively, from 2030s to 2090s. However, premature mortality for elderly individuals (>75 years) will increase, causing the contrary trends of improved air quality and increased total PM(2.5)-related deaths in the four SSPs. Our results emphasize the need for stronger air pollution mitigation measures to offset the future burden posed by population age.
Wildfires are thought to be increasing in severity and frequency as a result of climate change(1-5). Air pollution from landscape fires can negatively affect human health(4-6), but human exposure to landscape fire-sourced (LFS) air pollution has not been well characterized at the global scale(7-23). Here, we estimate global daily LFS outdoor fine particulate matter (PM(2.5)) and surface ozone concentrations at 0.25° × 0.25° resolution during the period 2000-2019 with the help of machine learning and chemical transport models. We found that overall population-weighted average LFS PM(2.5) and ozone concentrations were 2.5 µg m(-3) (6.1% of all-source PM(2.5)) and 3.2 µg m(-3) (3.6% of all-source ozone), respectively, in 2010-2019, with a slight increase for PM(2.5), but not for ozone, compared with 2000-2009. Central Africa, Southeast Asia, South America and Siberia experienced the highest LFS PM(2.5) and ozone concentrations. The concentrations of LFS PM(2.5) and ozone were about four times higher in low-income countries than in high-income countries. During the period 2010-2019, 2.18 billion people were exposed to at least 1 day of substantial LFS air pollution per year, with each person in the world having, on average, 9.9 days of exposure per year. These two metrics increased by 6.8% and 2.1%, respectively, compared with 2000-2009. Overall, we find that the global population is increasingly exposed to LFS air pollution, with socioeconomic disparities.
Global warming is a result of the increased emission of greenhouse gases. The consequences of this climate change threaten society, biodiversity, food and resource availability. The consequences include an increased risk of cardiovascular (CV) disease and cardiovascular mortality. In this position paper, we summarize the data from the main studies that assess the risks of a temperature increase or heat waves in CV events (CV mortality, myocardial infarction, heart failure, stroke, and CV hospitalizations), as well as the data concerning air pollution as an enhancer of temperature-related CV risks. The data currently support global warming/heat waves (extreme temperatures) as cardiovascular threats. Achieving neutrality in emissions to prevent global warming is essential and it is likely to have an effect in the global health, including the cardiovascular health. Simultaneously, urgent steps are required to adapt the society and individuals to this new climatic context that is potentially harmful for cardiovascular health. Multidisciplinary teams should plan and intervene healthcare related to temperature changes and heat waves and advocate for a change in environmental health policy.
Ground-level ozone is a major air pollutant harmful to human health. In the scope of climate change, it is essential to provide high-quality local-scale assessments of the anticipated changes for public health and policy interventions. Assessments and projections of ground-level ozone usually rely on numerical modeling, but statistical approaches are also available. The present study enhances the validity of statistical downscaling by taking climate change as well as air pollution changes into account. Besides considering meteorological predictors such as air temperature, short-wave radiation, humidity, and wind, ozone trends from changes in precursor emissions were included in the statistical models. Meteorological and ozone predictor information extracted from reanalysis data for the observational period and output of seven Earth System Models (ESMs) for the projection periods were used, with three of them having interactive chemical modeling, while the other four used prescribed ozone changes. Ground-level ozone, more precisely daily maximum 8-hr running means (MDA8) as well as daily maximum 1-hr values (MDA1), at 798 measurement stations across the European area in the “ozone season ” from April to September were assessed. Results depended strongly on whether only meteorological information or additional information about emission changes were considered. As a general picture under the consideration of climate and emission changes, decreasing ground-level ozone concentrations were projected under the moderate SSP2-4.5 scenario, while for the more pessimistic scenario SSP3-7.0 increasing ozone concentrations over Europe, especially at the end of the 21st century, were assessed.
Plant species vary under different climate conditions and the distribution of pollen in the air and their trends can be used to assess the impact of climate change on public health. In 2015, MASK-air® (Mobile Airways Sentinel networK for rhinitis and asthma) was launched as a project of the European Innovation Partnership on Active and Healthy Ageing (EIP-on-AHA, DG Santé and DG CONNECT). This project aimed to develop a warning system to inform patients about the pollen season onset. SILAM (System for Integrated modeLling of Atmospheric composition), a global-to-meso-scale dispersion model was developed by the Finnish Meteorological Institute (FMI). It provides quantitative information on atmospheric pollution of anthropogenic and natural origins, particularly on allergenic pollens. POLLAR (Impact of Air Pollution on Asthma and Rhinitis, EIT Health) has combined MASK-air clinical data with SILAM forecasts. A new Horizon Europe grant, CATALYSE (Climate Action to Advance HeaLthY Societies in Europe; grant agreement number 101057131), which started in September 2022, aims at better understanding climate change and finding ways to counteract it. One objectives of this project is to develop early warning systems and predictive models to improve the effectiveness of adaptation strategies to climate change. One of warning system is focused on allergic rhinitis (CATALYSE Task 3.2). with a collaboration between the FMI (Finland), Porto University (Portugal), MASK-air SAS (France), ISGlobal (Spain), Hertie School (Germany) and the University of Zurich (Switzerland). It is to be implemented with the support of EAACI. This paper reports the planning of CATALYSE Task 3.2.
INTRODUCTION: Climate change is expected to worsen air pollution globally, which contributes to a multitude of negative health outcomes in humans. AIM: The purpose of this integrative review is to examine the relationship between exposure to fine particulate matter (PM(2.5) ) and mental health outcomes in children and adolescents. METHODS: This review utilized Whittemore and Knafl’s methodology for conducting an integrative review. After a thorough search of the literature, 17 articles were selected for this review and evaluated utilizing the Johns Hopkins Evidence Based Practice Appraisal Tool. RESULTS: Of the 17 articles, all were quantitative observational study designs. The studies were then synthesized into four outcome themes. These themes included emergent and general psychiatric outcomes, neurodevelopmental disorders, stress and anxiety, and depression. DISCUSSION: The strongest evidence supports a possible correlation between PM(2.5) exposure and adolescent mental health outcomes, although there were some studies that contradicted these associations. While research on this topic is in its early stages, more needs to be conducted to determine causality with any of the associations presented to improve generalizability of the findings. IMPLICATIONS FOR PRACTICE: Nurses must be aware of and part of the solution to address climate change and resulting air pollution, as it is a potentially significant threat to children’s mental health in the 21st century.
Aerobiological studies are still scarce in northwestern Mexico where allergenic pollen have great impacts on health. Current global pollution and climate change problems are closely related to many allergic diseases, enhancing the need to continue researching these issues and improve life quality. This study provides the first Pollen Calendar for Hermosillo, Sonora, México. Airborne pollen were continuously collected for 5 years (2015-2019). The standardized methodology with a Hirst-type spore trap proposed for global aerobiological studies was used. Weather data were also taken from a station located in the city and used to explore correlations between climate and airborne pollen concentrations in different seasons. The most important pollen taxa recorded in air belongs to herbaceous pollen, such as Poaceae, Ambrosia, Asteraceae, Chenopodiaceae-Amaranthaceae, and some shrub trees typical of this arid region, such as Nyctaginaceae, Prosopis, Parkinsonia, and Fabaceae. The most critical herbaceous pollen related to allergies have a long mean pollen season throughout the years, and the most critical periods with high pollen concentration in air occur in two seasons, spring (March-April) and summer-fall (August-October). In these 5 years, the correlation analyses for these two peaks indicate that a link exists between pollen in the air and decreases in precipitation and temperatures, and an increase in relative humidity. An inter-annual variability in pollen concentrations was recorded related to different weather conditions. Although pollen calendars are location-specific, they are useful for future research on biological air quality scenarios in different cities. Using this standardized method for other regions can provide pollen calendars that have been proven clinically important in allergic disease management worldwide.
Air pollution and climate change are the most important environmental issues for European citizens. Despite the air quality improvements achieved in recent years, with most pollutants’ concentrations below the European Union legislated values, it is necessary to understand whether this will continue in the future due to expected climate changes impacts. In this context, this work tries to answer two main questions: (i) What is the relative contribution of emission source regions/activities to air quality, now and in the future, considering a climate change scenario?; and (ii) What additional policies are needed to support win-win strategies for air quality and climate mitigation and/or adaptation, at urban scale? For that, a climate and air quality modelling system, with source apportionment tools, was applied to the Aveiro Region, in Portugal. Main results show that in the future, due to the implementation of carbon neutrality measures, air quality in the Aveiro Region may improve, with reduction up to 4 μg.m(-3) for particulate matter (PM) concentrations and 22 μg.m(-3) for nitrogen dioxide (NO(2)), and consequently, the premature deaths due to air pollution exposure will also decrease. The expected air quality improvement will ensure that, in the future, the limit values of the European Union (EU) Air Quality Directive will not be exceeded, but the same will not happen if the proposed revision of the EU Air Quality Directive is approved. Results also shown that, in the future, industrial sector will be the one with higher relative contribution for PM concentrations and the second one for NO(2). For that sector, additional emission abatement measures were tested, showing that, in the future, it is possible to comply with all the new limit values proposed by the EU.
This paper investigates the causal effect of wildfire exposure on birth outcomes and older people’s health outcomes in United States (US). The study focuses on three sub-questions for each health outcome: (1) the causal effect of each of the five largest wildfires on individual health, (2) the causal impact of multiple large wildfires on individual health outcomes, and (3) the causal influence of wildfires larger than different sizes within different distances of counties on health outcomes at the county level. The analysis exploits data from National Vital Statistics System, Behavioural Risk Factor Surveillance System and FIRESTAT. In terms of birth outcomes, the findings show that the largest wildfire slightly increased the risk of other circulatory or respiratory anomalies. Multiple large wildfires moderately raised the risk of prematurity and led to a small decline in the probability of getting omphalocele and cleft lip. The county-level analysis suggests an increased risk of macrosomia following maternal exposure to wildfires. As for the elderly aged 65 + , the results indicate that exposure to multiple massive wildfires led to frequent occurrence of asthma symptoms, while the largest wildfire led to sleeping difficulty caused by asthma symptoms. The number of days older people experienced psychological problems was increased following exposure to multiple large wildfires.
Extreme temperature events (ETEs), including heat wave and cold spell, have been linked to myocardial infarction (MI) morbidity; however, their effects on MI mortality are less clear. Although ambient fine particulate matter (PM(2.5)) is suggested to act synergistically with extreme temperatures on cardiovascular mortality, it remains unknown if and how ETEs and PM(2.5) interact to trigger MI deaths. METHODS: A time-stratified case-crossover study of 202 678 MI deaths in Jiangsu province, China, from 2015 to 2020, was conducted to investigate the association of exposure to ETEs and PM(2.5) with MI mortality and evaluate their interactive effects. On the basis of ambient apparent temperature, multiple temperature thresholds and durations were used to build 12 ETE definitions. Daily ETEs and PM(2.5) exposures were assessed by extracting values from validated grid datasets at each subject’s geocoded residential address. Conditional logistic regression models were applied to perform exposure-response analyses and estimate relative excess odds due to interaction, proportion attributable to interaction, and synergy index. RESULTS: Under different ETE definitions, the odds ratio of MI mortality associated with heat wave and cold spell ranged from 1.18 (95% CI, 1.14-1.21) to 1.74 (1.66-1.83), and 1.04 (1.02-1.06) to 1.12 (1.07-1.18), respectively. Lag 01-day exposure to PM(2.5) was significantly associated with an increased odds of MI mortality, which attenuated at higher exposures. We observed a significant synergistic interaction of heat wave and PM(2.5) on MI mortality (relative excess odds due to interaction >0, proportion attributable to interaction >0, and synergy index >1), which was higher, in general, for heat wave with greater intensities and longer durations. We estimated that up to 2.8% of the MI deaths were attributable to exposure to ETEs and PM(2.5) at levels exceeding the interim target 3 value (37.5 μg/m(3)) of World Health Organization air quality guidelines. Women and older adults were more vulnerable to ETEs and PM(2.5). The interactive effects of ETEs or PM(2.5) on MI mortality did not vary across sex, age, or socioeconomic status. CONCLUSIONS: This study provides consistent evidence that exposure to both ETEs and PM(2.5) is significantly associated with an increased odds of MI mortality, especially for women and older adults, and that heat wave interacts synergistically with PM(2.5) to trigger MI deaths but cold spell does not. Our findings suggest that mitigating both ETE and PM(2.5) exposures may bring health cobenefits in preventing premature deaths from MI.
People with HIV (PWH) are disproportionately vulnerable to the impacts of wildfires, given the need for frequent access to healthcare systems, higher burden of comorbidities, higher food insecurity, mental and behavioral health challenges, and challenges of living with HIV in a rural area. In this study, we aim to better understand the pathways through which wildfires impact health outcomes among PWH. METHODS: From October 2021 through February 2022, we conducted individual semi-structured qualitative interviews with PWH impacted by the Northern California wildfires and clinicians of PWH who were impacted by wildfires. The study aims were to explore the influence of wildfires on the health of PWH and to discuss measures at the individual, clinic, and system levels that helped to mitigate these impacts. RESULTS: We interviewed 15 PWH and 7 clinicians. While some PWH felt that surviving the HIV epidemic added to their resilience against wildfires, many felt that the wildfires compounded the HIV-related traumas that they have experienced. Participants outlined five main routes by which wildfires negatively impacted their health: (1) access to healthcare (medications, clinics, clinic staff), (2) mental health (trauma; anxiety, depression, or stress; sleep disturbances; coping strategies), (3) physical health (cardiopulmonary, other co-morbidities), (4) social/economic impacts (housing, finances, community), and (5) nutrition and exercise. The recommendations for future wildfire preparedness were at the (1) individual-level (what to have during evacuation), (2) pharmacy-level (procedural, staffing), and (3) clinic- or county-level (funds and vouchers; case management; mental health services; emergency response planning; other services such as telehealth, home visits, home laboratory testing). CONCLUSIONS: Based on our data and prior research, we devised a conceptual framework that acknowledges the impact of wildfires at the community-, household-, and individual-level with implications for physical and mental health outcomes among PWH. These findings and framework can help in developing future interventions, programs, and policies to mitigate the cumulative impacts of extreme weather events on the health of PWH, particularly among individuals living in rural areas. Further studies are needed to examine health system strengthening strategies, innovative methods to improve access to healthcare, and community resilience through disaster preparedness. TRIAL REGISTRATION: N/A.
As described in the previous chapter, Chapter 4: Air pollution and pregnancy, there is robust literature on the adverse health impacts of ambient air pollution on perinatal outcomes. With climate change contributing to more extreme weather patterns, wildfire events are becoming more intense and frequent. Wildfire smoke is a major contributor to poor air quality and data are beginning to emerge with respect to the negative impact on perinatal outcomes. The aim of this chapter is to provide an overview of the current literature on wildfire smoke exposure in pregnancy and associated adverse outcomes.
Climate and pollution challenges have been increasing over the last decades. The eyes are susceptible to those challenges. Modern life allows the population to search internet engine tools for information regarding eye symptoms. Drug sales are globally monitored to orient the actions of pharmaceutical companies. Monitoring those two big data sources of information (i.e., trends in internet search of eye diseases and symptoms and eye drop sales) can be correlated with climate and pollution data of the same locations and time to create standards capable of alerting about climate and pollution challenges. The present hypothesis is that climate and pollution level changes correlate with an increase in the search for ocular discomfort on the internet and the sales volume of symptomatic-relieving eye drops, providing a new tool to people’s health and preventive medicine. The potential correlation with statistical significance and a reliable confidence interval will allow using these correlations as tools to monitor remotely and to compare the parameters among different regions and over time. The benefits are to provide subsidies to public health strategies to predict and minimize climatic and environmental parameters effects.
In this study, a total of 90 definitions were set up based on six air pollution definitions, five cold spell definitions, and three combined exposure scenarios. The relative risks (RRs) on all-cause, circulatory, and respiratory mortality were explored by a model combining a distributed linear lag model with quasi-Poisson regression. The definition in which daily PM(2.5) increases more than 75 μg/m(3) for at least 2 days and the average temperature falls below the 10th percentile for at least 2 days produced the best model fit performance in all-cause mortality. The high peaks of the health effect were generally observed around the lag days 6-9. The cumulative relative risks (CRRs) were more significant in the simultaneous-exposure scenario and higher in respiratory mortality, where the highest CRR (12.15, 3.69-40.03) was observed in definition P1T5, in which daily PM(2.5) increases more than 75 μg/m(3), and the average temperature falls below the 2.5th percentile for at least two days. For relative risk due to interaction (RERI), we found positive additive interactions (RERI > 0) between PM(2.5) pollution and cold spell, especially in respiratory mortality. Clarifying the definition of combined events can help policymakers to capture health risks and construct more effective risk warning systems.
Air pollution is one of the most important problems the world is facing nowadays, adversely affecting public health and causing millions of deaths every year. Particulate matter is a criteria pollutant that has been linked to increased morbidity, as well as all-cause and cause-specific mortality. However, this association remains under-investigated in smaller-size cities in the Eastern Mediterranean, which are also frequently affected by heat waves and dust storms. This study explores the impact of particulate matter with an aerodynamic diameter ≤ 10 μm (PM(10)) and ≤ 2.5 μm (PM(2.5)) on mortality (all-cause, cardiovascular, respiratory) in two coastal cities in the Eastern Mediterranean; Thessaloniki, Greece and Limassol, Cyprus. Generalized additive Poisson models were used to explore overall and gender-specific associations, controlling for long- and short-term patterns, day of week and the effect of weather variables. Moreover, the effect of different lags, season, co-pollutants and dust storms on primary associations was investigated. A 10 μg/m(3) increase in PM(2.5) resulted in 1.10 % (95 % CI: -0.13, 2.34) increase in cardiovascular mortality in Thessaloniki, and in 3.07 % (95 % CI: -0.90, 7.20) increase in all-cause mortality in Limassol on the same day. Additionally, significant positive associations were observed between PM(2.5) as well as PM(10) and mortality at different lags up to seven days. Interestingly, an association with dust storms was observed only in Thessaloniki, having a protective effect, while the gender-specific analysis revealed significant associations only for the males in both cities. The outcome of this study highlights the need of city- or county-specific public health interventions to address the impact of climate, population lifestyle behaviour and other socioeconomic factors that affect the exposure to air pollution and other synergistic effects that alter the effect of PM on population health.
Carbon dioxide emissions (CO(2)e) which is caused by energy use contributes to the global average surface temperature increase by 1.5 °C as compared to the mid-1800s which is causing a certain change in the climate and becoming an adverse effect on health and economy. The relationship between health status, CO(2)e, and energy use has yet to be thoroughly investigated in the top 20 highest emitting economies. The data from 2000 to 2019 is analyzed by using advanced techniques of cross-sectional augmented distributed lag (CS-DL) and cross-sectional augmented autoregressive distributed lag (CS-ARDL) which take into consideration crucial elements of panel data, namely dynamics, heterogeneity, and cross-sectional dependence. Moreover, cross-sectional augmented error correction method (CS-ECM) and the common dynamic process of the augmented mean group (AMG) are applied for robustness checks. The empirical findings revealed that (i) CO(2)e weakens the health status only in the short-run, whereas health expenditure improves the health status in the both short- and long-runs, while economic growth is not contributing to the health status in the both short- and long-runs; (ii) health expenditure and economic growth only help to mitigate CO(2)e in the long-run, whereas energy use causes CO(2)e in the both short- and long-runs; (iii) energy use causes high economic growth in the both short- and long-runs, whereas CO(2)e aids economic growth in the short-run but is extremely damaging to economic growth in the long-run, while in the both short- and long-runs health expenditure is not aiding the economic growth. This study provides policy recommendations on improving human health by advocating massive health expenditures, CO(2)e easing, promoting renewable energy use or low-emission energy, and steering the economy toward green economic growth.
BACKGROUND: The impact of wildfire smoke is a growing public health issue, especially for those living with preexisting respiratory conditions. Understanding perceptions and behaviors relevant to the use of individual protective strategies, and how these affect the adoption of these strategies, is critical for the development of future communication and support interventions. This study focused on the use of masks by people living in the Australian community with asthma or chronic obstructive pulmonary disease (COPD). METHODS: Semi-structured phone interviews were undertaken with people living in the community aged 18 years and over. Participants lived in a bushfire-prone area and reported having been diagnosed with asthma or COPD. RESULTS: Twenty interviews were undertaken between July and September 2021. We found that, during wildfire episodes, there was an overwhelming reliance on closing windows and staying inside as a means of mitigating exposure to smoke. There was limited use of masks for this purpose. Even among those who had worn a mask, there was little consideration given to the type of mask or respirator used. Reliance on sensory experiences with smoke was a common prompt to adopting an avoidance behavior. Participants lacked confidence in the information available from air-quality apps and websites, however they were receptive to the idea of using masks in the future. CONCLUSIONS: Whilst COVID-19 has changed the nature of community mask use over the last couple of years, there is no guarantee that this event will influence an individual’s mask behavior during other events like bushfires. Instead, we must create social support processes for early and appropriate mask use, including the use of air quality monitoring.
Perinatal exposure to heat and air pollution has been shown to affect the risk of preterm birth (PTB). However, limited evidence exists regarding their joint effects, particularly in heavily polluted regions like China. This study utilized data from the ongoing China Birth Cohort Study, including 103 040 birth records up to December 2020, and hourly measurements of air pollution (PM2.5, NO2, and O-3) and temperature. We assessed the nonlinear associations between air pollution and temperature extereme exposures and PTB by employing generalized additive models with restricted cubic slines. Air pollution and temperature thresholds (corresponding to minimum PTB risks) were determined by the lowest Akaike Information Criterion. We found that maternal exposures to PM2.5, NO2, O-3, and both low and high temperature during the third trimester of pregnancy were independently associated with increased risk of PTB. The adjusted risk ratios for PTB of PM2.5, O-3, NO2, and temperature at the 95th percentile against thresholds were 1.32 (95% CI: 1.23, 1.42), 1.33 (95% CI: 1.18, 1.50), 1.44 (95% CI: 1.33, 1.56) and 1.70 (95% CI: 1.56, 1.85), respectively. Positive additive interactions [relative excess risk due to interaction (RERI) > 0] of PM2.5-high temperature (HT), O-3-HT, O-3-low temperature (LT) are identified, but the interactive effects of PM2.5 and LT were negative (RERI < 0). These observed independent effects of air pollution and temperature, along with their potential joint effects, have important implications for future studies and the development of public health policies aimed at improving perinatal health outcomes.
Exposure to environmental variables including declining air quality and increasing temperatures can exert detrimental effects on human health including acute exacerbations of chronic diseases. We aim to investigate the association between these exposures and acute health outcomes in a rural community in Colorado. Meteorological and adult emergency department visit data were retrospectively collected (2013-2017); for asthma outcomes, additional data were available (2003-2017). Daily environmental exposure data included PM(10), maximum daily temperature (MDT), and mean humidity and precipitation. Total daily counts of emergency department (ED) diagnoses for myocardial infarction, congestive heart failure, urolithiasis, and exacerbation of chronic obstructive pulmonary disease (COPD) and asthma, were calculated during the study period. Time series models using generalized estimating equations were fit for each disease and included all four environmental factors. Between 2013 and 2017, asthma and COPD exacerbation accounted for 30.8% and 25.4% of all ED visits (n=5,113), respectively. We found that for every 5˚C increase in MDT, the rate of urolithiasis visits increased by 13% (95% CI: 2%, 26%) and for every 10μg/m(3) increase in 3-day moving average PM(10), the rate of urolithiasis visits increased by 7% (95% CI: 1%, 13%). The magnitude of association between 3-day moving average PM(10) and rate of urolithiasis visits increased with increasing MDT. The rate of asthma exacerbation significantly increased as 3-day, 7-day, and 21-day moving average PM(10) increased. This retrospective study on ED visits is one of the first to investigate the impact of several environmental exposures on adverse health outcomes in a rural community. Research into mitigating the negative impacts of these environmental exposures on health outcomes is needed.
Sub-micron particles are ubiquitous in the indoor environment, especially during wildfire smoke episodes, and have a higher impact on human health than larger particles. Conventional fibrous air filters installed in heating, ventilation, and air conditioning (HVAC) systems play an important role in controlling indoor air quality by removing various air pollutants, including particulate matter (PM). However, it is evident that the removal efficiency of wildfire smoke PM and its effect on filter performance is significantly under-studied. This study delves into the size-specific removal efficiency of pine needle smoke, a representative of wildfire smoke and emissions. We test an array of filter media with minimum efficiency reporting values (MERV) spanning 11-15. Both size-resolved particle number concentrations and mass concentrations were measured using an Optical Particle Sizer (OPS, TSI, Inc.) and a Scanning Mobility Particle Sizer (SMPS, TSI, Inc.). Furthermore, we characterize the filter media morphology and smoke particles deposited on filter fibers using Scanning Electron Microscopy (SEM) to gain insights into the interaction dynamics of these particles. Our findings add to the comprehension of the relationship between MERV designations and smoke removal efficiency. Such insight can inform standards and guidelines and equip decision-makers with the knowledge needed to initiate measures for mitigating the impact of air pollution, specifically on the indoor environment.
Numerous environmental contaminants significantly contribute to human disease, affecting climate change and public and individual health, resulting in increased mortality and morbidity. Because of the scarcity of information regarding pollution exposure from less developed nations with inadequate waste management, higher levels of poverty, and limited adoption of new technology, the relationship between pollutants and health effects needs to be investigated more. A similar situation is present in many developed countries, where solutions are only discovered after the harm has already been done and the necessity for safeguards has subsided. The connection between environmental toxins and health needs to be better understood due to difficulties in quantifying exposure levels and a lack of systematic monitoring. Different pollutants are to blame for both chronic and acute disorders. Additionally, research becomes challenging when disease problems are seen after prolonged exposure. This review aims to discuss the present understanding of the association between environmental toxins and human health in bridging this knowledge gap. The genesis of cancer and the impact of various environmental pollutants on the human body’s cardiovascular, respiratory, reproductive, prenatal, and neural health are discussed in this overview.
Climate change is an urgent public health crisis that significantly impacts disease development, health outcomes, and access to care. The major approaches to climate change are mitigation and adaptation. The purpose of this review is to discuss the effects of climate change on health and health disparities, review the carbon footprint of surgical care and discuss strategies for surgeons to reduce emissions and advocate for sustainability. RECENT FINDINGS: Recent studies increasingly demonstrate the direct and indirect health effects of climate change, including the relationship between climate and otolaryngologic disease. Within the domain of otolaryngology, we summarize findings related to climate change and health and healthcare delivery; health disparities; healthcare-associated emissions; and the role of otolaryngologists in mitigating and adapting to the climate crisis. There are many recent studies that identify impactful sustainability opportunities and initiatives for healthcare providers. Climate solutions may also reduce cost and have potential clinical benefits. SUMMARY: Climate change and air pollution directly impact disease burden in otolaryngology patients and are underrecognized social determinants of health. Surgeons can lead on climate change by implementing sustainability initiatives in the operating room and engaging in research and advocacy.
This review provides an overview of the impact of air pollution on respiratory health, by examining the relationship between air pollution and climate change, as well as the effects of indoor and outdoor allergens, on airway respiratory health.Recent FindingsThe majority of the world’s population is exposed to air pollution levels that exceed the WHO’s air quality standards. Outdoor air pollution, particularly traffic-related air pollution, is linked to several respiratory disorders. Indoor air pollution resulting from the use of biomass and coal for cooking and heating is a significant contributor to respiratory illnesses. Climate change worsens air pollution by increasing the severity and frequency of extreme weather events, leading to higher levels of outdoor allergens.Air pollution is a public health issue globally, and its deleterious effects on respiratory health are particularly concerning. The interplay between air pollution and climate change poses a significant threat to vulnerable populations.
BACKGROUND: Environmental factors have been implicated in various eye pathologies. The purpose of this review is to synthesise the published research on environmental effects on eye disease. METHODS: Four databases were searched for terms relating to environmental exposures and ophthalmic disease. Titles and abstracts were screened followed by full-text review. Data was extracted from 118 included studies. Quality assessment was conducted for each study. RESULTS: Air pollutants, including nitrogen dioxide, nitrites, sulphur dioxide, particulate matter, carbon monoxide, ozone and hydrocarbons are associated with ocular conditions ranging from corneal damage to various retinopathies, including central retinal artery occlusion. Certain chemicals and metals, such as cadmium, are associated with increased risk of age-related macular degeneration. Climate factors, such as sun exposure, have been associated with the development of cataracts. Living in rural areas was associated with various age-related eye diseases whereas people living in urban settings had higher risk for dry eye disease and uveitis. CONCLUSION: Environmental exposures in every domain are associated with various ophthalmic conditions. These findings underscore the importance of continued research on the interplay between the environment and eye health.
Wildfire smoke has been associated with adverse respiratory outcomes, but the impacts of wildfire on other health outcomes and sensitive subpopulations are not fully understood. We examined associations between smoke events and emergency department visits (EDVs) for respiratory, cardiovascular, diabetes, and mental health outcomes in California during the wildfire season June-December 2016-2019. Daily, zip code tabulation area-level wildfire-specific fine particulate matter (PM(2.5)) concentrations were aggregated to air basins. A “smoke event” was defined as an air basin-day with a wildfire-specific PM(2.5) concentration at or above the 98th percentile across all air basin-days (threshold = 13.5 μg/m(3)). We conducted a two-stage time-series analysis using quasi-Poisson regression considering lag effects and random effects meta-analysis. We also conducted analyses stratified by race/ethnicity, age, and sex to assess potential effect modification. Smoke events were associated with an increased risk of EDVs for all respiratory diseases at lag 1 [14.4%, 95% confidence interval (CI): (6.8, 22.5)], asthma at lag 0 [57.1% (44.5, 70.8)], and chronic lower respiratory disease at lag 0 [12.7% (6.2, 19.6)]. We also found positive associations with EDVs for all cardiovascular diseases at lag 10. Mixed results were observed for mental health outcomes. Stratified results revealed potential disparities by race/ethnicity. Short-term exposure to smoke events was associated with increased respiratory and schizophrenia EDVs. Cardiovascular impacts may be delayed compared to respiratory outcomes.
Air pollution negatively affects a range of health outcomes. Wildfire smoke is an increasingly important contributor to air pollution, yet wildfire smoke events are highly salient and could induce behavioral responses that alter health impacts. We combine geolocated data covering all emergency department (ED) visits to nonfederal hospitals in California from 2006 to 2017 with spatially resolved estimates of daily wildfire smoke PM[Formula: see text] concentrations and quantify how smoke events affect ED visits. Total ED visits respond nonlinearly to smoke concentrations. Relative to a day with no smoke, total visits increase by 1 to 1.5% in the week following low or moderate smoke days but decline by 6 to 9% following extreme smoke days. Reductions persist for at least a month. Declines at extreme levels are driven by diagnoses not thought to be acutely impacted by pollution, including accidental injuries and several nonurgent symptoms, and declines come disproportionately from less-insured populations. In contrast, health outcomes with the strongest physiological link to short-term air pollution increase dramatically in the week following an extreme smoke day: We estimate that ED visits for asthma, COPD, and cough all increase by 30 to 110%. Data from internet searches, vehicle traffic sensors, and park visits indicate behavioral changes on high smoke days consistent with declines in healthcare utilization. Because low and moderate smoke days vastly outweigh high smoke days, we estimate that smoke was responsible for an average of 3,010 (95% CI: 1,760-4,380) additional ED visits per year 2006 to 2017. Given the increasing intensity of wildfire smoke events, behavioral mediation is likely to play a growing role in determining total smoke impacts.
Autoimmune eye diseases (AEDs), a collection of autoimmune inflammatory ocular conditions resulting from the dysregulation of immune system at the ocular level, can target both intraocular and periorbital structures leading to severe visual deficit and blindness globally. The roles of air pollution and meteorological factors in the initiation and progression of AEDs have been increasingly attractive, among which the systemic and local mechanisms are both involved in. Exposure to excessive air pollution and extreme meteorological conditions including PM(2.5)/PM(0.1), environmental tobacco smoke, insufficient sunshine, and high temperature, etc., can disturb Th17/Treg balance, regulate macrophage polarization, activate neutrophils, induce systemic inflammation and oxidative stress, decrease retinal blood flow, promote tissue fibrosis, activate sympathetic nervous system, adversely affect nutrients synthetization, as well as induce heat stress, therefore may together deteriorate AEDs. The crosstalk among inflammation, oxidative stress and dysregulated immune system appeared to be prominent. In the present review, we will concern and summarize the potential mechanisms underlying linkages of air pollution and meteorological factors to ocular autoimmune and inflammatory responses. Moreover, we concentrate on the specific roles of air pollutants and meteorological factors in several major AEDs including uveitis, Graves’ ophthalmopathy (GO), ocular allergic disease (OAD), glaucoma, diabetic retinopathy (DR), etc.
The chemical composition of PM(2.5) has a significant impact on human health and air quality, and its accurate knowledge can be used to identify contributing emission sources. Assessing and quantifying the impacts of various factors (e.g., emissions, meteorology, and large-scale climate patterns) on the main PM(2.5) chemical components can give guidance for implementing effective regulations to improve air quality in the future. In this study, we developed generalized additive models (GAMs) to assess how emissions, meteorological factors, and large-scale climate indices affected ammonium, sulfate, nitrate, elemental carbon, and organic carbon from 2002 to 2019 in the South Coast Air Basin (SoCAB). Concentration trends from three sites in the SoCAB are studied. The statistical results showed that GAMs can capture the variability of these species’ daily concentrations (R(2) = 0.6 to 0.7) and annual concentrations (R(2) = 0.93 to 0.99). Precursor emissions most significantly affect PM(2.5) species production, though meteorological factors like maximum temperature, relative humidity, wind speed, and boundary layer height, also influence PM(2.5) composition. In the future, these meteorological factors will become more significant in affecting PM(2.5) speciation, although emissions will continue to strongly affect formation. Results show that the composition of most PM(2.5) species will decrease in the future except for OC, which will become the largest contributor to PM(2.5).
BACKGROUND: In February 2022, an online Wildfire Smoke Communication Workshop series identified priorities and strategies to improve wildfire smoke communication in Canada. We evaluated the engagement methods, the workshop series and workshop summary report, to determine if participants/organizations initiated changes identified in the workshop to optimize wildfire smoke communication plans. METHODS: Three evaluation surveys were developed using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework dimensions and PRISM (Practical, Robust, Implementation, and Sustainability Model) contextual domains to measure the engagement impact. Surveys 1, 2, and 3 were disseminated to workshop participants between February 2022 (post-workshop series), May 2022 (pre-wildfire season), and September 2022 (post-wildfire season). Likert survey responses were analyzed descriptively using means and standard deviations. Open-ended written responses were analyzed using deductive reasoning and response proportions. RESULTS: Of 69 workshop participants, 28, 19, and 13 responded to surveys 1, 2, and 3, respectively. Workshop participation helped survey 1 respondents consider optimizing wildfire smoke communication (M = 3.93, SD = 0.88). Workshop participation and the summary report helped survey 2 respondents consider new actions to optimize wildfire smoke communication (M = 3.84, SD = 0.74). The most intended action in survey 2 (68%, n = 13) and the most common action taken in survey 3 (62%, n = 8) was to simplify message content. The primary limitation to optimization was capacity. CONCLUSION: The engagement methods, particularly the summary report, were beneficial for organizations to take action to optimize wildfire smoke communication in Canada. Future engagement methods should examine persisting system-level issues and capacity limitations as they undermine the ability to optimize wildfire smoke communication in Canada.
Climate change poses significant threats to human health, propelling Japan to take decisive action through the Climate Change Adaptation Act of 2018. This Act has led to the implementation of climate change adaptation policies across various sectors, including healthcare. In this review, we synthesized existing scientific evidence on the impacts of climate change on health in Japan and outlined the adaptation strategies and measures implemented by the central and local governments. The country has prioritized tackling heat-related illness and mortality and undertaken various adaptation measures to mitigate these risks. However, it faces unique challenges due to its super-aged society. Ensuring effective and coordinated strategies to address the growing uncertainties in vulnerability to climate change and the complex intersectoral impacts of disasters remains a critical issue. To combat the additional health risks by climate change, a comprehensive approach embracing adaptation and mitigation policies in the health sector is crucial. Encouraging intersectoral communication and collaboration will be vital for developing coherent and effective strategies to safeguard public health in the face of climate change.
With global climate change and rapid urbanization, the prevalence of allergic diseases caused by pollen is rising dramatically worldwide with unprecedented complexity and severity, especially for children in mega-cities. However, because of the lack of long time-series pollen concentrations data, the accurate evaluation of the impact of pollen on allergic rhinitis (AR) was scarce in the Chinese metropolis. A generalized additive model was used to assess the effect of pollen concentration on pediatric AR outpatient visits in Beijing from 2014 to 2019. A stratified analysis of 10 pollen species and age-gender-specific groups was also conducted during the spring and summer-autumn peak pollen periods separately. Positive associations between pollen concentration and pediatric AR varied with the season and pollen species were detected. Although the average daily pollen concentration is higher during the spring tree pollen peak, the influence was stronger at the summer-autumn weed pollen peak with the maximum relative risk 1.010 (95% CI 1.009, 1.011), which was higher than the greatest relative risk, 1.003 (95% CI 1.002, 1.004) in the spring peak. The significant adverse effects can be sustained to lag10 during the study period, and longer in the summer-autumn peak (lag13) than in the spring peak (lag8). There are thresholds for the health effects and they varied between seasons. The significant effect appeared when the pollen concentration was higher than 3.74 × 10(5) grain·m(-2)·d(-1) during the spring tree pollen peaks and 4.70 × 10(4) grain·m(-2)·d(-1) during the summer-autumn weed pollen peaks. The stratified results suggested that the species-specific effects were heterogeneous. It further highlights that enough attention should be paid to the problem of pollen allergy in children, especially school-aged children aged 7-18 years and weed pollen in the summer-autumn peak pollen period. These findings provide a more accurate reference for the rational coordination of medical resources and improvement of public health.
Management of adverse health-related effects from heat waves requires comprehensive and accessible sour-ces of information. This paper examines the effects of temperature and air pollution on human health and identifies areas with increased occurrence of emergency ambulance dispatches in the city of Wu & BULL;rzburg, Bavaria, Germany, and discusses the applicability for health care interventions and urban planning. An overdispersed Poisson generalized additive model was used to examine and predict the association and potential lag of exposure between temperature, air pollution, and three types of emergency ambulance dispatches during the study period from 2011 to 2019. A linear model was used to esti-mate heat-wave effects. A line density function was used to identify areas with increased occurrence of dispatches. Signifi- cant effects of temperature were detected for nontraumatic and cardiovascular diseases after exceeding a threshold temperature. The exposure-response relationships showed an increased relative risk up to two days after exposure for non-traumatic and cardiovascular diseases. Results indicate a significant association between presence of heat waves and cardio-vascular diseases with up to 17% (95% confidence interval: 5.9%-30.0%) increased relative risk on a heat-wave day relative to a non-heat-wave day. Dispatches for cardiovascular diseases occur more often in areas with a high population and building density, especially in summer. The analyses identified hotspots of heat-related dispatches in areas with in-creased population and building density and provides baseline information for interventions in future urban planning and public health care management based on data commonly available even in small cities. SIGNIFICANCE STATEMENT: The purpose of this study is to demonstrate how authorities in even medium-and small-sized cities can assess health impacts of heat stress or air pollution using free accessible emergency ambulance data and software to incorporate the outcomes in their spatial planning or health care management. This is important as ongoing climate change requires all urban communities to adapt and reduce adverse impacts of climate change and air pollution. Our results show that extreme heat leads to increased emergency ambulance dispatches in a medium-sized city in Germany and provide a spatial overview of where health care interventions and urban planning can focus to mitigate adverse effects.
The comfort level of outdoor thermal environments is affected by several factors. Previous studies of thermal comfort have generally investigated the main microclimatic factors as dependent variables, such as the temperature, wind speed, humidity, and thermal radiation, but the influence of the air quality has rarely been explored. In this study, we acquired meteorological element observations and conducted questionnaire surveys in Peach Blossom Park, Hebei University of Technology, and Xigu Park in Tianjin. We analyzed the effects of the outdoor air quality and thermal environment on the thermal comfort in order to provide a theoretical basis for comprehensive evaluations of the outdoor environment and the mechanism. The results showed that thermal resistance of clothing and ambient temperature followed a negative step change, where people generally reduced the minimum amount of clothing when the temperature exceeded 28 °C. One unit change in the thermal sensation vote (TSV) occurred for every 11 °C rise in the physiological equivalent temperature (PET). The neutral PET was 21.68 °C, and the comfortable PET was about 23 °C. The air quality index (AQI) and air satisfaction were negatively correlated, and satisfaction decreased by 1 unit for every change of 230 AQI. The transitional season was most comfortable when the temperature felt slightly cool (TSV = -0.70). The neutral TSV was 0.507 in the summer and -0.334 in the winter. Air quality had a significant effect on the thermal comfort vote (TCV) (p = 0.0485 < 0.05). The effect of PET on TCV was highly significant (p < 0.01).
There is a growing body of modelling evidence that demonstrates the potential for immediate and substantial benefits to adult health from greenhouse gas mitigation actions, but the effects on the health of younger age groups is largely unknown. We conducted a systematic review to identify the available published evidence of the modelled effects on child and adolescent health (≤18 years of age) of greenhouse gas mitigation. We searched six databases of peer-reviewed studies published between January 1, 1990 and July 27, 2022, screened 27,282 original papers and included 23 eligible papers. All included studies were set in high- and middle-income countries; and all studies modelled the effects of interventions that could mitigate greenhouse gas emissions and improve air quality. Most of the available evidence suggests positive benefits for child and adolescent respiratory health from greenhouse gas mitigation actions that simultaneously reduce air pollution (specifically PM2.5 and nitrogen dioxide). We found scant evidence on child and adolescent health from regions more vulnerable to climate change, or on mitigation interventions that could affect exposures other than air pollution.
Climate change is one of the most significant global challenges and is already having detrimental effects on people’s health. Pollution levels and ambient temperatures continue to increase, resulting in higher levels of humidity and pollen production. These environmental threats can affect many vulnerable patients, particularly those with respiratory and cardiovascular conditions, and nurses have a crucial role in raising awareness of the health implications of climate change. This article explores the pathophysiological effects of climate change on patients with asthma, chronic obstructive pulmonary disease and cardiovascular disease, and aims to enhance nurses’ understanding of the health challenges of climate change.
This scoping review assesses the current evidence on the health impacts of climate change and associated economic costs in South America. In total, 3281 studies were identified using a systematic search strategy, but only 23 articles met the inclusion criteria and were analysed. The results from these articles indicate that the health effects of climate change will likely be costly for South America; however, evidence is limited to a handful of countries or regional analyses that ignore heterogeneity across and within countries. Most of the analysed studies looking at extreme weather events related to climate change focus on the effects and costs of droughts and fire events. A broader understanding of the topic could be achieved by estimating other extreme weather events’ health effects and costs, using appropriate research methods to identify causal impacts, and including a more comprehensive and representative regional population sample. Beyond identifying effects, it is important to investigate demand responses for healthcare services, associated costs, availability and expansion of infrastructure, and cost-effectiveness of policies aimed at coping with and adapting to the health dimension of climate change.
In urban environments, the nonuniform distribution of pollution contributes to disproportionate exposure to harmful pollutants in low-income and high-poverty neighborhoods. Particulate matter, especially of the class PM2.5, results from combustion processes which are a main driver for human-caused global warming and climate change. A resulting impact on socio-economically disadvantaged communities like the Bronx, NY is the high incidence of asthma, other respiratory diseases, and cardiovascular disease. This disparity is an environmental justice concern. Project FRESH Air is educating the community through STEM outreach with sensors for monitoring particulate matter, student projects, curriculum development, and wider community engagement in order to educate for environmental justice.
BACKGROUND: Meteorological factors and air pollutants are believed to be associated with cardiovascular disease. Ischemic heart disease (IHD) is a major public health issue worldwide. Few studies have investigated the associations among meteorological factors, air pollutants and IHD daily hospital admissions in Lanzhou, China. METHODS: We conducted a distributed lag non-linear model (DLNM) on the basis of five years data, aiming at disentangling the impact of meteorological factors and air pollutants on IHD hospital admissions. All IHD daily hospital admissions recorded from January 1, 2015 and December 31, 2019 were obtained from three hospitals in Lanzhou, China. Daily air pollutant concentrations and meteorological data were synchronously collected from Gansu Meteorological Administration and Lanzhou Environmental Protection Administration. Stratified analyses were performed by sex and two age-groups. RESULTS: A total of 23555 IHD hospital admissions were recorded, of which 10477 admissions were for coronary artery disease (CAD), 13078 admissions were for acute coronary syndrome (ACS). Our results showed that there was a non-linear (J-shaped) relationship between temperature and IHD hospital admissions. The number of IHD hospital admissions were positively correlated with NO2, O3, humidity and pressure, indicating an increased risk of hospital admissions for IHD under NO2, O3, humidity and pressure exposure. Meanwhile, both extremely low (-12ºC) and high (30ºC) temperature reduced IHD hospital admissions, but the harmful effect increased with the lag time in Lanzhou, China, while the cold effect was more pronounced and long-lasting than the heat effect. Subgroup analysis demonstrated that the risk on CAD hospital admissions increased significantly in female and <65 years of age at -12ºC. CONCLUSION: Our findings added to the growing evidence regarding the potential impact of meteorological factors, air pollutants on policymaking from the perspective of hospital management efficiency.
An area with the potential of producing high concentrations of airborne pollen is defined as the ‘potential pollinosis area’. However, the detailed dynamics of pollen dispersion are not fully understood. Further, studies on the detailed dynamics of the pollen-generating environment are limited. This study aimed to determine the relationship between the dynamics of potential pollinosis areas and annual meteorological factors with high spatiotemporal resolution. We visualised and analysed the dynamics of the potential polliosis area based on 11-year high-spatial-density observation data for the atmospheric concentrations of Cryptomeria japonica pollen. The results showed that the potential pollinosis area headed northeast with repeated expansion and contraction, while the centre of the potential pollinosis area leaped to the north in mid-March. The variance in the fluctuation of the coordinates for the potential pollinosis area before the northward leap was strongly related to the variance in the relative humidity of the previous year. These results indicated that the pollen grains of C. japonica across Japan are distributed based on the meteorological conditions of the previous year until mid-March, after which, the pollen grains are distributed through flowering synchrony. Our results suggest that daily nationwide flowering synchrony has a significant annual impact, and changes in relative humidity caused by, for example, global warming would affect the occurrence and predictability of seasonal changes in the pollen dispersion dynamics of C. japonica and other pollen-producing species. Our study showed that pollen production by C. japonica through flowering synchrony is a major cause of nationwide pollinosis and other allergy-related health problems.
The results of two previously published reports of the events and impacts of the Campfire wildfire smoke exposure that occurred in California in 2018 are amplified from the point of view of the potential toxic mechanism involved. The Campfire wildfire led to the exposure of a breeding colony of macaque monkeys (Macaca mulatta) during the peak of their breeding season in 2018-2019. Considering the timing, adverse effects, and endocrine implications reported, the cumulative evidence points to an early toxic sensitive period that can lead to birth defects in higher primates and human pregnancies. This deeper inspection of the published observations provides important caveats and useful guidance for future investigators. The unique higher primate placental-adrenal-brain axis may limit the use of many traditional toxicologic approaches. Retrospective neurological evaluations of human fetuses exposed to air pollutants during organogenesis and subsequent retrospective characterization of air samples using in vitro and animal models may be the best procedures to follow.
California experienced extreme and prolonged drought conditions during the early 2010s. To date, little is known regarding the influence of drought on air quality. Our study quantified site-specific associations between drought (defined by the Standardized Precipitation-Evapotranspiration Index; SPEI) and daily maximum 8-h ozone (O(3)) concentrations for California, USA, and then pooled these associations for the years 2009-2015. Overall, ambient O(3) concentration was higher during droughts by 1.18 ppb (95% confidence interval (CI) = 1.00-1.36). The sensitivity of O(3) to drought was greater during the warm season than during the cool season (1.73 ppb versus 0.79 ppb higher O(3) during droughts) with substantial regional variation. In a pooled analysis with meteorological parameters as potential effect modifiers, the spatial heterogeneity of drought-O(3) associations was explained strongly by average relative humidity for each season (71.9% (warm season) and 73.4% (cool season) of the drought-O(3) associations explained), followed by the drought-related changes in relative humidity (47.6% (warm season)) and temperature (53.6% (cool season)). The pooled regression further identified regions susceptible for drought-related O(3) increases as those with relatively low average relative humidity (10-25(th) percentiles or 44.3-47.3%) and larger drought-related decrease in relative humidity and increase in temperature. As the drought events are projected to occur with increased frequency and intensity in the era of climate change, the excess health burdens from O(3) exposures attributed to the projected drought events need to be taken into account when allocating air quality and health resources. The impacts of O(3) on health during droughts would confound the health burdens from the drought itself.
Southwest Florida is one of the most rapidly growing regions of the United States and has been impacted over the past decade with water-quality issues and some associated health problems. The ionic ratios of the dust measured in southwest Florida vary significantly from those on the Florida east coast and in the Caribbean. The metals concentrations reported herein are enriched in potassium and calcium from local sources. Atmospheric deposition of metals and nutrients appears to have potential impacts on both indirect health problems and environmental issues of concern, particularly harmful algal blooms. However, no significant past research has been performed on measurement of the concentration of either metals including the micronutrient iron or nutrient concentrations occurring in atmospheric dry and wet fallout in southwest Florida. Measurements of the composition of key metals and nutrients were made over a one-year period. Concentrations of total phosphorus in the dust ranged from 0-80.5 mg/kg with an average of 4 mg/kg and in rainfall from 1-15.8 og/L with an average of 4 mg/kg. Nitrate ranged from 0-746 og/L with an average of 114.4 og/L in rainfall in a soluble form, and from 1.3 to 718 mg/kg with an average of 209.9 mg/kg in an insoluble form. Ammonia was measured to range from 1.4 to 658 mg/kg with an average of 101.4 mg/kg in rainfall. Iron was found in the dust at concentrations ranging from 0-81 mg/kg with an average of 3.8 mg/kg and in rainfall from 0-125.7 mg/kg with an average of 3.0 mg/kg. While the measured nutrient and iron concentrations are not likely to initiate a harmful algal bloom, they are likely to sustain an existing bloom. Global climate change may exacerbate the atmospheric aerosol issue by increased wind speeds over Africa associated with longer term drought conditions caused by atmospheric temperature increases.
Dust storms are extreme weather events that can lead to sharp short-duration reductions in environmental quality. Is the US and elsewhere, dust storms are becoming more frequent due to climate change and altered land-use patterns. However, our present understanding of their impacts to social welfare is limited. To address this gap, I undertake the first nationwide US study of dust storm impacts on subjective well-being using life satisfaction (LS) data from the CDC Behavioral Risk Factor Surveillance System (BRFSS) over 2005-2010. I find that LS is lower by 0.008 points on a 4-point scale on days when a dust storm occurred in a respondent’s county-of-residence, as identified by the National Weather Service. The observed LS impact is precisely estimated; occurring only on a dust storm event day and not the days immediately before or after. I calculate that individuals are willing-to-pay $111 to avoid a single dust storm event day, on the basis of the estimated well-being externality. I also show that public dust storm alerts on event days can offset more than 50% of the negative LS effect, suggestive of an important role for public risk communication.(c) 2023 Elsevier B.V. All rights reserved.
Under global warming and rapid urbanization, heat extremes, ozone pollution, and their co-occurrences are emerging and posing severe risks to human health. However, possibly different characteristics of independent heat days (IHD), independent ozone pollution (IOP) and compound heat-ozone pollution (CHOP) events are unclear. In this study, we present an investigation of the spatial distribution and mechanisms associated with IHD, IOP and CHOP events during May-October in 2014-2022 by taking the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China as an example. The results show that central GBA faces higher compound risk than northwestern and southeastern regions. IHD events are primarily driven by extremely high temperatures and accompanied by anomalous anticyclone and high pressure at both lower and upper troposphere levels, under the joint effects of the South Asian high and western North Pacific subtropical high. IOP events are predominantly accompanied by decreased cloud cover, air humidity and enhanced downward solar radiation. CHOP events are influenced by increases in both temperature and downward solar radiation. The circulation patterns of CHOP events are somewhat similar to IOP but with much stronger magnitude and faster developing process, and both are likely related to tropical cyclone activities. Our findings can strengthen the early forecasting of these extreme events and mitigate their negative impacts.
Climate change will be a major challenge for the world’s health systems in the coming decades. Elevated temperatures and increasing frequencies of heat waves, wildfires, heavy precipitation and other weather extremes can affect health in many ways, especially if chronic diseases are already present. Impaired responses to heat stress, including compromised vasodilation and sweating, diabetes-related comorbidities, insulin resistance and chronic low-grade inflammation make people with diabetes particularly vulnerable to environmental risk factors, such as extreme weather events and air pollution. Additionally, multiple pathogens show an increased rate of transmission under conditions of climate change and people with diabetes have an altered immune system, which increases the risk for a worse course of infectious diseases. In this review, we summarise recent studies on the impact of climate-change-associated risk for people with diabetes and discuss which individuals may be specifically prone to these risk conditions due to their clinical features. Knowledge of such high-risk groups will help to develop and implement tailored prevention and management strategies to mitigate the detrimental effect of climate change on the health of people with diabetes.
Air pollution associated with agricultural activities and land-cover change poses significant health problems in developing countries. However, studies on the respiratory health impacts of these activities are scarce. Su-matra, Indonesia, is a region well known for its frequent land fires and haze. Here, we link data on healthcare attendances for respiratory illnesses between 2001 and 2018 with biophysical and socioeconomic variables known to be important drivers of respiratory ailments. We show that the prevalence of respiratory illnesses increased by 8.5% during dry years over the last two decades. This was largely attributed to changes in rain-fall patterns and land cover. Increasingly severe drought during El Nin similar to o events, combined with reduced forest cover and increased land degradation on peatland, has further escalated fires with concomitant air pollution impacts on respiratory health. Our study highlights the need to explicitly incorporate health costs of environ-mental damage into land-use planning and public health interventions.
BACKGROUND: Traffic enforcers are vulnerable to work accidents, injuries, and illnesses because they are commonly exposed to ergonomic risk factors while performing their tasks. OBJECTIVE: The purpose of this study is to determine the effects of environmental risk factors and postural risk factor to the prevalence of musculoskeletal disorders (MSDs) among traffic enforcers in Manila City, Philippines using binary logistic regression analysis. METHODS: A total of 120 participants were included in the study. The Nordic Musculoskeletal Questionnaire (NMQ) and Rapid Entire Body Assessment (REBA) were utilized. In addition, several devices such as a noise dosimeter, digital air thermometer, and IAQ sensors were also utilized to measure the environmental exposure of enforcers during their work shift. RESULTS: The prevalence of MSDs among traffic enforcers was high, with 71% of the respondents reporting symptoms of MSDs in more than one part of the body for the past 7 days. The body part that has highest prevalence was upper back, followed by lower back, and legs/ankles. Logistic regression analysis revealed that awkward work posture (OR = 4.61, 95% CI = 2.17, 9.83), noise exposure (OR = 1.42, 95% CI = 1.11, 1.82), heat exposure (OR = 0.53, 95% CI = 0.85, 1.05), and pollution exposure (OR = 0.94, 95% CI = 0.85, 1.05) were significant contributors for the prevalence of MSDs among traffic enforcers in Manila City. CONCLUSION: The prevalence of MSDs among traffic enforcers is caused by their work posture and exposure to psychosocial factors such as noise, heat, and poor air quality. Thus, to minimize the risk of MSDs, it is suggested to provide administrative controls, such as job rotation or shifting, and introduce frequent rest breaks. It is also recommended to provide enforcers with appropriate personal protective equipment, such as cooling vests, noise-canceling earplugs and N95 facemasks. This would help in uplifting musculoskeletal health for traffic enforcers and other workers in a similar field.
Worldwide, approximately 1900 people die by suicide daily. Daily elevations in air pollution and temperature have previously been linked to a higher risk of death from suicide. To date, there have been relatively few studies of air pollution and suicide, particularly at a national level. National analyses play an important role in shaping health policy to mitigate against adverse health outcomes. METHODS: We used a time-stratified case-crossover study design to investigate the influence of short-term (i.e., day to day) interquartile range (IQR) increases in air pollutants (nitrogen dioxide [NO(2)], ozone [O(3)], and fine particulate matter [PM(2.5)]) and temperature on suicide mortality in Canada between 2002 and 2015. For air pollution models, odds ratios (ORs) derived from conditional logistic regression models were adjusted for average daily temperature, and holidays. For temperature models, ORs were adjusted for holidays. Stratified analyses were undertaken by suicide type (non-violent and violent), sex, age, and season. RESULTS: Analyses are based on 50,800 suicide deaths. Overall, temperature effects were stronger than those for air pollution. A same day IQR increase in temperature (9.6 °C) was associated with a 10.1% increase (95% confidence interval (CI): 9.0%-11.2%) of death from suicide. For 3-day average increase of O(3) (IQR = 14.1 ppb), PM(2.5) (IQR = 5.6 μg/m(3)) and NO(2) (IQR = 9.7 ppb) the corresponding risks were 4.7% (95% CI: 3.9, 5.6), 3.4% (95% CI: 3.0, 3.8), and 2.0% (95% CI: 1.1, 2.8), respectively. All pollutants showed stronger associations with suicide during the warmer season (April-September). Stratified analyses revealed stronger associations for both temperature and air pollution in women. CONCLUSIONS: Daily increases in air pollution and temperature were found to increase the risk of death from suicide. Females, particularly during warmer season, were most vulnerable to these exposures. Policy decisions related to air pollution and climate change should consider effects on mental health.
Events of high dust loading are extreme meteorological phenomena with important climate and health implications. Therefore, early forecasting is critical for mitigating their adverse effects. Dust modeling is a long-standing challenge due to the multiscale nature of the governing meteorological dynamics and the complex coupling between atmospheric particles and the underlying atmospheric flow patterns. While physics-based numerical modeling is commonly being used, we propose a meteorological-based deep multi-task learning approach for forecasting dust events. Our approach consists of forecasting the local PM10 (primary task) measured in situ, and simultaneously to predict the satellite-based regional PM10 (auxiliary task); thus, leveraging valuable information from a correlated task. We use 18 years of regional meteorological data to train a neural forecast model for dust events in Israel. Twenty-four hours before the dust event, the model can detect 76% of the events with even higher predictability of winter and spring events. Further analysis shows that local dynamics drive most misclassified events, meaning that the coherent driving meteorology in the region holds a predictive skill. Further, we use machine-learning interpretability methods to reveal the meteorological patterns the model has learned, thus highlighting the important features that govern dust events in the Middle East, being primarily lower-tropospheric winds, and Aerosol Optical Depth.
BACKGROUND: Extreme temperatures and air pollution have raised widespread concerns about their impact on population health. AIM: To explore the quantitative exposure risks of high/low temperatures and types of air pollutants on the health of various populations in urban areas in China, this study assessed the effects of temperature and air pollutants on daily non-accidental deaths in Rencheng District, Jining City, China from 2019 to 2021. METHODS: A combination of Poisson regression models and distributed lag non-linear models was used to examine the relationships between temperature, air pollutants, and daily non-accidental deaths. We found that temperature and air pollutants had a significant non-linear effect on non-accidental mortality. Both high and low temperatures had a noticeable impact on non-accidental deaths, with heat effects occurring immediately and lasting 2-3 days, while cold effects lasted for 6-12 days. The relative risks of non-accidental deaths from PM(2.5), NO(2), and SO(2) were highest in winter and lowest in autumn. The relative risk of non-accidental deaths from O(3) was highest in spring, with no significant variations in other seasons. Older adults (≥75) and outdoor workers were at the greatest risk from temperature and air pollutant exposure. CONCLUSIONS/INTERPRETATION: Exposure to extreme temperatures and air pollutants in the Rencheng District was associated with an increased mortality rate. Under the influence of climate change, it is necessary for policymakers to take measures to reduce the risk of non-accidental deaths among residents.
Hot extremes and ozone pollution have long been known detrimental to public health, but until very recently disproportionate health impacts from their joint occurrence-compound hot and ozone extremes (CHOEs)-have not been sufficiently aware of. Based on high-quality observations of air temperature and surface ozone concentration, we here examined the features of urban CHOEs and their dependence on city population and background climates. Results show the ozone-temperature slope (m(O3-T)) is significantly correlated with city population size, and the correlation is much weaker (0.38) in moister and cloudier cities (Cluster I) as opposed to that (0.69) in drier and sunnier cities (Cluster II). Larger cities are more susceptible to CHOEs with Cluster II megacities (population > 10 million) registering about 8 days of CHOEs during ozone season but similar to 3 days for small cities (population <= 1 million). Most cities experience elevated risks of CHOEs in urban areas relative to surrounding rural areas, especially so for densely-populated cities and those located in drier and sunnier environments. This study emphasizes the importance and urgency of emission reduction to mitigate the health burden from not only hot extremes but also their hazardous compounding with surface ozone.
Globally, more people die from cardiovascular disease than any other cause. Climate change, through amplified environmental exposures, will promote and contribute to many noncommunicable diseases, including cardiovascular disease. Air pollution, too, is responsible for millions of deaths from cardiovascular disease each year. Although they may appear to be independent, interchangeable relationships and bidirectional cause-and-effect arrows between climate change and air pollution can eventually lead to poor cardiovascular health. In this topical review, we show that climate change and air pollution worsen each other, leading to several ecosystem-mediated effects. We highlight how increases in hot climates as a result of climate change have increased the risk of major air pollution events such as severe wildfires and dust storms. In addition, we show how altered atmospheric chemistry and changing patterns of weather conditions can promote the formation and accumulation of air pollutants: a phenomenon known as the climate penalty. We demonstrate these amplified environmental exposures and their associations to adverse cardiovascular health outcomes. The community of health professionals-and cardiologists, in particular-cannot afford to overlook the risks that climate change and air pollution bring to the public’s health.
This review systematically gathers and provides an analysis of pollutants levels emitted from wildfire (WF) and their impact on short-term health effects of affected populations. The available literature was searched according to Population, Exposure, Comparator, Outcome, and Study design (PECOS) database defined by the World Health Organization (WHO) and a meta-analysis was conducted whenever possible. Data obtained through PECOS characterized information from the USA, Europe, Australia, and some Asian countries; South American countries were seldom characterized, and no data were available for Africa and Russia. Extremely high levels of pollutants, mostly of fine fraction of particulate matter (PM) and ozone, were associated with intense WF emissions in North America, Oceania, and Asia and reported to exceed several-fold the WHO guidelines. Adverse health outcomes include emergency department visits and hospital admissions for cardiorespiratory diseases as well as mortality. Despite the heterogeneity among exposure and health assessment methods, all-cause mortality, and specific-cause mortality were significantly associated with WF emissions in most of the reports. Globally, a significant association was found for all-cause respiratory outcomes including asthma, but mixed results were noted for cardiovascular-related effects. For the latter, estimates were only significant several days after WF emissions, suggesting a more delayed impact on the heart. Different research gaps are presented, including the need for the application of standardized protocols for assessment of both exposure and adverse health risks. Mitigation actions also need to be strengthened, including dedicated efforts to communicate with the affected populations, to engage them for adoption of protective behaviors and measures.
Poisson regression is a common approach for modelling discrete data. However, due to characteristics of Poisson distribution, Poisson regression might not be suitable since most data are over-dispersed or under-dispersed. This study compared four generalised linear models (GLMs): negative binomial, generalised Poisson, zero-truncated Poisson and zero-truncated negative binomial. An air-pollution-related disease, upper respiratory tract infection (URTI), and its relationship with various air pollution and climate factors were investigated. The data were obtained from Johor Bahru, Malaysia, from January 1, 2012, to December 31, 2013. Multicollinearity between the covariates and the independent variables was examined, and model selection was performed to find the significant variables for each model. This study showed that the negative binomial is the best model to determine the association between the number of URTI cases and air pollution and climate factors. Particulate Matter (PM10), Sulphur Dioxide (SO2) and Ground Level Ozone (GLO) are the air pollution factors that affect this disease significantly. However, climate factors do not significantly influence the number of URTI cases. The model constructed in this study can be utilised as an early warning system to prevent and mitigate URTI cases. The involved parties, such as the local authorities and hospitals, can also employ the model when facing the risk of URTI cases that may occur due to air pollution factors.
IMPORTANCE Emerging evidence indicates that exposure to fine particulate matter (PM2.5) air pollution may increase dementia risk in older adults. Although this evidence suggests opportunities for intervention, little is known about the relative importance of PM2.5 from different emission sources. OBJECTIVE To examine associations of long-term exposure of total and source-specific PM2.5 with incident dementia in older adults. DESIGN, SETTING, AND PARTICIPANTS The Environmental Predictors of Cognitive Health and Aging study used biennial survey data from January 1, 1998, to December 31, 2016, for participants in the Health and Retirement Study, which is a nationally representative, population-based cohort study in the US. The present cohort study included all participants older than 50 years who were without dementia at baseline and had available exposure, outcome, and demographic data between 1998 and 2016 (N = 27 857). Analyses were performed from January 31 toMay 1, 2022. EXPOSURES The 10-year mean total PM2.5 and PM2.5 from 9 emission sources at participant residences for each month during follow-up using spatiotemporal and chemical transport models. MAIN OUTCOMES AND MEASURES The main outcomewas incident dementia as classified by a validated algorithm incorporating respondent-based cognitive testing and proxy respondent reports. Adjusted hazard ratios (HRs) were estimated for incident dementia per IQR of residential PM2.5 concentrations using time-varying, weighted Cox proportional hazards regression models with adjustment for the individual- and area-level risk factors. RESULTS Among 27 857 participants (mean [SD] age, 61 [10] years; 15 747 [56.5%] female), 4105 (15%) developed dementia during a mean (SD) follow-up of 10.2 [5.6] years. Higher concentrations of total PM2.5 were associated with greater rates of incident dementia (HR, 1.08 per IQR; 95% CI, 1.01-1.17). In single pollutant models, PM2.5 from all sources, except dust, were associated with increased rates of dementia, with the strongest associations for agriculture, traffic, coal combustion, and wildfires. After control for PM2.5 from all other sources and copollutants, only PM2.5 from agriculture (HR, 1.13; 95% CI, 1.01-1.27) and wildfires (HR, 1.05; 95% CI, 1.02-1.08) were robustly associated with greater rates of dementia. CONCLUSION AND RELEVANCE In this cohort study, higher residential PM2.5 levels, especially from agriculture and wildfires, were associated with higher rates of incident dementia, providing further evidence supporting PM2.5 reduction as a population-based approach to promote healthy cognitive aging. These findings also indicate that intervening on key emission sources might have value, although more research is needed to confirm these findings.
PM2.5-bound trace elements were chosen for health risk assessment because they have been linked to an increased risk of respiratory and cardiovascular illness. Since the Korean national air quality standard for ambient particulate matter is based on PM2.5 mass concentration, there have only been a few measurements of PM2.5 particles together with trace elements that can be utilized to evaluate their effects on air quality and human health. Thus, this study describes the trace elements bound to PM2.5 in Seoul (urban area) and Seosan (rural area) using online nondestructive energy-dispersive X-ray fluorescence analysis from December 2020 to January 2021. At both the Seoul and Seosan sites, S, K, Si, Ca, and Fe constituted most of the PM2.5-bound trace elements (similar to 95%); major components such as S, K, and soil (estimatedcalculatedcalculated based on oxides of Si, Fe, Ca, and Ti) were presumably from anthropogenic and crustal sources, as well as favorable meteorological conditions. During winter, synoptic meteorology favored the transport of particles from severely contaminated regions, such as the East Asian outflow and local emissions. The total dry deposition flux for crustal elements was 894.5 +/- 320.8 mu g m(-2) d(-1) in Seoul and 1088.8 +/- 302.4 mu g m(-2) d(-1) in Seosan. Moreover, potential health risks from the trace elements were estimated. Cancer risk values for carcinogenic trace elements (Cr, As, Ni, and Pb) were within the tolerable limit (1 x 10(-6)), suggesting that adults and children were not at risk of cancer throughout the study period in Seoul and Seosan. Furthermore, a potential risk assessment of human exposure to remaining carcinogens (Cr, As, Ni, and Pb) and non-carcinogens (Cu, Fe, Zn, V, Mn, and Se) indicated that these trace elements posed no health risks. Nevertheless, trace element monitoring, risk assessment, and mitigation must be strengthened throughout the study area to confirm that trace-element-related health effects remain harmless. Researchers and policymakers can use the database from this study on spatial and temporal variation to establish actions and plans in the future.
Cities in the global south face dire climate impacts. It is in socioeconomically marginalized urban communities of the global south that the effects of climate change are felt most deeply. Santiago de Chile, a major mid-latitude Andean city of 7.7 million inhabitants, is already undergoing the so-called “climate penalty” as rising temperatures worsen the effects of endemic ground-level ozone pollution. As many cities in the global south, Santiago is highly segregated along socioeconomic lines, which offers an opportunity for studying the effects of concurrent heatwaves and ozone episodes on distinct zones of affluence and deprivation. Here, we combine existing datasets of social indicators and climate-sensitive health risks with weather and air quality observations to study the response to compound heat-ozone extremes of different socioeconomic strata. Attributable to spatial variations in the ground-level ozone burden (heavier for wealthy communities), we found that the mortality response to extreme heat (and the associated further ozone pollution) is stronger in affluent dwellers, regardless of comorbidities and lack of access to health care affecting disadvantaged population. These unexpected findings underline the need of a site-specific hazard assessment and a community-based risk management.
Extreme heat exposure has been associated with hypertension. However, its interactive influences with air pollution, green and blue spaces are unclear. This study aimed to explore the interaction between heatwaves, air pollution, green and blue spaces on hypertension. Cohort data enrolled 6448 Chinese older adults aged 65 years and over were derived from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) between 2008 and 2018. Nine heatwave definitions, combining three heat thresholds (92.5th, 95th, and 97.5th percentiles of daily maximum temperature) and three durations (≥2, 3 and 4 days) were used as time-varying variables in the analysis and were the one-year exposure before survival events. Fine particulate matter (PM ≤2.5 μm in aerodynamic diameter (PM(2.5))), the Normalized Difference Vegetation Index (NDVI) and the average proportion of open water bodies were used to reflect the air pollution, green and blue space exposures, respectively. PM(2.5), green and blue space exposures were time-varying indicators and contemporaneous with heatwaves. Mixed Cox models with time-varying variables were fitted to assess the multiplicative and additive interaction of heatwaves, PM(2.5), and green and blue spaces on hypertension, measured by a traditional product term with the ratio of hazard ratio (HR) and relative risk due to interaction (RERI), respectively. A positive multiplicative (HRs >1) and additive interaction (RERIs >0) between heatwaves and higher PM(2.5) levels was observed. There was a synergistic effect between heatwaves and decreasing greenness levels on hypertension incidence on additive and multiplicative scales. No significant interaction between heatwaves and blue space was observed in the analysis. The combined effects of heatwaves, air pollution, green and blue space exposures on the risk of hypertension varied with age, gender, and educational attainment. This study’s findings complemented the existing evidence and revealed synergistic harmful impacts for heatwaves with air pollution and lack of green space on hypertension incidence.
A narrative review on the interlinking effects of climate change and air pollution, and their impacts on human health in the Arabian Peninsula and its Neighbouring Regions (APNR) is provided. The APNR is experiencing the direct impacts of climate change through increasingly extreme temperatures in the summer season, increasing maximum and minimum temperatures, and increased frequency and severity of dust events. The region is also experiencing significant air pollution, of which particulate matter (PM), nitrogen dioxide (NO2) and sulphur dioxide (SO2) are of specific concern. Air pollution in the APNR is mainly caused by unprecedented industrial, population and motorization growth. The discovery of oil in the early 20th century has been the major economic driving force behind these changes. Climate change and air pollution impact human health in the region, primarily respiratory and cardiovascular health. Despite an increase in research capacity, research intensity was found to be inconsistent across the APNR countries, with Saudi Arabia, the UAE, Qatar and Iraq publishing more research articles than the other countries. In this review article, the existing research gaps in the region are investigated and the lack of synthesis between the interacting effects of air pollution and climate change upon human health is highlighted.
Respiratory allergy correlates strictly with air pollution and climate change. Due to climate change, the atmospheric content of trigger factors such as pollens and moulds increase and induce rhinitis and asthma in sensitized patients with IgE-mediated allergic reactions.Pollen allergy is frequently used to evaluate the relationship between air pollution and allergic respiratory diseases. Pollen allergens trigger the release of immunomodulatory and pro-inflammatory mediators and accelerate the onset of sensitization to respiratory allergens in predisposed children and adults. Lightning storms during pollen seasons can exacerbate respiratory allergy and asthma not only in adults but also in children with pollinosis. In this study, we have focalized the trigger (chemical and biologic) factors of outdoor air pollution. RECENT FINDINGS: Environmental pollution and climate change have harmful effects on human health, particularly on respiratory system, with frequent impact on social systems.Climate change is characterized by physic meteorological events inducing increase of production and emission of anthropogenic carbon dioxide (CO 2 ) into the atmosphere. Allergenic plants produce more pollen as a response to high atmospheric levels of CO 2 . Climate change also affects extreme atmospheric events such as heat waves, droughts, thunderstorms, floods, cyclones and hurricanes. These climate events, in particular thunderstorms during pollen seasons, can increase the intensity of asthma attacks in pollinosis patients. SUMMARY: Climate change has important effects on the start and pathogenetic aspects of hypersensitivity of pollen allergy. Climate change causes an increase in the production of pollen and a change in the aspects increasing their allergenic properties. Through the effects of climate change, plant growth can be altered so that the new pollen produced are modified affecting more the human health. The need for public education and adoption of governmental measures to prevent environmental pollution and climate change are urgent. Efforts to reduce greenhouse gases, chemical and biologic contributors to air pollution are of critical importance. Extreme weather phenomena such as thunderstorms can trigger exacerbations of asthma attacks and need to be prevented with a correct information and therapy.
Climate change will alter environmental risks that influence pulmonary health, including heat, air pollution, and pollen. These exposures disproportionately burden populations already at risk of ill health, including those at vulnerable life stages, with low socioeconomic status, and systematically targeted by oppressive policies. Climate change can exacerbate existing environmental injustices by affecting future exposure, as well as through differentials in the ability to adapt; this is compounded by disparities in rates of underlying disease and access to health care. Climate change is therefore a dire threat not only to individual and population health but also to health equity.
This review article delves into the multifaceted relationship between climate change, air quality, and respiratory health, placing a special focus on the process of particle deposition in the lungs. We discuss the capability of climate change to intensify air pollution and alter particulate matter physicochemical properties such as size, dispersion, and chemical composition. These alterations play a significant role in influencing the deposition of particles in the lungs, leading to consequential respiratory health effects. The review paper provides a broad exploration of climate change’s direct and indirect role in modifying particulate air pollution features and its interaction with other air pollutants, which may change the ability of particle deposition in the lungs. In conclusion, climate change may play an important role in regulating particle deposition in the lungs by changing physicochemistry of particulate air pollution, therefore, increasing the risk of respiratory disease development. Climate change influences particle deposition in the lungs by modifying the physicochemical properties of particulate air pollution, thereby escalating the risk of respiratory disease development. It is crucial for healthcare providers to educate patients about the relationship between climate change and respiratory health. People with conditions such as asthma, COPD, and allergies must understand how changes in weather, air pollution, and allergens can exacerbate their symptoms. Instruction on understanding air quality indices and pollen predictions, along with recommendations on adapting everyday activities and medication regimens in response, is essential.
One of the important adverse impacts of climate change on human health is increases in allergic respiratory diseases such as allergic rhinitis and asthma. This impact is via the effects of increases in atmospheric carbon dioxide concentration and air temperature on sources of airborne allergens such as pollen and fungal spores. This review describes these effects and then explores three translational mitigation approaches that may lead to improved health outcomes, with recent examples and developments highlighted. Impacts have already been observed on the seasonality, production and atmospheric concentration, allergenicity, and geographic distribution of airborne allergens, and these are projected to continue into the future. A technological revolution is underway that has the potential to advance patient management by better avoiding associated increased exposures, including automated real-time airborne allergen monitoring, airborne allergen forecasting and modelling, and smartphone apps for mitigating the health impacts of airborne allergens.
PURPOSE: Climate change poses one of the greatest risks to human health as air pollution increases, surface temperatures rise, and extreme weather events become more frequent. Environmental exposures related to climate change have a disproportionate effect on pregnant women through influencing food and water security, civil conflicts, extreme weather events, and the spread of disease. Our research team sought to identify the current peer-reviewed research on the effects of climate change-related environmental exposures on perinatal and maternal health in the United States. DESIGN AND METHODS: A systematic literature review of publications identified through a comprehensive search of the PubMed and Web of Science databases was conducted using a modified Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. The initial search across both databases identified a combined total of 768 publications. We removed 126 duplicates and 1 quadruplet, and the remaining 639 publications were subjected to our pre-set inclusion and exclusion criteria. We excluded studies outside of the United States. A total of 39 studies met our inclusion criteria and were retained for thematic analysis. FINDINGS: A total of 19 studies investigated the effect of either hot or cold temperature exposure on perinatal and maternal health outcomes. The effect of air pollution on perinatal outcomes was examined in five studies. A total of 19 studies evaluated the association between natural disasters (hurricanes, flash floods, and tropical cyclones) and perinatal and maternal health outcomes. High and low temperature extremes were found to negatively influence neonate and maternal health. Significant associations were found between air pollutant exposure and adverse pregnancy outcomes. Adverse pregnancy outcomes were linked to hurricanes, tropical cyclones, and flash floods. CONCLUSIONS: This systematic review suggests that climate change-related environmental exposures, including extreme temperatures, air pollution, and natural disasters, are significantly associated with adverse perinatal and maternal health outcomes across the United States.
Climate change adversely impacts global health. Increasingly, temperature variability, inclement weather, declining air quality, and growing food and clean water supply insecurities threaten human health. Earth’s temperature is projected to increase up to 6.4 °C by the end of the 21st century, exacerbating the threat. Public and health care professionals, including pulmonologists, perceive the detrimental effects of climate change and air pollution and support efforts to mitigate its effects. In fact, evidence is strong that premature cardiopulmonary death is associated with air pollution exposure via inhalation through the respiratory system, which functions as a portal of entry. However, little guidance is available for pulmonologists in recognizing the effects of climate change and air pollution on the diverse range of pulmonary disorders. To educate and mitigate risk for patients competently, pulmonologists must be armed with evidence-based findings of the impact of climate change and air pollution on specific pulmonary diseases. Our goal is to provide pulmonologists with the background and tools to improve patients’ health and to prevent adverse outcomes despite climate change-imposed threats. In this review, we detail current evidence of climate change and air pollution impact on a diverse range of pulmonary disorders. Knowledge enables a proactive and individualized approach toward prevention strategies for patients, rather than merely treating ailments reactively.
Anthropogenic climate change adversely impacts human health. In this perspective, we examine the impact of climate change on respiratory health risk. We describe five respiratory health threats-heat, wildfires, pollen, extreme weather events, and viruses-and discuss their impact on health outcomes in a warming climate. The risk of experiencing an adverse health outcome occurs at the intersection of exposure and vulnerability, consisting of sensitivity and adaptive capacity. Exposed individuals and communities most at risk are those with high sensitivity and low adaptive capacity, as influenced by the social determinants of health. We call for the implementation of a transdisciplinary strategy for accelerating respiratory health research, practice, and policy in the context of climate change.
Climate change is one of the major public health emergencies with already unprecedented impacts on our planet, environment and health. Climate change has already resulted in substantial increases in temperatures globally and more frequent and extreme weather in terms of heatwaves, droughts, dust storms, wildfires, rainstorms and flooding, with prolonged and altered allergen and microbial exposure as well as the introduction of new allergens to certain areas. All these exposures may have a major burden on patients with respiratory conditions, which will pose increasing challenges for respiratory clinicians and other healthcare providers. In addition, complex interactions between these different factors, along with other major environmental risk factors (e.g. air pollution), will exacerbate adverse health effects on the lung. For example, an increase in heat and sunlight in urban areas will lead to increases in ozone exposure among urban populations; effects of very high exposure to smoke and pollution from wildfires will be exacerbated by the accompanying heat and drought; and extreme precipitation events and flooding will increase exposure to humidity and mould indoors. This review aims to bring respiratory healthcare providers up to date with the newest research on the impacts of climate change on respiratory health. Respiratory clinicians and other healthcare providers need to be continually educated about the challenges of this emerging and growing public health problem and be equipped to be the key players in solutions to mitigate the impacts of climate change on patients with respiratory conditions. EDUCATIONAL AIMS: To define climate change and describe major related environmental factors that pose a threat to patients with respiratory conditions.To provide an overview of the epidemiological evidence on climate change and respiratory diseases.To explain how climate change interacts with air pollution and other related environmental hazards to pose additional challenges for patients.To outline recommendations to protect the health of patients with respiratory conditions from climate-related environmental hazards in clinical practice.To outline recommendations to clinicians and patients with respiratory conditions on how to contribute to mitigating climate change.
Evidence of the health impact of climate change has been extensively documented in recent scholarly literature. In order to mitigate the adverse health effects induced by climate change, the need for conducting vulnerability assessments (VAs) has been emphasised. A higher vulnerability to climate change is often linked with substantial risks to human lives and built environment. Despite the potential of VAs in alleviating risks posed by climate change, only a limited amount of scholarly work in this domain has been conducted in the Indian context. The present research addresses this lacuna and contributes to the limited scholarship on climate change and health VAs in India. Drawing on the VA framework introduced by the fourth assessment report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), this paper estimates district-level health vulnerabilities caused by climate change using multi-dimensional indices. The indices are multi-dimensional since they integrate 50 district-level indicators from 8 data sources for all 640 Census 2011 districts. The statistical technique of Principal Component Analysis (PCA) has been used for integrating the indicators. The findings of this paper indicate that nearly 56% of India’s population in 344 districts is highly vulnerable to the health impact of climate change. The results show that high vulnerability in certain districts is mediated by high adaptive capacity (AC). Since climate exposure varies across districts, the paper highlights the need for local-level responses and Complex Adaptive System (CAS) thinking to understand the implications of climate change and human health.
Climate change presents multiple challenges to rural communities. Here, we investigated the toxicological potential of the six types of particulate matter most common to rural Arkansas: soil, road, and agricultural dusts, pollen, traffic exhaust, and particles from biomass burning in human small airway epithelial cells (SAECs). Biomass burning and agricultural dust demonstrated the most potent toxicological responses, exhibited as significant (p < 0.05) up-regulation of HMOX1 (oxidative stress) and TNF alpha (inflammatory response) genes as well as epigenetic alterations (altered expression of DNA methyltransferases DNMT1, DNMT3A, and DNMT3B, enzymatic activity, and DNA methylation of alpha satellite elements) that were evident at both 24 h and 72 h of exposure. We further demonstrate evidence of aridification in the state of Arkansas and the presence of winds capable of transporting agricultural dust- and biomass burning-associated particles far beyond their origination. Partnerships in the form of citizen science projects may provide important solutions to prevent and mitigate the negative effects of the rapidly evolving climate and improve the well-being of rural communities. Furthermore, the identification of the most toxic types of particulate matter could inform local policies related to agriculture, biomass burning, and dust control.
Gaseous emissions have contributed to global warming, an increase in the frequency of extreme weather events and poorer air quality. The associated health impacts have been well reported in temperate regions. In Singapore, key climate change adaptation measures and activities include coastal and flood protection, and mitigating heat impacts. We systematically reviewed studies examining climate variability and air quality with population health in Singapore, a tropical city-state in South-East Asia (SEA), with the aim to identify evidence gaps for policymakers. We included 14 studies with respiratory illnesses, cardiovascular outcomes, foodborne disease and dengue. Absolute humidity (3 studies) and rainfall (2 studies) were positively associated with adverse health. Extreme heat (2 studies) was inversely associated with adverse health. The effects of mean ambient temperature and relative humidity on adverse health were inconsistent. Nitrogen dioxide and ozone were positively associated with adverse health. Climate variability and air quality may have disease-specific, differing directions of effect in Singapore. Additional high quality studies are required to strengthen the evidence for policymaking. Research on effective climate action advocacy and adaptation measures for community activities should be strengthened. FUNDING: There was no funding source for this study.
With the deepening of research on the correlation between meteorological factors and autoimmune diseases, the relationship between climate change and dermatomyositis (DM) has come to our attention. This study aimed to explore the short-term correlation between meteorological factors and DM outpatient visits. Daily records of hospital outpatient visits for DM, air pollutants, and meteorological factor data in Hefei from January 1, 2018 to December 31, 2021 were obtained. The mean temperature (MT), relative humidity (RH), diurnal temperature range (DTR), and temperature change between neighboring days (TCN) were used to quantify environmental temperature and humidity and their variations. And we performed a time series analysis using a generalized linear model (GLM) in combination with a distributed lag nonlinear model (DLNM). Furthermore, gender and age were further stratified for the analysis. The sensitivity analysis was also performed. A total of 4028 DM outpatient visits were recorded during this period. There were statistically significant associations of low temperature (5th, 1.5 °C), low RH (1st, 48.6%), high RH (99th, 99%), high DTR (75th, 12.6°c), and low TCN (10th, -2.7 °C) that were associated with risk of DM outpatient visits, with lag days of 30, 16, 16, 10, and 14, respectively. Moreover, women were more susceptible to high RH exposure and low TCN exposure, while the elderly were more susceptible to low temperature. This study concluded that exposure to low temperature, extreme RH, and temperature changes (especially high DTR and low TCN) was associated with an increased risk of DM outpatient visits.
Wildland firefighters (WFFs) are exposed to many inhalation hazards working in the wildland fire environment. To assess occupational exposures and acute and subacute health effects among WFFs, the wildland firefighter exposure and health effects study collected data for a 2-year repeated measures study. This manuscript describes the exposure assessment from one Interagency Hotshot Crew (N = 19) conducted at a wildfire incident. Exposures to benzene, toluene, ethylbenzene, xylene isomers, formaldehyde, acetaldehyde, and naphthalene were measured through personal air sampling each work shift. Biological monitoring was done for creatinine-adjusted levoglucosan in urine pre- and post-shift. For 3 days sampling at the wildfire incident, benzene, toluene, ethylbenzene, xylene isomers (m and p, and o) exposure was highest on day 1 (geometric mean [GM] = 0.015, 0.042, 0.10, 0.42, and 0.15 ppm, respectively) when WFFs were not exposed to smoke but used chainsaws to remove vegetation and prepare fire suppression breaks. Exposure to formaldehyde and acetaldehyde was highest on day 2 (GM = 0.03 and 0.036 ppm, respectively) when the WFFs conducted a firing operation and were directly exposed to wildfire smoke. The greatest difference of pre- and post-shift levoglucosan concentrations were observed on day 3 (pre-shift: 9.7 and post-shift: 47 μg/mg creatinine) after WFFs conducted mop up (returned to partially burned area to extinguish any smoldering vegetation). Overall, 65% of paired samples (across all sample days) showed a post-shift increase in urinary levoglucosan and 5 firefighters were exposed to benzene at concentrations at or above the National Institute for Occupational Safety and Health (NIOSH) recommended exposure limit. Our findings further demonstrate that exposure to inhalation hazards is one of many risks that wildland firefighters experience while suppressing wildfires.
The mobilisation of potentially harmful chemical constituents in wildfire ash can be a major consequence of wildfires, posing widespread societal risks. Knowledge of wildfire ash chemical composition is crucial to anticipate and mitigate these risks. Here we present a comprehensive dataset on the chemical characteristics of a wide range of wildfire ashes (42 types and a total of 148 samples) from wildfires across the globe and examine their potential societal and environmental implications. An extensive review of studies analysing chemical composition in ash was also performed to complement and compare our ash dataset. Most ashes in our dataset had an alkaline reaction (mean pH 8.8, ranging between 6 and 11.2). Important constituents of wildfire ash were organic carbon (mean: 204 g kg(-1)), calcium, aluminium, and iron (mean: 47.9, 17.9 and 17.1 g kg(-1)). Mean nitrogen and phosphorus ranged between 1 and 25 g kg(-1), and between 0.2 and 9.9 g kg(-1), respectively. The largest concentrations of metals of concern for human and ecosystem health were observed for manganese (mean: 1488 mg kg(-1); three ecosystems > 1000 mg kg(-1)), zinc (mean: 181 mg kg(-1); two ecosystems > 500 mg kg(-1)) and lead (mean: 66.9 mg kg(-1); two ecosystems > 200 mg kg(-1)). Burn severity and sampling timing were key factors influencing ash chemical characteristics like pH, carbon and nitrogen concentrations. The highest readily dissolvable fractions (as a % of ash dry weight) in water were observed for sodium (18 %) and magnesium (11.4 %). Although concentrations of elements of concern were very close to, or exceeded international contamination standards in some ashes, the actual effect of ash will depend on factors like ash loads and the dilution into environmental matrices such as water, soil and sediment. Our approach can serve as an initial methodological standardisation of wildfire ash sampling and chemical analysis protocols.
Climate and land use changes together are altering the particle content of desert dust storms on regional and local scales. These storms now carry a wide variety of pollutants and pathogens arising from urbanization, industrialization, mass transportation, warfare, or aerosolized waste in locations worldwide where deserts are intertwined with built infrastructure, transportation centers, and high-density human habitation. Accordingly, the modern desert dust storm has an anthropogenic particle load which presumably sets it apart from pre-industrial dust storms. Evidence for how particle content for modern dust storms is changing over the Arabian Peninsula holds relevance because dust storms are now more frequent and more severe. Furthermore, the Arabian Peninsula has asthma rates which are the highest worldwide. How the modern desert dust storm contributes to asthma and human health is a nascent issue. Meanwhile, public health decisions can benefit from a climate × health framework for dust storms, as proposed here. An imperative is testing each dust storm’s particle content type, and for this, we propose the A-B-C-X model. Sampling a dust storm for its particle content data and then archiving samples for future analyses is advised. A storm’s particle content data, once combined with its atmospheric data, allows a particle’s source, transport, and deposition to be determined. In closing, the modern desert dust storm’s changing particle content has far-reaching consequences for public health, transboundary issues, and international climate dialog. SIGNIFICANCE : Locally and regionally sourced particle pollution is a growing problem in deserts worldwide. Proposed here is a climate × health framework for studying how dust storm particles, entrained from both natural and engineered systems, may be contributing to declining human respiratory health.
Many air pollutants and climate variables have proven to be significantly associated with pediatric asthma and have worsened asthma symptoms. However, their exact causal effects remain unclear. We explored the causality between air pollutants, climate, and daily pediatric asthma patient visits with a short-term lag effect. Based on eight years of daily environmental data and daily pediatric asthma patient visits, Spearman correlation analysis was used to select the air pollutants and climate variables that correlated with daily pediatric asthma patient visits at any time (with a lag of 1-6 days). We regarded these environmental variables as treatments and built multiple- and single-treatment causal inference models using the Dowhy library (a Python library for causal inference by graphing the model, quantitatively evaluating causal effects, and validating the causal assumptions) to estimate the quantitative causal effect between these correlated variables and daily pediatric asthma patient visits in lag time. The multiple-treatment causal inference model was a model with 8 treatments (Visibility, Precipitation, PM(10), PM(2.5), SO(2), NO(2), AQI and CO), 1 outcome (daily pediatric asthma patients visits), and 5 confounders (Humidity, Temperature, Sea level pressure, wind speed and unobserved confounders “U”). Single-treatment causal inference models were 8 models, and each model has 1 treatment, 1 outcome and 12 confounders. Spearman correlation analysis showed that precipitation, wind speed, visibility, air quality index, PM(2.5), PM(10), SO(2), NO(2), and CO were significantly associated variables at all times (p < 0.05). The multiple-treatment model showed that pooled treatments had significant causality for the short-term lag (lag1-lag6; p < 0.05). Causality was mainly due to SO(2). In the single-treatment models, visibility, SO(2), NO(2), and CO exhibited significant causal effects at any one time (p < 0.05). SO(2) and CO exhibited stronger positive causal effects. The causal effect of SO(2) reached its maxima (causal effect = 11.41, p < 0.05) at lag5. The greatest causal effect of CO appeared at lag3 (causal effect = 10.67, p < 0.05). During the eight year-period, the improvements in SO(2), CO, and NO(2) in Hangzhou were estimated to reduce asthma visits by 8478.03, 3131.08, and 1341.39 per year, respectively. SO(2), NO(2), CO, and visibility exhibited causal effects on daily pediatric asthma patient visits; SO(2) was the most crucial causative variable with a relatively higher causal effect, followed by CO. Improvements in atmospheric quality in the Hangzhou area have effectively reduced the incidence of asthma.
Type I respiratory allergies to birch pollen and pollen from related trees of the order Fagales are increasing in industrialized countries, especially in the temperate zone of the Northern hemisphere, but the reasons for this increase are still debated and seem to be multifaceted. While the most important allergenic molecules of birch pollen have been identified and characterized, the contribution of other pollen components, such as lipids, non-allergenic immunomodulatory proteins, or the pollen microbiome, to the development of allergic reactions are sparsely known. Furthermore, what also needs to be considered is that pollen is exposed to external influences which can alter its allergenicity. These external influences include environmental factors such as gaseous pollutants like ozone or nitrogen oxides or particulate air pollutants, but also meteorological events like changes in temperature, humidity, or precipitation. In this review, we look at the birch pollen from different angles and summarize current knowledge on internal and external influences that have an impact on the allergenicity of birch pollen and its interactions with the epithelial barrier. We focus on epithelial cells since these cells are the first line of defense in respiratory disease and are increasingly considered to be a regulatory tissue for the protection against the development of respiratory allergies.
Environmental factors such as meteorological conditions and air pollutants are recognized as important for human health, where mortality and morbidity of certain diseases may be related to abrupt climate change or air pollutant concentration. In the literature, environmental factors have been identified as risk factors for chronic diseases such as ischemic heart disease. However, the likelihood evaluation of the disease occurrence probability due to environmental factors is missing. METHOD: We defined people aged 51-90 years who were free from ischemic heart disease (ICD9: 410-414) in 1996-2002 as the susceptible group. A Bayesian conditional logistic regression model based on a case-crossover design was utilized to construct a risk information system and applied to data from three databases in Taiwan: air quality variables from the Environmental Protection Administration (EPA), meteorological parameters from the Central Weather Bureau (CWB), and subject information from the National Health Insurance Research Database (NHIRD). RESULTS: People living in different geographic regions in Taiwan were found to have different risk factors; thus, disease risk alert intervals varied in the three regions. CONCLUSIONS: Disease risk alert intervals can be a reference for weather bureaus to issue health warnings. With early warnings, susceptible groups can take measures to avoid exacerbation of disease when meteorological conditions and air pollution become hazardous to their health.
Air pollution exposure is an important environmental risk factor involved in the development of systemic lupus erythematosus (SLE). This study was conducted to investigate the relationships between particulate matter (PM) air pollutants exposure and the risk of SLE admission in Xi’an, China. The records of SLE admission, air pollutants and meteorological data were retrieved from the First Affiliated Hospital of Xi’an Jiaotong University, the Xi’an Environmental Monitoring Station and China Meteorological Data Network, respectively. A distributed lagged nonlinear model combined with Poisson generalized linear regression was used to evaluate the effect of air pollution on SLE admission. Exposure-response curves showed positive associations of PM ≤ 2.5 (PM(2.5)) and 10 microns (PM(10)) in aerodynamic diameter exposures with the risk of SLE admission. Subgroup analyses showed that PM(2.5) exposure was associated with the increased risk of SLE admission in women, age over 65 years old, and during the cold season, and PM(10) exposure showed an increased risk of SLE in women and during the cold season, but additional tests did not observe the significant associations of PM(2.5) and PM(10) exposure with SLE admission between subgroups. In addition, null associations of carbon monoxide (CO), nitrogen dioxide (NO(2)), ozone (O(3)), and sulfur dioxide (SO(2)) with the risk of SLE admission were found. Our study indicates that PM(2.5) and PM(10) exposures have significant effects on the risk of SLE admission, and early measures should be taken for high PM(2.5) and PM(10) exposure to protect vulnerable populations, rational use of limited health care resources.
Landscape fires are increasing in frequency and severity globally. In Australia, extreme bushfires cause a large and increasing health and socioeconomic burden for communities and governments. People with asthma are particularly vulnerable to the effects of landscape fire smoke (LFS) exposure. Here, we present a position statement from the Thoracic Society of Australia and New Zealand. Within this statement we provide a review of the impact of LFS on adults and children with asthma, highlighting the greater impact of LFS on vulnerable groups, particularly older people, pregnant women and Aboriginal and Torres Strait Islander peoples. We also highlight the development of asthma on the background of risk factors (smoking, occupation and atopy). Within this document we present advice for asthma management, smoke mitigation strategies and access to air quality information, that should be implemented during periods of LFS. We promote clinician awareness, and the implementation of public health messaging and preparation, especially for people with asthma.
Changes in climate and land-use may elicit an increased emission of allergenic pollen amounts in the air, causing a rise in respiratory allergies and affecting public health more than previously thought. Here we have used a well -established pollen transport model SILAM (System for Integrated modeLling of Atmospheric coMposition) for attributing the long-term changes in airborne pollen concentrations of birches and grasses to climate change and vegetation dynamics. The pollen transport model is applied for Belgium and is driven by ECMWF ERA5 mete-orological data (European Centre for Medium-Range Weather Forecasts, fifth generation of ECMWF atmospheric reanalysis of the global climate). The dynamic vegetation components of the model are based on multi-decadal datasets for 1982-2019 on spatially distributed birch and grass pollen emission sources. For each model gridcell we have computed the change rate of the seasonal birch and grass pollen cycles based on daily pollen concen-trations, and of the daily meteorological model input. Finally, the gridcell based association between trends in pollen and climate change are derived. Our findings show that during the period 1982-2019 a strong increase in birch pollen concentrations is associated with increasing radiation, decreasing precipitation and decreasing horizontal wind speed near the surface. A strong decrease of grass pollen concentrations over time is driven by a decreasing trend in grass pollen sources, and it is also associated with decreasing precipitation. The magnitude of the associations between meteorology and airborne birch pollen concentrations are almost twice the association between meteorology and grass pollen, and the spatial variations are substantial even on the scales of small countries. The specific contribution of birch tree and pollen production dynamics to the concentrations of birch pollen in the air over time is highly associated with wind speed and precipitation. Introducing the inter-seasonal variation in birch pollen production during the period 1982-2019 intensifies the climate induced increase of airborne birch pollen concentrations with-6%. In contrast, the grass pollen production dynamics resulted into-10 times less grass pollen over the studied period compared to climate change effects.
Background: Prior studies have shown that meteorological factors may be associated with increases in legion-ellosis (Legionnaire’s disease, (LD)), caused by Legionella, a globally ubiquitous bacterium found naturally in aquatic habitats, soils, and compost. The aim of this retrospective time series analysis was to examine the as-sociation between meteorological factors and air pollution parameters and the incidence of sporadic, community -acquired, laboratory confirmed LD.Methods: Daily cases of community-acquired legionellosis, meteorological and air pollution data from two urban areas, Auckland (North Island) and Christchurch (South Island) were collected from January 1, 1997 until December 31, 2020. Using Quasi-Poisson regression, associations between symptom onset and meteorological and air pollution variables were investigated using an interrupted time series analysis.Results: The two cities had different meteorological conditions and LD epidemiology and seasonal patterns of Legionella spp. LD incidence rates (per 100,000 population) were higher in Christchurch than Auckland for L. pneumophila (25.8 vs 10.8) and L.longbeachae (78.2 vs 4.9). Seasonal patterns were detected in Christchurch with a higher risk of LD during spring and summer (RR: 1.87, 95% CI: 1.42, 2.49) compared to autumn and winter months. In Auckland, the level of particulate matter 9-10 days prior to the onset date was positively associated with LD occurrence (RR: 1.02, 95% CI: 1.00, 1.04) compared to Christchurch, where Tmax recorded one day prior the onset (RR: 1.03, 95% CI: 1.00, 1.07) and sulphur dioxide 6 days prior to the onset date (RR: 1.27, 95% CI: 1.10, 1.45) were positively associated with LD occurrence. Atmospheric pressure 12 days prior (RR: 0.95, 95% CI: 0.90, 1.00) and wind speed 13 days prior (RR: 0.94, 95% CI: 0.89, 0.99) to the onset date were negatively associated with LD risk. In both cities, no association was detected between the level of precipitation and LD risk.Conclusions: Meteorological factors and air pollutants were associated with the risk of LD. However, different seasonal patterns and prevalent LD species seem to have distinct patterns of association between the two cate-gories of exposures. These findings suggest the importance of considering meteorological and air quality con-ditions in conjunction with the source of exposure and the LD species involved. They also imply potential climate change impacts on LD and benefits from reducing air pollution, though findings need to be replicated in other geographical regions.
Chronic exposure to particulate matter air pollution (PM(2.5) ) is associated with chronic rhinosinusitis (CRS). Elevated ambient temperature may increase PM(2.5) levels and thereby exacerbate sinonasal symptoms. This study investigates the association between high ambient temperature and the risk of CRS diagnosis. METHODS: Patients with CRS were diagnosed at Johns Hopkins hospitals from May to October 2013-2022, and controls were matched patients without CRS meanwhile. A total of 4752 patients (2376 cases and 2376 controls) were identified with a mean (SD) age of 51.8 (16.8) years. The effect of maximum ambient temperature on symptoms was estimated with a distributed lag nonlinear model (DLNM). Extreme heat was defined as 35.0°C (95(th) percentile of the maximum temperature distribution). Conditional logistic regression models estimated the association between extreme heat and the risk of CRS diagnosis. RESULTS: Exposure to extreme heat was associated with increased odds of exacerbation of CRS symptoms (odds ratio [OR] 1.11, 95% confidence interval [CI] 1.03-1.19). The cumulative effect of extreme heat during 0-21 lag days was significant (OR 2.37, 95% CI 1.60-3.50) compared with the minimum morbidity temperature (MMT) at 25.3°C. Associations were more pronounced among young and middle-aged patients and patients with abnormal weight. CONCLUSIONS: We found that short-term exposure to high ambient temperature is associated with increased CRS diagnosis, suggesting a cascading effect of meteorological phenomena. These results highlight climate change’s potentially deleterious health effects on upper airway diseases, which could have a significant public health impact.
Little is known about the associations between long-term exposure to wildfire-related fine particulate matter (PM(2.5)) and mortality. We aimed to explore theses associations using the data from the UK Biobank cohort. Long-term wildfire-related PM(2.5) exposure was defined as the 3-year cumulative concentrations of wildfire-related PM(2.5) within a 10-km buffer surrounding the residential address for each individual. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated using the time-varying Cox regression model. We included 492,394 participants aged between 38 and 73 years. We found that after adjusting for potential covariates, a 10 μg/m(3) increase of wildfire-related PM(2.5) exposure was associated with a 0.4% higher risk of all-cause mortality (HR = 1.004 [95% CI: 1.001, 1.006]) and nonaccidental mortality (HR = 1.004 [95% CI: 1.002, 1.006]), and a 0.5% higher risk of neoplasm mortality (HR = 1.005 [95% CI: 1.002, 1.008]). However, no significant associations were observed between wildfire-related PM(2.5) exposure and mortality from cardiovascular, respiratory, and mental diseases. Additionally, no significant modification effects of a series of modifiers were observed. Targeted health protection strategies should be adopted in response to wildfire-related PM(2.5) exposure, in order to reduce the risk of premature mortality.
Effects of green space on human health have been well-documented in western, high-income countries. Evidence for similar effects in China is limited. Moreover, the underlying mechanisms linking green space and mortality are yet to be established. We therefore conducted a nation-wide study to assess the association between green space and mortality in China using a difference-in-difference approach, which applied a causal framework and well controlled unmeasured confounding. In addition, we explored whether air pollution and air temperature could mediate the association. METHODS: In this analysis, we collected data on all-cause mortality and sociodemographic characteristics for each county in China from the 2000 and 2010 censuses and the 2020 Statistical Yearbook. Green space exposure was assessed using county-level normalized difference vegetation index (NDVI) and the percentage of green space (forest, grasslands, shrub land and wetland). We applied a difference-in-differences approach to evaluate the association between green space and mortality. We also performed mediation analysis (by air pollution and air temperature). RESULTS: Our sample consisted of 2726 counties in 2000 and 2010 as well as 1432 counties in 2019. In the 2000 versus 2019 comparison, a 0.1 unit increase in NDVI was associated with a 2.4 % reduction in mortality [95 % confidence interval (CI) 0.4-4.3 %], and a 10 % increase in percentage of green space was associated with a 4.7 % reduction (95 % CI 0-9.2 %) in mortality. PM(2.5) and air temperature mediated 0.3 % to 12.3 % of the associations. CONCLUSIONS: Living in greener counties may be associated with lower risk of mortality in China. These findings could indicate the potential of a population-level intervention to reduce mortality in China, which has important public health implications at the county level.
BACKGROUND: Asthma and its main phenotype allergic asthma are prevalent, chronic, and complex diseases affecting 4% of the population. One main trigger for allergic asthma exacerbations is pollen. Online health information search behavior by people is increasing, and analysis of web-search data can provide valuable insight into disease burden and risk factors of a population. OBJECTIVES: We sought to perform a web-search data analysis and correlation to climate factors and pollen in 2 European countries. METHODS: We analyzed the national web-search volume for allergic asthma-related keywords in Germany and Sweden from 2018 to 2021 and correlated it to local pollen counts, climatic factors, and drug prescription rates. RESULTS: Per capita, more searches were conducted in Sweden than in Germany. A complex geographic stratification within the countries was observed. Search results were seasonal with a peak in spring and correlated with pollen counts in both countries. However, anti-asthmatic drug prescription rates in Sweden, as well as temperature and precipitation in both countries, did not correlate with search volume. CONCLUSION: Our analysis offers population-level insights about this complex disease by reporting its needs and establishing the correlation to pollen counts, which enables a targeted approach in the public health management of allergic asthma. Local pollen counts, as opposed to temperature or precipitation, might be good predictors of allergic asthma disease burden.
The latest forecasts indicate wildfire activity in many parts of the world. Wildfire smoke contains haz-ardous air pollutants such as carbon monoxide, nitrogen dioxide, ozone, particulate matter et cetera. However, prediction of this impact and on time medical care are difficult due to the lack of digital decision-making systems. The aim of this study is to assess population health risks associated with the sub-daily exposure to wildfire smoke produced by massive foci of combustion near the populated areas and at a significant distance from them. We consider reflex reactions as a response to a short-term exposure. The maximum value of the 95th percentile from the series of observations at the moni-toring point was used to assess the hazard. For the mathematical description of the “concentration -ef-fect” relationship, the model of individual thresholds is applicable. This model describes a dependence as a straight line under the condition that the concentration is expressed in the form of a normal -probabilistic scale. The frequency of additional cases is determined by studying the number of re-quests for medical assistance (including calls for ambulance) with complaints of respiratory disorders, lacrimation, etc. on the territories affected by wildfires smokes. The indicator is calculated per 1000 population. The probability of negative biological effects in response to the impact of wildfire smoke is associated mainly with the content of CO and TPM in the conditions of the Baikal region. The frequency of additional requests for medical care ranged from 0.137 to 0.933 per 1000 exposed population during the fire period in settlements where risk levels are >0.01. We developed a digital environment that al-lows us to get information about harmful substances in the outdoor air from different sources and in different formats and data schemes. The digital environment supports implementation of models for assessing hazards to human body organs.(c) 2022 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
BACKGROUND: Understanding lung deposition dose of black carbon is critical to fully reconcile epidemiological evidence of combustion particles induced health effects and inform the development of air quality metrics concerning black carbon. Macrophage carbon load (MaCL) is a novel cytology method that quantifies lung deposition dose of black carbon, however it has limited feasibility in large-scale epidemiological study due to the labor-intensive manual counting. OBJECTIVE: To assess the association between MaCL and episodic elevation of combustion particles; to develop artificial intelligence based counting algorithm for MaCL assay. METHODS: Sputum slides were collected during episodic elevation of ambient PM(2.5) (n = 49, daily PM(2.5) > 10 µg/m(3) for over 2 weeks due to wildfire smoke intrusion in summer and local wood burning in winter) and low PM(2.5) period (n = 39, 30-day average PM(2.5) < 4 µg/m(3)) from the Lovelace Smokers cohort. RESULTS: Over 98% individual carbon particles in macrophages had diameter <1 µm. MaCL levels scored manually were highly responsive to episodic elevation of ambient PM(2.5) and also correlated with lung injury biomarker, plasma CC16. The association with CC16 became more robust when the assessment focused on macrophages with higher carbon load. A Machine-Learning algorithm for Engulfed cArbon Particles (MacLEAP) was developed based on the Mask Region-based Convolutional Neural Network. MacLEAP algorithm yielded excellent correlations with manual counting for number and area of the particles. The algorithm produced associations with ambient PM(2.5) and plasma CC16 that were nearly identical in magnitude to those obtained through manual counting. IMPACT STATEMENT: Understanding lung black carbon deposition is crucial for comprehending health effects of combustion particles. We developed "Machine-Learning algorithm for Engulfed cArbon Particles (MacLEAP)", the first artificial intelligence algorithm for quantifying airway macrophage black carbon. Our study bolstered the algorithm with more training images and its first use in air pollution epidemiology. We revealed macrophage carbon load as a sensitive biomarker for heightened ambient combustion particles due to wildfires and residential wood burning.
Urbanization and industrial development have resulted in increased air pollution, which is concerning for public health. This study evaluates the effect of meteorological factors and air pollution on hospital visits for respiratory diseases (pneumonia, acute upper respiratory infections, and chronic lower respiratory diseases). The test dataset comprises meteorological parameters, air pollutant concentrations, and outpatient hospital visits for respiratory diseases in Linyi, China, from January 1, 2016 to August 20, 2022. We use support vector regression (SVR) to build models that enable analysis of the effect of meteorological factors and air pollutants on the number of outpatient visits for respiratory diseases. Spearman correlation analysis and SVR model results indicate that NO(2), PM(2.5), and PM(10) are correlated with the occurrence of respiratory diseases, with the strongest correlation relating to pneumonia. An increase in the daily average temperature and daily relative humidity decreases the number of patients with pneumonia and chronic lower respiratory diseases but increases the number of patients with acute upper respiratory infections. The SVR modeling has the potential to predict the number of respiratory-related hospital visits. This work demonstrates that machine learning can be combined with meteorological and air pollution data for disease prediction, providing a useful tool whereby policymakers can take preventive measures.
Background: Cardiovascular diseases (CVD) remain the predominant global cause of mortality, with both low and high temperatures increasing CVD-related mortalities. Climate change impacts human health directly through temperature fluctuations and indirectly via factors like disease vectors. Elevated and reduced temperatures have been linked to increases in CVD-related hospitalizations and mortality, with various studies worldwide confirming the significant health implications of temperature variations and air pollution on cardiovascular outcomes. Methods: A database of daily Emergency Room admissions at the Giovanni XIII Polyclinic in Bari (Southern Italy) was developed, spanning from 2013 to 2019, including weather and air quality data. A Random Forest (RF) supervised machine learning model was used to simulate the trend of hospital admissions for CVD. The Seasonal and Trend decomposition using Loess (STL) decomposition model separated the trend component, while cross-validation techniques were employed to prevent overfitting. Model performance was assessed using specific metrics and error analysis. Additionally, the SHapley Additive exPlanations (SHAP) method, a feature importance technique within the eXplainable Artificial Intelligence (XAI) framework, was used to identify the feature importance. Results: An R2 of 0.97 and a Mean Absolute Error of 0.36 admissions were achieved by the model. Atmospheric pressure, minimum temperature, and carbon monoxide were found to collectively contribute about 74% to the model’s predictive power, with atmospheric pressure being the dominant factor at 37%. Conclusions: This research underscores the significant influence of weatherclimate variables on cardiovascular diseases. The identified key climate factors provide a practical framework for policymakers and healthcare professionals to mitigate the adverse effects of climate change on CVD and devise preventive strategies.
This paper demonstrates the strong link between the implementation of a GHG emission mitigation policy and the reduction of human health risk related to air pollution in Russia. The human health risk analysis method was introduced in Russia in the late 1990s. After a few pilot studies, this method has been in studies in several Russian cities with high populations and high air pollution. These studies demonstrate that among the hundreds of pollutants controlled by Russian law, a handful are responsible for up to 90% of human health risk from air pollution (PM$_{10}$ and SO$_{2}$ contribute the most). Fossil fuel combustion is the main source of the aforementioned conventional pollutants. This paper provides an overview of local ancillary benefits studies in selected Russian cities. The countrywide energy study presented in this paper proves that reduction of GHG emissions in the power generation sector would result in the reduction of these conventional pollutants in all regions. A major challenge for Russia in this process is a potential increase of the share of coal in the fuel mix. Such a change would result in the additional loss of 118,000 years of life countrywide. In the Central and Volgo-Viatsky regions additional mortality could increase by more than 30%. As a result of a GHG mitigation policy that avoided an increase in the coal share of the fuel mix could produce ancillary benefits in 2010 around $60 per ton of CO2 emission reduction in power sector alone.
PURPOSE: Atmospheric fungi are associated with respiratory allergies in humans, and some fungal spores can cause allergic diseases. Environmental and biological factors influence the concentrations of atmospheric spores. In this study, we evaluated the climate change-induced annual variations in fungal spore concentrations and allergic sensitization rates in the Seoul Metropolitan Area over a period of 25 years. METHODS: Fungal spores and pollen were obtained from Hanyang University Seoul and Guri Hospitals; they were identified and counted for 25 years (1998-2022). The study participants included patients who underwent tests for allergic diseases in both hospitals. Their allergenic sensitization rates were determined via allergic skin prick and serum tests, after which their sensitization rates to allergenic fungi and pollens were calculated. The daily climatic variables were obtained from the Korea Meteorological Administration. RESULTS: The total annual atmospheric fungal concentrations decreased in both areas during the period. Simultaneously, we recruited 21,394 patients with allergies (asthma, 1,550; allergic rhinitis, 5,983; and atopic dermatitis, 5,422) from Seoul and Guri Hospitals for allergenic fungal sensitization evaluations over the period. The allergenic fungal sensitization rates decreased annually in both areas over that time `+(Alternaria [3.5%] and Cladosporium [4.4%] in 1998; Alternaria [0.2%] and Cladosporium [0.2%] in 2022). In contrast, the annual pollen concentrations increased with the sensitization rates to pollen in children. CONCLUSIONS: The atmospheric fungal concentrations decreased annually, with allergic sensitization rate decreasing over the period of 25 years. Allergenic fungal sporulation could decrease with climate changes, such as desertification and drought. Extended monitoring periods and further large-scale studies are required to confirm the causality and to evaluate the impact of climate change.
The high incidence and mortality and the increasing trend of prostate cancer has been one of the public health issues in many countries and regions. Meanwhile, the spatio-temporal heterogeneity of prostate cancer implies that lifestyle and ecological changes may be associated with prostate cancer, however, sufficient evidence is still lacking. This paper tried to reveal the spatial and temporal distribution characteristics of prostate cancer in China and explore the potential associations with related socioeconomic and natural condition factors. Data on prostate cancer incidence and mortality in 182 counties (districts) in mainland China from 2014-2016 were collected, and the distribution characteristics of prostate cancer were analyzed using spatiotemporal scan statistic. Spatial regression models and geodetector method were used to analyze the potential associations between meteorological conditions, socioeconomic development, and prostate cancer incidence and mortality. SaTScan, GeoDa, and GeoDetector were used for the above statistical analyses. The high-risk clusters for prostate cancer incidence and mortality were located in southeastern China, and the low-risk clusters were located in north-central China. Spatial regression models showed that the number of industrial enterprises/km(2) (incidence: β = 0.322, P < 0.001; mortality: β = 0.179, P < 0.001), GDP (incidence:β = 0.553, P < 0.001; mortality: β = 0.324, P < 0.001), number of beds in medical and health institutions/1000 persons (incidence: β = 0.111, P = 0.005; mortality: β = 0.068, P = 0.021), and urbanization rate (incidence: β = 0.156, P < 0.001; mortality: β = 0.100, P < 0.001) were positively associated with the incidence and mortality of prostate cancer. The urbanization rate (incidence: q = 0.185, P < 0.001; mortality: q = 0.182, P < 0.001) has the greatest explanatory power, and the interaction of all factors was bivariate enhanced or nonlinearly enhanced. The distribution of prostate cancer in China has obvious spatial heterogeneity. The incidence and mortality rate of prostate cancer are on the rise, and special plans should be formulated in each region according to local conditions.
Air pollution poses well-established risks to physical health, but little is known about its effects on mental health. We study the relationship between wildfire smoke exposure and suicide risk in the United States in 2007 to 2019 using data on all deaths by suicide and satellite-based measures of wildfire smoke and ambient fine particulate matter (PM(2.5)) concentrations. We identify the causal effects of wildfire smoke pollution on suicide by relating year-over-year fluctuations in county-level monthly smoke exposure to fluctuations in suicide rates and compare the effects across local areas and demographic groups that differ considerably in their baseline suicide risk. In rural counties, an additional day of smoke increases monthly mean PM(2.5) by 0.41 μg/m(3) and suicide deaths by 0.11 per million residents, such that a 1-μg/m(3) (13%) increase in monthly wildfire-derived fine particulate matter leads to 0.27 additional suicide deaths per million residents (a 2.0% increase). These effects are concentrated among demographic groups with both high baseline suicide risk and high exposure to outdoor air: men, working-age adults, non-Hispanic Whites, and adults with no college education. By contrast, we find no evidence that smoke pollution increases suicide risk among any urban demographic group. This study provides large-scale evidence that air pollution elevates the risk of suicide, disproportionately so among rural populations.
PURPOSE OF REVIEW: Environmental exposures have been associated with increased risk of cardiovascular mortality and acute coronary events, but their relationship with out-of-hospital cardiac arrest (OHCA) and sudden cardiac death (SCD) remains unclear. SCD is an important contributor to the global burden of cardiovascular disease worldwide. RECENT FINDINGS: Current literature suggests a relationship between environmental exposures and cardiovascular disease, but their relationship with OHCA/SCD remains unclear. A literature search was conducted in PubMed, Embase, Web of Science, and Global Health. Of 5138 studies identified by our literature search, this review included 30 studies on air pollution, 42 studies on temperature, 6 studies on both air pollution and temperature, and 1 study on altitude exposure and OHCA/SCD. Particulate matter air pollution, ozone, and both hot and cold temperatures are associated with increased risk of OHCA/SCD. Pollution and other exposures related to climate change play an important role in OHCA/SCD incidence.
Cambodia’s 16.5 million people are exposed to air pollution in excess of World Health Organisation guidelines. The Royal Government of Cambodia has regulated air pollutant emissions and concentrations since 2000, but rapid economic growth and energy consumption means air pollution continues to impact human health. In December 2021, the Ministry of Environment of Cambodia published Cambodia’s first Clean Air Plan that outlines actions to reduce air pollutant emissions over the next decade. This work presents the quantitative air pollution mitigation assessment underpinning the identification and evaluation of measures included in Cambodia’s Clean Air Plan. Historic emissions of particulate matter (PM(2.5), black carbon, organic carbon) and gaseous (nitrogen oxides, volatile organic compounds, sulphur dioxide, ammonia, and carbon monoxide) air pollutants are quantified between 2010 and 2015, and projected to 2030 for a baseline scenario. Mitigation scenarios reflecting implementation of 14 measures included in Cambodia’s Clean Air Plan were modelled, to quantify the national reduction in emissions, from which the reduction in ambient PM(2.5) exposure and attributable health burdens were estimated. In 2015, the residential, transport, and waste sectors contribute the largest fraction of national total air pollutant emissions. Without emission reduction measures, air pollutant emissions could increase by between 50 and 150% in 2030 compared to 2015 levels, predominantly due to increases in transport emissions. The implementation of the 14 mitigation measures could substantially reduce emissions of all air pollutants, by between 60 and 80% in 2030 compared to the baseline. This reduction in emissions was estimated to avoid approximately 900 (95% C.I.: 530-1200) premature deaths per year in 2030 compared to the baseline scenario. In addition to improving air pollution and public health, Cambodia’s Clean Air Plan could also to lead to additional benefits, including a 19% reduction in carbon dioxide emissions, simultaneously contributing to Cambodia’s climate change goals.
Climate change-driven temperature increases worsen air quality in places where coal combustion powers electricity for air conditioning. Climate solutions that substitute clean and renewable energy in place of polluting coal and promote adaptation to warming through reflective cool roofs can reduce cooling energy demand in buildings, lower power sector carbon emissions, and improve air quality and health. We investigate the air quality and health co-benefits of climate solutions in Ahmedabad, India-a city where air pollution levels exceed national health-based standards-through an interdisciplinary modeling approach. Using a 2018 baseline, we quantify changes in fine particulate matter (PM(2.5)) air pollution and all-cause mortality in 2030 from increasing renewable energy use (mitigation) and expanding Ahmedabad’s cool roofs heat resilience program (adaptation). We apply local demographic and health data and compare a 2030 mitigation and adaptation (M&A) scenario to a 2030 business-as-usual (BAU) scenario (without climate change response actions), each relative to 2018 pollution levels. We estimate that the 2030 BAU scenario results in an increase of PM(2.5) air pollution of 4.13 µg m(-3) from 2018 compared to a 0.11 µg m(-3) decline from 2018 under the 2030 M&A scenario. Reduced PM(2.5) air pollution under 2030 M&A results in 1216-1414 fewer premature all-cause deaths annually compared to 2030 BAU. Achievement of National Clean Air Programme, National Ambient Air Quality Standards, or World Health Organization annual PM(2.5) Air Quality Guideline targets in 2030 results in up to 6510, 9047, or 17 369 fewer annual deaths, respectively, relative to 2030 BAU. This comprehensive modeling method is adaptable to estimate local air quality and health co-benefits in other settings by integrating climate, energy, cooling, land cover, air pollution, and health data. Our findings demonstrate that city-level climate change response policies can achieve substantial air quality and health co-benefits. Such work can inform public discourse on the near-term health benefits of mitigation and adaptation.
Airborne pollen monitoring has been conducted for more than a century now, as knowledge of the quantity and periodicity of airborne pollen has diverse use cases, like reconstructing historic climates and tracking current climate change, forensic applications, and up to warning those affected by pollen-induced respiratory allergies. Hence, related work on automation of pollen classification already exists. In contrast, detection of pollen is still conducted manually, and it is the gold standard for accuracy. So, here we used a new-generation, automated, near-real-time pollen monitoring sampler, the BAA500, and we used data consisting of both raw and synthesised microscope images. Apart from the automatically generated, commercially-labelled data of all pollen taxa, we additionally used manual corrections to the pollen taxa, as well as a manually created test set of bounding boxes and pollen taxa, so as to more accurately evaluate the real-life performance. For the pollen detection, we employed two-stage deep neural network object detectors. We explored a semi-supervised training scheme to remedy the partial labelling. Using a teacher-student approach, the model can add pseudo-labels to complete the labelling during training. To evaluate the performance of our deep learning algorithms and to compare them to the commercial algorithm of the BAA500, we created a manual test set, in which an expert aerobiologist corrected automatically annotated labels. For the novel manual test set, both the supervised and semi-supervised approaches clearly outperform the commercial algorithm with an F1 score of up to 76.9 % compared to 61.3 %. On an automatically created and partially labelled test dataset, we obtain a maximum mAP of 92.7 %. Additional experiments on raw microscope images show comparable performance for the best models, which potentially justifies reducing the complexity of the image generation process. Our results bring automatic pollen monitoring a step forward, as they close the gap in pollen detection performance between manual and automated procedure.
Higher ambient temperature and air pollution may contribute to increased risk of behaviors harmful to oneself or to others; however, quantitative evidence is limited. We examined the relationship of deaths due to suicide and homicide with temperature and air pollution in California-a state prone to high levels of both exposures. METHOD: California death certificates from 2014 to 2019 were used to identify deaths due to suicide and homicide. Residential data for decedents were used to assign exposure to daily temperature (maximum[T(max)], minimum[T(min)]) and daily average air pollution concentrations (particulate matter <10 μm[PM(10)] and < 2.5 μm[PM(2.5)], nitrogen dioxide[NO(2)], ozone[O(3)]). T(min) served as a surrogate for nighttime temperature. A time-stratified case-crossover study design using conditional logistic regression was used to assess the effects of daily exposure to temperature and air pollutants on suicide and homicide mortality, adjusting for relative humidity. Effect modification by sex and age was assessed. RESULTS: We observed 24,387 deaths due to suicide and 10,767 deaths due to homicide. We found a monotonic temperature association for both outcomes. A 5 °C increase in T(max) at lag-2 and T(min) at lag-0 was associated with 3.1 % (95 % confidence interval [CI]: 1.1 %-5.2 %) and 3.8 % (95%CI: 0.9 %-6.8 %) increased odds of death due to suicide, respectively. The increased odds of homicide mortality per 5 °C increase in T(max) at lag-0 and T(min) at lag-1 were 4.9 % (95%CI: 1.6 %-8.1 %) and 6.2 % (95%CI: 1.6 %-11.0 %), respectively. No air pollutant associations were statistically significant. Temperature associations were robust after adjustment for PM(2.5). Some temperature effects were larger among women for suicide and men for homicide mortality, and among those over age 65 years for both outcomes. CONCLUSION: Risk of suicide and homicide mortality increases with increasing daily ambient temperatures. Findings have public health relevance given anticipated increases in temperatures due to global climate change.
Maternal exposure to ambient heat may be associated with congenital anomalies, but evidence is still limited. OBJECTIVES: We aimed to estimate the association between maternal exposure to ambient heat during the 3-12 weeks post-conception (critical window of organogenesis) and risk of total and various diagnostic categories of major structural anomalies among live singleton births in the contiguous United States (US). METHODS: We included data on 2,352,529 births with the first day of critical developmental windows falling within months of May through August from 2000 to 2004 across 525 US counties. We used a validated spatial-temporal model to estimate daily county-level population-weighted temperature. We used logistic regression to estimate the association between ambient temperature and risk of diagnostic categories of anomalies during the critical window after adjusting for individual and county-level factors. We conducted subgroup analysis to identify potential susceptible subpopulations. RESULTS: A total of 29,188 anomalies (12.4 per 1000 births) were recorded during the study period. Maternal exposure to extreme heat (> 95th percentile) was associated with higher risk of total anomalies, central nervous system anomalies, and other uncategorized anomalies with an odds ratio (OR) of 1.05 (95 % CI: 1.00, 1.11), 1.17 (95 % CI: 1.01, 1.37), and 1.16 (95 % CI: 1.04, 1.29) compared with minimum morbidity temperature, respectively. The associations were homogeneous across subgroups defined by maternal age, maternal race/ethnicity, marital status, educational attainment, and parity, but were more pronounced among mothers residing in more socially vulnerable counties and births with multiple anomalies. CONCLUSIONS: Among US live singleton births, maternal exposure to ambient heat may be associated with higher risk of total anomalies, central nervous system anomalies, and other uncategorized anomalies. We suggest additional research is carried out to better understand the relations between maternal heat exposure and congenital anomalies in the presence of global warming.
INTRODUCTION: Ambient ozone pollution becomes critical in China. Conclusions on the short-term effects of ozone on cardiovascular mortality have been controversial and limited on cause-specific cardiovascular mortalities and their interactions with season and temperature. This research aimed to investigate the short-term effects of ozone and the modifications of season and temperature on cardiovascular mortality. METHODS: Cardiovascular death records, air pollutants, and meteorological factors in Shenzhen from 2013 to 2019 were analyzed. Daily 1-h maximum of ozone and daily maximum 8-h moving average of ozone were studied. Generalized additive models (GAMs) were applied to evaluate their associations with cardiovascular mortalities in sex and age groups. Effect modifications were assessed by stratifying season and temperature. RESULTS: Distributed lag impacts of ozone on total cardiovascular deaths and cumulative effects on mortality due to ischemic heart disease (IHD) were most significant. Population under 65 years old was most susceptible. Majority of significant effects were found in warm season, at high temperature, and at extreme heat. Ozone-associated risks in total deaths caused by hypertensive diseases reduced in warm season, while risks in IHD in males increased at high temperature. Extreme heat enhanced ozone effects on deaths caused by CVDs and IHD in the population under 65 years old. DISCUSSION: The revealed cardiovascular impacts of ozone below current national standard of air quality suggested improved standards and interventions in China. Higher temperature, particularly extreme heat, rather than warm season, could significantly enhance the adverse effects of ozone on cardiovascular mortality in population under 65 years old.
OBJECTIVE: The purpose of this study was to understand the experiences of agricultural workers during periods of heat and wildfire smoke exposure and to support the development and implementation of protective workplace interventions. METHODS: Using community-engaged research and the Center for Disease Control (CDC) framework for policy evaluation, a qualitative descriptive study was conducted with current and former agricultural workers in Central Washington (WA). Twelve participants answered semi-structured questions via interviews or by attending a focus group. Interviews and focus groups were conducted in Spanish, recorded, transcribed, and translated into English; one interview was conducted in English. RESULTS: Using Braun and Clarke’s Reflexive Thematic Analysis, five themes were identified among workers from various worksites: 1) Extreme weather and working conditions are becoming increasingly hazardous to worker health, 2) Employers and supervisors lack training and education on current labor laws, and health and safety rules, 3) Employers and supervisors use intimidation and retaliation to ensure productivity and to evoke feelings of replaceability among workers, 4) Workers do not trust regulatory agencies to enforce rules or hold employers accountable, 5) Solutions to climate-driven problems in the agricultural industry need to value worker health and safety, not just productivity. Participants reported experiencing adverse health symptoms related to heat and smoke exposure at work. Workers proposed solutions including improving education, training, and communication, and increased enforcement of existing and forthcoming occupational health and safety rules. CONCLUSION: The agricultural workforce is essential for ensuring a robust food supply and is facing extreme weather events due to climate change. Western states impacted by wildfires and heat are working to develop and implement occupational health and safety rules. Developing effective policies and interventions inclusive of worker perspectives is critical to adapt to a changing climate, retain a stable workforce and promote optimal health.
Exposure to air pollution is a major contributor to the pathogenesis of COPD worldwide. Indeed, most recent estimates suggest that 50% of the total attributable risk of COPD may be related to air pollution. In response, the Global Initiative for Chronic Obstructive Lung Disease (GOLD) Scientific Committee performed a comprehensive review on this topic, qualitatively synthesised the evidence to date and proffered recommendations to mitigate the risk. The review found that both gaseous and particulate components of air pollution are likely contributors to COPD. There are no absolutely safe levels of ambient air pollution and the relationship between air pollution levels and respiratory events is supra-linear. Wildfires and extreme weather events such as heat waves, which are becoming more common owing to climate change, are major threats to COPD patients and acutely increase their risk of morbidity and mortality. Exposure to air pollution also impairs lung growth in children and as such may lead to developmental COPD. GOLD recommends strong public health policies around the world to reduce ambient air pollution and for implementation of public warning systems and advisories, including where possible the use of personalised apps, to alert patients when ambient air pollution levels exceed acceptable minimal thresholds. When household particulate content exceeds acceptable thresholds, patients should consider using air cleaners and filters where feasible. Air pollution is a major health threat to patients living with COPD and actions are urgently required to reduce the morbidity and mortality related to poor air quality around the world.
Increased fossil fuel usage and extreme climate change events have led to global increases in greenhouse gases and particulate matter with 99% of the world’s population now breathing polluted air that exceeds the World Health Organization’s recommended limits. Pregnant women and neonates with exposure to high levels of air pollutants are at increased risk of adverse health outcomes such as maternal hypertensive disorders, postpartum depression, placental abruption, low birth weight, preterm birth, infant mortality, and adverse lung and respiratory effects. While the exact mechanism by which air pollution exerts adverse health effects is unknown, oxidative stress as well as epigenetic and immune mechanisms are thought to play roles. Comprehensive, global efforts are urgently required to tackle the health challenges posed by air pollution through policies and action for reducing air pollution as well as finding ways to protect the health of vulnerable populations in the face of increasing air pollution.
In 2016, unprecedented intense wildfires burned over 150,000 acres in the southern Appalachian Mountains in the United States. Smoke from these fires greatly impacted the region and exposure to this smoke was significant. A bidirectional case-crossover design was applied to assess the relationship between PM(2.5) (a surrogate for wildfire smoke) exposure and respiratory- and cardiovascular-related emergency department (ED) visits in Western North Carolina during these events. For 0-, 3-, and 7-day lags, findings indicated a significant increase in the odds of being admitted to the ED for a respiratory (ORs: 1.055, 95% CI: 1.048-1.063; 1.083, 1.074-1.092; 1.066, 1.058-1.074; respectively) or cardiovascular event (ORs: 1.052, 95% CI: 1.045-1.060; 1.074, 1.066-1.081; 1.067, 1.060-1.075; respectively) for every 5 μg/m(3) increase in PM(2.5) over a chosen cutpoint of 20.4 μg/m(3). For all endpoints assessed except for emphysema, there were statistically significant increases in odds from 5.1% to 8.3%. In general, this increase was most pronounced 3 days after exposure. Additionally, individuals aged 55+ generally experience higher odds of heart disease at the 3- and 7-day lag points, and Black/African Americans generally experience higher odds of asthma at the 3-day lag point. In general, larger fires and increased numbers of fires within counties resulted in higher health burden at same day exposure. In a secondary analysis, the odds of an ED visit increased by over 40% in several cases among people exposed to days above the Environmental Protection Agency 24-hr PM(2.5) standard of 35 μg/m(3). Our findings provide new understanding on the health impacts of wildfires on rural populations in the southeastern US.
Little is known about how low-income residents of urban communities engage their knowledge, attitudes, behaviors, and resources to mitigate the health impacts of wildfire smoke and other forms of air pollution. We interviewed 40 adults in Los Angeles, California, to explore their threat assessments of days of poor air quality, adaptation resources and behaviors, and the impacts of air pollution and wildfire smoke on physical and mental health. Participants resided in census tracts that were disproportionately burdened by air pollution and socioeconomic vulnerability. All participants reported experiencing days of poor air quality due primarily to wildfire smoke. Sixty percent received advanced warnings of days of poor air quality or routinely monitored air quality via cell phone apps or news broadcasts. Adaptation behaviors included remaining indoors, circulating indoor air, and wearing face masks when outdoors. Most (82.5%) of the participants reported some physical or mental health problem or symptom during days of poor air quality, but several indicated that symptom severity was mitigated by their adaptive behaviors. Although low-income residents perceive themselves to be at risk for the physical and mental health impacts of air pollution, they have also adapted to that risk with limited resources.
BACKGROUND: Urban areas are disproportionately affected by multiple pressures from overbuilding, traffic, air pollution, and heat waves that often interact and are interconnected in producing health effects. A new synthetic tool to summarize environmental and climatic vulnerability has been introduced for the city of Rome, Italy, to provide the basis for environmental and health policies. METHODS: From a literature overview and based on the availability of data, several macro-dimensions were identified on 1,461 grid cells with a width of 1 km(2) in Rome: land use, roads and traffic-related exposure, green space data, soil sealing, air pollution (PM(2.5), PM(10), NO(2), C(6)H(6), SO(2)), urban heat island intensity. The Geographically Weighted Principal Component Analysis (GWPCA) method was performed to produce a composite spatial indicator to describe and interpret each spatial feature by integrating all environmental dimensions. The method of natural breaks was used to define the risk classes. A bivariate map of environmental and social vulnerability was described. RESULTS: The first three components explained most of the variation in the data structure with an average of 78.2% of the total percentage of variance (PTV) explained by the GWPCA, with air pollution and soil sealing contributing most in the first component; green space in the second component; road and traffic density and SO(2) in the third component. 56% of the population lives in areas with high or very high levels of environmental and climatic vulnerability, showing a periphery-centre trend, inverse to the deprivation index. CONCLUSIONS: A new environmental and climatic vulnerability indicator for the city of Rome was able to identify the areas and population at risk in the city, and can be integrated with other vulnerability dimensions, such as social deprivation, providing the basis for risk stratification of the population and for the design of policies to address environmental, climatic and social injustice.
Ongoing and future climate change driven expansion of aeroallergen-producing plant species comprise a major human health problem across Europe and elsewhere. There is an urgent need to produce accurate, temporally dynamic maps at the continental level, especially in the context of climate uncertainty. This study aimed to restore missing daily ragweed pollen data sets for Europe, to produce phenological maps of ragweed pollen, resulting in the most complete and detailed high-resolution ragweed pollen concentration maps to date. To achieve this, we have developed two statistical procedures, a Gaussian method (GM) and deep learning (DL) for restoring missing daily ragweed pollen data sets, based on the plant’s reproductive and growth (phenological, pollen production and frost-related) characteristics. DL model performances were consistently better for estimating seasonal pollen integrals than those of the GM approach. These are the first published modelled maps using altitude correction and flowering phenology to recover missing pollen information. We created a web page (http://euragweedpollen.gmf.u-szeged.hu/), including daily ragweed pollen concentration data sets of the stations examined and their restored daily data, allowing one to upload newly measured or recovered daily data. Generation of these maps provides a means to track pollen impacts in the context of climatic shifts, identify geographical regions with high pollen exposure, determine areas of future vulnerability, apply spatially-explicit mitigation measures and prioritize management interventions.
INTRODUCTION: Environmental Health in a Global World at New York University was re-designed as a class participatory effort, challenging undergraduate students to understand environmental hazards and the resultant adverse health outcomes by embracing the inherent complexity of environmental risks and proposing solutions. METHODS: Following introductory lectures, students are placed into teams and assigned a specific perspective, or avatar, which includes learning to see the challenge from the perspective of a technical expert such as a biologist, an engineer, or an anthropologist. The teams then design specific systems maps to visualize the complex interactions that lead to adverse health outcomes after a given environmental exposure. The maps highlight potential leverage points where relatively minor interventions can provide a disproportionate benefit in health outcomes. The teams then explore potential interventions and identify the potential unintended consequences of those actions, develop and advocate for innovative new strategies to mitigate risk and improve outcomes. RESULTS AND DISCUSSION: Over the past 5 years, we have taught this methodology to over 680 students with strong, student-oriented results. The teams created and presented more than 100 strategies, addressing a diverse set of environmental challenges that include water contamination, gun violence, air pollution, environmental justice, health security, and climate change. Developing the strategies helped the students understand environmental threats in a more holistic way, provided them with some agency in finding solutions, and offered an opportunity for them to improve their presentation skills. The responses in course evaluations have been enthusiastic, with many students reporting a deep impact on their college experience.
While chemicals are vital to modern society through materials, agriculture, textiles, new technology, medicines, and consumer goods, their use is not without risks. Unfortunately, our resources seem inadequate to address the breadth of chemical challenges to the environment and human health. Therefore, it is important we use our intelligence and knowledge wisely to prepare for what lies ahead. The present study used a Delphi-style approach to horizon-scan future chemical threats that need to be considered in the setting of chemicals and environmental policy, which involved a multidisciplinary, multisectoral, and multinational panel of 25 scientists and practitioners (mainly from the United Kingdom, Europe, and other industrialized nations) in a three-stage process. Fifteen issues were shortlisted (from a nominated list of 48), considered by the panel to hold global relevance. The issues span from the need for new chemical manufacturing (including transitioning to non-fossil-fuel feedstocks); challenges from novel materials, food imports, landfills, and tire wear; and opportunities from artificial intelligence, greater data transparency, and the weight-of-evidence approach. The 15 issues can be divided into three classes: new perspectives on historic but insufficiently appreciated chemicals/issues, new or relatively new products and their associated industries, and thinking through approaches we can use to meet these challenges. Chemicals are one threat among many that influence the environment and human health, and interlinkages with wider issues such as climate change and how we mitigate these were clear in this exercise. The horizon scan highlights the value of thinking broadly and consulting widely, considering systems approaches to ensure that interventions appreciate synergies and avoid harmful trade-offs in other areas. We recommend further collaboration between researchers, industry, regulators, and policymakers to perform horizon scanning to inform policymaking, to develop our ability to meet these challenges, and especially to extend the approach to consider also concerns from countries with developing economies. Environ Toxicol Chem 2023;42:1212-1228. © 2023 Crown copyright and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article is published with the permission of the Controller of HMSO and the King’s Printer for Scotland.
This paper aims to develop a Life Cycle Assessment-based methodology to assess and compare the potential burden shifting between indoor air quality and energy consumption, as well as between the building construction and use stages, focusing on three insulation materials. We model the complete cause-to-effect chain to determine the mass of substances initially encapsulated inside the construction materials emitted into the indoor and outdoor compartment and further human intake, as well as the energy consumption needed for use stage heating.We found that human health damage due to indoor exposure is dominant over outdoor exposure for all insulation materials, except extruded polystyrene due to the off-gassing of tetrafluoroethane which has a high global warming potential. From a material life cycle perspective, the damage related to indoor emissions during the use stage is substantial for polyurethane foam, due to formaldehyde for both inner and outer insulations and also to Tris (1-chloro-2-propyl) phosphate for outer insulation, while restricted for polystyrene. Total damages on human health depend on building materials production, their emissions during use stage, and impacts related to energy load. They are minimized with a 20-25 cm outer insulation combined with a heat exchanger to ensure sufficient air quality while maximizing solar gain and minimizing air renewal-related heat losses.This methodology is valuable in addressing the trade-off between energy and exposure to materials-related emissions during building use stage, as a function of insulation thickness and air renewal rate, and paves the way to optimize the design of more sustainable buildings.
Air quality, especially particulate matter pollution levels in urban areas, is an essential academic and social topic due to its association with health issues and climate change. In Romania, increasing awareness of urban communities and the availability of low-cost sensors has led to the development of an independent monitoring network currently distributed in over 194 cities and towns. The uRADMonitor((R)) network consists of 630 sensors measuring PM10 and PM2.5 concentration levels. The spatial distribution of the sensors complements the national air quality network with sensors in residential areas, intense traffic zones, and industrial areas. The data are available through a user-friendly web-based platform from uRADMonitor((R)). Based on data collected in 2021, we present an analysis of PM10 pollution levels in Romania’s five most populated urban areas by employing five annual statistical indicators recommended by the European Environmental Agency. For the case of Timis,oara, we also compare the data measured by independent sensors with those from the national monitoring network. The results highlight the usefulness of our community-based network as it complements the national one.
INTRODUCTION: As wildfire smoke events increase in intensity and frequency in the Pacific Northwest, there is a growing need for effective communication on the health risks of smoke exposure. Delivery through a trusted source or intermediary has been shown to improve reception of risk communication messages. This is especially salient in rural and tribal communities who may be hesitant to trust information from state and federal agency sources. This study aims to identify and characterize trusted sources for smoke risk information in the Okanogan River Airshed Emphasis Area (ORAEA), a rural region of North Central Washington state that is heavily impacted by smoke from wildfires and prescribed fire. METHODS: The research team conducted a qualitative study using data collected through key informant interviews and focus groups to assess the role of various sources and intermediaries in disseminating smoke risk information. We used a consensual coding approach in NVivo Qualitative Analysis Software to sort data into preliminary categories, which were grouped into themes using a thematic analysis approach. We used member checking and iterative feedback processes with local project partners throughout the project to ensure credibility of results. RESULTS: Through the analysis, we identified three themes characterizing trusted sources for smoke risk communication in the ORAEA. These themes were: (1) local and tribal sources of information are perceived as more trustworthy than state and federal government sources, (2) trustworthiness is determined by an evaluation of multiple factors, in particular, perceived credibility, quality of information, and relationship with the source, and (3) conservative political ideology and perceived parallels with COVID-19 communication influence perception of trust. Within each theme, we identified several sub-themes, which contributed additional nuance to our analysis. CONCLUSION: This study provides insights into which sources of information are trusted by rural and tribal community members in the ORAEA and why. Results from our study emphasize the importance of relationships and collaboration with local and tribal partners in smoke risk communication. In this paper, we discuss implications for state and federal agency practitioners and present recommendations for how to work with local and tribal partners on smoke risk communication.
Wildfire severity is a key indicator of both direct ecosystem impacts and indirect emissions impacts that affect air quality, climate, and public health far beyond the spatial footprint of the flames. Comprehensive, accurate inventories of severity and emissions are essential for assessing these impacts and setting appropriate fire management and health care preparedness strategies, as is the ability to project emissions for future wildfires. The frequency of large wildfires and the magnitude of their impacts have increased in recent decades, fueling concerns about decreased air quality. To improve the availability of accurate fire severity and emissions estimates, we developed the wildfire burn severity and emissions inventory (WBSE). WBSE is a retrospective spatial burn severity and emissions inventory at 30 m resolution for event-based assessment and 500 m resolution for daily emissions calculation. We applied the WBSE framework to calculate burn severity and emissions for historically observed large wildfires (>404 hectares (ha)) that burned during 1984-2020 in the state of California, U.S., a substantially more extended period than existing inventories. We assigned the day of burning and daily emissions for each fire during 2002-2020. The framework described here can also be applied to estimate severity for smaller wildfires and can also be used to estimate emissions for fires simulated in California for future climate and land-use scenarios. The WBSE framework implemented in R and Google Earth Engine can provide quick estimates once a desired fire perimeter is available. The framework developed here could also easily be applied to other regions with user-modified vegetation, fuel data, and emission factors.
Air quality impacts from wildfires are poorly understood, particularly indoors. As frequencies increase, it is important to optimize methodologies to understand and reduce chemical exposures from wildfires. Public health recommendations use air quality estimates from outdoor stationary air monitors, discounting indoor air conditions, and do not consider chemicals in the vapor phase, known to elicit adverse effects. We investigated vapor-phase polycyclic aromatic hydrocarbons (PAHs) in indoor and outdoor air before, during, and after wildfires using a community-engaged research approach. Paired passive air samplers were deployed at 15 locations across four states. Twelve unique PAHs were detected only in outdoor air during wildfires, highlighting a PAH exposure mixture for future study. Heavy-molecular-weight (HMW) outdoor PAH concentrations and average Air Quality Index (AQI) values were positively correlated (p < 0.001). Indoor PAH concentrations were higher in 77% of samples across all sampling events. Even during wildfires, 58% of sampled locations still had higher indoor PAH air concentrations. When AQI values exceeded 140 (unhealthy for sensitive groups), outdoor PAH concentrations became similar to or higher than indoors. Cancer and noncancer inhalation risk estimates from vapor-phase PAHs were higher indoors than outdoors, regardless of the wildfire impact. Consideration of indoor air quality and vapor-phase PAHs could inform public health recommendations regarding wildfires.
The physical and mental health impacts of wildfires are wide-ranging. We assessed associations between exposure to wildfire smoke and self-reported symptoms affecting mental health among adults living in Oregon. We linked by interview date and county of residence survey responses from 5807 adults who responded to the 2018 Behavioral Risk Factor Surveillance System’s depression and anxiety module with smoke plume density, a proxy for wildfires and wildfire smoke exposure. Associations between weeks in the past year with medium and heavy smoke plume densities and symptoms affecting mental health during the two weeks before the interview date were estimated using predicted marginal probabilities from logistic regression models. In the year before completing the interview, 100% of respondents experienced ≥2 weeks of medium or heavy smoke, with an average exposure duration of 32 days. Nearly 10% reported being unable to stop or control their worrying more than half the time over the past two weeks. Medium or heavy smoke for 6 or more weeks in the past year, compared to ≤4 weeks in the past year, was associated with a 30% higher prevalence of being unable to stop or control worrying more than half the time during the past two weeks (prevalence ratio: 1.30, 95% confidence interval: 1.03, 1.65). Among adults in Oregon, selected symptoms affecting mental health were associated with extended durations of medium and heavy smoke. These findings highlight the burden of such symptoms among adults living in communities affected by wildfires and wildfire smoke.
Climate change is accelerating the intensity and frequency of wildfires globally. Understanding how wildfire smoke (WS) may lead to adverse pregnancy outcomes and alterations in placental function via biological mechanisms is critical to mitigate the harms of exposure. We aim to review the literature surrounding WS, placental biology, biological mechanisms underlying adverse pregnancy outcomes as well as interventions and strategies to avoid WS exposure in pregnancy. This review includes epidemiologic and experimental laboratory-based studies of WS, air pollution, particulate matter (PM), and other chemicals related to combustion in relation to obstetric outcomes and placental biology. We summarized the available clinical, animal, and placental studies with WS and other combustion products such as tobacco, diesel, and wood smoke. Additionally, we reviewed current recommendations for prevention of WS exposure. We found that there is limited data specific to WS; however, studies on air pollution and other combustion sources suggest a link to inflammation, oxidative stress, endocrine disruption, DNA damage, telomere shortening, epigenetic changes, as well as metabolic, vascular, and endothelial dysregulation in the maternal-fetal unit. These alterations in placental biology contribute to adverse obstetric outcomes that disproportionally affect the most vulnerable. Limiting time outdoors, wearing N95 respirator face masks and using high quality indoor air filters during wildfire events reduces exposure to related environmental exposures and may mitigate morbidities attributable to WS.
BACKGROUND: Increasing wildfire activity worldwide has led to exposure to poor air quality and numerous detrimental health impacts. This study hypothesized an association between exposure to poor air quality from wildfire smoke and adverse respiratory events under general anesthesia in pediatric patients. METHODS: This was a single-center retrospective double-cohort study examining two significant wildfire events in Northern California. Pediatric patients presenting for elective surgery during periods of unhealthy air quality were compared with those during periods of healthy air quality. The primary exposure, unhealthy air, was determined using local air quality sensors. The primary outcome was the occurrence of an adverse respiratory event under anesthesia. Secondary analysis included association with other known risk factors for adverse respiratory events. RESULTS: A total of 625 patients were included in the analysis. The overall risk of a respiratory complication was 42.4% (265 of 625). In children without a history of reactive airway disease, the risk of adverse respiratory events did not change during unhealthy air periods (102 of 253, 40.3%) compared with healthy air periods (95 of 226, 42.0%; relative risk 0.96 [0.77 to 1.19], P = 0.703). In children with a history of reactive airway disease, the risk of adverse respiratory events increased from 36.8% (25 of 68) during healthy air periods to 55.1% (43 of 78) during periods with unhealthy air (1.50 [1.04 to 2.17], P = 0.032). The effect of air quality on adverse respiratory events was significantly modified by reactive airways disease status (1.56 [1.02 to 2.40], P = 0.041). CONCLUSIONS: Pediatric patients with underlying risk factors for respiratory complications under general anesthesia had a greater incidence of adverse respiratory events during periods of unhealthy air quality caused by wildfire smoke. In this vulnerable patient population, postponing elective anesthetics should be considered when air quality is poor.
The prevalence of wildfires continues to grow globally with exposures resulting in increased disease risk. Characterizing these health risks remains difficult due to the wide landscape of exposures that can result from different burn conditions and fuel types. This study tested the hypothesis that biomass smoke exposures from variable fuels and combustion conditions group together based on similar transcriptional response profiles, informing which wildfire-relevant exposures may be considered as a group for health risk evaluations. Mice (female CD-1) were exposed via oropharyngeal aspiration to equal mass biomass smoke condensates produced from flaming or smoldering burns of eucalyptus, peat, pine, pine needles, or red oak species. Lung transcriptomic signatures were used to calculate transcriptomic similarity scores across exposures, which informed exposure groupings. Exposures from flaming peat, flaming eucalyptus, and smoldering eucalyptus induced the greatest responses, with flaming peat grouping with the pro-inflammatory agent lipopolysaccharide. Smoldering red oak and smoldering peat induced the least transcriptomic response. Groupings paralleled pulmonary toxicity markers, though they were better substantiated by higher data dimensionality and resolution provided through -omic-based evaluation. Interestingly, groupings based on smoke chemistry signatures differed from transcriptomic/toxicity-based groupings. Wildfire-relevant exposure groupings yield insights into risk assessment strategies to ultimately protect public health.
PURPOSE OF REVIEW: Increasing wildfire size and severity across the western United States has created an environmental and social crisis that must be approached from a transdisciplinary perspective. Climate change and more than a century of fire exclusion and wildfire suppression have led to contemporary wildfires with more severe environmental impacts and human smoke exposure. Wildfires increase smoke exposure for broad swaths of the US population, though outdoor workers and socially disadvantaged groups with limited adaptive capacity can be disproportionally exposed. Exposure to wildfire smoke is associated with a range of health impacts in children and adults, including exacerbation of existing respiratory diseases such as asthma and chronic obstructive pulmonary disease, worse birth outcomes, and cardiovascular events. Seasonally dry forests in Washington, Oregon, and California can benefit from ecological restoration as a way to adapt forests to climate change and reduce smoke impacts on affected communities. RECENT FINDINGS: Each wildfire season, large smoke events, and their adverse impacts on human health receive considerable attention from both the public and policymakers. The severity of recent wildfire seasons has state and federal governments outlining budgets and prioritizing policies to combat the worsening crisis. This surging attention provides an opportunity to outline the actions needed now to advance research and practice on conservation, economic, environmental justice, and public health interests, as well as the trade-offs that must be considered. Scientists, planners, foresters and fire managers, fire safety, air quality, and public health practitioners must collaboratively work together. This article is the result of a series of transdisciplinary conversations to find common ground and subsequently provide a holistic view of how forest and fire management intersect with human health through the impacts of smoke and articulate the need for an integrated approach to both planning and practice.
The increasing prevalence and severity of wildfire events around the world have emphasized the importance of wildfire resiliency in indoor environmental design. This study focuses on developing wildfire-resilient me-chanical ventilation systems and ventilation strategies for application in single-detached residences in western Canada. Outdoor PM2.5 concentration datasets during wildfire conditions were used in conjunction with indoor air quality (IAQ) mathematical models to assess the impact of ventilation and building-related input variables on indoor PM2.5 levels. A cost-benefit analysis was conducted to compare the cost of ventilation retrofit options with regional estimates of reasonable monetary contributions per resident towards health risk mitigation. Ventilation retrofit options were recommended based on IAQ simulations, model sensitivity, and cost-benefit analysis results. It was recommended that residential ventilation systems increase the minimum filter effi-ciency from MERV6 to MERV11 or MERV13 during wildfire operation and implement higher recirculation ratios during peak exposure scenarios. Multi-filter mechanical ventilation system configurations were recommended for residential dwellings located in regions prone to severe PM2.5 exposure. This study provides insight into the integration of wildfire-resiliency in existing residential mechanical ventilation systems for indoor air quality improvement. This work sets the foundation for future experimental verification of the performance of venti-lation strategies to improve urban safety, health and wellness in wildfire conditions.
As global warming intensifies, hot extremes and heavy precipitation frequently happen in East of China. Meanwhile, severe surface ozone (O-3) pollution resulting from the interactions of anthropogenic emissions and meteorological conditions also occur more frequently. In this study, we quantified the impact of weather extremes on ground-level O-3 concentration during the summers of 2015-2021 and associated premature deaths in East of China. The O-3 pollution influenced by hot extremes [maximum 8-h average O-3 concentration (MDA8 O-3) = 152.7 mu g m(-3)] was 64.2% more severe than that associated with heavy rain (MDA8 O-3 = 93 mu g m(-3)) on the daily time scale. The compound hot and dry air extremes had a larger impact, and the associated MDA8 O-3 could be up to 165.5 mu g m(-3). Thus, weather extremes could drastically perturb the O-3 level in the air to exhibit large variability. Based on GEOS-Chem simulations with fixed anthropogenic emissions, forcing of weather extremes could successfully reproduce the large daily variability of O-3 concentration because the weather extremes significantly influenced the physicochemical processes in the atmosphere. Furthermore, hot extremes magnified the single-day O-3-related premature death to 153% of that under other-condition events, while heavy rain events decreased it to 70% in East of China. The findings of the present study have the potential to promote daily to weekly O-3 forecasts and further improve our comprehensive understanding of the health effects of weather extremes and air pollution.
BACKGROUND: Extreme, prolonged wildfire smoke (WFS) events are becoming increasingly frequent phenomena across the Western United States. Rural communities, dependent on contributions of nature to people’s quality of life, are particularly hard hit. While prior research has explored the physical health impacts of WFS exposure, little work has been done to assess WFS impacts on mental health and wellbeing, or potential adaptation solutions. METHODS: Using qualitative methods, we explore the mental health and wellbeing impacts experienced by community members in a rural Washington State community that has been particularly hard hit by WFS in recent years, as well as individual, family, and community adaptation solutions. We conducted focus groups with residents and key informant interviews with local health and social service providers. RESULTS: Participants identified a variety of negative mental health and wellbeing impacts of WFS events, including heightened anxiety, depression, isolation, and a lack of motivation, as well as physical health impacts (e.g., respiratory issues and lack of exercise). Both positive and negative economic and social impacts, as well as temporary or permanent relocation impacts, were also described. The impacts were not equitably distributed; differential experiences based on income level, outdoor occupations, age (child or elderly), preexisting health conditions, housing status, and social isolation were described as making some residents more vulnerable to WFS-induced physical and mental health and wellbeing challenges than others. Proposed solutions included stress reduction (e.g., meditation and relaxation lessons), increased distribution of air filters, development of community clean air spaces, enhancing community response capacity, hosting social gatherings, increasing education, expanding and coordination risk communications, and identifying opportunities for volunteering. Findings were incorporated into a pamphlet for community distribution. We present a template version herein for adaptation and use in other communities. CONCLUSIONS: Wildfire smoke events present significant mental health and wellbeing impacts for rural communities. Community-led solutions that promote stress reduction, physical protection, and community cohesion have the opportunity to bolster resilience amid this growing public health crisis.
BACKGROUND: The associations between viral etiology of acute respiratory infections (ARI) with meteorological factors and air pollutants among children is not fully understood. This study aimed to explore the viral etiology among children hospitalized for ARI and the association of meteorological factors and air pollutants with children hospitalization due to viral ARI. METHODS: Electronic health record data about children (aged between 1 month and 14 years) admitted for ARI at Kiang Wu Hospital in Macao between 2014 and 2017 was analyzed retrospectively. xMAP multiplex assays were used to detect viruses in the nasopharyngeal swab and distributed-lag nonlinear model (DLNM) was used to evaluate associations. RESULTS: Among the 4880 cases of children hospitalization due to ARI, 3767 (77.2%) were tested positive for at least one virus and 676 (18%) exhibited multiple infections. Enterovirus (EV)/rhinovirus (HRV), adenovirus (ADV), respiratory syncytial virus (RSV) and influenza virus (IFV) were the most common viral pathogens associated with ARI and human bocavirus (hBOV) exhibited the highest multiple infection rates. Meteorological factors and air pollutants (PM(10), PM(2.5) and NO(2)) were associated with the risk of viral ARI hospitalization. The relative risk of viral infection increased with daily mean temperature but plateaued when temperature exceeded 23 °C, and increased when the relative humidity was < 70% and peaked at 50%. The effect of solar radiation was insignificant. Air pollutants (including PM(10), PM(2.5,) NO(2) and O(3)) showed strong and immediate effect on the incidence of viral infection. CONCLUSIONS: The effects of mean temperature, relative humidity and air pollutants should be taken into account when considering management of ARI among children.
Air pollution is a major threat to human health in India. More than three-quarters of the people in India are exposed to pollution levels higher than the limits recommended by the National Ambient Air Quality Standards in India and significantly higher than those recommended by the World Health Organization. Despite the poor air quality, the monitoring of air pollution levels is limited even in large urban areas in India and virtually absent in small towns and rural areas. The lack of data results in a minimal understanding of spatial and temporal patterns of air pollutants at local and regional levels. This paper is the second in a planned series of papers presenting particulate air pollution trends monitored in small cities and towns in India. The findings presented here are important for framing state and regional level policies for addressing air pollution problems in urban areas, and achieve the sustainable development goals (SDGs) linked to public health, reduction in the adverse environmental impact of cities, and adaptation to climate change, as indicated by SDGs 3.9, 11.6 and 11.b.
The Getis-Ord G(i)* statistic clustering technique was used to create a hot spot exposure map using 14 potentially toxic elements (PTEs) found in urban dust samples in a semiarid city in northwest Mexico. The dust distribution and deposition in this city are influenced by the seasonal wind and rain from the North American Monsoon. The spatial clustering patterns of hot spots were used in combination with a sensitivity analysis to determine which variables most influenced the PTE hot spot exposure base map. The hot spots areas (%) were used as indicators of environmental vulnerability, and a final integrated map was selected to represent the highest vulnerability of PTEs with a 99% level of confidence. The results of the sensitivity analysis indicated that the flood zones and pervious and impervious zones were the most sensitive variables due to their weight in the spatial distribution. The hot spot areas were reduced by 60.4% by not considering these variables. The hot spot analysis resulted in an effective tool that allowed the combination of different spatial layers with specific characteristics to determine areas that present greater vulnerability to the distribution of PTEs, with impacts on public and environmental health.
High ground-level ozone concentrations and high air temperatures present two health-relevant natural hazards. The most severe health outcomes are generally associated with concurrent elevated levels of both variables, representing so-called compound ozone and temperature (o-t-) events. These o-t-events, their relationship with identified main meteorological and synoptic drivers, as well as ozone and temperature levels themselves and the linkage between both variables, vary temporally and with the location of sites. Due to the serious health burden and its spatiotemporal variations, the analysis of o-t-events across the European domain represents the focus of the current work. The main objective is to model and project present and future o-t-events, taking region-specific differences into account. Thus, a division of the European domain into six o-t-regions with homogeneous, similar ground-level ozone and temperature characteristics and patterns built the basis of the study. In order to assess region-specific main meteorological and synoptic drivers of o-t-events, statistical downscaling models were developed for selected representative stations per o-t-region. Statistical climate change projections for all central European o-t-regions were generated to assess potential frequency shifts of o-t-events until the end of the 21st century. The output of eight Earth System Models from the sixth phase of the Coupled Model Intercomparison Project considering SSP245 and SSP370 scenario assumptions was applied. By comparing midcentury (2041-2060) and late century (2081-2100) time slice differences with respect to a historical base period (1995-2014), substantial increases of the health-relevant compound o-t-events were projected across all central European regions.
Widespread population exposure to wildland fire smoke underscores the urgent need for new techniques to characterize fire-derived pollution for epidemiologic studies and to build climate-resilient communities especially for aging populations. Using atmospheric chemical transport modeling, we examined air quality with and without wildland fire smoke PM(2.5). In 12-km gridded output, the 24-hour average concentration of all-source PM(2.5) in California (2007-2018) was 5.16 μg/m(3) (S.D. 4.66 μg/m(3)). The average concentration of fire-PM(2.5) in California by year was 1.61 μg/m(3) (~30% of total PM(2.5)). The contribution of fire-source PM(2.5) ranged from 6.8% to 49%. We define a “smokewave” as two or more consecutive days with modeled levels above 35 μg/m(3). Based on model-derived fire-PM(2.5), 99.5% of California’s population lived in a county that experienced at least one smokewave from 2007 to 2018, yet understanding of the impact of smoke on the health of aging populations is limited. Approximately 2.7 million (56%) of California residents aged 65+ years lived in counties representing the top 3 quartiles of fire-PM(2.5) concentrations (2007-2018). For each year (2007-2018), grid cells containing skilled nursing facilities had significantly higher mean concentrations of all-source PM(2.5) than cells without those facilities, but they also had generally lower mean concentrations of wildland fire-specific PM(2.5). Compared to rural monitors in California, model predictions of wildland fire impacts on daily average PM(2.5) carbon (organic and elemental) performed well most years but tended to overestimate wildland fire impacts for high-fire years. The modeling system isolated wildland fire PM(2.5) from other sources at monitored and unmonitored locations, which is important for understanding exposures for aging population in health studies.
An accurate carbon emissions map is of great significance for urban planning to reduce carbon emissions, mitigate the heat island effect, and avoid the impact of high temperatures on human health. However, little research has focused on carbon emissions maps at the land patch level, which makes poor integration with small and medium-sized urban planning based on land patches. In this study, a vectorization method for spatial allocation of carbon emissions at the land patch level was proposed. The vector maps and spatial autocorrelation of carbon emissions in Zhangdian City, China were explored using multi-source data. In addition, the differences between different streets were analyzed, and the carbon emissions ratio of the land patch was compared. The results show that the vector carbon emissions map can help identify the key carbon reduction land patches and the impact factors of carbon emissions. The vector maps of Zhangdian City show that in 2021, the total carbon emissions and carbon absorptions were 4.76 × 10(9)kg and 4.28 × 10(6)kg respectively. Among them, industrial land accounted for 70.16% of carbon emissions, mainly concentrated in three industrial towns. Forest land carbon absorption accounted for 98.56%, mainly concentrated in the peripheral streets away from urban areas. The Moran’s I of land patch level carbon emissions was 0.138, showing a significant positive spatial correlation. The proportion of land patches is an important factor in determining carbon emissions, and the adjustment of industrial structure is the most critical factor in reducing carbon emissions. The results achieved can better help governments develop different carbon reduction strategies, mitigate the heat island effect, and support low-carbon and health-oriented urban planning.
High concentration levels of air pollutants may cause damage to plants, animals, and the health of some groups of human beings. Therefore, it is important to investigate different topics related to the high air pollution levels and to find reliable answers to the questions about the possible damages, which might take place when these levels exceed some limits. A few of the numerous questions, the answers of which are highly desirable, are listed below: (a) When are the air pollution levels dangerous? (b) What is the reason for the increased air pollution levels? (c) How can the air pollution levels be decreased? (d) Will the future climate changes result in higher and more dangerous air pollution levels? It is necessary to study carefully many issues connected with the distribution of air pollutants in a given region and with the reasons for the increases of the concentrations to high levels, which might be damaging. In order to do this, it is necessary to develop a Digital Twin of all relevant physical processes in the atmosphere and to use after that this tool in different applications. Such a tool, its name is DIGITAL AIR, has been created. Digital Twins are becoming more and more popular). Many complex problems, arising taking place in very complicated surroundings, can be handled and resolved successfully by applying Digital Twins. The preparation of such a digital tool as well as its practical implementation in the treatment of a special problem, the increase of some potentially dangerous ozone levels, will be discussed and tested in this paper. The Unified Danish Eulerian Model (UNI-DEM) is a very important part of DIGITAL AIR. This mathematical model, UNI-DEM, can be applied in many different studies related to damaging effects caused by high air pollution levels. We shall use it in this paper to get a reliable answer to a very special but extremely important question: will the future climatic changes lead to an increase in the ozone pollution levels in Bulgaria and Europe, which can potentially become dangerous for human health?
Wildfires cause elevated air pollution that can be detrimental to human health. However, health impact assessments associated with emissions from wildfire events are subject to uncertainty arising from different sources. Here, we quantify and compare major uncertainties in mortality and morbidity outcomes of exposure to fine particulate matter (PM(2.5)) pollution estimated for a series of wildfires in the Southeastern U.S. We present an approach to compare uncertainty in estimated health impacts specifically due to two driving factors, wildfire-related smoke PM(2.5) fields and variability in concentration-response parameters from epidemiologic studies of ambient and smoke PM(2.5). This analysis, focused on the 2016 Southeastern wildfires, suggests that emissions from these fires had public health consequences in North Carolina. Using several methods based on publicly available monitor data and atmospheric models to represent wildfire-attributable PM(2.5), we estimate impacts on several health outcomes and quantify associated uncertainty. Multiple concentration-response parameters derived from studies of ambient and wildfire-specific PM(2.5) are used to assess health-related uncertainty. Results show large variability and uncertainty in wildfire impact estimates, with comparable uncertainties due to the smoke pollution fields and health response parameters for some outcomes, but substantially larger health-related uncertainty for several outcomes. Consideration of these uncertainties can support efforts to improve estimates of wildfire impacts and inform fire-related decision-making.
SignificanceRecord-setting fires in the western United States over the last decade caused severe air pollution, loss of human life, and property damage. Enhanced drought and increased biomass in a warmer climate may fuel larger and more frequent wildfires in the coming decades. Applying an empirical statistical model to fires projected by Earth System Models including climate-ecosystem-socioeconomic interactions, we show that fine particulate pollution over the US Pacific Northwest could double to triple during late summer to fall by the late 21st century under intermediate- and low-mitigation scenarios. The historic fires and resulting pollution extremes of 2017-2020 could occur every 3 to 5 y under 21st-century climate change, posing challenges for air quality management and threatening public health.
In Australia, tropospheric ozone measurements in rural locations are scarce with measurements mostly made in cities. This limits the ability to estimate background ozone levels that inform policy development. The few studies that have assessed rural ozone in Australia have been associated with short campaign monitoring or specific, short-term research programs. Recognising this deficit of information, the New South Wales Government has established long-term ozone monitoring at two rural locations. This paper presents results from the first three years of monitoring at Gunnedah. We assess seasonal, diurnal and sectoral patterns of ozone. Several events are analysed, including high ozone associated with the 2019/20 Australian Bushfire Emergency and an extreme heatwave event. We find that ozone levels at Gunnedah exceed the screening standards set by Australia’s National Environmental Protection (Ambient Air Quality) Measure, emphasising the need for additional ozone monitoring in rural and regional Australia. Our early results indicate that in NSW, background ozone mixing ratios for airmasses of continental origin is likely in the range of 36-39 ppb, higher than the 14-30 ppb associated with air masses of marine origin and greater than the 30 ppb background mixing ratio used for monitoring design and standard setting in Australia. Maximum 8-hourly ozone in non-bushfire impacted events is as high as 64 ppb, demonstrating the challenges that rural/regional communities may face in always meeting the new Australian 8-h ozone standard of 65 ppb. These results add to our understanding of rural background ozone within Australia and in the southern hemisphere.
OBJECTIVES: Dry powder inhalers (DPIs) and soft mist inhalers have a substantially lower global warming potential than pressurised metered-dose inhalers (pMDIs). To help mitigate climate change, we assessed the potential emission reduction in CO(2) equivalents when replacing pMDIs by non-propellant inhalers (NPIs) in Dutch respiratory healthcare and estimated the associated cost. DESIGN: We performed a descriptive analysis of prescription data from two national databases of two independent governmental bodies. First, we calculated the number of patients with chronic obstructive pulmonary disease (COPD) and asthma that were using inhalation medication (2020). Second, we calculated the number and total of daily defined doses of pMDIs and NPIs including DPIs and soft mist inhalers, as well as the number of dispensed spacers per patient (2020). Third, we estimated the potential emission reduction in CO(2) equivalents if 70% of patients would switch from using pMDIs to using NPIs. Fourth, we performed a budget impact analysis. SETTING: Dutch respiratory healthcare. PRIMARY AND SECONDARY OUTCOME MEASURES: The carbon footprint of current inhalation medication and the environmental and financial impact of replacing pMDIs with NPIs. RESULTS: In 2020, 1.4 million patients used inhalers for COPD or asthma treatment. A total of 364 million defined daily doses from inhalers were dispensed of which 49.6% were dispensed through pMDIs. We estimated that this could be reduced by 70% which would lead to an annual reduction in greenhouse gas emission of 63 million kg.CO2 equivalents saving at best EUR 49.1 million per year. CONCLUSIONS: In the Netherlands, substitution of pMDIs to NPIs for eligible patients is theoretically safe and in accordance with medical guidelines, while reducing greenhouse gas emission by 63 million kg.CO2 equivalents on average and saving at best EUR 49.1 million per year. This study confirms the potential climate and economic benefit of delivering a more eco-friendly respiratory care.
Ozone pollution that threatens human health and the ecosystem is a global environmental challenge. In megacities, ozone pollution has long been mainly attributed to anthropogenic sources. However, the processes and mechanisms of cross-regional transport of ozone and its precursors under interactions between mixed sources remain unclear. Here, we show that Northwest Pacific typhoons could intensify the chemical interactions between anthropogenic and biogenic emissions, resulting in extreme ozone pollution in two main city clusters in China. By integrating field and satellite observations together with model simulations, we show that biogenic emission and cross-regional ozone transport are greatly enhanced by approaching typhoons, with the increments reaching up to 78.0 and 22.5%, respectively. Ozone formation efficiency has more than doubled because of abundant precursors and active photochemistry. This study highlights the importance of natural emissions in areas with intensive human activity, which needs to be considered in future air pollution control in China.
Biodiesel is created through the transesterification of fats/oils and its usage is increasing worldwide as global warming concerns increase. Biodiesel fuel properties change depending on the feedstock used to create it. The aim of this study was to assess the different toxicological properties of biodiesel exhausts created from different feedstocks using a complex 3D air-liquid interface (ALI) model that mimics the human airway. Primary human airway epithelial cells were grown at ALI until full differentiation was achieved. Cells were then exposed to 1/20 diluted exhaust from an engine running on Diesel (ULSD), pure or 20% blended Canola biodiesel and pure or 20% blended Tallow biodiesel, or Air for control. Exhaust was analysed for various physio-chemical properties and 24-h after exposure, ALI cultures were assessed for permeability, protein release and mediator response. All measured exhaust components were within industry safety standards. ULSD contained the highest concentrations of various combustion gases. We found no differences in terms of particle characteristics for any of the tested exhausts, likely due to the high dilution used. Exposure to Tallow B100 and B20 induced increased permeability in the ALI culture and the greatest increase in mediator response in both the apical and basal compartments. In contrast, Canola B100 and B20 did not impact permeability and induced the smallest mediator response. All exhausts but Canola B20 induced increased protein release, indicating epithelial damage. Despite the concentrations of all exhausts used in this study meeting industry safety regulations, we found significant toxic effects. Tallow biodiesel was found to be the most toxic of the tested fuels and Canola the least, both for blended and pure biodiesel fuels. This suggests that the feedstock biodiesel is made from is crucial for the resulting health effects of exhaust exposure, even when not comprising the majority of fuel composition.
BACKGROUND: Previous research has shown an association between individual thunderstorm events in the presence of high pollen, commonly called thunderstorm asthma, and acute severe asthma events, but little work has studied risk over long periods of time, using detailed measurements of storms and pollen. METHODS: We estimated change in the risk of asthma-related emergency room visits related to thunderstorm asthma events in the Minneapolis-St. Paul metropolitan area over the years 2007-2018. We defined thunderstorm asthma events as daily occurrence of two or more lightning strikes during high pollen periods interpolating weather and pollen monitor data and modeling lightning counts. We acquired daily counts of asthma-related emergency department visits from the Minnesota Hospital Association and used a quasi-Poisson time-series regression to estimate overall relative risk of emergency department visits during thunderstorm asthma events. RESULTS: We observed a 1.047 times higher risk (95% confidence interval = 1.012, 1.083) of asthma-related emergency department visits on the day of thunderstorm asthma event. Our findings are robust to adjustment for temperature, humidity, wind, precipitation, ozone, PM 2.5 , day of week, and seasonal variation in asthma cases. Occurrence of lightning alone or pollen alone showed no association with the risk of severe asthma. A two-stage analysis combining individual zip code-level results shows similar RR, and we see no evidence of spatial correlation or spatial heterogeneity of effect. DISCUSSION: Our results support an association between co-occurrence of lightning and pollen and risk of severe asthma events. Our approach incorporates lightning and pollen data and small-spatial area exposure and outcome counts.
Current studies on air pollutant exposure during pregnancy and orofacial clefts (OFCs) have inconsistent results, and few studies have investigated refined susceptible windows for OFCs. We aim to estimate association between air pollution and OFCs during the first trimester of pregnancy and identify specific susceptible windows. Birth data was obtained from Birth Defects Surveillance Network in Lanzhou from 2014 to 2019. Air pollution data and temperature data were obtained from ambient air monitoring stations and China Meteorological Data Network, respectively. A distribution lag nonlinear model (DLNM) was applied to estimate weekly-exposure-lag-response association between air pollutant levels and OFCs. The study included 320,787 perinatal infants from 2014 to 2019, of which 685 (2.14‰) were OFCs. The results demonstrated that exposure of pregnant women to aerodynamic diameter ≤ 10 μm (PM(10)) at lag 4-5 weeks was significantly associated with the risk of OFCs, with the greatest impact at the lag 4 week (RR = 1.029, 95% CI = 1.001-1.057). Exposure to sulfur dioxide (SO(2)) at lag 2-4 weeks was significantly associated with the risk of OFCs, with the greatest impact at the lag 3 week (RR = 1.096, 95% CI = 1.041-1.177). This study provides further evidence that exposure to air pollution increases the risk of OFCs in the first trimester of pregnancy.
Pollen allergy has already been an increasingly prominent ecosystem disservice in tourism attractions. However, few studies have assessed the tourist risk of pollen allergy through integrating multidisciplinary knowledge of ecology, medicine, phenology, and risk management. Basing on the conceptual framework of risk assessment proposed by UNISDR, we first established an index system of pollen-allergy risk for tourists in attractions and outlined assessment methods 18 available indexes were put forward to cover three aspects: hazard of plant allergen, tourist vulnerability, and resilience of assessment units. Subsequently, taking the Summer Palace as the case study area, we conducted a tourist risk assessment of pollen allergy. Values of nine available indexes were obtained via ecological investigation, phenological observation, and data mining of visitors’ logs on Sina Weibo. Risk levels of spring pollen allergy for tourists in different assessment units were revealed by combining the green zone allergenicity index model and three-dimensional risk assessment matrix. The results showed that: (1) There were seven primary pollen-allergenic plants in the Summer Palace, including Platycladus orientalis, Sabina chinensis, Salix babylonica, Pinus tabulaeformis, Populus tomentosa Carr, Morus alba L. and Fraxinus chinesis, among which Platycladus orientalis and Salix babylonica were the highest allergenic. (2) Among 18 spots, tourists faced the highest risk level of pollen allergy in spring at three spots, namely the Hall of Serenity, Hall of Benevolence and Longevity, and Gallery of Literary and Prosperity. (3) The two routes of the Long Corridor and Longevity Hill scored high on the risk level. (4) Among four areas, risk levels of the Front-hill and Rear-hill areas were high. Given the increasing spatial-temporal uncertainty of pollen allergy and tourist behaviors under global warming and urbanization, the related monitoring should be strengthened in the future. Furthermore, the dynamic and improved assessment of pollen-allergy risk should be institutionalized and be integrated into the evaluation of tourism experience quality. Tourism administration should make full use of relevant assessment results and conduct more effective risk communication.
Environmental issues such as environmental pollutions and climate change are the impacts of globalization and become debatable issues among academics and industry key players. One of the environmental issues which is air pollution has been catching attention among industrialists, researchers, and communities around the world. However, it has always neglected until the impacts on human health become worse, and at times, irreversible. Human exposure to air pollutant such as particulate matters, sulfur dioxide, ozone and carbon monoxide contributed to adverse health hazards which result in respiratory diseases, cardiorespiratory diseases, cancers, and worst, can lead to death. This has led to a spike increase of hospitalization and emergency department visits especially at areas with worse pollution cases that seriously impacting human life and health. To address this alarming issue, a predictive model of air pollution is crucial in assessing the impacts of health due to air pollution. It is also critical in predicting the air quality index when assessing the risk contributed by air pollutant exposure. Hence, this systemic review explores the existing studies on anticipating air quality impact to human health using the advancement of Artificial Intelligence (AI). From the extensive review, we highlighted research gaps in this field that are worth to inquire. Our study proposes to develop an AI-based integrated environmental and health impact assessment system using federated learning. This is specifically aims to identify the association of health impact and pollution based on socio-economic activities and predict the Air Quality Index (AQI) for impact assessment. The output of the system will be utilized for hospitals and healthcare services management and planning. The proposed solution is expected to accommodate the needs of the critical and prioritization of sensitive group of publics during pollution seasons. Our finding will bring positive impacts to the society in terms of improved healthcare services quality, environmental and health sustainability. The findings are beneficial to local authorities either in healthcare or environmental monitoring institutions especially in the developing countries.
Background: The global burden of acute lower respiratory infection (ALRI) attributable to air pollution has increased in recent years, but the association between ALRI and exposure to size-specific particulate matter has not been investigated using different exposure metrics. Methods: We obtained ALRI admission from seven cities from 2014 to 2016 in China. Different sized particles were measured using three metrics (a) daily mean, (b) hourly peak, and (c) daily excessive concentration hours (DECH). Generalized additive models were fitted for each of the seven cities, and the city-specific estimates were then pooled using random-effects meta-analysis models. Stratified analyses were conducted to examine the effect modifications of gender, age, and season. We also estimated the disease burden due to particulate matter exposures. Results: There were 111,426 ALRI (79,803 pneumonia and 31,622 bronchiolitis) hospital admissions under the age of 15 between 2014 and 2016 in our study. Daily means were associated with the largest ALRI estimates (95% confidence interval [CI]): 2.43% (0.79%, 4.11%) for PM2.5, 2.25% (0.11%, 4.44%) for PMc, and 2.64% (0.73%, 4.58%) for PM10. The magnitude of effect sizes were followed by DECH: 1.94% (0.51%, 3.39%) for PM2.5, 0.88% (-0.14%, 1.92%) for PMc, 1.86% (0.50%, 2.01%) for PM10; and hourly peak: 0.70% (-0.60%, 2.01%) for PM2.5, 1.05% (-0.13%, 2.66%) for PMc, and 1.20% (-0.20%, 2.62%) for PM10 at lag03. We found significantly higher effects in cold seasons than that in warm seasons, while we did not find a significant different between gender and age groups. Conclusions: The adverse effects of exposure to particulate matter on ALRI hospitalizations are reconfirmed. DECH was a possible alternative exposure indicator for PM2.5 assessment, which may affect air quality standards in the future. (C) 2021 Published by Elsevier B.V.
Purpose of Review The increase in wildfire prevalence and severity has generated alarm as wildfire air pollution is associated with significant respiratory morbidity. We aim to summarize the pathophysiology of wildfire air pollution causing lung disease, current knowledge of pulmonary health effects, and precautionary guidance to the public. We also propose specific guidance for high-risk patients during wildfires. Recent Findings Health effects of wildfire air pollution have been difficult to evaluate; however, respiratory morbidity has been firmly established including exacerbation of known pulmonary disease and increased hospitalizations, emergency department visits, and dispensation of reliever medications. Public health agencies and officials provide wildfire preparation recommendations and active updates to the public during a wildfire event but fail to address specific needs of chronic lung disease patients considered high-risk for pulmonary complications. To fill this void, it is increasingly important for pulmonary physicians to understand wildfire-related pulmonary morbidity and provide specific guidance to their patients. This review summarizes the health effects of wildfire air pollution and provides guidance for the management of high-risk patients during wildfires.
Epidemic asthma events represent a significant risk to emergency services as well as the wider community. In southeastern Australia, these events occur in conjunction with relatively high amounts of grass pollen during the late spring and early summer, which may become concentrated in populated areas through atmospheric convergence caused by a number of physical mechanisms including thunderstorm outflow. Thunderstorm forecasts are therefore important for identifying epidemic asthma risk factors. However, the representation of thunderstorm environments using regional numerical weather prediction models, which are a key aspect of the construction of these forecasts, have not yet been systematically evaluated in the context of epidemic asthma events. Here, we evaluate diagnostics of thunderstorm environments from historical simulations of weather conditions in the vicinity of Melbourne, Australia, in relation to the identification of epidemic asthma cases based on hospital data from a set of controls. Skillful identification of epidemic asthma cases is achieved using a thunderstorm diagnostic that describes near-surface water vapor mixing ratio. This diagnostic is then used to gain insights on the variability of meteorological environments related to epidemic asthma in this region, including diurnal variations, long-term trends, and the relationship with large-scale climate drivers. Results suggest that there has been a long-term increase in days with high water vapor mixing ratio during the grass pollen season, with large-scale climate drivers having a limited influence on these conditions.
The impact of suspended particles in the urban air on the health of different groups of the population of Tomsk, Russia, is studied. It is shown that women are generally most susceptible to the adverse effects of aerosol air pollution and extreme (high summer and low winter) air temperatures. Women at age of 65-74 are the most vulnerable to the environment hazards. The age-and-sex matched analysis of mortality allows us to determined groups of population (age, causes of death) the most susceptible to high aerosol concentrations and extreme air temperatures: women aged 65-74, cancer of the digestive system, breast cancer, and acute myocardial infarction; women aged 34-50, undetermined causes; women aged 75-87, breast-pang; men aged 53-65, other forms of coronary artery disease; men 78+, male reproductive organ cancer. The general mortality of the population is shown to be mainly due factors not studied in this work. However, the risk of the negative impact of air pollution is significant for the selected groups of population in the region under study.
Summertime ozone (O(3)) pollution has frequently occurred in the Beijing-Tianjin-Hebei (BTH) region, China, since 2013, resulting in detrimental impacts on human health and ecosystems. The contribution of weather shifts to O(3) concentration variability owing to climate change remains elusive. By combining regional air chemistry model simulations with near-surface observations, we found that anthropogenic emission changes contributed to approximately 23% of the increase in maximum daily 8-h average O(3) concentrations in the BTH region in June-July-August (JJA) 2017 (compared with that in 2013). With respect to the weather shift influence, the frequencies, durations, and magnitudes of O(3) exceedance were consistent with those of the heat wave events in the BTH region during JJA in 2013-2017. Intensified heat waves are a significant driver for worsening O(3) pollution. In particular, the prolonged duration of heat waves creates consecutive adverse weather conditions that cause O(3) accumulation and severe O(3) pollution. Our results suggest that the variability in extreme summer heat is closely related to the occurrence of high O(3) concentrations, which is a significant driver of deteriorating O(3) pollution.
BACKGROUND: Smoke from wildfires is a growing public health risk due to the enormous amount of smoke-related pollution that is produced and can travel thousands of kilometers from its source. While many studies have documented the physical health harms of wildfire smoke, less is known about the effects on mental health and well-being. Understanding the effects of wildfire smoke on mental health and well-being is crucial as the world enters a time in which wildfire smoke events become more frequent and severe. We conducted a scoping review of the existing information on wildfire smoke’s impact on mental health and well-being and developed a model for understanding the pathways in which wildfire smoke may contribute to mental health distress. METHODS: We conducted searches using PubMed, Medline, Embase, Google, Scopus, and ProQuest for 1990-2022. These searches yielded 200 articles. Sixteen publications met inclusion criteria following screening and eligibility assessment. Three more publications from the bibliographies of these articles were included for a total of 19 publications. RESULTS: Our review suggests that exposure to wildfire smoke may have mental health impacts, particularly in episodes of chronic and persistent smoke events, but the evidence is inconsistent and limited. Qualitative studies disclose a wider range of impacts across multiple mental health and well-being domains. The potential pathways connecting wildfire smoke with mental health and well-being operate at multiple interacting levels including individual, social and community networks, living and working conditions, and ecological levels. CONCLUSIONS: Priorities for future research include: 1) applying more rigorous methods; 2) differentiating between mental illness and emotional well-being; 3) studying chronic, persistent or repeated smoke events; 4) identifying the contextual factors that set the stage for mental health and well-being effects, and 5) identifying the causal processes that link wildfire smoke to mental health and well-being effects. The pathways model can serve as a basis for further research and knowledge synthesis on this topic. Also, it helps public health, community mental health, and emergency management practitioners mitigate the mental health and well-being harms of wildfire smoke.
The influence of temperature on childhood asthma was self-evident, yet the issue of whether the relationship will be synergized by air pollution remains unclear. The study aimed to investigate whether the relationship between short-term temperature exposure and childhood asthma hospitalization was modified by particulate matter (PM). Data on childhood asthma hospitalization, meteorological factors, and air pollutants during 2013-2016 in Hefei, China, were collected. First, a basic Poisson regression model combined with a distributed lag nonlinear model was used to assess the temperature-childhood asthma hospitalization relationship. Then, two interactive strategies were applied to explore the modification effect of PM on the temperature-childhood asthma hospitalization association. We found a greater effect of cold (5th percentile of temperature) on asthma during days with higher PM(2.5) (RR: 2.16, 95% CI: 1.38, 3.38) or PM(10) (RR: 1.87, 95% CI:1.20, 2.91) than that during days with lower PM(2.5) (RR: 1.64, 95% CI: 1.06, 2.54) or PM(10) (RR: 1.52, 95% CI: 0.98, 2.36). In addition, we observed a greater modification effect of PM(2.5) on the cold-asthma association than did PM(10), with a per 10 μg/m(3) increase in PM(2.5) and PM(10) associated with increases of 0.065 and 0.025 for the RR corresponding to the 5th temperature percentile, respectively. For the temperature-related AF, moderate cold showed the largest change magnitude with the PM levels rising compared with other temperature ranges. For the subgroup, Females and those aged 6-18 years were more sensitive to the modification effect of PM(2.5) or PM(10) on the cold-asthma association. Our findings demonstrated that particulate matter could modify the associations between temperature and childhood asthma hospitalization.
PURPOSE OF REVIEW: Several studies have found that air pollution and climate change can have an impact on acute coronary syndromes (ACS), the leading cause of death worldwide. We synthesized the latest information about the impact of air pollution and climate change on ACS, the latest data about the pathophysiological mechanisms of meteorological factors and atmospheric pollutants on atherosclerotic disease, and an overall image of air pollution and coronary heart disease in the context of the COVID-19 pandemic. RECENT FINDINGS: The variation of meteorological factors in different seasons increased the risk of ACS. Both the increase and the decrease in apparent temperature were found to be risk factors for ACS admissions. It was also demonstrated that exposure to high concentrations of air pollutants, especially particulate matter, increased cardiovascular morbidity and mortality. Climate change as well as increased emissions of air pollutants have a major impact on ACS. The industrialization era and the growing population cause a constant increase in air pollution worldwide. Thus, the number of ACS favored by air pollution and the variations in meteorological factors is expected to increase dramatically in the next few years.
BACKGROUND AND AIMS: As average temperatures rise and wildfire events increase in the United States, outdoor workers may be at an increased risk of injury. Recent research suggests that heat exposure increases outdoor workers’ risk of traumatic injuries, but co-exposures of heat and wildfire smoke have not been evaluated. METHODS: Oregon workers’ compensation data from 2009 to 2018 were linked to satellite data by the date of injury to determine if acute heat (maximum Heat Index) and wildfire smoke (presence/absence) were associated with a traumatic injury. North American Industry Classification System (NAICS) codes were utilized to identify accepted, disabling injury claims from construction (NAICS 23) and agriculture, forestry, fishing, and hunting (NAICS 11). Claims from April to October were analyzed using negative binomial models to calculate incident rate ratios (IRR) by heat and wildfire exposure for All workers and specifically for Agricultural (Ag)/Construction workers. RESULTS: During the study period, 91,895 accepted, traumatic injury claims were analyzed. All workers had an injury IRR of 1.04 (95% confidence interval [CI]: 1.02-1.06) while Ag/Construction workers had an IRR of 1.11 (95% CI: 1.06-1.16) when wildfire smoke was present. When the maximum Heat Index was 75°F or greater, the IRR significantly increased as temperatures increased. When the maximum Heat Index was above 80-84°F, All workers had an IRR of 1.04 (95% CI: 1.01-1.06) while Ag/construction workers had an IRR of 1.14 (95% CI: 1.08-1.21) with risk increasing with increased temperatures. In joint models, heat remained associated with injury rates, but not wildfire smoke. No multiplicative interactions between exposures were observed. CONCLUSION: Increasing temperature was associated with increased rates of traumatic injury claims in Oregon that were more pronounced in Ag/Construction workers. Future work should focus on further understanding these associations and effective injury prevention strategies.
Converging global evidence highlights the dire consequences of climate change for human mental health and wellbeing. This paper summarises literature across relevant disciplines to provide a comprehensive narrative review of the multiple pathways through which climate change interacts with mental health and wellbeing. Climate change acts as a risk amplifier by disrupting the conditions known to support good mental health, including socioeconomic, cultural and environmental conditions, and living and working conditions. The disruptive influence of rising global temperatures and extreme weather events, such as experiencing a heatwave or water insecurity, compounds existing stressors experienced by individuals and communities. This has deleterious effects on people’s mental health and is particularly acute for those groups already disadvantaged within and across countries. Awareness and experiences of escalating climate threats and climate inaction can generate understandable psychological distress; though strong emotional responses can also motivate climate action. We highlight opportunities to support individuals and communities to cope with and act on climate change. Consideration of the multiple and interconnected pathways of climate impacts and their influence on mental health determinants must inform evidence-based interventions. Appropriate action that centres climate justice can reduce the current and future mental health burden, while simultaneously improving the conditions that nurture wellbeing and equality. The presented evidence adds further weight to the need for decisive climate action by decision makers across all scales.
OBJECTIVES: Under current global climate conditions, there are insufficient studies on the health influences of cold spells, especially on mental health. This study aimed to examine the effect of cold spells on schizophrenia admissions and to analyze the potential interaction effect with the air quality index (AQI). METHODS: Daily data on schizophrenia admissions and climatic variables in Hefei were collected from 2013 to 2019. Based on 20 definitions, the impacts of cold spells were quantified separately to find the most appropriate definition for the region, and meta-regression was used to explore the different effect sizes of the different days in a cold spell event. In addition, the potential interaction effect was tested by introducing a categorical variable, CSH, reflecting the cold spell and AQI level. RESULTS: The cold spell defined by temperature below the 6th centile while lasting for at least three days produced the optimum model fit performance. In general, the risk of schizophrenia admissions increased on cold spell days. The largest single-day effect occurred on the 12th day with RR = 1.081 (95% CI: 1.044, 1.118). In a single cold spell event, the effect of the 3rd and subsequent days of a cold spell (RR = 1.082, 95% CI: 1.036, 1.130) was higher than that on the 2nd day (RR = 1.054, 95% CI: 1.024, 1.085). Similarly, the effect of the 2nd day was also higher than that of the 1st day (RR = 1.027, 95% CI: 1.012, 1.042). We found a synergistic effect between cold spells and high AQI in the male group, and the relative excess risk due to interaction (RERI) was 0.018 (95% CI: 0.005-0.030). CONCLUSIONS: This study suggested that the impacts of cold spells should be considered based on the definition of the most appropriate for the region when formulating targeted measures of schizophrenia. The discovery of the synergistic effect was referred to help the selection of the timing of precautions for susceptible people.
BACKGROUND: Sustained elevated concentration of GHGs is predicted to increase global mortality. With the Australian health sector responsible for 7% of the nation’s GHG emissions, the benefits and costs of various decarbonisation trajectories are currently being investigated. To assist with this effort, we model the impact earlier decarbonisation has on temperature-related mortality. DESIGN: We used DICE-EMR, an Integrated Assessment Model with an endogenous mortality response, to simulate Australian GHG trajectories and estimate the temperature-related mortality impact of early decarbonisation. We modelled a linear decline of the Australian health sector’s and economy’s GHG annual emissions to net-zero targets of 2040 and 2050. MAIN OUTCOME MEASURE: Deaths averted and monetary-equivalent welfare gain. RESULTS: Decarbonisation of the Australian health sector by 2050 and 2040 is projected to avert an estimated 69,000 and 77,000 global temperature-related deaths respectively in a Baseline global emissions scenario. Australian economy decarbonisation by 2050 and 2040 is projected to avert an estimated 988,000 and 1,101,000 global deaths respectively. Assuming a low discount rate and high global emissions trajectory, we estimate a monetary equivalent welfare gain of $151 billion if the Australian health sector decarbonises by 2040, only accounting for the benefits in reducing temperature-related mortality. CONCLUSIONS: Earlier decarbonisation has a significant impact on temperature-related mortality. Many uncertainties exist and health impacts other than temperature-related mortality are not captured by this analysis. Nevertheless, such models can help communicate the health risk of climate change and improve climate policy decision making.
Excessive greenhouse gas emissions might be the major culprit for environmental degradation, which have direct and indirect adverse impacts in various ways. As the largest emitter of carbon emissions, China suffered great harm from climate change during the past 40 years. Therefore, it becomes necessary to study the impact of carbon emissions on health issues and their potential mechanism. Using the panel data from 30 provinces in China between 2002 and 2017, this study employes and extends the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and mediating effect model to analyze the direct and indirect effects of carbon emissions. The main results are as follows: (1) Carbon emissions has a certain negative impact on public health, which would increase with the rise of temperature. (2) The increase in carbon emissions has a more significant negative effect on health with the average temperature exceeding 17.75 °C, indicating that the temperature has a threshold effect. (3) The potential health risks become higher with the development of urbanization, but there is no obvious spillover effect in the health consequences. The results remain robust after controlling other factors. This study supplements the literature of climate governance and human health, potentially contributing to the next stage of high-quality and sustainable development.
BACKGROUND: Indonesian peatlands have been drained for agricultural development for several decades. This development has made a major contribution to economic development. At the same time, peatland drainage is causing significant air pollution resulting from peatland fires. Peatland fires occur every year, even though their extent is much larger in dry (El Niño) years. We examine the health effects of long-term exposure to fine particles (PM(2.5)) from all types of peatland fires (including the burning of above and below ground biomass) in Sumatra and Kalimantan, where most peatland fires in Indonesia take place. METHODS: We derive PM(2.5) concentrations from satellite imagery calibrated and validated with Indonesian Government data on air pollution, and link increases in these concentrations to peatland fires, as observed in satellite imagery. Subsequently, we apply available epidemiological studies to relate PM(2.5) exposure to a range of health outcomes. The model utilizes the age distribution and disease prevalence of the impacted population. RESULTS: We find that PM(2.5) air pollution from peatland fires, causes, on average, around 33,100 adults and 2900 infants to die prematurely each year from air pollution. In addition, peatland fires cause on average around 4390 additional hospitalizations related to respiratory diseases, 635,000 severe cases of asthma in children, and 8.9 million lost workdays. The majority of these impacts occur in Sumatra because of its much higher population density compared to Kalimantan. A main source of uncertainty is in the Concentration Response Functions (CRFs) that we use, with different CRFs leading to annual premature adult mortality ranging from 19,900 to 64,800 deaths. Currently, the population of both regions is relatively young. With aging of the population over time, vulnerabilities to air pollution and health effects from peatland fires will increase. CONCLUSIONS: Peatland fire health impacts provide a further argument to combat fires in peatlands, and gradually transition to peatland management models that do not require drainage and are therefore not prone to fire risks.
It is of great practical significance to analyze the hot issues, research frontiers, and trends concerning the relationship between air pollution and public health and to adopt reasonable strategies to control air pollution and prevent health hazards for follow-up research in this field. Unlike traditional literature reviews, this paper adopts a visual, flexible, and scientifically systematic approach to the analysis, which makes these analysis results more intuitive and comprehensive. Based on the core collection of the Web of Science and CNKI databases, this paper uses CiteSpace software to draw and comment on the maps of Chinese and English keywords, publishing time, author, country, and research institutions in this field. The results show the following: (1) The number of studies on the relationship between air pollution and health has increased year by year; researchers have formed sub cooperation networks, and the trend of cooperation and exchange has become more and more obvious in recent years; the impact of air pollution on health is a hot topic in the world. (2) Research hot topics mainly focus on the selection of air pollutants, health economic consequences of air pollution and the global burden of disease it causes, health indicators, research samples, which are gradually being refined, the synergistic governance of air pollution, and climate change. (3) The analysis of research frontiers and trends reveals that, first, the study of air pollutants in the English literature has undergone a refinement from nitrogen dioxide to fine particulate matter, and the sources of air pollutants in the Chinese literature have undergone changes in the petrochemical industry, indoor formaldehyde pollution, and haze. Second, atmospheric pollution has a significant negative impact on health, increasing the incidence of respiratory and cardiovascular diseases, and even causing death. Third, sustained exposure to pollution then causes greater damage to health and will be a key direction for future research. Fourth, the literature not only studies the correlation but also emphasizes the causal inference between air pollution and health and measures the economic costs associated with health. Finally, air pollution and climate change need to be governed synergistically. The article points out that the three areas of sustained pollution exposure, indirect consequences of negative health effects of air pollution, and air pollution and climate change may be the future focus of the field.
BACKGROUND: In-utero exposure to particulate matter with aerodynamic diameter less than 2.5 μm (PM(2.5)) is associated with low birth weight and health risks later in life. Pregnant women are mobile and locations they spend time in contribute to their personal PM(2.5) exposures. Therefore, it is important to understand how mobility and exposures encountered within activity spaces contribute to personal PM(2.5) exposures during pregnancy. METHODS: We collected 48-h integrated personal PM(2.5) samples and continuous geolocation (GPS) data for 213 predominantly Hispanic/Latina pregnant women in their 3(rd) trimester in Los Angeles, CA. We also collected questionnaires and modeled outdoor air pollution and meteorology in their residential neighborhood. We calculated three GPS-derived activity space measures of exposure to road networks, greenness (NDVI), parks, traffic volume, walkability, and outdoor PM(2.5) and temperature. We used bivariate analyses to screen variables (GPS-extracted exposures in activity spaces, individual characteristics, and residential neighborhood exposures) based on their relationship with personal, 48-h integrated PM(2.5) concentrations. We then built a generalized linear model to explain the variability in personal PM(2.5) exposure and identify key contributing factors. RESULTS: Indoor PM(2.5) sources, parity, and home ventilation were significantly associated with personal exposure. Activity-space based exposure to roads was associated with significantly higher personal PM(2.5) exposure, while greenness was associated with lower personal PM(2.5) exposure (β = -3.09 μg/m(3) per SD increase in NDVI, p-value = 0.018). The contribution of outdoor PM(2.5) to personal exposure was positive but relatively lower (β = 2.05 μg/m(3) per SD increase, p-value = 0.016) than exposures in activity spaces and the indoor environment. The final model explained 34% of the variability in personal PM(2.5) concentrations. CONCLUSIONS: Our findings highlight the importance of activity spaces and the indoor environment on personal PM(2.5) exposures of pregnant women living in Los Angeles, CA. This work also showcases the multiple, complex factors that contribute to total personal PM(2.5) exposure.
Air pollution (AP) represents one of the main environmental threats to public health and exposure to AP has been connected to upper airway (UA) disease. We evaluated the relationships between the ENT urgent referrals recorded at the Hospital of Padua and the daily levels of particulate matter (PM) as well as other environmental factors in a single year. Patients with UA disorders were included in the study group while those referred for facial trauma or foreign body inhalation formed the control group. Daily PM concentrations, meteorological data and the concentrations of the commonest aeroallergens were obtained. 6368 patients formed the study group and 910 the control one. The concentration of compositae allergens showed a positive effect on the total number of admissions (p = 0.001). PM10 did not demonstrate an effect on the total number of admissions or either the study or control groups admissions (p = 0.25). Alternaria positively influenced admissions of patients in the study group (p = 0.005). Significant relationships were found between the following: PM10 measured on the seventh day before A&E admission and rhinosinusitis (p = 0.007), PM10 on the fifth day and laryngitis (p = 0.01), PM10 on the second day and otitis media (p = 0.03), PM10 on the admission day and epistaxis (p = 0.0198). Our study confirms the causal relationship between aeroallergen concentration and ENT admissions. The levels of PM10 at specific days preceding A&E admission correlated with certain UA disorders. This study strongly points towards the harmful effects of pollution and climate change on UA disease.
Climate change has important implications on human health, affecting almost every system in the body. Multiple studies have raised the possibility of climate change impacting eye health. In this review, we aimed to summarize current literature on the impact of air pollution and climate change on eye health. We performed a search in four different databases, including Medline, Scopus, Cochrane, and Web of Sciences databases. The search strategy combined terms regarding eye health and environmental/climate changes. The outcome of interest included all eye conditions. The search yielded 2,051 unique articles. After applying inclusion and exclusion criteria, 61 articles were included in this systematic review with data covering 2,620,030 participants. Most studies originated from China, India, South Korea, and USA. Climate change adversely affected different eye conditions, with ocular surface diseases (e.g., conjunctivitis and dry eye) being most affected. Moreover, higher particulate matter (PM) was the most widely assessed pollutant and was adversely associated with the majority of eye conditions, increasing the burden on patients and healthcare providers. We found a low frequency of publications related to the delivery of eye care and its impact on climate change in countries with high air pollution and climate change burden.
Rationale: Extremes of heat and particulate air pollution threaten human health and are becoming more frequent because of climate change. Understanding the health impacts of coexposure to extreme heat and air pollution is urgent. Objectives: To estimate the association of acute coexposure to extreme heat and ambient fine particulate matter (PM(2.5)) with all-cause, cardiovascular, and respiratory mortality in California from 2014 to 2019. Methods: We used a case-crossover study design with time-stratified matching using conditional logistic regression to estimate mortality associations with acute coexposures to extreme heat and PM(2.5). For each case day (date of death) and its control days, daily average PM(2.5) and maximum and minimum temperatures were assigned (0- to 3-day lag) on the basis of the decedent’s residence census tract. Measurements and Main Results: All-cause mortality risk increased 6.1% (95% confidence interval [CI], 4.1-8.1) on extreme maximum temperature-only days and 5.0% (95% CI, 3.0-8.0) on extreme PM(2.5)-only days, compared with nonextreme days. Risk increased by 21.0% (95% CI, 6.6-37.3) on days with exposure to both extreme maximum temperature and PM(2.5). Increased risk of cardiovascular and respiratory mortality on extreme coexposure days was 29.9% (95% CI, 3.3-63.3) and 38.0% (95% CI, -12.5 to 117.7), respectively, and were more than the sum of individual effects of extreme temperature and PM(2.5) only. A similar pattern was observed for coexposure to extreme PM(2.5) and minimum temperature. Effect estimates were larger over age 75 years. Conclusions: Short-term exposure to extreme heat and air pollution alone were individually associated with increased risk of mortality, but their coexposure had larger effects beyond the sum of their individual effects.
Fine particulate matter (PM(2.5)) has been reported to be an important risk factor for asthma. This study was designed to evaluate the relationship between PM(2.5) and lung function among children with asthma in Shanghai, China. From 2016 to 2019, a total of 70 Chinese children aged 4 to 14 in Shanghai were recruited for this panel study. The questionnaire was used to collect baseline information, and the lung function covering forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1) and peak expiratory flow (PEF) were carried out for each child more than twice during follow-up. Meanwhile, the simultaneous daily air atmospheric pollutants and meteorological data were collected. The linear mixed effect (LME) model was used to assess the relationship between air pollutants and lung function. A significantly negative association was found between PM(2.5) and lung function in children with asthma. In the single-pollutant model, the largest effects of PM(2.5) on lung function were found for lag 0-2, with FVC and FEV1 decreasing by 0.91% [95% confidence interval (CI): -1.75, -0.07] and 1.05% (95% CI: -2.09, 0.00), respectively, for each 10 μg/m(3) increase in PM(2.5). In the multi-pollution model (adjusted PM(2.5) + SO(2) + O(3)), the maximum effects of PM(2.5) on FVC and FEV1 also appeared for lag 0-2, with FVC and FEV1 decreasing by 1.57% (95% CI: -2.69, -0.44) and 1.67% (95% CI: -3.05, -0.26), respectively, for each 10 μg/m(3) increase in PM(2.5). In the subgroup analysis, boys, preschoolers (<6 years old) and hot seasons (May to September) were more sensitive to changes. Our findings may contribute to a better understanding of the short-term exposure effects of PM(2.5) on lung function in children with asthma.
Purpose This paper aims to explore the ecological efficiency through assessing the relation of the “carbon intensity of well-being” (CIWB) to gender equality, gross domestic product (GDP)/capita, the urban intensity of the population, the age structure of the population, foreign direct investment as a percentage of GDP and manufacturing as a percentage of GDP. Design/methodology/approach CIWB equation is estimated for a panel of 18 MENA economies and Turkey over the period 1995-2018 using the two-way fixed effects Prais-Winsten regression with panel-corrected standard errors. Findings The elasticity coefficients obtained from the estimated models indicated mixed effects on CIWB. While the increase of female educational attainment, accompanied with an increase in the female labor force participation rate, reduce CIWB, the younger female population and the younger population, in general, increase CIWB. Furthermore, while increasing FDI inflows reduces CIWB, increasing the manufacturing share of GDP increases CIWB. Originality/value The pursuit of Sustainable Development Goals worldwide has moved the relevant literature on climate change mitigation and adaptation measures to a new level, where using the CIWB method is increasingly used to reflect carbon dioxide emissions per capita unit of expected lifespan. The present paper’s contribution to the literature is two-fold: one is computing and estimating the CIWB to examine ecological efficiency for the middle east and north africa (MENA) economies and Turkey over the period of study; and two is integrating and validating the beneficial impacts of integrating the gender equality dimension in the CIWB-climate change literature.
BACKGROUND: Few studies have simultaneously examined the effect of long-term exposure to air pollution and ambient temperature on the rate of hospital admissions with cardiovascular and respiratory disease using causal inference methods. METHODS: We used a variation of a difference-in-difference (DID) approach to assess the effects of long-term exposure to warm-season temperature, cold-season temperature, NO(2), O(3), and PM(2.5) on the rate of hospital admissions for cardiovascular disease (CVD), myocardial infarction (MI), ischemic stroke, and respiratory diseases from 2001 to 2016 among Medicare beneficiaries who use fee-for-service programs. We computed the rate of admissions by zip code and year. Covariates included demographic and socioeconomic variables which were obtained from the decennial Census, the American Community Survey, the Behavioral Risk Factor Surveillance System, and the Dartmouth Health Atlas. As a secondary analysis, we restricted the analysis to zip code-years that had exposure to low concentrations of our pollutants. RESULTS: PM(2.5) was associated with a significant increase in the absolute rate of annual admissions with cardiovascular disease by 47.71 admissions (95 % CI: 41.25-56.05) per 100,000 person-years, myocardial infarction by 7.44 admissions (95 % CI: 5.53-9.63) per 100,000 person-years, and 18.58 respiratory admissions (95 % CI: 12.42-23.72) for each one μg/m(3) increase in two-year average levels. O(3) significantly increased the rates of all the studied outcomes. NO(2) was associated with a decreased rate of admissions with MI by 0.83 admissions (95 % CI: 0.10-1.55) per 100,000 person-years but increased rate of admissions for respiratory disease by 3.16 admissions (95 % CI: 1.34-5.24) per 100,000 person-years. Warmer cold-season temperature was associated with a decreased admissions rate for all outcomes. CONCLUSION: Air pollutants, particularly PM(2.5) and O(3), increased the rate of hospital admissions with cardiovascular and respiratory disease among the elderly, while higher cold-season temperatures decreased the rate of admissions with these conditions.
Few data are currently available on the effects of aeroallergens in triggering respiratory symptoms in children. To evaluate the potential effects of daily outdoor aeroallergens loads on childhood admissions, in this case-crossover study, we analyzed data from 85 children hospitalized at the University Hospital of Pisa, Italy, for asthma or asthma-like symptoms without respiratory infection, between 2010 and 2019. Data were linked to outdoor allergens, temperature, nitrogen dioxide, and relative humidity observed during the same period. A 10-grains/m(3) increase in the total aeroallergen concentration was associated with an increased risk of admission at lag 0 (OR = 1.054, 95% CI: 1.011-1.098), with a smaller effect at lag 1 (OR = 1.037, 95% CI: 1.008-1.067) and lag 2 (OR = 1.021, 95% CI: 1.003-1.039). Trends to larger effects were observed in children with sensitization to one or more aeroallergens (OR = 1.085, 95% CI: 1.004-1.173 at lag 0), in males (OR = 1.069, 95% CI: 1.009-1.132 at lag 0) and in older children (OR = 1.065, 95% CI: 1.007-1.127 at lag 0). Our study shows an association between increased outdoor allergens loads and asthma or asthma-like symptoms in children up to at least two days prior to hospitalization, suggesting that tracking aeroallergen counts may be useful to improve the management of respiratory allergic diseases.
Polycyclic aromatic hydrocarbons (PAHs) are formed during incomplete combustion of organic matter, and firefighters are highly exposed to these toxic compounds at fire sites. Exposure to PAHs can cause cognitive decline and neurodegeneration; however, to date, few studies have examined the potential effects of PAH exposure on structural changes in the brain. We aimed to investigate the association between the four types of PAH metabolites and the corresponding changes in neuroimaging markers based on smoking status and hypertension in male firefighters. For this, we utilized the 2-year follow-up data of 301 Korean male firefighters aged over 40 years. The concentrations of four PAH metabolites in urine were measured. Subcortical volume and cortical thickness were estimated using 3 T magnetic resonance imaging of the brain. A generalized linear model was used to investigate the effects of PAHs on changes in the subcortical volume and cortical thickness. We found an association between 1-hydroxyphenathrene (1-OHPHE) and 2-hydroxyfluorene (2-OHF) and changes in several brain regions in all the study participants. Individuals who had never smoked showed significantly thinner frontal (p < 0.001), parietal (p < 0.001), temporal (p < 0.001), and cingulate lobes (p < 0.001) with 1% increase each in the urinary concentration of 1-OHPHE. Hypertension interacted with the concentration of 1-OHPHE to reduce the volume of gray matter and cause cortical thinning in the frontal, parietal, and temporal lobes. Exposure to PAHs may reduce cortical thickness and subcortical volume, which are definitive markers of neurodegeneration. Notably, hypertension can accelerate the degenerative effects of PAHs.
OBJECTIVES: As wildfires and air pollution become more common across the United States, it is increasingly important to understand the burden they place on public health. Previous studies have noted relationships between air quality and use of Emergency Medical Services (EMS), but until now, these studies have focused on day-to-day air quality. The goal of this study is to investigate the effect of sustained periods of poor air quality on EMS call characteristics and volume. METHODS: Using a time-stratified case-crossover design, the effect of exposure to periods of poor air quality on number and type of EMS calls in California, USA from 2014-2019 was observed. Poor air quality periods greater than three days were identified at the United States Environmental Protection Agency’s (EPA’s) Air Quality Index (AQI) levels of Unhealthy for Sensitive Groups (AQI 100) and Unhealthy (AQI 150). Periods less than three days apart were combined. Each poor air quality period was matched with two one-week controls, the first being the closest preceding week that did not intersect a different case. The second control was the closest week at least three days after the case and not intersecting with a different case. Due to seasonal variation in EMS usage, from the initial cases, cases were used only if it was possible to identify controls within 28 days of the case. A conditional Poisson regression calculated risk ratios for EMS call volume. RESULTS: Comparing the case periods to the controls, significant increases were found at AQI >100 for total number of calls, and the primary impressions categories of emotional state or behavior, level of consciousness, no patient complaint, other, respiratory, and abdominal. At an AQI >150, significance was found for the primary impressions categories of other, pain, respiratory, and digestive. CONCLUSION: These data demonstrate increased EMS calls during sustained poor air quality, and that several EMS primary impression categories are disproportionately affected. This study is limited by the imprecision of the primary impression’s classification provided by the EMS clinician responding to the EMS call. More research is needed to understand the effects of periods of poor air quality on the EMS system for more efficient deployment of resources.
BACKGROUND: To reduce the negative health effects from wildfire smoke exposure, effective risk and health communication strategies are vital. We estimated the behavioral effects from changes in message framing and messenger in public health messages about wildfire smoke on Facebook. METHODS: During September and October 2021, we conducted a preregistered online randomized controlled experiment in Facebook. Adult Facebook users (n = 1,838,100), living in nine wildfire-prone Western U.S. states, were randomly assigned to see one of two ad versions (narrative frame vs. informational frame) from one of two messengers (government vs. academic). We estimated the effects of narrative framing, the messenger, and their interactions on ad click-through rates, a measure of recipient information-seeking behavior. RESULTS: Narrative frame increased click-through rates by 25.3% (95% CI = 22.2, 28.4%), with larger estimated effects among males, recipients in areas with less frequent exposure to heavy wildfire smoke, and in areas where predominant political party affiliation of registered voters was Republican (although not statistically different from predominantly-Democrat areas). The estimated effect from an academic messenger compared to a government messenger was small and statistically nonsignificant (2.2%; 95% CI = - 0.3, 4.7%). The estimated interaction effect between the narrative framing and the academic messenger was also small and statistically nonsignificant (3.9%; 95% CI = - 1.1, 9.1%). CONCLUSIONS: Traditional public service announcements rely heavily on communicating facts (informational framing). Shifting from a fact-focused, informational framing to a story-focused, narrative framing could lead to more effective health communication in areas at risk of wildfires and in public health contexts more broadly. TRIAL REGISTRATION: Date registered: August 19, 2021; Registration DOI: https://doi.org/10.17605/OSF.IO/JMWUF.
Information on the allergenic pollen season provides insight on the state of the environment of a region and facilitates allergy symptom management. We present a retrospective analysis of the duration and severity of the allergenic pollen season and the role of meteorological factors in Istanbul, Turkey. Aerobiological sampling from January 2013 to June 2016, pollen identification and counting followed current standard methodology. Pollen seasons were defined according to 95% of the Annual Pollen Integral (APIn) and the season start date was compared with the first day of 5 day consecutive non-zero records. Generalized additive models (GAMs) were created to study the effect of meteorological factors on flowering. The main pollen contributors were taxa of temperate and Mediterranean climates, and neophytic Ambrosia. Cupressaceae, Poaceae, Pinaceae, Quercus and Ambrosia had the greatest relative abundance. The pollen season defined on 95% of the APIn was adequate for our location with total APIns around 10.000 pollen*day*m(-3). Woody taxa had generally shorter seasons than herbaceous taxa. In trees, we see precipitation as the main limiting factor for assimilate production prior to anthesis. A severe tree pollen season in 2016 suggests intense synchronous flowering across taxa and populations triggered by favourable water supply in the preceding year. GAM models can explain the effect of weather on pollen concentrations during anthesis. Under the climatic conditions over the study period, temperature had a negative effect on spring flowering trees, and a positive one on summer flowering weeds. Humidity, atmospheric pressure and precipitation had a negative effect on weeds. Our findings contribute to environmental and allergological knowledge in southern Europe and Turkey with relevancy in the assessment of impacts of climate change and the management of allergic disease.
Wildfire is a natural phenomenon with substantial economic consequences, and its management is complex, dynamic, and rife with incentive problems. This article reviews the contribution of economics to our understanding of wildfire and highlights remaining knowledge gaps. We first summarize economic impacts to illustrate scale and trends. We then focus on wildfire management in three phases: mitigation before fires occur, response during fires, and response after fires. The literature highlights economic interdependencies and spillover effects across fire-prone landscapes as the source of economic inefficiencies and motivation for public institutional response. The literature illustrates the complexity of this problem with its myriad threads, including the trade-offs of living in fire-prone environments, the prospects for using controlled fire and mechanical fuel removal for reducing wildfire severity, the decision-making environment that firefighters face, and the economic consequences of wildfire smoke on health. Economics provides valuable insights, but fundamental questions remain unanswered.
BACKGROUND: Allergic rhinitis affects half a billion people globally, including a fifth of the Australian population. As the foremost outdoor allergen source, ambient grass pollen exposure is likely to be altered by climate change. The AusPollen Partnership aimed to standardize pollen monitoring and examine broad-scale biogeographical and meteorological factors influencing interannual variation in seasonality of grass pollen aerobiology in Australia. METHODS: Daily airborne grass and other pollen concentrations in four eastern Australian cities separated by over 1700 km, were simultaneously monitored using Hirst-style samplers following the Australian Interim Pollen and Spore Monitoring Standard and Protocols over four seasons from 2016 to 2020. The grass seasonal pollen integral was determined. Gridded rainfall, temperature, and satellite-derived grassland sources up to 100 km from the monitoring site were analysed. RESULTS: The complexity of grass pollen seasons was related to latitude with multiple major summer-autumn peaks in Brisbane, major spring and minor summer peaks in Sydney and Canberra, and single major spring peaks occurring in Melbourne. The subtropical site of Brisbane showed a higher proportion of grass out of total pollen than more temperate sites. The magnitude of the grass seasonal pollen integral was correlated with pasture greenness, rainfall and number of days over 30 °C, preceding and within the season, up to 100 km radii from monitoring sites. CONCLUSIONS: Interannual fluctuations in Australian grass pollen season magnitude are strongly influenced by regional biogeography and both pre- and in-season weather. This first continental scale, Southern Hemisphere standardized aerobiology dataset forms the basis to track shifts in pollen seasonality, biodiversity and impacts on allergic respiratory diseases.
Airborne particles in urban Palangka Raya, Kalimantan from Oct 2011 until Oct 2020 have been collected and analyzed for PM(2.5), PM(10), and Black Carbon (BC) concentrations. Palangka Raya is a city that serves the capital of the Central Kalimantan province on the island of Borneo. Kalimantan is affected by peat fires that occur periodically. There were identified increases in PM(2.5) and PM(10) concentrations during El Niño periods. During the forest fire episode in September – October 2015, PM(2.5) and PM(10) concentrations increased significantly, to nearly 400 µg/m(3) and 800 µg/m(3), respectively, and visibility in the city was reduced to < 0.2 miles. The highest BC concentrations were observed during this massive forest fires episode. The regression analyses for PM(2.5), PM(10) and visibility in Palangka Raya during the period of 2011-2020, showed a non-linear correlation with reduction in visibility due to increased PM(2.5) and PM(10). There was no correlation for BC with visibility. Air quality in Palangka Raya was at a relatively good level with concentrations below the national ambient air quality standard when there were no forest fires event. Emissions from forest fires caused a substantial reduction in air quality reaching concentrations well above ambient air quality standards and are likely to have caused adverse health effects on the people living in the area.Implications: Indonesia has repeatedly experienced forest fires, especially on Kalimantan and Sumatera Islands, which burned large areas of peatland. The forest fires leading to increasing PM concentrations especially in the PM(2.5) size range which influence visibility. The seasonal variations of BC in Palangka Raya and the relationships of fine particulates with visibility were assessed. The results of regression analyses for PM(2.5) and PM(10) to visibility during the period of 2011-2020 showed non-linear relationships. An increasing of PM(2.5) and PM(10) concentrations during El Nino periods were detected well above the ambient air quality standard. To ensure effective and continued handling and prevention of forest and peatland fires, the government set up a special task force and review on several rules, including laws and government regulations as well as governor regulations that permit the burning of forest and peatland areas. These results are expected to be used to formulate more effective mitigations in reducing forest fires events in Indonesia.
This study aimed to examine the short-term effects of ambient temperature on hospital admissions due to respiratory diseases among Hanoi residents. We collected 34,653 hospital admissions for 365 days (November 1, 2017, to November 31, 2018) from two hospitals in Hanoi. A quasi-Poisson regression model with time series analysis was used to explore the temperature-health outcome relationship’s overall pattern. The non-linear curve indicated the temperatures with the lowest risk range from 22 degrees (Celcius) to 25 degrees (Celcius). On average, cold temperatures showed a higher risk than hot temperatures across all genders and age groups. Hospital admissions risk was highest at 13 degrees (Celcius) (RR = 1.39; 95% CI = 1.26-1.54) for cold effects and at 33 degrees (Celcius) (RR = 1.21, 95% CI = 1.04-1.39) for the hot effects. Temporal pattern analysis showed that the most effect on respiratory diseases occurred at a lag of 0 days for hot effect and at a lag of 1 day for cold effect. The risk of changing temperature among women and people over 5 years old was higher than other groups. Our results suggest that the risk of respiratory admissions was greatest when the temperature was low. Public health prevention programs should be enhanced to improve public awareness about the health risks of temperature changes, especially respiratory diseases risked by low temperatures.
The 2020 COVID-19 outbreak in New South Wales (NSW), Australia, followed an unprecedented wildfire season that exposed large populations to wildfire smoke. Wildfires release particulate matter (PM), toxic gases and organic and non-organic chemicals that may be associated with increased incidence of COVID-19. This study estimated the association of wildfire smoke exposure with the incidence of COVID-19 in NSW. A Bayesian mixed-effect regression was used to estimate the association of either the average PM(10) level or the proportion of wildfire burned area as proxies of wildfire smoke exposure with COVID-19 incidence in NSW, adjusting for sociodemographic risk factors. The analysis followed an ecological design using the 129 NSW Local Government Areas (LGA) as the ecological units. A random effects model and a model including the LGA spatial distribution (spatial model) were compared. A higher proportional wildfire burned area was associated with higher COVID-19 incidence in both the random effects and spatial models after adjustment for sociodemographic factors (posterior mean = 1.32 (99% credible interval: 1.05-1.67) and 1.31 (99% credible interval: 1.03-1.65), respectively). No evidence of an association between the average PM(10) level and the COVID-19 incidence was found. LGAs in the greater Sydney and Hunter regions had the highest increase in the risk of COVID-19. This study identified wildfire smoke exposures were associated with increased risk of COVID-19 in NSW. Research on individual responses to specific wildfire airborne particles and pollutants needs to be conducted to further identify the causal links between SARS-Cov-2 infection and wildfire smoke. The identification of LGAs with the highest risk of COVID-19 associated with wildfire smoke exposure can be useful for public health prevention and or mitigation strategies.
Our results suggested that short-term exposure to particulate matter (PM) might increase the risks of hospitalizations for osteoporotic fractures. Government should protect its citizens by putting in place policies to reduce unhealthy emissions and air pollution. INTRODUCTION: Osteoporotic fractures are accompanied by high rates of disability and mortality. PM has been linked with many health outcomes. However, few studies focus on the association of short-term exposure to ambient PM and osteoporotic fractures. METHODS: Data on daily mean air pollution, meteorological factors, and hospitalizations for osteoporotic fractures were collected from Hangzhou, China, 2020-2021. A time-stratified case-crossover design with extended Cox proportional hazards regression was applied to assess the associations between PM and osteoporotic fractures. RESULTS: Short-term exposure to PM significantly increased the risks of hospitalizations for osteoporotic fractures at cumulative lag days. Per 10 μg/m(3) increased in PM(2.5) (PM with an aerodynamic diameter ≤ 2.5 μm), PM(C) (PM with an aerodynamic diameter between 2.5 μm and 10 μm), and PM(10) (PM with an aerodynamic diameter ≤ 10 μm) were associated with 5.65% (95% confidence intervals (CIs): 1.29, 10.19), 3.19% (0.11, 6.36), and 2.45% (0.57, 4.37) increase in hospitalizations for osteoporotic fractures, respectively. Significant PM-osteoporotic fracture associations were only observed in females and people aged over 65 years old. For the season, the estimates of PM on hospitalizations for osteoporotic fractures were 6.30% (95% CIs: 1.62, 11.20) in the cold season vs. 2.16% (95% CIs: - 4.62, 9.42) in the warm season for per 10 μg/m(3) increase of PM(2.5), and 0.99 (95% CIs: - 2.69, 4.80) vs. 6.72% (95% CIs: 0.68, 13.13) for PM(C). CONCLUSIONS: Our study showed PM was positively linked with the risk of osteoporotic fractures. Females and people aged over 65 years old were more susceptible to PM. The adverse impacts of PM(2.5) in the cold season and PM(C) in the warm season were worthy of special attention.
BACKGROUND: Greenhouse gas emissions are changing the Earth’s climate, most directly by modifying temperatures and temperature variability (TV). Residents of low- and middle-income countries (LMICs) are likely more adversely affected, due to lack of air conditioning to compensate. To date, there is no local epidemiological evidence documenting the cardio-respiratory health effects of TV in Dhaka, Bangladesh, one of the most climate change vulnerable cities in the world. OBJECTIVES: We assessed short-term TV associations with daily cardiovascular disease (CVD) and respiratory emergency department (ED) visits, as well as effect modification by age and season. METHODS: TV was calculated from the standard deviations of the daily minimum and maximum temperatures over exposure days. Time-series regression modeling was applied to daily ED visits for respiratory and CVD from January 2014 through December 2017. TV effect sizes were estimated after controlling for long-term trends and seasonality, day-of-week, holidays, and daily mean relative humidity and ambient temperature. RESULTS: A 1 °C increase in TV was associated with a 1.00% (95 %CI: 0.05%, 1.96%) increase in CVD ED visits at lag 0-1 days (TV(0-1)) and a 2.77% (95 %CI: 0.24%, 5.20%) increase in respiratory ED visits at lag 0-7 days (TV(0-7)). TV-CVD associations were larger in the monsoon and cold seasons. Respiratory ED visit associations varied by age, with older adults more affected by the TV across all seasons. A 1 °C increase in TV at lag 0-7 days (TV(0-7)) was associated with a 7.45% (95 %CI: 2.33%, 12.57%) increase in respiratory ED visits among patients above 50 years of age. CONCLUSION: This study provided novel and important evidence that cardio-pulmonary health in Dhaka is adversely affected year-round by day-to-day increases in TV, especially among older adults. TV is a key factor that should be considered in evaluating the potential human health impacts of climate change induced temperature changes.
Polycyclic aromatic hydrocarbons (PAHs), as a critical toxic component of PM2.5, have been proven to be carcinogenic to humans. Previous studies have explored the characteristics and health risk of PAHs, but long-term monitoring of ambient PAHs remains limited. In this study, ambient PM2.5 was sampled each month from the 10th to 16th of January 2014 to December 2017 in an industrial area in Jinan, a heavily air-polluted city in China. We described the season and year temporal characteristics of 16 priority-control PAHs outlined by the US EPA after substantial air pollution control measures implementation. The carcinogenic risk caused by 7 PM2.5-related PAH inhaled exposure was assessed. The diagnostic ratio method was used for the source resolution of PAHs. Pair-wise Spearman’s analysis was used to calculate the correlation coefficient between 16 PAHs and meteorological variables. Results showed that 16 PM2.5-related PAHs presented clearly seasonal differences with peak concentrations in the cold season. BaP accounted for the largest proportion of the total excess carcinogenic risks. 5-ring PAHs occupied the highest proportion of the 16 PAHs. Coal, wood, grass combustion and liquid fossil fuel burning all contributed to pyrogenic sources, and vehicular combustion accounted for a larger proportion of pyrogenic sources. Notably, the correlation between 16 PAHs and meteorological variables was not identical in different seasons. We concluded that air quality has been improved to some extent in Jinan, but air pollution control policies should further focus on reducing combustion product emissions, especially coal combustion. [GRAPHICS] .
Dust storms and particulate matters had been increased due to climate change in the Middle East. On the other hand, urbanization and industrialization raised levels of gaseous air pollutants in all big cities. In the current study, air pollution information collected from Environmental Protection Agency of Khuzestan and Tehran containing hourly O(3), NO(2), CO, SO(2), PM(10) and PM(2.5) concentrations between 2014 and 2015. This study evaluated the air quality of these two cities by Air Quality Index (AQI). As a result, mean concentrations of O(3), NO(2), PM(10) and PM(2.5) were higher in Ahvaz than Tehran while Tehran was more pollutant in terms of CO and SO(2). Diurnal variations of O(3) in weekend were the only trend located above weekday variations along the daytimes. Hourly variations of all pollutants changed with a wider range of concentrations in Ahvaz. Diurnal peaks of all pollutants showed their highest level on Monday as the busiest day in mega city, Tehran with the exception of SO(2). PM(2.5) was the worst and limiting pollutant for both cities. Accordingly, winter was the most polluted season by 77 and 33 μg m(-3) in Ahvaz and Tehran, respectively. Number of clean days was significantly lower in Ahvaz (no-day) than mega city, Tehran (<17 days). The number of unhealthy days was also presented significantly higher in Ahvaz (>186 days). Although, annual PM(2.5) concentrations were more in Ahvaz, the higher at-risk population in Tehran caused more health endpoints in the capital of Iran. Consequently, both cities should have their own especial pattern to control air pollution and attributed health damages.
OBJECTIVES: Heatwaves have been linked to increased levels of health service demand in Australia. This systematic literature review aimed to explore health service demand during Australian heatwaves for hospital admissions, emergency department presentations, ambulance call-outs, and risk of mortality. STUDY DESIGN: A systematic review to explore peer-reviewed heatwave literature published from 2000 to 2020. DATA SOURCES: Articles were reviewed from six databases (MEDLINE, Scopus, Web of Science, PsychINFO, ProQuest, Science Direct). Search terms included: heatwave, extreme heat, ambulance, emergency department, and hospital. Studies were included if they explored heat for a period of two or more consecutive days. Studies were excluded if they did not define a threshold for extreme heat or if they explored data only from workers compensation claims and major events. DATA SYNTHESIS: This review was prospectively registered with PROSPERO (# CRD42021227395 ). Forty-five papers were included in the final review following full-text screening. Following a quality assessment using the GRADE approach, data were extracted to a spreadsheet and compared. Significant increases in mortality, as well as hospital, emergency, and ambulance demand, were found across Australia during heatwave periods. Admissions for cardiovascular, renal, respiratory, mental and behavioural conditions exhibited increases during heatwaves. The most vulnerable groups during heatwaves were children (< 18 years) and the elderly (60+). CONCLUSIONS: Heatwaves in Australia will continue to increase in duration and frequency due to the effects of climate change. Health planning is essential at the community, state, and federal levels to mitigate the impacts of heatwaves on health and health service delivery especially for vulnerable populations. However, understanding the true impact of heatwaves on health service demand is complicated by differing definitions and methodology in the literature. The Excess Heat Factor (EHF) is the preferred approach to defining heatwaves given its consideration of local climate variability and acclimatisation. Future research should explore evidence-based and spatially relevant heatwave prevention programs. An enhanced understanding of heatwave health impacts including service demand will inform the development of such programs which are necessary to promote population and health system resilience.
BACKGROUND: Influenza seasonality has been frequently studied, but its mechanisms are not clear. Urban in-situ studies have linked influenza to meteorological or pollutant stressors. Few studies have investigated rural and less polluted areas in temperate climate zones. OBJECTIVES: We examined influences of medium-term residential exposure to fine particulate matter (PM(2.5)), NO(2), SO(2), air temperature and precipitation on influenza incidence. METHODS: To obtain complete spatial coverage of Baden-Württemberg, we modeled environmental exposure from data of the Copernicus Atmosphere Monitoring Service and of the Copernicus Climate Change Service. We computed spatiotemporal aggregates to reflect quarterly mean values at post-code level. Moreover, we prepared health insurance data to yield influenza incidence between January 2010 and December 2018. We used generalized additive models, with Gaussian Markov random field smoothers for spatial input, whilst using or not using quarter as temporal input. RESULTS: In the 3.85 million cohort, 513,404 influenza cases occurred over the 9-year period, with 53.6% occurring in quarter 1 (January to March), and 10.2%, 9.4% and 26.8% in quarters 2, 3 and 4, respectively. Statistical modeling yielded highly significant effects of air temperature, precipitation, PM(2.5) and NO(2). Computation of stressor-specific gains revealed up to 3499 infections per 100,000 AOK clients per year that are attributable to lowering ambient mean air temperature from 18.71 °C to 2.01 °C. Stressor specific gains were also substantial for fine particulate matter, yielding up to 502 attributable infections per 100,000 clients per year for an increase from 7.49 μg/m(3) to 15.98 μg/m(3). CONCLUSIONS: Whilst strong statistical association of temperature with other stressors makes it difficult to distinguish between direct and mediated temperature effects, results confirm genuine effects by fine particulate matter on influenza infections for both rural and urban areas in a temperate climate. Future studies should attempt to further establish the mediating mechanisms to inform public health policies.
Surface ozone (O-3) is a secondary air pollutant, harmful to human health and vegetation. To provide a long-term study of O-3 concentrations in Portugal (study period: 2009-2019), a statistical analysis of ozone trends in rural stations (where the highest concentrations can be found) was first performed. Additionally, the effect of nitrogen oxides (NOx) and meteorological variables on O-3 concentrations were evaluated in different environments in northern Portugal. A decreasing trend of O-3 concentrations was observed in almost all monitoring stations. However, several exceedances to the standard values legislated for human health and vegetation protection were recorded. Daily and seasonal O-3 profiles showed high concentrations in the afternoon and summer (for all inland rural stations) or spring (for Portuguese islands). The high number of groups obtained from the cluster analysis showed the difference of ozone behaviour amongst the existent rural stations, highlighting the effectiveness of the current geographical distribution of monitoring stations. Stronger correlations between O-3, NO, and NO2 were detected at the urban site, indicating that the O-3 concentration was more NOx-sensitive in urban environments. Solar radiation showed a higher correlation with O-3 concentration regarding the meteorological influence. The wind and pollutants transport must also be considered in air quality studies. The presented results enable the definition of air quality policies to prevent and/or mitigate unfavourable outcomes from O-3 pollution.
Climate change continues to pose a dangerous threat to human health. However, not only is health impacted by this crisis, healthcare itself adds to the problem, through significant contributions to greenhouse gas emissions. In the UK, the National Health Service (NHS) is responsible for an estimated 4% of the overall national carbon footprint. Medicines account for a quarter of this and whilst they are vital for health now, through sustainable use they can also positively influence the environmental health of the future. In this review, we explore how clinical pharmacologists and other health care professionals can practice sustainable medicines use or eco-pharmaco-stewardship. We will discuss current and near future environmental practices within the NHS, which we suspect will resonate with other health systems. We will suggest approaches for championing eco-pharmaco-stewardship in drug manufacturing, clinical practice and patient use, to achieve a more a sustainable healthcare system.
Wildland fires produce smoke plumes that impact air quality and human health. To understand the effects of wildland fire smoke on humans, the amount and composition of the smoke plume must be quantified. Using a fire emissions inventory is one way to determine the emissions rate and composition of smoke plumes from individual fires. There are multiple fire emissions inventories, and each uses a different method to estimate emissions. This paper presents a comparison of four emissions inventories and their products: Fire INventory from NCAR (FINN version 1.5), Global Fire Emissions Database (GFED version 4s), Missoula Fire Labs Emissions Inventory (MFLEI (250 m) and MFLEI (10 km) products), and Wildland Fire Emissions Inventory System (WFEIS (MODIS) and WFEIS (MTBS) products). The outputs from these inventories are compared directly. Because there are no validation datasets for fire emissions, the outlying points from the Bayesian models developed for each inventory were compared with visible images and fire radiative power (FRP) data from satellite remote sensing. This comparison provides a framework to check fire emissions inventory data against additional data by providing a set of days to investigate closely. Results indicate that FINN and GFED likely underestimate emissions, while the MFLEI products likely overestimate emissions. No fire emissions inventory matched the temporal distribution of emissions from an external FRP dataset. A discussion of the differences impacting the emissions estimates from the four fire emissions inventories is provided, including a qualitative comparison of the methods and inputs used by each inventory and the associated strengths and limitations.
Wildfires and hazard reduction burns produce smoke that contains pollutants including particulate matter. Particulate matter less than 2.5 mu m in diameter (PM2.5) is harmful to human health, potentially causing cardiovascular and respiratory issues that can lead to premature deaths. PM2.5 levels depend on environmental conditions, fire behaviour and smoke dispersal patterns. Fire management agencies need to understand and predict PM2.5 levels associated with a particular fire so that pollution warnings can be sent to communities and/or hazard reduction burns can be timed to avoid the worst conditions for PM2.5 pollution. We modelled PM2.5, measured at air quality stations in New South Wales (Australia) from similar to 1400 d when individual fires were burning near air quality stations, as a function of fire and weather variables. Using Visible Infrared Imaging Radiometer Suite (VIIRS) satellite hotspots, we identified days when one fire was burning within 150 km of at least 1 of 48 air quality stations. We extracted ERAS grid-ded weather data and daily active fire area estimates from the hotspots for our modelling. We created random forest models for afternoon, night and morning PM2.5 levels to understand drivers of and predict PM2.5. Fire area and boundary layer height were important predictors across the models, with temperature, wind speed and relative humidity also being important. There was a strong increase in PM2.5 with decreasing distance, with a sharp increase when the fire was within 20 km. The models improve our understanding of the drivers of PM2.5 from individual fires and demonstrate a promising approach to PM2.5 model development. However, although the models predicted well overall, there were several large under-predictions of PM2.5 that mean further model development would be required for the models to be deployed operationally.
Exposure to airborne particulate matter (PM) can be considered as an important risk factor for human health. Some cytokines have been recognized as the biomarkers of exposure to air pollution. Experimental studies indicate that PM exposure could be associated with inflammation. Thus, the purpose of this study was to evaluate whether the exposure to air PM is associated with biomarkers of inflammation. The specific aim of this study was to determine the correlation between airborne PM levels and IL-6 and TNF-alpha as airway inflammation biomarkers among two groups of late adolescents in northwest of Iran. This study included 46 subjects, comprising 23 asthmatic subjects and 23 non-asthmatic persons. Environmental PM (PM10, PM2.5 and PM1) levels were measured in dust storm and non-dust storm days during both cold and warm seasons. Following the sampling of PM, Two pro-infiammatory cytokines of IL-6 and TNF-alpha in exhaled breath condensate (EBC) were also determined in the EBC samples via commercial ELISA kits. Daily mean ambient air PM10, PM2.5 and PM1 concentrations during the dust storm days was 221.79, 93.13 and 25.52 mu g m(-3) and in non-dusty days 48.37, 18.54 and 6.1 mu g m(-3), respectively. Biomarkers levels were significantly (p < 0.001) higher in asthmatic students compared to the non-asthmatic subjects. EBC cytokines levels were in-creased in dust storm days compared to the non-dusty days (p < 0.001) and were positively correlated with different size of ambient PM concentration. Dust storm conditions can increase the pro-infiammatory cytokines and cause ad-verse effects on pulmonary health and lung tissue damage.
In the context of urban construction and reconstruction, the sustainable development of cities, air quality and the health of urban residents need to be considered, especially urban street canyons that are closely related to residents. However, traditional street canyons are optimized from a single urban microclimate level, and lack multi-dimensional optimization strategies to deal with climate change and pay attention to human respiratory health. In this study, the Changhuai Street Canyon in Hefei, Anhui Province, China was taken as the measure-ment object, and ENVI-met was used to simulate the fine particles and the physical environment. First, control the three-dimensional space of street canyons reasonably, and then optimize the spatial form of urban street canyons. Second, the PM2.5 concentrations at different selected points and heights were obtained. Finally, the optimization strategy of reducing building height, widening road width and increasing street canyon greening is proposed. This study is based on the comparison of pollutant concentrations between winter and summer in Changhuai street canyons, different sample locations, and different building heights to improve the spatial form of urban street canyons, implement the “dual carbon” goal, and promote sustainable urban development.
Multiple environmental stressors threaten the environmental quality in urban areas. Several policies were implemented in Italy to improve environmental quality, following the rationale that the more populated municipalities need high intervention priority and funds. Nevertheless, this approach not necessarily ensures to address real environmental challenges. This study aims to provide an innovative approach to explore interventions’ priority at the national scale, based on Environmental Quality Standards (EQS) of five factors related to three environmental stressors, air pollution (O-3, PM10, NO2), thermal stress (heatwave days), and hydraulic vulnerability (flooding events). A multi-criteria analysis assessed the cumulative effect of factors by combining them into a single Aggregate Index of Challenge (AIC), and a hotspot analysis identified AIC spatial aggregation through the territory. Finally, the spatial mismatch between Italian environmental policies and the co-occurrence of factors was explored. Results evidenced EQS exceedances in the national territory of O-3 for 89%, PM10 for 8%, NO2 for less than 1%, heatwaves for 45%, and hydraulic vulnerability for 10%. AIC highlighted that 43% of the national surface shows the coexistence of at least two factors in EQS exceedance. Results highlighted that administrative boundaries are not sufficient to delimit an area of analysis and intervention as opposed to an evidence-based approach which seems promising for enhancing the costeffectiveness of funds allocation as well as their return in terms of human wellbeing. This study provides a novel approach to enhance environmental policies and planning, giving insight for future research, especially for Nature-Based Solutions implementation, performance, and multifunctionality.
The disease dengue is associated with both mesoscale and synoptic scale meteorology. However, previous studies for south-east Asia have found a very limited association between synoptic variables and the reported number of dengue cases. Hence there is an urgent need to establish a more clear association with dengue incidence rates and the most relevant meteorological variables in order to institute an early warning system.& nbsp;This article develops a rigorous Bayesian modelling framework to identify the most important covariates and their lagged effects for constructing an early warning system for the Central Region of Malaysia where the case rates have increased substantially in the recent past. Our modelling includes multiple synoptic scale Nin tilde o indices, which are related to the phenomenon of El Nin tilde o Southern Oscillation (ENSO), along with other relevant mesoscale environmental measurements and an unobserved variable derived from reanalysis data. An empirically well validated hierarchical Bayesian spatio-temporal is used to build a probabilistic early warning system for detecting an upcoming dengue epidemic.& nbsp;Our study finds a 46.87% increase in dengue cases due to one degree increase in the central equatorial Pacific sea surface temperature with a lag time of six weeks. We discover the existence of a mild association with relative risk 0.9774 (CI: 0.9602, 0.9947) between the rate of cases and a distant lagged cooling effect in the region of coastal South America related to a phenomenon called El Nin tilde o Modoki. The Bayesian model also establishes that the synoptic meteorological drivers can enhance short-term early detection of dengue outbreaks and these can also potentially be used to provide longer-term forecasts.
Community and composition of dust-borne microbes would affect human health and are regulated by microbial community assembly. The dust in kindergarten is always collected to evaluate the microbial exposure of children, yet the microbial assembly, their interactions, and potential pathogens in kindergarten dust remain unclear. Here, we aim to investigate the microbial community assembly and structures, and potential bacterial pathogens in outdoor dust of kindergartens, and reveal the factors influencing the assembly and composition of microbial community. A total of 118 urban dust samples were collected on the outdoor impervious surfaces of 59 kin-dergartens from different districts of Xiamen in January and June 2020. We extracted microbial genomic DNA in these dusts and characterized the microbial (i.e., bacteria and fungi) community compositions and diversities using target gene-based (16S rRNA genes for bacterial community and ITS 2 regions for fungal community) high -throughput sequencing. Potential bacterial pathogens were identified and the interactions between microbes were determined through a co-occurrence network analysis. Our results showed the predominance of Actino-bacteria and alpha-Proteobacteria in bacterial communities and Capnodiales in fungal communities. Season altered microbial assembly, composition, and interactions, with both bacterial and fungal communities exhibiting a higher heterogeneity in summer than those in winter. Although stochastic processes predominated in bacterial and fungal community assembly, the season-depended environmental factors (e.g., temperature) and interactions between microbes play important roles in dust microbial community assembly. Potential bacterial pathogens were detected in all urban dust, with significantly higher relative abundance in summer than that in winter. These results indicated that season exerted more profound effects on microbial community composition, as-sembly, and interactions, and suggested the seasonal changes of potential risk of microbes in urban dust. Our findings provide new insights into microbial community, community assembly, and interactions between mi-crobes in the urban dust, and indicate that taxa containing opportunistic pathogens occur commonly in urban dust.
Air pollution is one of the foremost environmental threats to human health. However, the meteorological and social factors that lead to respiratory and cardiovascular diseases have not been fully elucidated. In this study, we use Principal Component Analysis and Generalized Linear Model (PCA-GLM) to investigate the combined effect of socioeconomic development and air pollution on cardiorespiratory hospitalization in southern Brazil. This region has the highest rates of hospitalization by cardiorespiratory diseases in the country. We analyze three main sources of data: (i) air pollutants density from TROPOMI/Sentinel-5p satellite; (ii) temperature, humidity, and planetary boundary layer height (PBLH) modeled with the Weather Research Forecast model; and (iii) hospitalization by cardiorespiratory diseases obtained from the Brazilian National Health System. We estimate the Relative Risk (RR) using the PCA-GLM coefficients and interquartile variations of air pollutants density and meteorological parameters. Our results show that the population living in colder and drier municipalities is more prone to cardiorespiratory hospitalization. Regarding respiratory hospitalization, municipalities with lower socioeconomic development are more sensitive to meteorology and pollution variability than highly developed ones. In less developed municipalities, we observe the highest rates of cardiorespiratory hospitalization even if air pollution is low, which we interpret in terms of higher vulnerability. The RR analysis suggests that air pollution is an important environmental risk to cardiovascular diseases and respiratory diseases is more sensitive to air pollution and meteorology than cardiovascular ones. Our findings corroborate the mounting evidence that social vulnerability is a significant factor affecting the increase of cardiorespiratory hospitalization in the world.
Wildfires are an important disturbance in the Earth system, and their emissions have regional and even global impacts on radiation, clouds, and climate. The increased frequency and magnitude of California wildfires in recent years is altering the terrestrial carbon cycle, undermining the state’s efforts to reduce the Greenhouse Gases (GHGs) to confront climate change. Air quality and public health are also greatly affected by air pollution from wildfires. The severity of wildfire burns is a critical indicator of both their direct and indirect ecological and human impacts. To formulate targeted mitigation strategies, it is imperative to understand the evolving scale, location and timing of wildfire burn severity and emissions. This study analyzed spatial and temporal patterns of burn severity and emissions at 30 m resolution from large wildfires (>404 hectares) burning in California during 1984-2020 from the recently developed Wildfire Burn Severity and Emissions Inventory. Results show vegetation and severity play critical roles in controlling the spatial and seasonal distribution of emissions. California’s annual burned area and emissions increased, notably in early and late parts of what once was the typical fire season, although peak wildfire burned area and emissions continue to occur in mid-Summer. Emissions and areas burned in moderate to high severity were particularly high and increasing in North Coast and Sierra Nevada forests. The 2020 fire year-with the most megafires in California history-had 15 times the annual average emissions that occurred during 1984-2015.
Persons with disabilities (PwD), the world’s largest minority, can be more susceptible to particulate matter (PM) than persons without disabilities. Although numerous studies have addressed population susceptibility to PM, PwD have not been studied in air pollution epidemiology. This study investigated the association between short-term exposure to PM with an aerodynamic diameter smaller than 10 μm (PM(10)) and cardiovascular hospital admissions by the existence of a disability, while also considering intersections of disability and other socio-demographic characteristics in South Korea. We used the National Health Insurance Service-National Sample Cohort (NHIS-NSC) to investigate the association between short-term exposure to PM(10) and cardiovascular hospital admissions in seven metropolitan cities from 2002 to 2015. We conducted a time-stratified case-crossover analysis using conditional logistic regression and adjusted for daily temperature, relative humidity, air pressure, and national holidays. We conducted stratified analyses according to the existence of a disability, disability type and severity, and socio-demographic characteristics. The results showed that a 10 μg/m(3) increase in the 0-3 moving average level of PM(10) was associated with 1.9 % (95 % confidence interval [CI]: 0.7 %, 3.2 %) and 0.0 % (95 % CI: -0.5 %, 0.5 %) increase in cardiovascular admissions in persons with and without disabilities, respectively. Among PwD, the associations were pronounced in people with brain lesion disorders (percent change [PC]: 2.7 %, 95 % CI: 0.5 %, 5.0 %), people with visual impairment (PC: 3.0 %, 95 % CI: -1.0 %, 7.1 %), and people with severe disability (PC: 3.0 %, 95 % CI: 0.9 %, 5.0 %). We found that PwD may be more adversely affected by PM(10) than their non-disabled counterparts. This suggests that PwD is a social identity reflecting the socially marginalized and disadvantaged population in air pollution epidemiology.
BACKGROUND: There is increasing evidence that long-term exposure to fine particulate matter [PM ≤ 2.5 μm in aerodynamic diameter (PM2.5)] may adversely impact cognitive performance. Wildfire smoke is one of the biggest sources of PM2.5 and concentrations are likely to increase under climate change. However, little is known about how short-term exposure impacts cognitive function. OBJECTIVES: We aimed to evaluate the associations between daily and subdaily (hourly) PM2.5 and wildfire smoke exposure and cognitive performance in adults. METHODS: Scores from 20 plays of an attention-oriented brain-training game were obtained for 10,228 adults in the United States (U.S.). We estimated daily and hourly PM2.5 exposure through a data fusion of observations from multiple monitoring networks. Daily smoke exposure in the western U.S. was obtained from satellite-derived estimates of smoke plume density. We used a longitudinal repeated measures design with linear mixed effects models to test for associations between short-term exposure and attention score. Results were also stratified by age, gender, user behavior, and region. RESULTS: Daily and subdaily PM2.5 were negatively associated with attention score. A 10 μg/m3 increase in PM2.5 in the 3 h prior to gameplay was associated with a 21.0 [95% confidence interval (CI): 3.3, 38.7]-point decrease in score. PM2.5 exposure over 20 plays accounted for an estimated average 3.7% (95% CI: 0.7%, 6.7%) reduction in final score. Associations were more pronounced in the wildfire-impacted western U.S. Medium and heavy smoke density were also negatively associated with score. Heavy smoke density the day prior to gameplay was associated with a 117.0 (95% CI: 1.7, 232.3)-point decrease in score relative to no smoke. Although differences between subgroups were not statistically significant, associations were most pronounced for younger (18-29 y), older ( ≥ 70 y), habitual, and male users. DISCUSSION: Our results indicate that PM2.5 and wildfire smoke were associated with reduced attention in adults within hours and days of exposure, but further research is needed to elucidate these relationships. https://doi.org/10.1289/EHP10498.
To assess mortality risks and burdens associated with short-term exposure to wildfire-related fine particulate matter with diameter ≤ 2.5 μm (PM(2.5)), we collect daily mortality data from 2000 to 2016 for 510 immediate regions in Brazil, the most wildfire-prone area. We integrate data from multiple sources with a chemical transport model at the global scale to isolate daily concentrations of wildfire-related PM(2.5) at a 0.25 × 0.25 resolution. With a two-stage time-series approach, we estimate (i) an increase of 3.1% (95% confidence interval [CI]: 2.4, 3.9%) in all-cause mortality, 2.6% (95%CI: 1.5, 3.8%) in cardiovascular mortality, and 7.7% (95%CI: 5.9, 9.5) in respiratory mortality over 0-14 days with each 10 μg/m(3) increase in daily wildfire-related PM(2.5); (ii) 0.65% of all-cause, 0.56% of cardiovascular, and 1.60% of respiratory mortality attributable to acute exposure to wildfire-related PM(2.5), corresponding to 121,351 all-cause deaths, 29,510 cardiovascular deaths, and 31,287 respiratory deaths during the study period. In this study, we find stronger associations in females and adults aged ≥ 60 years, and geographic difference in the mortality risks and burdens.
Pollen levels in rapidly developing urban areas are of particular interest due to their negative impact on human health, being responsible for the increasing prevalence of seasonal allergic diseases. This study analyzed multiyear data (2014-2019) of the pollen concentrations in correlation with major air pollutants PM10, PM2.5, NOx, CO, VOCs, O-3, SO2 and meteorological parameters from Bucharest, in order to find potential links between them. The pollen monitoring performed at Colentina Clinical Hospital using a Hirst-type pollen trap showed that maximum values of pollen concentration from trees are reached in early spring, from grasses in spring and early summer and from weeds in late summer and fall. The correlation analysis was performed using the Spearman correlation coefficient on annual and seasonal basis and revealed the influence of air pollutants and meteorological parameters on pollen concentrations. No monotonic decreasing or increasing trend was detected for Bucharest during the investigated 6-year period, but a general constant behavior.
BACKGROUND:The challenges of climate change and increasing frequency of severe weather conditions has demanded innovative approaches to wildfire suppression. Australia’s wildfire management includes an expanding aviation program, providing both fixed and rotary wing aerial platforms for reconnaissance, incident management, and quick response aerial fire suppression. These operations have typically been limited to day visual flight rules operations, but recently trials have been undertaken extending the window of operations into the night, with the assistance of night vision systems. Already a demanding job, night aerial firefighting operations have the potential to place even greater physical and mental demands on crewmembers. This study was designed to investigate sleep, fatigue, and performance outcomes in Australian aerial firefighting crews.METHODS:A total of nine subjects undertook a 21-d protocol, completing a sleep and duty diary including ratings of fatigue and workload. Salivary cortisol was collected daily, with additional samples provided before and after each flight, and heart rate variability was monitored during flight. Actigraphy was also used to objectively measure sleep during the data collection period.RESULTS:Descriptive findings suggest that subjects generally obtained >7 h sleep prior to flights, but cortisol levels and self-reported fatigue increased postflight. Furthermore, the greatest reported workload was associated with the domains of ‘performance’ and ‘mental demand’ during flights.DISCUSSION:Future research is necessary to understand the impact of active wildfire response on sleep, stress, and workload on aerial firefighting crews.Sprajcer M, Roberts S, Aisbett B, Ferguson S, Demasi D, Shriane A, Thomas MJW. Sleep, workload, and stress in aerial firefighting crews. Aerosp Med Hum Perform. 2022; 93(10):749-754.
Recent evidence has shown an association between wildfire smoke and COVID-19 cases and deaths. The San Francisco Bay Area, in California (USA), experienced two major concurrent public health threats in 2020: the COVID-19 pandemic and dense smoke emitted by wildfires. This provides a unprecedented context to unravel the role of acute air pollution exposure on COVID-19 severity. A smoke product provided by the National Oceanic and Atmospheric Association Hazard Mapping System was used to identify counties exposed to heavy smoke in summer and fall of 2020. Daily COVID-19 cases and deaths for the United States were downloaded at the County-level from the CDC COVID Data Tracker. Synthetic control methods were used to estimate the causal effect of the wildfire smoke on daily COVID-19 case fatality ratios (CFRs), adjusting for population mobility. Evidence of an impact of wildfire smoke on COVID-19 CFRs was observed, with precise estimates in Alameda and San Francisco. Up to 58 (95% CI: 29, 87) additional deaths for every 1000 COVID-19 incident daily cases attributable to wildfire smoke was estimated in Alameda in early September. Findings indicated that extreme weather events such as wildfires smoke can drive increased vulnerability to infectious diseases, highlighting the need to further study these colliding crises. Understanding the environmental drivers of COVID-19 mortality can be used to protect vulnerable populations from these potentially concomitant public health threats.
Wildfires are occurring worldwide with greater frequency and intensity. Wildfires, as well as other sources of air pollution including environmental tobacco smoke, household biomass combustion, agricultural burning, and vehicular emissions, release large amounts of toxic substances into the atmosphere. The ocular surface is constantly exposed to the ambient air and is hence vulnerable to damage from air pollutants. This review describes the detrimental effects of wildfire smoke and air pollution on the ocular surface and resultant signs and symptoms. The latest relevant evidence is synthesised and critically evaluated. A mechanism for the pathophysiology of ocular surface damage will be proposed considering the existing literature on respiratory effects of air pollution. Current strategies to reduce human exposure to air pollutants are discussed and specific possible approaches to protect the ocular surface and manage air pollution induced ocular surface damage are suggested. Further avenues of research are suggested to understand how acute and chronic air pollution exposure affects the ocular surface including the short and long-term implications.
RATIONALE: Studies examining the association of short-term air pollution exposure and daily deaths have typically been limited to cities and used citywide average exposures, with few using causal models. OBJECTIVES: To estimate the associations between short-term exposures to fine particulate matter (PM(2.5)), ozone (O(3)), and nitrogen dioxide (NO(2)) and all-cause and cause-specific mortality in multiple US states using census tract or address exposure and including rural areas, using a double negative control analysis. METHODS: We conducted a time-stratified case-crossover study examining the entire population of seven US states from 2000-2015, with over 3 million non-accidental deaths. Daily predictions of PM(2.5), O(3), and NO(2) at 1×1 km grid cells were linked to mortality based on census track or residential address. For each pollutant, we used conditional logistic regression to quantify the association between exposure and the relative risk of mortality conditioning on meteorological variables, other pollutants, and using double negative controls. RESULTS: A 10 μg/m(3) increase in PM(2.5) exposure at the moving average of lag 0-2 day was significantly associated with a 0.67% (95%CI: 0.34-1.01%) increase in all-cause mortality. 10 ppb increases in NO(2) or O(3) exposure at lag 0-2 day were marginally associated with and 0.19% (95%CI: -0.01-0.38%) and 0.20 (95% CI-0.01, 0.40), respectively. The adverse effects of PM(2.5) persisted when pollution levels were restricted to below the current global air pollution standards. Negative control models indicated little likelihood of omitted confounders for PM(2.5), and mixed results for the gases. PM(2.5) was also significantly associated with respiratory mortality and cardiovascular mortality. CONCLUSIONS: Short-term exposure to PM(2.5) and possibly O(3) and NO(2) are associated with increased risks for all-cause mortality. Our findings delivered evidence that risks of death persisted at levels below currently permissible.
Objective The objective of this study was to evaluate the relationship between short-term fine particulate matter (PM2.5)/inhalable particulate matter (PM10) exposure and lung cancer mortality. Method From 2015 to 2019, data concerning air pollution, meteorology, and deaths were obtained in Wuhai, China. The association between PM2.5/PM10 and lung cancer mortality was investigated using time series analysis. Result According to the single-pollutant model, a 10 mu g/m(3) increase in PM2.5/PM10 was associated with an excess risk of 7.95% (95% CI, 2.22-13.95%), and 2.44% (95% CI, 0.32-4.62%), respectively (P < 0.05). PM2.5/PM10 had a stronger impact on men and the elderly (>65 years old). Particulate matter had a larger influence on lung cancer mortality during the warm season than the cold season. Furthermore, except for PM2.5 and PM10, the two-pollution model indicated that the other models were statistically significant. The study’s single and dual pollutant models were both relatively robust. Conclusion Short-term exposure to PM2.5/PM10 was correlated with a higher risk of lung cancer death in Wuhai, particularly among men and the elderly (>65 years old). Exposure to PM2.5/PM10 really does have a bigger effect on the population during the warm season. Moreover, it is essential that health administration departments should strengthen their regulatory mechanisms for particulate emissions and take the responsibility for safeguarding the vulnerable populations. (C) 2022 Wolters Kluwer Health, Inc. All rights reserved.
BACKGROUND: A large body of evidence has linked air pollution and temperature with chronic kidney disease (CKD) prevalence and hospitalizations. However, most studies have focused on the influence of heat stress on CKD prevalence, and the potential effect modification of temperature on the association between air pollution and CKD has not been well-investigated. In this study, we examined the associations of the whole temperature spectrum and air pollution with CKD-related hospital visits and explored whether temperature modifies the short-term association of air pollution with CKD-related hospital visits. METHODS AND FINDINGS: We collected 40 276 CKD-related hospital visits from the first Affiliated Hospital of Anhui Medical University and Anhui Provincial Hospital in Hefei, China, during 2015-2019. A two-stage time-series design was conducted to investigate the associations of air pollution and daily mean temperature with CKD-related hospital visits. First, we estimated the associations between air pollution and CKD-related hospital visits as well as temperature and CKD-related hospital visits. Second, we analyzed the associations of air pollution with CKD hospital visits at different temperatures. We found that NO(2) exposure and low temperature were associated with an increased risk of CKD-related hospital visits. Low temperature enhanced the association between NO(2) exposure and CKD-related hospital visits, with an increase of 4.30% (95% CI: 2.47-5.92%) per 10 μg/m(3) increment in NO(2) at low temperature. Effect modification of the association between NO(2) and the risk of CKD-related hospital visits was stronger at low temperature across the whole population. CONCLUSIONS: Our findings indicate that low temperature-related chronic kidney damage should be of immediate public health concern. Impact of NO(2) exposure on the risk of CKD-related hospital visits may increase under the low temperature, which suggests the need for NO(2) exposure mitigation strategies in the context of climate change and an enhanced understanding of the mechanisms underlying the temperature variance of air pollution effect to help reduce the magnitude of the CKD burden on the healthcare systems.
The present study was conducted to assess the short-term effects of the meteorological factors on the COVID-19 mortality in Qom, Iran. The GAM with a quasi-Poisson link function was used to evaluate the impact of temperature, DTR, relative humidity, and absolute humidity on the COVID-19 mortality, controlling potential confounders such as time trend, air pollutants, and day of the week. The results showed that the risk of COVID-19 mortality was reduced, in single-day lag/multiple-day average lag, per one-unit increase in absolute humidity (percentage change in lag 0=-33.64% (95% CI (-42.44, -23.49)), and relative humidity (percentage change in lag 0=-1.87% (95% CI (-2.52, -1.22)). Also, per one-unit increase in DTR value, COVID death risk increased in single-day and multiple-day average lag. This study demonstrated a significant relationship between the four meteorological variables and the COVID-19 mortality.
Background The high risks for childhood respiratory diseases are associated with exposure to ambient air pollution. However, there are few studies that have explored the association between air pollution exposure and respiratory diseases among young children (particularly aged 0-2 years) based on the entire population in a megalopolis. Methods Daily hospital admission records were obtained from 54 municipal hospitals in Wuhan city, China. We included all children (aged 0-2 years) hospitalized with respiratory diseases between January 2017 and December 2018. Individual air pollution exposure assessment was used in Land Use Regression model and inverse distance weighted. Case-crossover design and conditional logistic regression models were adopted to estimate the hospitalization risk associated with air pollutants. Results We identified 62,425 hospitalizations due to respiratory diseases, of which 36,295 were pneumonia. Particulate matter with an aerodynamic diameter less than 2.5 mu m (PM2.5) and nitrogen dioxide (NO2) were significantly associated with respiratory diseases and pneumonia. ORs of pneumonia were 1.0179 (95% CI 1.0097-1.0260) for PM2.5 and 1.0131 (95% CI 1.0042-1.0220) for NO2 at lag 0-7 days. Subgroup analysis suggested that NO2, Ozone (O-3) and sulfur dioxide (SO2) only showed effects on pneumonia hospitalizations on male patients, but PM2.5 had effects on patients of both genders. Except O-3, all pollutants were strongly associated with pneumonia in cold season. In addition, children who aged elder months and who were in central urban areas had a higher hospitalization risk. Conclusions Air pollution is associated with higher hospitalization risk for respiratory diseases, especially pneumonia, among young children, and the risk is related to gender, month age, season and residential location.
As the underlying mechanisms of the adverse effects of cold spells on cardiac events are not well understood, we explored the effects of cold spells on plasma viscosity, a blood parameter linked to cardiovascular disease. This cross-sectional study involved 3622 participants from the KORA S1 Study (1984-1985), performed in Augsburg, Germany. Exposure data was obtained from the Bavarian State Office for the Environment. Cold spells were defined as two or more consecutive days with daily mean temperatures below the 3(rd), 5(th), or 10(th) percentile of the distribution. The effects of cold spells on plasma viscosity were explored by generalized additive models with distributed lag nonlinear models (DLNM). We estimated cumulative effects at lags 0-1, 0-6, 0-13, 0-20, and 0-27 days separately. Cold spells (mean temperature <3(rd), <5(th) or <10(th) percentile) were significantly associated with an increase in plasma viscosity with a lag of 0-1 days [%change of geometric mean (95% confidence interval): 1.35 (0.06-2.68), 1.35 (0.06-2.68), and 2.49 (0.34-4.69), respectively], and a lag of 0-27 days [18.81 (8.97-29.54), 17.85 (8.29-28.25), and 7.41 (3.35-11.0), respectively]. For the analysis with mean temperature <3(rd) or 10(th) percentile, we also observed significant associations at lag 0-20 days [8.34 (0.43-16.88), and 4.96 (1.68, 8.35), respectively]. We found that cold spells had significant immediate and longer lagged effects on plasma viscosity. This finding supports the complex interplay of multiple mechanisms of cold on adverse cardiac events and enriches the knowledge about how cold exposure acts on the human body.
Studies have associated the human respiratory syncytial virus which causes seasonal childhood acute bronchitis and bronchiolitis (CABs) with climate change and air pollution. We investigated this association using the insurance claims data of 3,965,560 children aged ≤ 12 years from Taiwan from 2006−2016. The monthly average incident CABs increased with increasing PM2.5 levels and exhibited an inverse association with temperature. The incidence was 1.6-fold greater in January than in July (13.7/100 versus 8.81/100), declined during winter breaks (February) and summer breaks (June−August). The highest incidence was 698 cases/day at <20 °C with PM2.5 > 37.0 μg/m3, with an adjusted relative risk (aRR) of 1.01 (95% confidence interval [CI] = 0.97−1.04) compared to 568 cases/day at <20 °C with PM2.5 < 15.0 μg/m3 (reference). The incidence at ≥30 °C decreased to 536 cases/day (aRR = 0.95, 95% CI = 0.85−1.06) with PM2.5 > 37.0 μg/m3 and decreased further to 392 cases/day (aRR = 0.61, 95% CI = 0.58−0.65) when PM2.5 was <15.0 μg/m3. In conclusion, CABs infections in children were associated with lowered ambient temperatures and elevated PM2.5 concentrations, and the high PM2.5 levels coincided with low temperature levels. The role of temperature should be considered in the studies of association between PM2.5 and CABs.
This paper investigates whether associations between birth weights and prenatal ambient environmental conditions-pollution and extreme temperatures-differ by 1) maternal education; 2) children’s innate health; and 3) interactions between these two. We link birth records from Guangzhou, China, during a period of high pollution, to ambient air pollution (PM(10) and a composite measure) and extreme temperature data. We first use mean regressions to test whether, overall, maternal education is an “effect modifier” in the relationships between ambient air pollution, extreme temperature, and birth weight. We then use conditional quantile regressions to test for effect heterogeneity according to the unobserved innate vulnerability of babies after conditioning on other confounders. Results show that 1) the negative association between ambient exposures and birth weight is twice as large at lower conditional quantiles of birth weights as at the median; 2) the protection associated with college-educated mothers with respect to pollution and extreme heat is heterogeneous and potentially substantial: between 0.02 and 0.34 standard deviations of birth weights, depending on the conditional quantiles; 3) this protection is amplified under more extreme ambient conditions and for infants with greater unobserved innate vulnerabilities.
BACKGROUND: Neighborhood-scale air pollution sampling methods have been used in a range of settings but not in low air pollution airsheds with extreme weather events such as volatile precipitation patterns and extreme summer heat and aridity-all of which will become increasingly common with climate change. The desert U.S. metropolis of Tucson, AZ, has historically low air pollution and a climate marked by volatile weather, presenting a unique opportunity. METHODS: We adapted neighborhood-scale air pollution sampling methods to measure ambient NO(2), NO(x), and PM(2.5) and PM(10) in Tucson, AZ. RESULTS: The air pollution concentrations in this location were well below regulatory guidelines and those of other locations using the same methods. While NO(2) and NO(x) were reliably measured, PM(2.5) measurements were moderately correlated with those from a collocated reference monitor (r = 0.41, p = 0.13), potentially because of a combination of differences in inlet heights, oversampling of acutely high PM(2.5) events, and/or pump operation beyond temperature specifications. CONCLUSION: As the climate changes, sampling methods should be reevaluated for accuracy and precision, especially those that do not operate continuously. This is even more critical for low-pollution airsheds, as studies on low air pollution concentrations will help determine how such ambient exposures relate to health outcomes.
Ongoing climate variability and change is impacting pollen exposure dynamics among sensitive populations. However, pollen data that can provide beneficial information to allergy experts and patients alike remains elusive. The lack of high spatial resolution pollen data has resulted in a growing interest in using phenology information that is derived using satellite observations to infer key pollen events including start of pollen season (SPS), timing of peak pollen season (PPS), and length of pollen season (LPS). However, it remains unclear if the agreement between satellite-based phenology information (e.g. start of season: SOS) and the in-situ pollen dynamics vary based on the type of satellite product itself or the processing methods used. To address this, we investigated the relationship between vegetation phenology indicator (SOS) derived from two separate sensor/satellite observations (MODIS, Landsat), and two different processing methods (double logistic regression (DLM) vs hybrid piecewise logistic regression (HPLM)) with in-situ pollen season dynamics (SPS, PPS, LPS) for three dominant allergenic tree pollen species (birch, oak, and poplar) that dominate the springtime allergy season in North America. Our results showed that irrespective of the data processing method (i.e. DLM vs HPLM), the MODIS-based SOS to be more closely aligned with the in-situ SPS, and PPS while upscaled Landsat based SOS had a better precision. The data products obtained using DLM processing methods tended to perform better than the HPLM based methods. We further showed that MODIS based phenology information along with temperature and latitude can be used to infer in-situ pollen dynamic for tree pollen during spring time. Our findings suggest that satellite-based phenology information may be useful in the development of early warning systems for allergic diseases.
According to WHO, by 2050, at least one person out of two will suffer from an allergy disorder resulting from the accelerating air pollution associated with toxic gas emissions and climate change. Airborne pollen, and associated allergies, are major public health topics during the pollination season, and their effects are further strengthened due to climate change. Therefore, assessing the airborne pollen allergy risk is essential for improving public health. This study presents a new computational fluid dynamics methodology for risk assessment of local airborne pollen transport in an urban environment. Specifically, we investigate the local airborne pollen transport from trees on a university campus in the north of France. We produce risk assessment maps for pollen allergy for five consecutive days during the pollination season. The proposed methodology could be extended to larger built-up areas for different weather conditions. The risk assessment maps may also be integrated with smart devices, thus leading to decision-aid tools to better guide and protect the public against airborne pollen allergy.
BACKGROUND: Climate change is a global health crisis. In most regions, heat waves are expected to become longer and more frequent and air quality is expected to worsen. Few physicians discuss climate and health with patients, and related guidelines are lacking. Our objective was to quantify the prevalence of risk factors for illness related to climate change in the U.S. ambulatory setting. METHODS: From the 2018 National Ambulatory Medical Care Survey, a national probability sample of nonfederal, ambulatory encounters, we identified adults with risk factors for illness related to heat or air pollution exposure. RESULTS: We found 91.4% of encounters involved a patient with at least 1 risk factor, while 46.7% had 2 or more. CONCLUSION: A high prevalence of patients with climate-related health risk factors exists in the ambulatory setting, representing a significant opportunity for evidence-based climate and health patient education and preventative care.
BACKGROUND: Over 3 million people die every year from diseases caused by exposure to outdoor PM(2·5) air pollution, and more than a quarter of these premature deaths occur in China. In addition to clean-air policies that target pollution emissions, climate policies aimed at reducing fossil-fuel CO(2) emissions (eg, to avoid 1·5°C of warming) might also greatly improve air quality and public health. However, no comprehensive accounting of public health outcomes has been done under different energy pathways and local clean-air management decisions in China. We aimed to develop an integrated method for quantifying the health co-benefits from different climate, energy, and clean-air policy scenarios and to assess the relationship between climate and clean-air policies and future health burdens in China, where an ageing population will further exacerbate the effects of air pollution. METHODS: For this modelling study, we used a China-focused integrated assessment model and a dynamic emission projection model to project future Chinese air quality in scenarios spanning a range of global climate targets (1·5°C, 2°C, national determined contributions [NDC], unambitious, baseline, and 4·5°C) and national clean-air actions (termed 2015-pollution, current-pollution, and ambitious-pollution). We then evaluated the health effects of PM(2·5) air pollution in the scenario matrix using the air quality model and the latest epidemiological concentration-response functions from the 2019 Global Burden of Diseases, Injuries, and Risk Factors Study. FINDINGS: We found that, without ambitious climate mitigation (eg, under current NDC pledge), Chinese deaths related to PM(2·5) air pollution might not always decrease-and might often grow-by 2050 compared with the base year of 2015, regardless of clean-air policies and air quality improvements. For example, in the scenario that tracks China’s current NDC pledge and uses the best available pollution control technologies (the ambitious-pollution and NDC goals scenario), PM(2·5)-related deaths in China would decrease slightly by 2030 to 1·23 million per year (95% CI 0·95-1·51) from 1·25 million (1·04-1·46) in 2015, but would not decrease further by 2050 (1·21 million, 0·86-1·60) despite substantial and continuous improvements in population-weighted air quality (from 27·2 μg/m(3) in 2030 to 16·0 μg/m(3) in 2050). The contrary trends of improving air quality and increasing PM(2·5)-related deaths in many of our scenarios revealed the extent to which extra efforts are needed to compensate for the increasing age of China’s population in the future. With the scenarios that included ambitious clean-air policies and met international climate goals to avoid 1·5°C and 2°C of warming (the ambitious-pollution-2°C goals scenario and the ambitious-pollution-1·5°C goals scenario), we observed substantial decreases in China’s PM(2·5)-related deaths of 0·32-0·55 million deaths compared with NDC goals in 2050, and age-standardised death rates decreased by 10·2-14·2 deaths per 100 000 population per year. INTERPRETATION: Our results show that ambitious climate policies (ie, limiting global average temperature rise to well below 2°C) and low-carbon energy transitions coupled with stringent clean-air policies are necessary to substantially reduce the human health effects from air pollution in China, regardless of socioeconomic assumptions. Our findings could help policy makers understand the crucial links between climate policy and public health. FUNDING: The National Natural Science Foundation of China.
OBJECTIVE: To examine respiratory-related ED admissions and presentations at Bathurst Base Hospital during the 2019-2020 New South Wales bushfire crisis. METHODS: A retrospective clinical audit was undertaken. Publicly available data on air quality were also examined. RESULTS: Poorer air quality (measured by PM10 levels) was correlated with increased presentations to the ED (R = 0.228, P = 0.012). ED patients with respiratory diagnoses were more likely to be admitted for inpatient care in 2019-2020 (n = 234, 49.3%) compared with 2018-2019 (n = 165, 39.6%). CONCLUSION: The impact of bushfire smoke needs to be considered in the allocation of resources in this area in future, but further research is warranted to understand the full extent of impact at the local level.
Nitrogen oxides (NOx = NO + NO2) are key precursors of tropospheric ozone (O-3) together with volatile organic compounds (VOC) and carbon monoxide (CO). Since O-3 has positive radiative forcing and is harmful to human health, the reduction of anthropogenic emissions of NOx is thought to be beneficial from the perspectives of climate change and air pollution in principle. However, there have been discussions contending that the reduction of NOx emissions is not necessarily beneficial for the mitigation of climate change and improvement of air quality, since 1) it decreases the atmospheric mixing ratio of hydroxyl radicals (OH), which increases the atmospheric lifetime of methane (CH4), and 2) O-3 formation is VOC-limited in urban areas and the decrease of NOx emission would increases urban O-3 by facilitating the NO titration effect. In order to scrutinize such discussion, literature review have been made on the temporal variations of the increasing rate of tropospheric CH4 in the last 30 years, and on urban/rural O-3 issues related to the NOx-limited/VOC-limited regime. Based on the review, it may be concluded that the variation of emissions of CH4 itself paly a dominant role, and the variation of consumption rate by OH play a minor role for the recent variation of CH4. It has been suggested that NOx and NMVOC should be reduced simultaneously in order to avoid the adverse effect on climate change mitigation. From the review on policy-related discussion of NOx-limited and VOC-limited O-3 formation, the increase of O-3 by the decrease in NOx emissions has generally been seen in winter and nighttime when photochemical production is minimal, and the higher percentile or diurnal maximum mixing ratios of O-3 in summer tends to decrease with the decrease in NOx emissions. We suggested that the NOx-limited/VOC-limited approach is not appropriate as a long-term policy guideline for ozone control, since it is unreasonable that NOx reduction is not recommended when ambient NOx levels are high, while further NOx reduction is recommended only when the VOC/NOx ratio gets high after NOx control has been achieved based on other policy principle. Simultaneous reduction of NOx and NMVOC would be beneficial for reducing global, regional, and urban O-3 to alleviate climate change and human health impacts. The ultimate reduction of anthropogenic emissions of NOx can be envisioned toward a denitrified (de-NOx) society along with a decarbonized (de-CO2) society.
Overall, European air quality has worsened in recent decades as a consequence of increased anthropogenic emissions, in particular from the power generation sector. The evidence of the effects of atmospheric pollution (and particularly fine particulate matter, PM2.5) on human health is now unquestionable; it is mainly associated with cardiovascular and respiratory diseases, along with morbidity and even mortality. These effects may even strengthen in the future as a consequence of climate penalties and future changes in the projected population. For all these reasons, the main objective of this contribution is the estimation of the annual excess premature deaths (PD) associated with PM2.5 in the present (1991-2010) and future (2031-2050) European population using non-linear exposure-response functions. The endpoints included are lung cancer (LC), chronic obstructive pulmonary disease (COPD), low respiratory infections (LRI), ischaemic heart disease (IHD), cerebrovascular disease (CEV) and other non-communicable diseases (other NCD). PM2.5 concentrations come from coupled chemistry-climate regional simulations under present and future (RCP8.5) scenarios. The cases assessed include the estimation of the present incidence of PD (PRE-P2010), the quantification of the role of a changing climate in PD (FUT-P2010) and the importance of changes in the population projected for the year 2050 in the incidence of excess PD (FUT-P2050). Two additional cases (REN80-P2010 and REN80-P2050) evaluate the impact on premature mortality rates of a mitigation scenario in which 80 % of European energy production comes from renewable sources. The results indicate that PM2.5 accounts for nearly 895 000 (95 % confidence interval (95 % CI) 725 000-1 056 000) annual excess PD over Europe, with IHD being the largest contributor to premature mortality associated with fine particles in both present and future scenarios. The case that isolates the effects of a climate penalty (FUT-P2010) estimates a variation of +0.2 % in mortality rates over the whole domain. However, under this scenario, the incidence of PD over central Europe will benefit from a decrease in PM2.5 (-2.2 PD/100 000 inhabitants), while in eastern (+1.3 PD/100 000 inhabitants) and western (+0.4 PD/100 000 inhabitants) Europe, PD will increase due to increased PM2.5 levels. The changes in the projected population (FUT-P2050) will lead to a large increase in annual excess PD (1 540 000, 95 % CI 1 247 000-1 818 000; +71.96 % with respect to PRE-P2010 and +71.67 % with respect to FUT-P2010) due to the ageing of the European population. Last, the mitigation scenario (REN80-P2050) demonstrates that the effects of a mitigation policy of increasing the ratio of renewable sources in the energy mix could lead to a decrease of over 60 000 (95 % CI 48 500-70 900) annual PD for the year 2050 (a decrease of -4 % in comparison with the no-mitigation scenario FUT-P2050). In spite of the uncertainties inherent in future estimations, this contribution reveals the need of governments and public entities to take action and choose air pollution mitigation policies.
BACKGROUND: The evidence between diurnal temperature range (DTR) and stroke remains controversial and sparse. We aimed to assess the relationship between DTR and emergency ambulance dispatches (EADs) due to stroke, and to explore whether there were effect modifications to the relationship. METHODS: A Quasi-Poisson generalized linear regression combined with a distributed lag non-linear model was used to examine the relationship between DTR and EADs for stroke between January 1st 2011 and June 30th 2018 in Guangzhou, China. We estimated the effects of the low DTR and high DTR (defined as DTR below and above 10 °C respectively) on EADs. The effects of minimum, maximum, 5th, 25th, 50th, 75th, and 95th percentiles of DTR compared with the DTR of 10 °C were also analyzed. RESULTS: A total of 20,275 EADs for stroke were included for analyses, among which 17,556 EADs were used in the model further adjusted for age and sex. A quasi-U-shaped relationship between DTR and EADs over lag0-2 days was observed. For the low DTR, per 1 °C decrease in DTR was significantly associated with an increase of 2.64% (RR = 1.03, 95% CI: 1.01-1.04) for EADs, while per 1 °C increase for the high DTR was non-significantly related with an increased risk of EADs (RR = 1.01, 95% CI: 0.90-1.13). Significant effects of the 5th and 25th percentiles of DTR on EADs were found when compared with the DTR of 10 °C. No significant effect modifications by age, sex or season were found to the association between DTR and EADs. CONCLUSIONS: We found a quasi-U-shaped relationship between DTR and EADs due to stroke in this study, while age, sex or season did not significantly modify the association between DTR and EADs. More high-quality evidence is needed to further explore and validate the relationship between DTR and stroke.
As the health impacts of climate change take on a more serious form, this study for the first time investigates the effect of meteorological factors on the risk of death from respiratory diseases (RD) in Wuhu, a representative city along the Yangtze River in subtropical humid region. Daily meteorological element data and RD deaths in Wuhu City were collected from 2014 to 2020. Time series analysis was conducted using distributed lagged nonlinear model (DLNM) combined with generalized additive model (GAM), and stratified by age and gender. In 7 years, a total of 8016 RD death cases were collected in Wuhu, China. The results demonstrated that the maximum impacts of short-term exposure to exceedingly low temperatures mean (Tmean) were at lag 9, with the maximum relative risk (RR) of 1.044 (lag 1, 95% CI: 1.001, 1.098). The risk of exceedingly high Tmean reached its maximum at lag 0 (RR = 1.070, 95% CI: 1.018, 1.125). Low relative humidity (RH) was negatively associated with the risk of RD death, with the lowest RR values occurring at lag 12 (RR = 0.987, 95% CI: 0.975, 0.999). No significant correlation was found for diurnal temperature range (DTR). Stratified analysis showed that Tmean exposure remained statistically significant for male, female and elderly, while RH and DTR only seemed to increase the mortality risk in the young. In a word, short-term exposure to extreme temperatures may increase the RD mortality risk in the population, and young people needed to be aware that exposure to exceedingly high RH and DTR also increased the risk.
Nitrogen (N) is a critical component of food security, economy and planetary health. Human production of reactive nitrogen (Nr) via Haber-Bosch process and cultivation-induced biological N(2) fixation (BNF) has doubled global N cycling over the last century. The most important beneficial effect of Nr is augmenting global food supplies due to increased crop yields. However, increased circulation of Nr in the environment is responsible for serious human health effects such as methemoglobinemia (“blue baby syndrome”) and eutrophication of coastal and inland waters. Furthermore, ammonia (NH(3)) emission mainly from farming and animal husbandary impacts not only human health causing chronic lung disease, inflammation of human airways and irritation of eyes, sinuses and skin but is also involved in the formation of secondary particulate matter (PM) that plays a critical role in environment and human health. Nr also affects human health via global warming, depletion of stratospheric ozone layer resulting in greater intensity of ultra violet B rays (UVB) on the Earth’s surface, and creation of ground-level ozone (through reaction of NO(2) with O(2)). The consequential indirect human health effects of Nr include the spread of vector-borne pathogens, increased incidence of skin cancer, development of cataracts, and serious respiratory diseases, besides land degradation. Evidently, the strategies to reduce Nr and mitigate adverse environmental and human health impacts include plugging pathways of nitrogen transport and loss through runoff, leaching and emissions of NH(3), nitrogen oxides (NO (x) ), and other N compounds; improving fertilizer N use efficiency; reducing regional disparity in access to N fertilizers; enhancing BNF to decrease dependence on chemical fertilizers; replacing animal-based proteins with plant-based proteins; adopting improved methods of livestock raising and manure management; reducing air pollution and secondary PM formation; and subjecting industrial and vehicular NO (x) emission to pollution control laws. Strategic implementation of all these presents a major challenge across the fields of agriculture, ecology and public health. Recent observations on the reduction of air pollution in the COVID-19 lockdown period in several world regions provide an insight into the achievability of long-term air quality improvement. In this review, we focus on complex relationships between Nr and human health, highlighting a wide range of beneficial and detrimental effects.
With global attention, air pollution is believed to have adverse impacts on human health. The provision of air quality performance, therefore, becomes an important problem for people’s well-being. Governments and people are increasingly concerned about air pollution since it impacts human health and sustainable development globally. As nations more industrialized, the pollution level in our environment rises, posing a serious threat to all living beings. Pollution levels rise quickly due to causes such as industry, urbanization, rising population, and automobile usage, all of which harm human health. With all those different pollutants available in the air, dangerous pollutant is Particulate matter PM2.5, which has a diameter of 2.5 micrometers or less and is easily inhaled, can travel deep into our lungs and bloodstream, causing serious health problems. This pollutant is emitted from a variety of sources, the most common of which being industry and automobiles. Air pollution is the most severe environmental issue which causes different diseases to the humans and contributes to global warming. To avoid such a negative imbalance in nature, a pollution monitoring system is critical. This model used to monitor the pollutant PM2.5 in the air which can be easily inhaled by the humans and it can travel deep into our lungs and bloodstream, causing serious health problems. The suggested design comprises a module such as dust sensor, as hardware using Arduino platform and software architecture for remotely monitoring pollution data through a single web-based graphical application which can be used in industrial areas and traffic places to monitor air quality level. Also air pollutant information must be displayed in public places, as every people can get awareness by knowing the pollutants level around them.
OBJECTIVES: To investigate public concerns about the impacts of climate change on people’s health in the UK and their priorities for action by local government. In the UK, local government are responsible for the environmental protection and health of their local population. STUDY DESIGN: Cross-sectional survey. METHODS: An online survey of UK adults aged ≥18 years was conducted in 2021 (n = 4050). Representative quotas were set for gender, age group, ethnic group, educational attainment and location (UK country/England region). Survey participants were asked about their concerns about the health impacts of climate change and, excluding those reporting no concerns, their top priorities for their local government to address. RESULTS: The dominant health concerns related to air pollution and severe floods. These exposures were also identified as the two most important priorities for local government to address. Separate logistic regression models investigated local-level factors that predicted the selection of each priority, taking account of socio-demographic factors. For both outcomes, awareness of the relevant exposure in the local area in the past 12 months doubled the odds of selecting it as a priority (air pollution: OR 2.01, 95%CI 1.71, 2.36; floods: OR 2.16, 95%CI 1.88, 2.48). CONCLUSIONS: The study demonstrates the potential of surveys to capture public priorities for local action on the health impacts of climate change, and to yield clear policy advice on the issues of greatest public concern.
A 16-year-old boy with asthma participated in recovery volunteer work following the 2018 heavy rains in Japan. One month later, he experienced chest pain and dyspnea. Chest computed tomography revealed a cavity with a fungal ball, and Aspergillus fumigatus was detected in his bronchoalveolar lavage fluid. He was treated with voriconazole, but new consolidations appeared rapidly. He also experienced allergic bronchopulmonary aspergillosis. After prednisolone prescription, the consolidations improved; however, his asthma worsened. He underwent partial lung resection to avoid allergens, and his symptoms improved. We must recognize cases of infection after a disaster, especially in patients with chronic respiratory diseases.
The University of Colorado Airborne Solar Occultation Flux (CU AirSOF) instrument conducted the first suborbital carbon monoxide (CO) mass flux measurements on the scale of large wildfires, showing that the destructive fires in northern California in October 2017 emitted 2,040 +/- 316 tonnes CO hr(-1). Pyrogenic estimates from seven satellite-based emission inventories bracket the observed flux, but their range spans a factor of 83. The simulated air quality impacts in the form of ozone and fine particulate matter scale primarily with these uncertain emission amounts, and range from insignificant to very severe. This uncertainty in predicting emissions is reduced to a factor of similar to 2 by the CU AirSOF flux measurements, with potential for future improvements. The uncertainty is primarily the result of uncertain vegetation types and sources of radiative power measurements, and to a lesser extent uncertain emission factors and fire diurnal cycles. Plain Language Summary Wildfire smoke is a major source of air pollution that affects public health and natural areas, but the amounts of vegetation that go up in smoke and the emitted amounts of smoke are not well known, due to a lack of direct measurements. The accuracy of models used to predict smoke impacts on public health in affected communities is significantly impacted by their reliance on uncertain emissions estimates. In this study, a new instrument, the University of Colorado Airborne Solar Occultation Flux (CU AirSOF), measured the amount of carbon monoxide (CO) produced by the destructive fires in northern California during October 2017. These are the first airborne emission measurements on the scale of a large wildfire. The measured CO emissions from the fires fall within the large range among satellite-based emission estimates, reducing the uncertainty in fire emissions. Air quality impacts in the form of ozone (O-3) and fine particulate matter (PM2.5) range from insignificant to very severe, in direct relationship to the uncertain satellite-based emission estimates.
Urban air pollution, known to seriously affect residents’ health, is a growing concern globally. In the past decade, the central-eastern region of China has become one of the most polluted areas in the world. In this study, we used data on PM2.5 and the exposed population, conducted an in-depth analysis using the ERA5 reanalysis dataset and analysis methods (including weather patterns clustering, and Moran’s I, exposure-response relationship). Aiming to identify regional pollution characteristics, meteorological impact mechanisms and the health concerns attributable to PM2.5 in central and eastern China. Through clustering technology, the weather during the study period was clustered into four weather patterns, denoted as T1-T4; among the four weather patterns, T2 and T4 were the main weather patterns in winter. Moreover, we discussed the interannual contribution of changing weather patterns (and their synergy with spatial effects) to PM2.5. The results indicated that, after considering spatial effects, there was a slight increase in the contribution rate of weather patterns to the interannual variations in PM2.5 (maximum increase of 4.1%). The results of health risk assessment revealed that the annual changes in the number of cases of acute and chronic bronchitis and PM2.5 concentrations in each city were correlated. Notably, these findings can provide a reliable reference for promoting optimal air quality in cities, by strengthening mitigation strategies and supporting policymakers to ensure the prevention and control of regional pollutants.
Climate change-related exposures such as flooding and ambient air pollution place people’s health at risk. A representative UK survey of adults investigated associations between reported flooding and air pollution (in the participants’ local area, by the participant personally, and/or by family and close friends) and climate change concerns (CCC) and perceptions of its health impacts (PIH). In regression analyses controlling for socio-demographic factors and health status, exposure was associated with greater CCC and more negative PIH. Compared to those with low CCC, participants who reported local-area exposure were significantly more likely to be fairly (OR 2.07, 95%CI 1.26, 3.40) or very concerned (OR 3.40, 95%CI 2.02, 5.71). Odds of greater CCC were higher for those reporting personal and/or family exposure (‘fairly concerned’: OR 2.83, 95%CI 1.20, 6.66; ‘very concerned’: OR 4.11, 95%CI 1.69, 10.05) and for those reporting both local and personal/family exposure (‘fairly concerned’: OR 3.35, 95%CI 1.99, 5.63; ‘very concerned’: OR 6.17, 95%CI 3.61, 10.55). For PIH, local exposure significantly increased the odds of perceiving impacts as ‘more bad than good’ (1.86, 95%CI 1.22, 2.82) or ‘entirely bad’ (OR 1.88; 95%CI 1.13, 3.13). Our study suggests that public awareness of climate-related exposures in their local area, together with personal exposures and those of significant others, are associated with heightened concern about climate change and its health impacts.
Projecting future air pollution and related health burdens remains challenging because of the complex interactions among future emissions, population, and climate change. In this study, we estimated the premature deaths attributed to ambient fine particulate matter (PM(2.5)) and ozone (O(3)) from 2015 to 2100 under four socioeconomic climate scenarios based on an age-stratified assessment method. We found that PM(2.5) will decrease in all shared socioeconomic pathway (SSP) scenarios and O(3) will decrease in the SSP1-2.6 and SSP2-4.5 scenarios, contributing to a decrease in premature mortality together with the declining total population in China. However, the benefits of a decline in population size and PM(2.5) and O(3) concentrations over time will be largely offset by population aging, and premature death caused by PM(2.5) and O(3) will continue to rise till 2060-2080. This impact was greater for the O(3)-related deaths than those for PM(2.5). Our study highlights the importance of future prevention strategies that must jointly improve air quality and susceptibility to aging.
Many children in India face the double burden of high exposure to ambient (AAP) and household air pollution, both of which can affect their linear growth. Although climate change mitigation is expected to decrease AAP, climate policies could increase the cost of clean cooking fuels. Here, we develop a static microsimulation model to project the air pollution-related burden of child stunting in India up to 2050 under four scenarios combining climate change mitigation (2 degrees C target) with national policies for AAP control and subsidised access to clean cooking. We link data from a nationally representative household survey, satellite-based estimates of fine particulate matter (PM2.5), a multi-dimensional demographic projection and PM2.5 and clean cooking access projections from an integrated assessment model. We find that the positive effects on child linear growth from reductions in AAP under the 2 degrees C Paris Agreement target could be fully offset by the negative effects of climate change mitigation through reduced clean cooking access. Targeted AAP control or subsidised access to clean cooking could shift this trade-off to result in net benefits of 2.8 (95% uncertainty interval [UI]: 1.4, 4.2) or 6.5 (UI: 6.3, 6.9) million cumulative prevented cases of child stunting between 2020-50 compared to business-as-usual. Implementation of integrated climate, air quality, and energy access interventions has a synergistic impact, reducing cumulative number of stunted children by 12.1 (UI: 10.7, 13.7) million compared to business-as-usual, with the largest health benefits experienced by the most disadvantaged children and geographic regions. Findings underscore the importance of complementing climate change mitigation efforts with targeted air quality and energy access policies to concurrently deliver on carbon mitigation, health and air pollution and energy poverty reduction goals in India.
Objective: The environmental crisis we are experiencing is becoming a more popular topic of expert discussion and analysis. Human activity and expansion on the planet are exacerbating climate change and global warming, this, together with the increase in plastic production, and general pollution, posing a threat to our resources, supplies, and survival. This research aims to review what is known about the association between pollution and pregnancy and sensitize experts to women’s education towards healthier behaviors. Mechanism: We chose to focus on the effects of the environment on fetal development and maternal health, considering various studies that highlight the potential consequences of exposure to certain environmental stressors. The paper briefly illustrates the probable mechanisms that, starting from cellular and intracellular damage, determined above all by plastics, lead to chronic activation of the immune system in response to danger and. therefore, to epigenetic modifications at the base of diseases in adulthood. Findings in Brief: We describe the effects of the main pollutants on pregnancy, with particular attention to the role of plastic. Finally, we briefly outline some individual possible solutions to this complex problem. Conclusions: In the era of environmental crisis, becoming aware of the mechanisms behind biological damage resulting from exposure to certain pollutants and plastics, especially in a period as sensitive as pregnancy, should be the driving force behind a change of direction. As physicians, this means educating our patients and recommending individual solutions to reduce the impact of contaminants to provide the best possible environment for women’s and children’s health, especially during the delicate period of pregnancy; but the ultimate solution is to drastically reduce global plastic production and pollution, and to recycle the plastic that is needed anyway.
Sustainable development and climate change mitigation can provide enormous public health benefits via improved air quality, especially in polluted areas. We use the latest state-of-the-art composition-climate model simulations to contrast human exposure to fine particulate matter in Africa under a “baseline” scenario with high material consumption, population growth, and warming to that projected under a sustainability scenario with lower consumption, population growth, and warming. Evaluating the mortality impacts of these exposures, we find that under the low warming scenario annual premature deaths due to PM(2.5) are reduced by roughly 515,000 by 2050 relative to the high warming scenario (100,000, 175,000, 55,000, 140,000, and 45,000 in Northern, West, Central, East, and Southern Africa, respectively). This reduction rises to ∼800,000 by the 2090s, though by that time much of the difference is attributable to the projected differences in population. By contrast, during the first half of the century benefits are driven predominantly by emissions changes. Depending on the region, we find large intermodel spreads of ∼25%-50% in projected future exposures owing to different physics across the ensemble of 6 global models. The spread of projected deaths attributable to exposure to fine particulate matter, including uncertainty in the exposure-response function, are reduced in every region to ∼20%-35% by the non-linear exposure-response function. Differences between the scenarios have an even narrower spread of ∼5%-25% and are highly statistically significant in all regions for all models. These results provide valuable information for policy-makers to consider when working toward climate change mitigation and sustainable development goals.
Coccidioidomycosis (Valley fever) is a disease caused by the fungal pathogens Coccidioides immitis and Coccidioides posadasii that are endemic to the southwestern United States and parts of Mexico and South America. Throughout the range where the pathogens are endemic, there are seasonal patterns of infection rates that are associated with certain climatic variables. Previous studies that looked at annual and monthly relationships of coccidioidomycosis and climate suggest that infection numbers are linked with precipitation and temperature fluctuations; however, these analytic methods may miss important nonlinear, nonmonotonic seasonal relationships between the response (Valley fever cases) and explanatory variables (climate) influencing disease outbreaks. To improve our current knowledge and to retest relationships, we used case data from three counties of high endemicity in southern Arizona paired with climate data to construct a generalized additive statistical model that explores which meteorological parameters are most useful in predicting Valley fever incidence throughout the year. We then use our model to forecast the pattern of Valley fever cases by month. Our model shows that maximum monthly temperature, average PM10, and total precipitation 1 month prior to reported cases (lagged model) were all significant in predicting Valley fever cases. Our model fits Valley fever case data in the region of endemicity of southern Arizona and captures the seasonal relationships that predict when the public is at higher risk of being infected. This study builds on and retests relationships described by previous studies regarding climate variables that are important for predicting risk of infection and understanding this fungal pathogen. IMPORTANCE The inhalation of environmental infectious propagules from the fungal pathogens Coccidioides immitis and Coccidioides posadasii by susceptible mammals can result in coccidioidomycosis (Valley fever). Arizona is known to be a region where the pathogen is hyperendemic, and reported cases are increasing throughout the western United States. Coccidioides spp. are naturally occurring fungi in arid soils. Little is known about ecological factors that influence the growth of these fungi, and a higher environmental burden may result in increases in human exposure and therefore case rates. By examining case and climate data from Arizona and using generalized additive statistical models, we were able to examine the relationship between disease outbreaks and climatic variables and predict seasonal time points of increased infection risk.
Airborne pollens are one of the common causative and triggering agents of respiratory allergy in a changing planetary environment. A growing number of people worldwide are contracting allergic diseases caused by pollens. The seasonal variations in pollens have occurred everywhere and the sensitization rate to pollens has increased in children as well as in adults. Moreover, allergenic plants, such as ragweed and Japanese hop, grow in soil damaged by human’s activities and deforestation with air pollution. It is impossible to avoid plants that cause allergies, because pollens can travel many kilometers in the breeze or wind. Hence, it is essential to survey and forecast pollens for the management of pollen allergy. Weather conditions may alter pollen concentrations. A number of studies have shown that increases in CO(2) concentration and atmospheric temperature raise pollen concentration. Hence most of the studies on the impact of climate change on aeroallergens must include the amount and allergenicity of pollens. It is yet unknown whether complex interactions with pollens, meteorological variables, and air pollutants in the changing environment. Considering the effect of climate change on the long-term trends in pollen levels and emerging viral infection, it is crucial to forecast and eliminate the associated risk for human health in future and take appropriate measures to reduce it.
Pollen allergy is considered a major public health problem that causes morbidity and subsequently affects a patient’s quality of life. Pollen due to their large size cannot enter the thoracic regions of the respiratory tract but can affect the nasopharyngeal mucous membrane. At the same time, the submicronic-pollen particles can act as respirable particles reaching deeper into the upper airways leading to exacerbation of asthma, chronic obstructive pulmonary disease (COPD) and other allergic reactions. Based on the existing literature, expanding evidence shows that climate change and air pollutants could affect the pollen number, morphology, season, allergen content, and distribution pattern. Hence, this will influence the prevalence and occurrence of allergies linked to pollen exposure. Being a part of biogenic pollutants, pollen allergens are not expected to diminish in the foreseeable future. Therefore, it is imperative that steps need to be strengthened to improve and optimize preventive/adaptive strategies. This paper aims to review the major causes of widespread allergy, identify the major gaps, and suggest key preventive/adaptive measures to address the onset and exacerbation of pollen-related allergic diseases with a major focus on lower and middle-income countries. The study also discusses how-to implement the prevention and control measures at the individual, health care communities and organizations, Local Governments, National/International Governments levels to decrease the risk of illnesses associated with pollen allergy.
Secondary food allergies due to cross-reactivity between pollen and plant food allergens are a significant and increasingly global health issue. The term ‘pollen-food allergy syndrome’ (PEAS) defines a series of clinical symptoms in pollen-sensitised patients after the ingestion of plant-derived food. The symptoms of PEAS range from localised oral symptoms to severe systemic reactions. The exact prevalence of PEAS is uncertain for various reasons, including a wide geographical distribution and the lack of standardised population-based studies. Three highly conserved protein classes responsible for most PFAS cases are the profilin, the pathogenesis-related protein group 10 (PR-10) and non-specific lipid transfer proteins (nsLTPs). It has been postulated that climate change, pollution and agricultural practices may increase the expression of these and other defence proteins in plants, causing an increase in allergen load exposure. With advances in component-resolved diagnostic testing, the role of these other allergens can now be revealed. The diagnosis of PFAS is multifaceted and includes a comprehensive clinical history focusing on inhalant allergy and potential cross-reactivities combined with different in vitro and in vivo tests. A better understanding of the cross-reacting allergens and their characteristics may create an awareness of this allergy syndrome essential to managing such patients correctly.
The incidences of respiratory allergies are at an all-time high. Pollen aeroallergens can reflect changing climate, with recent studies in Europe showing some, but not all, pollen types are increasing in severity, season duration and experiencing an earlier onset. This study aimed to identify pollen trends in the UK over the last twenty-six years for a range of pollen sites, with a focus on the key pollen types of Poaceae (grass), Betula (birch) and Quercus (oak) and to examine the relationship of these trends with meteorological factors. Betula pollen seasons show no significant trends for onset, first high day or duration but increasing pollen production in the Midlands region of the UK is being driven by warmer temperatures in the previous June and July. Quercus pollen seasons are starting earlier, due to increasing temperature and sunshine totals in April, but are not becoming more severe. The seasons are lasting longer, although no significant climate drivers for this were identified. The first high day of the Poaceae pollen season is occurring earlier in central UK regions due to an increasing trend for all temperature variables in the previous December, January, April, May and June. Severity and duration of the season show no significant trends and are spatially and temporally variable. Important changes are occurring in the UK pollen seasons that will impact on the health of respiratory allergy sufferers, with more severe Betula pollen seasons and longer Quercus pollen seasons. Most of the changes identified were caused by climate drivers of increasing temperature and sunshine total. However, Poaceae pollen seasons are neither becoming more severe nor longer. The reasons for this included a lack of change in some monthly meteorological variables, or land-use change, such as grassland being replaced by urban areas or woodland.
Pollen is responsible for seasonal allergies, such as allergic rhino-conjunctivitis (AR), and has become a growing public health concern. Climate change affects the range of allergenic species as well as the timing and length of the pollen season. In Egypt, data on pollinosis are scarce. This study aimed to identify the most prevalent pollen causing allergies among Egyptian patients with respiratory allergies. A total of 200 patients with respiratory allergic diseases, allergic rhinitis and/or bronchial asthma (BA), were included. Medical history taking and physical examinations were conducted on each patient. Complete blood count (CBC), total immunoglobulin E (IgE) determination, spirometry, specific IgE, and skin prick tests (SPTs) for common aeroallergens and food were performed. Of the 200 patients, 106 (53%) were females. The age of study subjects ranged 16-66 years (mean ± SD, 34.42 ± 13.0), and 65% were living in urban areas. Grass pollen, mainly from Timothy grass and maize, were the most prevalent allergens (28.5%). Timothy grass was the most common type of pollen in patients with AR (28.3 %). Elder pollen was more prevalent among asthmatic patients (P = 0.004). Bermuda grass was statistically more prevalent in rural than in urban areas (P = 0.008). Maize was linked to uncontrolled BA, whereas Timothy grass was the most prevalent among patients with moderate/severe AR. Forty-three patients had oral allergy syndrome; oranges and tomatoes were the most cross-reactive food allergies (12% and 11.5%, respectively). Exacerbation of allergic symptoms was noted during January, December, March, and June. In conclusion, pollen plays a substantial role in affecting patients with respiratory allergies in Egypt. Grass pollen is the most prevalent type of pollen, especially in urban areas.
The Lancet Commission on pollution and health reported that pollution was responsible for 9 million premature deaths in 2015, making it the world’s largest environmental risk factor for disease and premature death. We have now updated this estimate using data from the Global Burden of Diseases, Injuriaes, and Risk Factors Study 2019. We find that pollution remains responsible for approximately 9 million deaths per year, corresponding to one in six deaths worldwide. Reductions have occurred in the number of deaths attributable to the types of pollution associated with extreme poverty. However, these reductions in deaths from household air pollution and water pollution are offset by increased deaths attributable to ambient air pollution and toxic chemical pollution (ie, lead). Deaths from these modern pollution risk factors, which are the unintended consequence of industrialisation and urbanisation, have risen by 7% since 2015 and by over 66% since 2000. Despite ongoing efforts by UN agencies, committed groups, committed individuals, and some national governments (mostly in high-income countries), little real progress against pollution can be identified overall, particularly in the low-income and middle-income countries, where pollution is most severe. Urgent attention is needed to control pollution and prevent pollution-related disease, with an emphasis on air pollution and lead poisoning, and a stronger focus on hazardous chemical pollution. Pollution, climate change, and biodiversity loss are closely linked. Successful control of these conjoined threats requires a globally supported, formal science-policy interface to inform intervention, influence research, and guide funding. Pollution has typically been viewed as a local issue to be addressed through subnational and national regulation or, occasionally, using regional policy in higher-income countries. Now, however, it is increasingly clear that pollution is a planetary threat, and that its drivers, its dispersion, and its effects on health transcend local boundaries and demand a global response. Global action on all major modern pollutants is needed. Global efforts can synergise with other global environmental policy programmes, especially as a large-scale, rapid transition away from all fossil fuels to clean, renewable energy is an effective strategy for preventing pollution while also slowing down climate change, and thus achieves a double benefit for planetary health.
The aim of the study was to analyze the temporal trends, pollution sources, and carcinogenic health risks associated with PM2.5-bound arsenic (As). A total of 588 PM2.5 samples were collected in Jinan during January 2014-December 2020. The content and distribution characteristics were determined for As and Al in PM2.5, and the pollution sources were identified based on enrichment factors (EFs). The health risk of inhalation exposure to As was estimated using the risk assessment methods recommended by the United States Environmental Protection Agency (US EPA). The annual average concentration of As in PM2.5 was 4.5-17.5 ng m(-3), which was 0.8-2.9 times higher than the limit ruled by the European Union and China’s Ambient Air Quality Standards (6 ng m(-3)). From 2014 to 2020, the As concentration gradually decreased from 17.5 to 4.9 ng m(-3). After 2017, the concentration was close to the level required by the atmospheric quality standard (6 ng m(-3)). The PM2.5 and arsenic concentrations in the heating season were significantly higher than those in the non-heating season. The EF of As ranged from 144 to 607, which was higher than 10. The cancer risk of As in PM2.5 decreased to the lowest values (heating season 1.0 x 10(-5) and non-heating season 7.1 x 10(-6), respectively) in 2019. As in Jinan mainly came from anthropogenic pollution. The level of As pollution has been significantly reduced in recent years, but there is still a high risk of carcinogenesis. Air pollution control strategies and guidelines need to be implemented in urban areas, especially during the heating season in winter and spring.
Polycyclic aromatic hydrocarbons (PAHs) are a class of chemicals of considerable environmental significance. PAHs are chemical contaminants of fused carbon and hydrogen aromatic rings, basically white, light-yellow, or solid compounds without color. Natural sources of pollution are marginal or less significant, such as volcanic eruptions, natural forest fires, and moorland fires that trigger lightning bursts. The significant determinants of PAH pollution are anthropogenic pollution sources, classified into four groups, i.e., industrial, mobile, domestic, and agricultural pollution sources. Humans can consume PAHs via different routes, such as inhalation, dermal touch, and ingestion. The Effect of PAHs on human health is primarily based on the duration and route of exposure, the volume or concentration of PAHs to which one is exposed, and the relative toxicity of PAHs. Many PAHs are widely referred to as carcinogens, mutagens, and teratogens and thus pose a significant danger to human health and the well-being of humans. Skin, lung, pancreas, esophagus, bladder, colon, and female breast are numerous organs prone to tumor development due to long-term PAH exposure. PAH exposure may increase the risk of lung cancer as well as cardiovascular disease (CVD), including atherosclerosis, thrombosis, hyper-tension, and myocardial infarction (MI). Preclinical studies have found a relationship between PAH exposure, oxidative stress, and atherosclerosis. In addition, investigations have discovered a relationship between PAH exposure at work and CVD illness and mortality development. This review aims to explain PAH briefly, its transportation, its effects on human health, and a relationship between environmental exposures to PAHs and CVD risk in humans.
Climate change is one of the greatest global threats for planetary and human health. This leads to new challenges for public health. Hospitals emit large amounts of greenhouse gases (GHG) in their healthcare delivery through transportation, waste and other resources and are considered as key players in reducing healthcare’s environmental footprint. The aim of this scoping review is to provide the state of research on hospitals’ carbon footprint and to determine their contribution to mitigating emissions. We conducted a systematic literature search in three databases for studies related to measurement and actions to reduce GHG emissions in hospitals. We identified 21 studies, the oldest being published in 2012, and the most recent study in 2021. Eight studies focused on GHG emissions hospital-wide, while thirteen studies addressed hospital-based departments. Climate actions in the areas of waste and transportation lead to significant reductions in GHG emissions. Digital transformation is a key factor in implementing climate actions and promoting equity in healthcare. The increasing number of studies published over time indicates the importance of the topic. The results suggest a need for standardization of measurement and performance indicators on climate actions to mitigate GHG emissions.
Circadian rhythms are a series of endogenous autonomous oscillators that are generated by the molecular circadian clock which coordinates and synchronizes internal time with the external environment in a 24-h daily cycle (that can also be shorter or longer than 24 h). Besides daily rhythms, there exist as well other biological rhythms that have different time scales, including seasonal and annual rhythms. Circadian and other biological rhythms deeply permeate human life, at any level, spanning from the molecular, subcellular, cellular, tissue, and organismal level to environmental exposures, and behavioral lifestyles. Humans are immersed in what has been called the “circadian landscape,” with circadian rhythms being highly pervasive and ubiquitous, and affecting every ecosystem on the planet, from plants to insects, fishes, birds, mammals, and other animals. Anthropogenic behaviors have been producing a cascading and compounding series of effects, including detrimental impacts on human health. However, the effects of climate change on sleep have been relatively overlooked. In the present narrative review paper, we wanted to offer a way to re-read/re-think sleep medicine from a planetary health perspective. Climate change, through a complex series of either direct or indirect mechanisms, including (i) pollution- and poor air quality-induced oxygen saturation variability/hypoxia, (ii) changes in light conditions and increases in the nighttime, (iii) fluctuating temperatures, warmer values, and heat due to extreme weather, and (iv) psychological distress imposed by disasters (like floods, wildfires, droughts, hurricanes, and infectious outbreaks by emerging and reemerging pathogens) may contribute to inducing mismatches between internal time and external environment, and disrupting sleep, causing poor sleep quantity and quality and sleep disorders, such as insomnia, and sleep-related breathing issues, among others. Climate change will generate relevant costs and impact more vulnerable populations in underserved areas, thus widening already existing global geographic, age-, sex-, and gender-related inequalities.
Evidence for an association between the amount of particulate matter (PM) in the atmosphere and vitamin D status of pregnant women is limited. We aimed to examine the independent association between PM and maternal levels of serum 25-hydroxyvitamin D (25OHD) during the second trimester and to explore possible modifications to the association by meteorological factors. 27,768 pregnant women presenting for prenatal examination who were tested for serum 25OHD concentration during the second trimester between January 1, 2016, and December 31, 2020, were included in this retrospective analysis. Exposure to PM was evaluated based on daily average PM with an aerodynamic diameter of ≤ 2.5 μm (PM(2.5)) and PM with an aerodynamic diameter of ≤ 10 μm (PM(10)). Corresponding meteorological data for daily average atmospheric temperature, atmospheric pressure, relative humidity, sunshine duration, and wind speed were collected. The maximum cumulative effects of PM(2.5) occurred at lag 45 days, and the maximum cumulative effects of PM(10) occurred at lag 60 days. In crude models, 45-day moving daily average PM(2.5) concentrations were negatively associated with 25OHD levels (β, - 0.20; 95% CI - 0.21 to - 0.19), as were 60-day moving daily average PM(10) concentrations (β, - 0.14; 95% CI - 0.15 to - 0.14). After adjusting for temporal and meteorological factors, the effect values were drastically reduced (adjusted β of PM(2.5), - 0.032; 95% CI - 0.046 to - 0.018; adjusted β of PM(10), - 0.039; 95% CI - 0.049 to - 0.028). Our study showed there was a small, independent, negative association between PM in the atmosphere and maternal serum 25OHD levels during the second trimester of pregnancy after adjusting for temporal and/or meteorological factors, which indicates that PM may have a limited influence on maternal serum 25OHD levels. Besides taking vitamin D supplements, pregnant women should keep participating in outdoor activities while taking PM protection measures to improve their vitamin D levels when PM levels are high in winter and spring.
BACKGROUND: Air pollution is a major health burden and the leading environmental risk factor for non-communicable diseases worldwide. People’s perceptions and concerns about air pollution are important as they may predict protective behaviour or support for climate change mitigation policies. METHODS: This repeat cross-sectional study uses survey data collected from participants in Sydney, Australia in September-November 2019 (n = 1,647) and October-December 2020 (n = 1,458), before and after the devastating 2019/2020 bushfires and first COVID-19 lockdown restrictions in Sydney in 2020. Participants’ perceptions of air quality and concerns for health in relation to air quality were modeled against estimates of annual average NO(2) and PM(2.5) concentrations in their neighbourhood. RESULTS: Participants in suburbs with higher estimated air pollution concentrations generally perceived poorer air quality and were more concerned for health in relation to air quality. A 5 µg/m(3) increase in NO(2) was associated with perceived poorer air quality (OR 1.32, 95%CI 1.18-1.47). A 1 µg/m(3) increase in estimated PM(2.5) was associated with perceived poorer air quality (OR 1.37, 95%CI 1.24-1.52) and greater concern for health (OR 1.18, 95%CI 1.05-1.32). Air quality was perceived as better in 2020 than in 2019 in both NO(2) and PM(2.5) models (p<0.001). Air quality concern increased in 2020 in both models. DISCUSSION: This study provides the first Australian data on the association between estimated air quality exposure and air quality perceptions and concerns, contributing new evidence to inform public health approaches that increase awareness for air pollution and reduce the health burden.
Agricultural subsidies are an important factor for influencing food production and therefore part of a food system that is seen as neither healthy nor sustainable. Here we analyse options for reforming agricultural subsidies in line with health and climate-change objectives on one side, and economic objectives on the other. Using an integrated modelling framework including economic, environmental, and health assessments, we find that on a global scale several reform options could lead to reductions in greenhouse gas emissions and improvements in population health without reductions in economic welfare. Those include a repurposing of up to half of agricultural subsidies to support the production of foods with beneficial health and environmental characteristics, including fruits, vegetables, and other horticultural products, and combining such repurposing with a more equal distribution of subsidy payments globally. The findings suggest that reforming agricultural subsidy schemes based on health and climate-change objectives can be economically feasible and contribute to transitions towards healthy and sustainable food systems.
Climate change, environmental pollution, and virus epidemics have sharply increased the number of patients suffering from respiratory diseases in recent years. Prolonged periods of illness and drug use increase the occurrence of complications in these patients. Osteoporosis is the common bone metabolism disease with respiratory disturbance, which affects prognosis and increases mortality of patients. The problem of osteoporosis in patients with respiratory diseases needs more attention. In this review, we concluded the characteristics of osteoporosis in some respiratory diseases including COPD, asthma, COVID-19, tuberculosis, and lung cancer. We revealed that hypoxia was the common pathogenesis of osteoporosis secondary to respiratory diseases, with malnutrition and corticosteroid abuse driving the progression of osteoporosis. Hypoxia-induced ROS accumulation and activated HIF-1α lead to attenuated osteogenesis and enhanced osteoclastogenesis in patients with respiratory diseases. Tuberculosis and cancer also invaded bone tissue and reduced bone strength by direct infiltration. For the treatment of osteoporosis in respiratory patients, oral-optimized bisphosphonates were the best treatment modality. Vitamin D was a necessary supplement, both for calcium absorption in osteogenesis and for improvement of respiratory lesions. Reasonable adjustment of the dose and course of corticosteroids according to the etiology and condition of patients is beneficial to prevent the occurrence and development of osteoporosis. Additionally, HIF-1α was a potential target for the treatment of osteoporosis in respiratory patients, which could be activated under hypoxia condition and involved in the process of bone remodeling.
Wildfire activity is increasing in parts of the world where extreme drought and warming temperatures contribute to fireprone conditions, including the western United States. The elderly are among the most vulnerable, and those in long-term care with preexisting conditions have added risk for adverse health outcomes from wildfire smoke exposure. In this study, we report continuous co-located indoor and outdoor fine particulate matter (PM(2.5) ) measurements at four skilled nursing facilities in the western United States. Throughout the year 2020, over 8000 h of data were collected, which amounted to approximately 300 days of indoor and outdoor sampling at each facility. The highest indoor 24 h average PM(2.5) recorded at each facility was 43.6 µg/m(3) , 103.2 µg/m(3) , 35.4 µg/m(3) , and 202.5 µg/m(3) , and these peaks occurred during the wildfire season. The indoor-to-outdoor PM(2.5) ratio and calculated infiltration efficiencies indicated high variation in the impact of wildfire events on Indoor Air Quality between the four facilities. Notably, infiltration efficiency ranged from 0.22 to 0.76 across the four facilities. We propose that this variability is evidence that PM(2.5) infiltration may be impacted by modifiable building characteristics and human behavioral factors, and this should be addressed in future studies.
Wildfires have increased in frequency and magnitude and pose a significant public health challenge. The principal objective of this study was to assess the impact of wildfire smoke on respiratory peak flow performance of patients exposed to two different wildfire events. This longitudinal study utilized an observational approach and a cohort study design with a patient-level clinical dataset from a local outpatient allergy clinic (n = 842). Meteorological data from a local weather station served as a proxy for smoke exposure because air quality measurements were not available. This study found that there were decreases in respiratory peak flow among allergy clinic patients one year after each wildfire event. For every one percent increase in wind blowing from the fire towards the community, there was, on average, a 2.21 L per minute decrease in respiratory peak flow. This study observed an effect on respiratory peak flow performance among patients at a local allergy clinic one year after suspected exposure to wildfire smoke. There are likely multiple reasons for the observation of this relationship, including the possibility that wildfire smoke may enhance allergic sensitization to other allergens or that wildfire smoke itself may elicit a delayed immune response.
BACKGROUND: There is a discourse on whether air pollution mixture or air pollutant components are causally linked to increased mortality. In particular, there is uncertainty on whether the association of NO(2) with mortality is independent of fine particulate matter (PM(2.5)). Furthermore, effect modification by temperature on air pollution-related mortality also needs more evidence. METHODS: We used the Chinese Longitudinal Healthy Longevity Study (CLHLS), a prospective cohort with geographical and socio-economic diversity in China. The participants were enrolled in 2008 or 2009 and followed up in 2011-2012, 2014, and 2017-2018. We used remote sensing and ground monitors to measure nitrogen dioxide (NO(2)), fine particulate matter (PM(2.5)) , and temperature. We used the Cox-proportional hazards model to examine the association between component and composite air pollution and all-cause mortality, adjusted for demographic characteristics, lifestyle, geographical attributes, and temperature. We used the restricted cubic spline to visualize the concentration-response curve. RESULTS: Our study included 11 835 individuals with an average age of
A large population in China has been exposed to both severe ozone (O-3) pollution and extreme heat under global warming. Here, the spatiotemporal characteristics of coupled extremes in surface O-3 and heat (OPCs) over China are investigated using surface observations, a process-based chemical transport model (GEOS-Chem), and multi-model simulations from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). North China Plain (NCP; 37-41 degrees N; 114-120 degrees E) is identified as a hot spot of OPCs, where more than half of the O-3 pollution days are accompanied by high temperature extremes. OPCs over NCP exceeded 40 d during 2014-2019, exhibiting an increasing trend. Both O-3 concentrations and temperatures are elevated during OPCs compared with O-3 pollution days occurring individually (OPIs). Therefore, OPCs impose more severe health impacts to humans than OPIs, but the stronger health effects are mainly driven by the higher temperatures. GEOS-Chem simulations further reveal that enhanced chemical production resulting from hot and stable atmospheric conditions under anomalous weather patterns primarily contributes to the exacerbated O-3 levels during OPCs. In the future, CMIP6 projections suggest increased occurrences of OPCs over NCP in the middle of this century, but by the end of this century, OPCs may decrease or increase depending on the pollutant emission scenarios. However, for all future scenarios, extreme high temperatures will play an increasingly important role in modulating O-3 pollution in a warming climate.
Greenhouse gases are a global problem due to their dangerous impacts on the human health and environment. Climate change is the main result of greenhouse gases emissions which cause severe weather conditions, droughts, wild-fires, disruption of eco-system, floods, pollution of air, disturbance of food supply system and extinction of animal species. The main sources of greenhouse gases are fossil fuels combustion in manufacturing such as cement manufacturing, agriculture activities and deforestation. Greenhouse gases consist of many gases; the most important greenhouse gases are Carbon Dioxide (Co2), Methane, Nitrous oxide, fluorinated gases including ChloroFluoroCarbon, HydroFlouroCarbon, Sulfur Hexafluoride and Nitrogen Trifluoride. The aim of this study is to sort greenhouse gases based on their impacts on human and environment, radiative forcing and atmospheric life time using Multi criteria DecisionAnalysis (MCDA). Fuzzy PROMETHEE method was used for sorting; it’s a combination between PROMETHEE method and Fuzzy logic to consider ambiguous conditions. The results of the analysis sort Nitrogen Trifluoride as the first gas because it has less impacts on human and environment with less radiative forcing. Sulfur Hexafluoride, HydroFlouroCarbon and ChloroFluoroCarbon were sorted on second, third and fourth position. Carbon dioxide was sorted as the last gas because it has the worst impacts on human and environment due to high radiative forcing.
Exercising outdoors, in a polluted environment, can cause adverse health effects for people. Therefore, it is important to know the levels of pollutants in the environment in which the exercise is carried out. This article applies the Clustering technique to generate a recommendation system of hours of the day in which it is possible to perform physical activities, reducing the damage to health, considering the levels of pollutants present in the environment. A dataset provided by the Monitoring Network of the Public Mobility, Transit and Transport Company (EMOV EP) of Cuenca, Ecuador, was used. The results show that through an unsupervised learning data mining technique such as clustering, a recommendation system can be implemented. This system generates a range of time within physical activities are suggested to be performed, reducing the negative impact on people’s health of high levels of pollutants and meteorological variables present in the environment.
More recurrent heat waves and extreme ozone (O(3)) episodes are likely to occur during the next decades and a key question is about the concurrence of those hazards, the atmospheric patterns behind their appearance, and their joint effect on human health. In this work, we use surface maximum temperature and O(3) observations during extended summers in two cities from Morocco: Casablanca and Marrakech, between 2010 and 2019. We assess the connection between these data and climate indices (North Atlantic Oscillation (NAO), Mediterranean Oscillation (MO), and Saharan Oscillation (SaO)). We then identify concurrent heat waves and O(3) episodes, the weather type behind this concurrence, and the combined health risks. Our findings show that the concurrence of heat waves and O(3) episodes depends both on the specific city and the large-scale atmospheric circulation. The likely identified synoptic pattern is when the country is under the combined influence of an anticyclonic area in the north and the Saharan trough extending the depression centered in the south. This pattern generates a warm flow and may foster photochemical pollution. Our study is the first step toward the establishment of an alert system. It will help to provide recommendations for coping with concurrent heat waves and air pollution episodes.
Exposure of humans to high concentrations of PM2.5 has adverse effects on their health. Researchers estimate that exposure to particulate matter from fossil fuel emissions accounted for 18% of deaths in 2018-a challenge policymakers argue is being exacerbated by the increase in the number of extreme weather events and rapid urbanization as they tinker with strategies for reducing air pollutants. Drawing on a number of ensemble machine learning methods that have emerged as a result of advancements in data science, this study examines the effectiveness of using ensemble models for forecasting the concentrations of air pollutants, using PM2.5 as a representative case. A comprehensive evaluation of the ensemble methods was carried out by comparing their predictive performance with that of other standalone algorithms. The findings suggest that hybrid models provide useful tools for PM2.5 concentration forecasting. The developed models show that machine learning models are efficient in predicting air particulate concentrations, and can be used for air pollution forecasting. This study also provides insights into how climatic factors influence the concentrations of pollutants found in the air.
This review highlights the importance of air quality in the African urban development process. We address connections between air pollution and (a) rapid urbanization, (b) social problems, (c) health impacts, (d) climate change, (e) policies, and (f) new innovations. We acknowledge that air pollution levels in Africa can be extremely high and a serious health threat. The toxic content of the pollution could relate to region-specific sources such as low standards for vehicles and fuels, cooking with solid fuels, and burning household waste. We implore the pursuit of interdisciplinary research to create new approaches with relevant stakeholders. Moreover, successful air pollution research must regard conflicts, tensions, and synergies inherent to development processes in African municipalities, regions, and countries. This includes global relationships regarding climate change, trade, urban planning, and transportation. Incorporating aspects of local political situations (e.g., democracy) can also enhance greater political accountability and awareness about air pollution.
Using new satellite data from the European Space Agency’s Sentinel-5P system, this article investigates the spatial and temporal dynamics of vehicular traffic congestion, air pollution, and the distributional impacts on vulnerable populations in Dar es Salaam, Tanzania. The metro region’s rapid growth in vehicle traffic exceeds road network capacity, generating congestion, transport delays, and air pollution from excess fuel use. Dangerously high pollution levels from tailpipe emissions put the health of vulnerable residents at risk, calling for the need to adopt continuous air-quality monitoring and effective pollution control. Our results highlight significant impacts of seasonal weather and wind-speed factors on the spatial distribution and intensity of air pollution from vehicle emissions, which vary widely by area. In seasons when weather factors maximize pollution, the worst exposure occurs along the wind path of high-traffic roadways. The study identifies priority areas for reducing congestion to yield the greatest exposure reduction for young children and the elderly in poor households. This new research direction, based only on the use of free global information sources with the same coverage for all cities, offers metropolitan areas in developing regions the opportunity to benefit from the rigorous analyses traditionally limited to well-endowed cites in developing countries.
Externalities, such as air pollution and increased occupational hazards, resulting from global trends in climate change, rapid industrialization, and rapidly increasing populations are raising global concerns about the associated health risks. The Global Environmental and Occupational Health Hub for Eastern Africa was established to address some of these problems at national and regional levels through focused training and applied research that would yield evidence supporting policies and investments to mitigate risks of increasing environmental threats throughout the Eastern African region. Emphasis has been placed on air pollution, a leading risk factor for global mortality, accounting for over 7 million premature deaths or 8.7% of the 2017 global mortality burden. Despite the enormous disease burden that air pollution causes, global investment in air pollution monitoring and research capacity building in low-middle and middle-income countries have been inadequate. This study outlines the activities the Hub has undertaken in planning for and carrying out its initial capacity building and building its primary research programs and identifies central lessons that can inform other large global research partnerships.
RATIONALE: To date, there is no published local epidemiological evidence documenting the respiratory health effects of source specific air pollution in South Asia, where PM2.5 composition is different from past studies. Differences include more biomass and residue crop-burning emissions, which may have differing health implications. OBJECTIVES: We assessed PM2.5 associations with respiratory emergency department (ED) visits in a biomass-burning dominated high pollution region, and evaluated their variability by pollution source and composition. METHODS: Time-series regression modeling was applied to daily ED visits from January 2014 through December 2017. Air pollutant effect sizes were estimated after addressing long-term trends and seasonality, day-of-week, holidays, relative humidity, ambient temperature, and the effect modification by season, age, and sex. RESULTS: PM2.5 yielded a significant association with increased respiratory ED visits [0.84% (95% CI: 0.33%, 1.35%)] per 10 μg/m3 increase. The PM2.5 health effect size varied with season, the highest being during monsoon season, when fossil-fuel combustion sources dominated exposures. Results from a source-specific health effect analysis was also consistent with fossil-fuel PM2.5 having a larger effect size per 10 μg/m3 than PM2.5 from other sources [fossil-fuel PM2.5: 2.79% (0.33% to 5.31%), biomass-burning PM2.5: 1.27% (0% to 2.54%), and other-PM2.5: 0.95% (0.06% to 1.85%)]. Age-specific associations varied, with children and older adults being disproportionately affected by the air pollution, especially by the combustion-related particles. CONCLUSIONS: This study provided novel and important evidence that respiratory health in Dhaka is significantly affected by particle air pollution, with a greater health impact by fossil-fuel combustion derived PM2.5.
A large concern with estimates of climate and health co-benefits of “clean” cookstoves from controlled emissions testing is whether results represent what actually happens in real homes during normal use. A growing body of evidence indicates that in-field emissions during daily cooking activities differ substantially from values obtained in laboratories, with correspondingly different estimates of co-benefits. We report PM(2.5) emission factors from uncontrolled cooking (n = 7) and minimally controlled cooking tests (n = 51) using traditional chulha and angithi stoves in village kitchens in Haryana, India. Minimally controlled cooking tests (n = 13) in a village kitchen with mixed dung and brushwood fuels were representative of uncontrolled field tests for fine particulate matter (PM(2.5)), organic and elemental carbon (p > 0.5), but were substantially higher than previously published water boiling tests using dung or wood. When the fraction of nonrenewable biomass harvesting, elemental, and organic particulate emissions and modeled estimates of secondary organic aerosol (SOA) are included in 100 year global warming commitments (GWC(100)), the chulha had a net cooling impact using mixed fuels typical of the region. Correlation between PM(2.5) emission factors and GWC (R(2) = 0.99) implies these stoves are climate neutral for primary PM(2.5) emissions of 8.8 ± 0.7 and 9.8 ± 0.9 g PM(2.5)/kg dry fuel for GWC(20) and GWC(100), respectively, which is close to the mean for biomass stoves in global emission inventories.
Despite low per capita emissions, with over a billion population, India is pivotal for climate change mitigation globally, ranking as the third largest emitter of greenhouse gases. We linked a previously published multidimensional population projection with emission projections from an integrated assessment model to quantify the localised (i.e. state-level) health benefits from reduced ambient fine particulate matter in India under global climate change mitigation scenarios in line with the Paris Agreement targets and national scenarios for maximum feasible air quality control. We incorporated assumptions about future demographic, urbanisation and epidemiological trends and accounted for model feedbacks. Our results indicate that compared to a business-as-usual scenario, pursuit of aspirational climate change mitigation targets can avert up to 8.0 million premature deaths and add up to 0.7 years to life expectancy (LE) at birth due to cleaner air by 2050. Combining aggressive climate change mitigation efforts with maximum feasible air quality control can add 1.6 years to LE. Holding demographic change constant, we find that climate change mitigation and air quality control will contribute slightly more to increases in LE in urban areas than in rural areas and in states with lower socio-economic development.
This research was carried out to analyze variations in indoor and outdoor ozone concentrations and their health impact on local communities of megacities in Pakistan. For indoor ozone measurements, industrial units of an economic zone, Hattar Industrial Estate, Haripur, KPK, Pakistan, were selected. For outdoor ozone measurements, maximum and minimum peaks from different selected stations of three megacities (Islamabad, Abbottabad, and Haripur Hattar) in Pakistan were analyzed for paired comparisons. The tropospheric ozone levels were measured with the help of a portable SKY 2000-WH-O-3 meter from December 2018 to November 2019. According to the findings of this investigation, the indoor ozone concentrations at Hattar Industrial Estate exceeded the permissible limit devised by the WHO. The highest concentration (0.37 ppm) was recorded in the month of May in the food industry, while the lowest concentration (0.00 ppm) was recorded in the cooling area of the steel industry in the month of December. For outdoor ozone concentrations, the maximum concentration (0.23 ppm) was detected in Islamabad in the month of March 2019, whereas the rest of year showed comparatively lower concentrations. In Haripur, the maximum concentration (0.22 ppm) was detected in the month of February 2019 and a minimum concentration (0.11 ppm) was found in the month of November 2019. In Abbottabad, the maximum concentration (0.21 ppm) was detected in the month of March 2019 and the minimum concentration was 0.082 ppm. Increasing tropospheric ozone levels might be harmful for local communities and industrial laborers in the winter season because of the foggy weather. In the Abbottabad and Hattar regions, since COVID infection is indirectly related to low temperature and high emission of gases may compromise the respiratory systems of humans. The results of the present study were shared with industrialists to set precautions for ambient air quality and support the adoption of low emission techniques in industries for the safety of labour and nearby residents.
This paper examines the effect of biomass burning on adolescent health in India. The biomass burning problem is quite acute especially in North India, with some states experiencing forest fires and few states actively engaging in crop burning practice. We combine remote sensing data on biomass burning events with a pan-India survey on teenage girls (TAG survey). We exploit regional and temporal variation in our data to establish the link between occurrence of extremely high levels of biomass burning during early life and adolescent height for girls in India. Our results indicate that exposure to extremely high level of biomass burning during prenatal and postnatal period is associated with lower height (by 0.7 percent or 1.07 cm) later in life. Girls from North India are found to be especially vulnerable to the harmful effects of exposure to biomass burning. (c) 2021 Elsevier B.V. All rights reserved.
Smoke from wildfires is a growing health risk across the US. Understanding the spatial and temporal patterns of such exposure and its population health impacts requires separating smoke-driven pollutants from non-smoke pollutants and a long time series to quantify patterns and measure health impacts. We develop a parsimonious and accurate machine learning model of daily wildfire-driven PM(2.5) concentrations using a combination of ground, satellite, and reanalysis data sources that are easy to update. We apply our model across the contiguous US from 2006 to 2020, generating daily estimates of smoke PM(2.5) over a 10 km-by-10 km grid and use these data to characterize levels and trends in smoke PM(2.5). Smoke contributions to daily PM(2.5) concentrations have increased by up to 5 μg/m(3) in the Western US over the last decade, reversing decades of policy-driven improvements in overall air quality, with concentrations growing fastest for higher income populations and predominantly Hispanic populations. The number of people in locations with at least 1 day of smoke PM(2.5) above 100 μg/m(3) per year has increased 27-fold over the last decade, including nearly 25 million people in 2020 alone. Our data set can bolster efforts to comprehensively understand the drivers and societal impacts of trends and extremes in wildfire smoke.
Pakistan ranks third in the world in terms of mortality attributable to air pollution, with aerosol mass concentrations (PM2.5) consistently well above WHO (World Health Organization) air quality guidelines (AQG). However, regulation is dependent on a sparse network of air quality monitoring stations and insufficient ground data. This study utilizes long-term observations of aerosols and trace gases to characterize and rank the air pollution scenarios and pollution characteristics of 80 selected cities in Pakistan. Datasets used include (1) the Aqua and Terra (AquaTerra) MODIS (Moderate Resolution Imaging Spectmradiometer) Level 2 Collection 6.1 merged Dark Target and Deep Blue (DTB) aerosol optical depth (AOD) retrieval products; (2) the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis PM1, PM2.5, and PM10 data; (3) the MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) reanalysis PM2.5 data, (4) the OMI (Ozone Monitoring Instrument) tropospheric vertical column density (TVCD) of nitrogen dioxide (NO2), and VCD of sulfur dioxide (SO2) in the Planetary Boundary Layer (PBL), (5) the VIIRS (Visible Infrared Imaging Radiometer Suite) Nighttime Lights data, (6) MODIS Collection 6 Version 2 global monthly fire location data (MCD14ML), (7) population density, (8) MODIS Level 3 Collection 6 land cover types, (9) AERONET (AErosol RObotic NETwork) Version 3 Level 2.0 data, and (10) ground-based PM2.5 concentrations from air quality monitoring stations. Potential Source Contribution Function (PSCF) analyses were performed by integrating with ground-based PM2.5 concentrations and the NOAA (National Oceanic and Atmospheric Administration) HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) air parcel back trajectories to identify potential pollution source areas which are responsible for extreme air pollution in Pakistan. Results show that the ranking of the top polluted cities depends on the type of pollutant considered and the metric used.For example, Jhang, Multan, and Vehari were characterized as the top three polluted cities in Pakistan when considering AquaTerra DTB AOD products; for PM1, PM2.5, and PM10 Lahore, Gujranwala, and Okara were the top three; for tropospheric NO2 VCD Lahore, Rawalpindi, and Islamabad and for PBL SO2 VCD Lahore, Mirpur, and Gujranwala. The results demonstrate that Pakistan’s entire population has been exposed to high PM2.5 concentrations for many years, with a mean annual value of 54.7 mu g/m(3), over all Pakistan from 2003 to 2020.This value exceeds Pakistan’s National Environmental Quality Standards (Pak-NEQS, i.e., <15 mu g/m(3) annual mean) for ambient air defined by the Pakistan Environmental Protection Agency (Pak-EPA) as well as the WHO Interim Target-1 (i.e., mean annual PM2.5 < 35 mu g/m(3)).The spatial analyses of the concentrations of aerosols and trace gases in terms of population density, nighttime lights, land cover types, and fire location data, and the PSCF analysis indicate that Pakistan's air quality is strongly affected by anthropogenic sources inside of Pakistan, with contributions from surrounding countries.Statistically significant positive (increasing) trends in PM1, PM2. 5, PM10, tropospheric NO2 VCD, and SO2 VCD were observed in similar to 89%, similar to 67%, similar to 48%, 91%, and similar to 88% of the Pakistani cities (80 cities), respectively. This comprehensive analysis of aerosol and trace gas levels, their characteristics in spatio-temporal domains, and their trends over Pakistan, is the first of its kind. Results will be helpful to the Ministry of Climate Change (Government of Pakistan), Pak-EPA, SUPARCO (Pakistan Space and Upper Atmosphere Research Commission), policymakers, and the local research community to mitigate air pollution and its effects on human health.
The troubling trend of rising heat-associated mortalities in an urban desert region (Maricopa County, AZ, USA) has motivated us to explore the extent to which environmental factors may contribute to increased heat-health risks. Summertime data from 2010 to 2019 were used to construct a suite of models for daily heat-associated mortalities. The best-performing full model included the following predictors, ordered from strongest to weakest influence: daily average air temperature, average of previous 5 days daily average air temperature, year, day of year, average of previous 5 days daily average dew point temperature, average of previous 5 days daily average PM(2.5), and daily average PM(10). This full model exhibited a 5.39% reduction in mean absolute error in daily heat-associated mortalities as compared to the best-performing model that included only air temperature as an environmental predictor. The extent to which issued and modeled excessive heat warnings (from both the temperature only and full models) corresponded with heat-associated mortalities was also examined. Model hindcasts for 2020 and 2021 showed that the models were able to capture the high number of heat-associated mortalities in 2020, but greatly undercounted the highest yet observed number of heat-associated mortalities in 2021. Results from this study lend insights into environmental factors corresponding to an increased number of heat-associated mortalities and can be used for informing strategies towards reducing heat-health risks. However, as the best-performing model was unable to fully capture the observed number of heat-associated mortalities, continued scrutiny of both environmental and non-environmental factors affecting these observations is needed.
Concerns over regional climate change include its impact on air quality. A major contributor to unhealthy air quality is surface-based temperature inversions. Poor air quality is a serious public health concern that is often addressed by public health agencies. To assist with understanding the climatology and trend of temperature inversions for a large public health department, innovative pragmatic criteria were developed and used to determine morning and evening surface-based temperature inversions from datasets derived from Pittsburgh National Weather Service (NWS) radiosonde measurements made from 1 January 1991 through 31 December 2020. During this 30-year period, the strength of the morning (7 a.m. EST; 12 UTC) inversions was 3.9 °C on average. The depth of the inversion layer measured an average height of 246 m above the ground. The inversions tended to dissipate by 10 a.m. EST. The frequency of occurrence of morning inversions averaged 47%. The mean strength of the evening (7 p.m. EST; 00 UTC) inversions was 1.1 °C with a mean depth of 101 m above the ground. The frequency of evening inversion occurrence averaged 20% during this period. The 30-year climatology revealed generally declining frequency of inversions in the Pittsburgh area. Morning surface-based inversion strengths usually declined while morning depths and break times were steady. Evening inversion strengths and depths increased overall during the 30-year period. Monthly means showed a morning-evening overlap of some months that record the most frequent substantial inversions during the fall time of the year, coinciding with the time when the worst air pollution events occur.
The smart helmet is designed for a wildland firefighter to send vital data to their supervisor while they are working to extinguish an active fire. The smart helmet collects temperature, heart rate, and acceleration data from each firefighter via sensors inside and around the helmet. The data is used to alert the supervisor of potential health or emergency issues, such as heat-related illness, dehydration, potential falls or abnormal heart rates. A mobile app that the supervisor connects to their smart helmet device collects data in real time from the firefighters, without the need of any cellular coverage or WiFi.
The impacts of wildfires on the health of children are becoming a more urgent matter as wildfires become more frequent, intense and affecting, not only forested areas, but also urban locations. It is important that medical professionals be prepared to provide information to patients and families on how to minimize the adverse health effects on children of wildfire smoke and ash from wildfires. (C) 2021 Elsevier Inc. All rights reserved.
Bacteria in the air present patterns in space and time produced by different sources and environmental factors. Few studies have focused on the link between airborne pathogenic bacteria in densely populated cities, and the risk to the population’s health. Bacteria associated with particulate matter (PM) were monitored from the air of Mexico City (Mexico). We employed a metagenomic approach to characterise bacteria using the 16S rRNA gene. Airborne bacteria sampling was carried out in the north, centre, and south of Mexico City, with different urbanisation rates, during 2017. Bacteria added to the particles were sampled using high-volume PM10 samplers. To ascertain significant differences in bacterial diversity between zones and seasons, the Kruskal-Wallis, Wilcoxon tests were done on alpha diversity parameters. Sixty-three air samples were collected, and DNA was sequenced using next-generation sequencing. The results indicated that the bacterial phyla in the north and south of the city were Firmicutes, Cyanobacteria, Proteobacteria, and Actinobacteria, while in the central zone there were more Actinobacteria. There were no differences in the alpha diversity indices between the sampled areas. According to the OTUs, the richness of bacteria was higher in the central zone. Alpha diversity was higher in the rainy season than in the dry season; the Shannon index and the OTUs observed were higher in the central zone in the dry season. Pathogenic bacteria such as Kocuria, Paracoccus, and Micrococcus predominated in both seasonal times, while Staphylococcus, Corynebacterium, and Nocardioides were found during the rainy season, with a presence in the central zone. (C) Higher Education Press 2022
Understanding whether and how wildfires exacerbate COVID-19 outcomes is important for assessing the efficacy and design of public sector responses in an age of more frequent and simultaneous natural disasters and extreme events. Drawing on environmental and emergency management literatures, we investigate how wildfire smoke (PM(2.5)) impacted COVID-19 infections and deaths during California’s 2020 wildfire season and how public housing resources and hospital capacity moderated wildfires’ effects on COVID-19 outcomes. We also hypothesize and empirically assess the differential impact of wildfire smoke on COVID-19 infections and deaths in counties exhibiting high and low social vulnerability. To test our hypotheses concerning wildfire severity and its disproportionate impact on COVID-19 outcomes in socially vulnerable communities, we construct a county-by-day panel dataset for the period April 1 to November 30, 2020, in California, drawing on publicly available state and federal data sources. This study’s empirical results, based on panel fixed effects models, show that wildfire smoke is significantly associated with increases in COVID-19 infections and deaths. Moreover, wildfires exacerbated COVID-19 outcomes by depleting the already scarce hospital and public housing resources in local communities. Conversely, when wildfire smoke doubled, a one percent increase in the availability of hospital and public housing resources was associated with a 2 to 7 percent decline in COVID-19 infections and deaths. For California communities exhibiting high social vulnerability, the occurrence of wildfires worsened COVID-19 outcomes. Sensitivity analyses based on an alternative sample size and different measures of social vulnerability validate this study’s main findings. An implication of this study for policymakers is that communities exhibiting high social vulnerability will greatly benefit from local government policies that promote social equity in housing and healthcare before, during, and after disasters.
BACKGROUND: Increasing number of studies have linked air pollution exposure with renal function decline and disease. However, there is a lack of data on its impact among end-stage kidney disease (ESKD) patients and its potential modifying effect from extreme heat events (EHE). METHODS: Fresenius Kidney Care records from 28 selected northeastern US counties were used to pool daily all-cause mortality (ACM) and all-cause hospital admissions (ACHA) counts. County-level daily ambient PM(2.5) and ozone (O(3)) were estimated using a high-resolution spatiotemporal coupled climate-air quality model and matched to ESKD patients based on ZIP codes of treatment sites. We used time-stratified case-crossover analyses to characterize acute exposures using individual and cumulative lag exposures for up to 3 days (Lag 0-3) by using a distributed lag nonlinear model framework. We used a nested model comparison hypothesis test to evaluate for interaction effects between air pollutants and EHE and stratification analyses to estimate effect measures modified by EHE days. RESULTS: From 2001 to 2016, the sample population consisted of 43,338 ESKD patients. We recorded 5217 deaths and 78,433 hospital admissions. A 10-unit increase in PM(2.5) concentration was associated with a 5% increase in ACM (rate ratio [RR(Lag0)(-)(3)]: 1.05, 95% CI: 1.00-1.10) and same-day O(3) (RR(Lag0): 1.02, 95% CI: 1.01-1.03) after adjusting for extreme heat exposures. Mortality models suggest evidence of interaction and effect measure modification, though not always simultaneously. ACM risk increased up to 8% when daily ozone concentrations exceeded National Ambient Air Quality Standards established by the United States, but the increases in risk were considerably higher during EHE days across lag periods. CONCLUSION: Our findings suggest interdependent effects of EHE and air pollution among ESKD patients for all-cause mortality risks. National level assessments are needed to consider the ESKD population as a sensitive population and inform treatment protocols during extreme heat and degraded pollution episodes.
BACKGROUND/OBJECTIVE: Research suggests gestational exposure to particulate matter ≤2.5 μm (PM(2.5)) and extreme heat may independently increase risk of birth defects. We investigated whether duration of gestational extreme heat exposure modifies associations between PM(2.5) exposure and specific congenital heart defects (CHDs). We also explored nonlinear exposure-outcome relationships. METHODS: We identified CHD case children (n = 2824) and non-malformed live-birth control children (n = 4033) from pregnancies ending between 1999 and 2007 in the National Birth Defects Prevention Study, a U.S. population-based multicenter case-control study. We assigned mothers 6-week averages of PM(2.5) exposure during the cardiac critical period (postconceptional weeks 3-8) using the closest monitor within 50 km of maternal residence. We assigned a count of extreme heat days (EHDs, days above the 90th percentile of daily maximum temperature for year, season, and weather station) during this period using the closest weather station. Using generalized additive models, we explored logit-nonlinear exposure-outcome relationships, concluding logistic models were reasonable. We estimated joint effects of PM(2.5) and EHDs on six CHDs using logistic regression models adjusted for mean dewpoint and maternal age, education, and race/ethnicity. We assessed multiplicative and additive effect modification. RESULTS: Conditional on the highest observed EHD count (15) and at least one critical period day during spring/summer, each 5 μg/m(3) increase in average PM(2.5) exposure was significantly associated with perimembranous ventricular septal defects (VSDpm; OR: 1.54 [95% CI: 1.01, 2.41]). High EHD counts (8+) in the same population were positively, but non-significantly, associated with both overall septal defects and VSDpm. Null or inverse associations were observed for lower EHD counts. Multiplicative and additive effect modification estimates were consistently positive in all septal models. CONCLUSIONS: Results provide limited evidence that duration of extreme heat exposure modifies the PM(2.5)-septal defects relationship. Future research with enhanced exposure assessment and modeling techniques could clarify these relationships.
BACKGROUND: Individuals with respiratory conditions, such as asthma, are particularly susceptible to adverse health effects associated with higher levels of ambient air pollution and temperature. This study evaluates whether hourly levels of fine particulate matter (PM2.5) and dry bulb globe temperature (DBGT) are associated with the lung function of adult participants with asthma. METHODS AND FINDINGS: Global positioning system (GPS) location, respiratory function (measured as forced expiratory volume at 1 second (FEV1)), and self-reports of asthma medication usage and symptoms were collected as part of the Exposure, Location, and Lung Function (ELF) study. Hourly ambient PM2.5 and DBGT exposures were estimated by integrating air quality and temperature public records with time-activity patterns using GPS coordinates for each participant (n = 35). The relationships between acute PM2.5, DBGT, rescue bronchodilator use, and lung function collected in one week periods and over two seasons (summer/winter) were analyzed by multivariate regression, using different exposure time frames. In separate models, increasing levels in PM2.5, but not DBGT, were associated with rescue bronchodilator use. Conversely DBGT, but not PM2.5, had a significant association with FEV1. When DBGT and PM2.5 exposures were placed in the same model, the strongest association between cumulative PM2.5 exposures and the use of rescue bronchodilator was identified at the 0-24 hours (OR = 1.030; 95% CI = 1.012-1.049; p-value = 0.001) and 0-48 hours (OR = 1.030; 95% CI = 1.013-1.057; p-value = 0.001) prior to lung function measure. Conversely, DBGT exposure at 0 hours (β = 3.257; SE = 0.879; p-value>0.001) and 0-6 hours (β = 2.885; SE = 0.903; p-value = 0.001) hours before a reading were associated with FEV1. No significant interactions between DBGT and PM2.5 were observed for rescue bronchodilator use or FEV1. CONCLUSIONS: Short-term increases in PM2.5 were associated with increased rescue bronchodilator use, while DBGT was associated with higher lung function (i.e. FEV1). Further studies are needed to continue to elucidate the mechanisms of acute exposure to PM2.5 and DBGT on lung function in asthmatics.
Air pollution risk assessments typically estimate ozone-attributable mortality counts using concentration-response (C-R) parameters from epidemiologic studies that treat temperature as a potential confounder. However, some recent epidemiologic studies have indicated that temperature can modify the relationship between short-term ozone exposure and mortality, which has potentially important implications when considering the impacts of climate change on public health. This proof-of-concept analysis quantifies counts of temperature-modified ozone-attributable mortality using temperature-stratified C-R parameters from a multicity study in which the pooled ozone-mortality effect coefficients change in concert with daily temperature. Meteorology downscaled from two global climate models is used with a photochemical transport model to simulate ozone concentrations over the 21st century using two emission inventories: one holding air pollutant emissions constant at 2011 levels and another accounting for reduced emissions through the year 2040. The late century climate models project increased summer season temperatures, which in turn yields larger total counts of ozone-attributable deaths in analyses using temperature-stratified C-R parameters compared to the traditional temperature confounder approach. This analysis reveals substantial heterogeneity in the magnitude and distribution of the temperature-stratified ozone-attributable mortality results, which is a function of regional variability in both the C-R relationship and the model-predicted temperature and ozone.
The combined effects of heat events and poor air quality conditions can severely affect population health. A novel correlational method was developed to assess the impact of the short-term variations of environmental variables (air pollutants and ambient conditions) on community health responses (mortalities and emergency department visits). A multi-dimensional clustering approach was proposed by combining hierarchical and k-means clustering to promote flexibility and robustness to improve the correlation procedure. The study focused on the health records of the elderly population and people diagnosed with cardiorespiratory causes. The study investigated multiple health records on different levels of investigation: total, elderly, cause-based, and elderly cause-based records. The developed method was validated by investigating the short-term impact of ambient air temperature, relative humidity, ground-level ozone, and fine particulate matter on the health records during hot and warm seasons in the municipalities of Mississauga and Brampton, Peel Region, Ontario, Canada for 15 years. The analysis confirmed the association between moderate levels of environmental variables and increased short-term daily total deaths and emergency department visits, while the elderly sector showed higher vulnerability to environmental changes. Furthermore, the association with extreme heat conditions and poor air quality levels was affirmed with cause-based mortalities and emergency visits; the correlation was strongest with elderly cause-based health records. Findings confirm that cardiorespiratory patients, especially elderly people, were at the greatest risk of poor environmental conditions.
OBJECTIVES: We aimed to characterize polycyclic aromatic hydrocarbons (PAHs) in the breathing zone and on the skin of wildland firefighters and to assess their contribution to urinary 1-hydroxypyrene (1-HP) over repeated firefighting rotations. We asked if improved skin hygiene or discretionary use of an N95 mask would reduce absorption. METHODS: In collaboration with wildfire services of two Canadian provinces, Alberta and British Columbia (BC), we recruited wildland firefighters from crews willing to be followed up over successive rotations and to be randomly assigned to normal practice, enhanced skin hygiene (ESH), or ESH plus discretionary use of an N95 mask. We collected spot urine samples at the beginning and end of up to four rotations/firefighter. On designated fire days, as close as possible to the end of rotation, we collected skin wipes from the hands, throat, and chest at the beginning and end of the fire day and, in BC, start of fire-day urine samples. Volunteers carried air monitoring pumps. Participants completed questionnaires at the beginning and end of rotations. Exposure since the start of the fire season was estimated from fire service records. Urinary 1-HP was analyzed by LC-MS-MS. Analysis of 21 PAHs on skin wipes and 27 PAHs from air sampling was done by GC-MS-MS. Statistical analysis used a linear mixed effects model. RESULTS: Firefighters in Alberta were recruited from five helitack crews and two unit crews, and in BC from two unit crews with 80 firefighters providing data overall. The fire season in BC was very active with five monitored fire days. In Alberta, with more crews, there were only seven fire days. Overall, log 1-HP/creatinine (ng/g) increased significantly from the start (N = 145) to end of rotation (N = 136). Only three PAHs (naphthalene, phenanthrene, and pyrene) were found on >20% of skin wipes. PAHs from 40 air monitoring pumps included 10 PAHs detected on cassette filters (particles) and 5 on sorbent tubes (vapor phase). A principal component extracted from air monitoring data represented respiratory exposure and total PAH from skin wipes summarized skin exposure. Both routes contributed to the end of rotation urinary 1-HP. The ESH intervention was not demonstrated to effect absorption. Allocation of an N95 mask was associated with lower 1-HP when modeling respiratory exposure (β = -0.62, 95% CI -1.15 to -0.10: P = 0.021). End of rotation 1-HP was related to 1-HP at the start of the next rotation (β = 0.25, 95% CI 0.12 to 0.39: P < 0.001). CONCLUSIONS: Exposures to PAHs during firefighting were significant, with samples exceeding the American Conference of Governmental Industrial Hygienists Biological Exposure Index for 1-HP suggesting a need for control of exposure. PAH exposure accumulated during the rotation and was not fully eliminated during the break between rotations. Both respiratory and skin exposures contributed to 1-HP. While improved skin hygiene may potentially reduce dermal absorption, that was not demonstrated here. In contrast, those allocated to discretionary use of an N95 mask had reduced 1-HP excretion. Wildland firefighters in North America do not use respiratory protection, but the results of this study support more effective interventions to reduce respiratory exposure.
Wildfires can significantly impact air quality and human health. However, little is known about how different fuel bed components contribute to these impacts. This study investigates the air quality impacts of duff and peat consumption during wildfires in the southeastern United States, with a focus on the differing contributions of fine particulate matter less than 2.5 mu m in size (PM2.5) and ozone (O-3) to air quality episodes associated with the four largest wildfire events in the region during this century. The emissions of duff burning were estimated based on a field measurement of a 2016 southern Appalachian fire. The emissions from the burning of other fuels were obtained from the Fire INventory from NCAR (FINN). The air quality impacts were simulated using a three-dimensional regional air quality model. The results show the duff burning emitted PM2.5 comparable to the burning of the above-ground fuels. The simulated surface PM2.5 concentrations due to duff burning increased by 61.3% locally over a region approximately 300 km within the fire site and by 21.3% and 29.7% in remote metro Atlanta and Charlotte during the 2016 southern Appalachian fires and by 131.9% locally and by 17.7% and 24.8% in remote metro Orlando and Miami during the 2007 Okefenokee Fire. However, the simulated ozone impacts from the duff burning were negligible due to the small duff emission factors of ozone precursors such as NOx. This study suggests the need to improve the modeling of PM2.5 and the air quality, human health, and climate impacts of wildfires in moist ecosystems by including duff burning in global fire emission inventories.
Climate change-related disasters have drawn increased attention to the impact of air pollution on health. 122 children ages 9-11 years old, M(SD) = 9.91(.56), participated. Levels of particulate matter (PM2.5) near participants’ homes were obtained from the Environmental Protection Agency. Cytokines were assayed from 100 child serum samples: IL-6, IL-8, IL-10, and TNFα. Autonomic physiology was indexed by pre-ejection period (PEP), respiratory sinus arrhythmia (RSA), cardiac autonomic regulation (CAR), and cardiac autonomic balance (CAB). IL-6 was positively related to daily PM2.5 (r = .26, p = .009). IL-8 was negatively associated with monthly PM2.5 (r = -.23, p = .02). PEP was positively related to daily (r = .29, p = .001) and monthly PM2.5 (r = .18, p = .044). CAR was negatively associated with daily PM2.5 (r = -.29, p = .001). IL-10, TNFα, RSA, and CAB were not associated with PM2.5. Air pollution may increase risk of inflammation in children.
Major wildfires and heatwaves have begun to increase in frequency throughout much of the United States, particularly in western states such as California, causing increased risk to public health. Air pollution is exacerbated by both wildfires and warmer temperatures, thus adding to such risk. With climate change and the continued increase in global average temperatures, the frequency of major wildfires, heat days, and unhealthy air pollution episodes is projected to increase, resulting in the potential for compounding risks. Risks will likely vary by region and may disproportionately impact low-income communities and communities of color. In this study, we processed daily particulate matter (PM) data from over 18,000 low-cost PurpleAir sensors, along with gridMET daily maximum temperature data and government-compiled wildfire perimeter data from 2018-2020 in order to examine the occurrence of compound risk (CR) days (characterized by high temperature and high PM2.5) at the census tract level in California, and to understand how such days have been impacted by the occurrence of wildfires. Using American Community Survey data, we also examined the extent to which CR days were correlated with household income, race/ethnicity, education, and other socioeconomic factors at the census tract level. Results showed census tracts with a higher frequency of CR days to have statistically higher rates of poverty and unemployment, along with high proportions of child residents and households without computers. The frequency of CR days and elevated daily PM2.5 concentrations appeared to be strongly related to the occurrence of nearby wildfires, with over 20% of days with sensor-measured average PM2.5 > 35 mu g/m(3) showing a wildfire within a 100 km radius and over two-thirds of estimated CR days falling on such days with a nearby wildfire. Findings from this study are important to policymakers and government agencies who preside over the allocation of state resources as well as organizations seeking to empower residents and establish climate resilient communities.
Indoor flooding is a leading contributor to indoor dampness and the associated mold infestations in the coastal United States. Whether the prevalent mold genera that infest the coastal flood-prone buildings are different from those not flood-prone is unknown. In the current case study of 28 mold-infested buildings across the U.S. east coast, we surprisingly noted a trend of higher prevalence of indoor Aspergillus and Penicillium genera (denoted here as Asp-Pen) in buildings with previous flooding history. Hence, we sought to determine the possibility of a potential statistically significant association between indoor Asp-Pen prevalence and three building-related variables: (i) indoor flooding history, (ii) geographical location, and (iii) the building’s use (residential versus non-residential). Culturable spores and hyphal fragments in indoor air were collected using the settle-plate method, and corresponding genera were confirmed using phylogenetic analysis of their ITS sequence (the fungal barcode). Analysis of variance (ANOVA) using Generalized linear model procedure (GLM) showed that Asp-Pen prevalence is significantly associated with indoor flooding as well as coastal proximity. To address the small sample size, a multivariate decision tree analysis was conducted, which ranked indoor flooding history as the strongest determinant of Asp-Pen prevalence, followed by geographical location and the building’s use.
Fire Influence on Regional to Global Environments and Air Quality was a NOAA/NASA collaborative campaign conducted during the summer of 2019. The objectives included identifying and quantifying wildfire composition, smoke evolution, and climate and health impacts of wildfires and agricultural fires in the United States. Ground based mobile sampling via sorbent tubes occurred at the Nethker and Williams Flats fires (2019) and Chief Timothy and Whitetail Loop fires (2020) in Idaho and Washington. Air samples were analyzed through thermal desorption-gas chromatography-mass spectrometry for a variety of volatile organic compounds to elucidate both composition and health impacts. Benzene, toluene, ethylbenzene, xylenes, butenes, phenol, isoprene and pinenes were observed in the wildfire smoke, with benzene ranging from 0.04 to 25 ppbv. Health risk was assessed for each fire by determining sub-chronic (wildfire event) and projected chronic inhalation risk exposure from benzene, a carcinogen, as well as other non-carcinogenic compounds including toluene, ethylbenzene, xylenes, and hexane. The cancer risk of benzene from sub-chronic exposure was 1 extra cancer per million people and ranged from 1 to 19 extra cancers per million people for the projected chronic scenarios, compared to a background level of 1 extra cancer per million people. The hazard index of non-carcinogenic compounds was less than one for all scenarios and wildfires sampled, which was considered low risk for non-cancer health events.
Exposure to wildfire smoke increases the risk of respiratory and cardiovascular hospital admissions. Health impact assessments, used to inform decision-making processes, characterize the health impacts of environmental exposures by combining preexisting epidemiological concentration-response functions (CRFs) with estimates of exposure. These two key inputs influence the magnitude and uncertainty of the health impacts estimated, but for wildfire-related impact assessments the extent of their impact is largely unknown. We first estimated the number of respiratory, cardiovascular, and asthma hospital admissions attributable to fire-originated PM2.5 exposure in central California during the October 2017 wildfires, using Monte Carlo simulations to quantify uncertainty with respect to the exposure and epidemiological inputs. We next conducted sensitivity analyses, comparing four estimates of fire-originated PM2.5 and two CRFs, wildfire and nonwildfire specific, to understand their impact on the estimation of excess admissions and sources of uncertainty. We estimate the fires accounted for an excess 240 (95% CI: 114, 404) respiratory, 68 (95% CI: -10, 159) cardiovascular, and 45 (95% CI: 18, 81) asthma hospital admissions, with 56% of admissions occurring in the Bay Area. Although differences between impact assessment methods are not statistically significant, the admissions estimates’ magnitude is particularly sensitive to the CRF specified while the uncertainty is most sensitive to estimates of fire-originated PM2.5. Not accounting for the exposure surface’s uncertainty leads to an underestimation of the uncertainty of the health impacts estimated. Employing context-specific CRFs and using accurate exposure estimates that combine multiple data sets generates more certain estimates of the acute health impacts of wildfires.
Wildfire smoke is one of the most significant concerns of human and environmental health, associated with its substantial impacts on air quality, weather, and climate. However, biomass burning emissions and smoke remain among the largest sources of uncertainties in air quality forecasts. In this study, we evaluate the smoke emissions and plume forecasts from 12 state-of-the-art air quality forecasting systems during the Williams Flats fire in Washington State, US, August 2019, which was intensively observed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Model forecasts with lead times within 1 d are intercompared under the same framework based on observations from multiple platforms to reveal their performance regarding fire emissions, aerosol optical depth (AOD), surface PM2.5, plume injection, and surface PM2.5 to AOD ratio. The comparison of smoke organic carbon (OC) emissions suggests a large range of daily totals among the models, with a factor of 20 to 50. Limited representations of the diurnal patterns and day-to-day variations of emissions highlight the need to incorporate new methodologies to predict the temporal evolution and reduce uncertainty of smoke emission estimates. The evaluation of smoke AOD (sAOD) forecasts suggests overall underpredictions in both the magnitude and smoke plume area for nearly all models, although the high-resolution models have a better representation of the fine-scale structures of smoke plumes. The models driven by fire radiative power (FRP)-based fire emissions or assimilating satellite AOD data generally outperform the others. Additionally, limitations of the persistence assumption used when predicting smoke emissions are revealed by substantial underpredictions of sAOD on 8 August 2019, mainly over the transported smoke plumes, owing to the underestimated emissions on 7 August. In contrast, the surface smoke PM2.5 (sPM(2.5)) forecasts show both positive and negative overall biases for these models, with most members presenting more considerable diurnal variations of sPM(2.5). Overpredictions of sPM(2.5) are found for the models driven by FRP-based emissions during nighttime, suggesting the necessity to improve vertical emission allocation within and above the planetary boundary layer (PBL). Smoke injection heights are further evaluated using the NASA Langley Research Center’s Differential Absorption High Spectral Resolution Lidar (DIAL-HSRL) data collected during the flight observations. As the fire became stronger over 38 August, the plume height became deeper, with a day-today range of about 2-9 km a.g.l. However, narrower ranges are found for all models, with a tendency of overpredicting the plume heights for the shallower injection transects and underpredicting for the days showing deeper injections. The misrepresented plume injection heights lead to inaccurate vertical plume allocations along the transects corresponding to transported smoke that is 1 d old. Discrepancies in model performance for surface PM2.5 and AOD are further suggested by the evaluation of their ratio, which cannot be compensated for by solely adjusting the smoke emissions but are more attributable to model representations of plume injections, besides other possible factors including the evolution of PBL depths and aerosol optical property assumptions. By consolidating multiple forecast systems, these results provide strategic insight on pathways to improve smoke forecasts.
Background: Recent increases in wildfire frequency and severity necessitate better understanding of health effects of wildfire smoke to protect affected populations. Objectives: We examined relationships between fine particulate matter (PM2.5) and morbidity during wildfires in California, and whether those relationships differed during the fire compared to a similar non-fire period. Methods: For nine San Francisco Bay Area counties, daily county- level diagnosis-specific counts of emergency department visits (EDVs) and hospitalizations were linked with county-level estimates of daily mean PM2.5 during the October 2017 Northern California wildfires and similar October days in 2015, 2016, and 2017. Associations were estimated using Poisson regression. Results: The median difference between county PM2.5 during the fire versus the non-fire period was 23.4 mu g/ m3, with days exceeding 80 mu g/m3 in some counties. Over the entire study period, PM2.5 was most consistently linked to EDVs for respiratory disease ( RREDV(lag0) per 23.4 mu g/ m3 increase: 1.25, 95% CI: 1.21, 1.30), asthma, chronic lower respiratory disease (CLRD; RREDV(lag0): 1.18, 95% CI: 1.10, 1.27), and acute myocardial infarction (RREDV(lag0): 1.14, 95% CI: 1.03, 1.25). Increases in acute upper respiratory infections and decreases in mental/behavioral EDVs were observed but were sensitive to model specification, specifically the inclusion of time-related covariates. Comparing fire and non-fire period EDV associations, we observed indications that PM2.5 during the fire was more strongly associated with asthma (RRlag0: 1.46, 95% CI: 1.38, 1.55) compared to non-fire period PM2.5 (RRlag0: 0.77, 95% CI: 0.55, 1.08), and the opposite observed for dysrhythmia, with the asthma difference being particularly robust to model choice. For hospitalizations, the most robust PM2.5 relationships were positive associations with respiratory, CLRD, and diabetes, and inverse associations with pneumonia. Respiratory and CLRD effect estimates were generally similar or smaller than for EDVs. Conclusions: Elevated short-term PM2.5 levels from wildfire smoke appears to impact respiratory and other health domains. (c) 2021 Elsevier B.V. All rights reserved.
BACKGROUND AND OBJECTIVES: Exposure to airborne fine particles with diameters <= 2.5 mu m (PM2.5) pollution is a well-established cause of respiratory diseases in children; whether wildfire-specific PM2.5 causes more damage, however, remains uncertain. We examine the associations between wildfire-specific PM2.5 and pediatric respiratory health during the period 2011-2017 in San Diego County, California, and compare these results with other sources of PM2.5. METHODS: Visits to emergency and urgent care facilities of Rady's Children Hospital network in San Diego County, California, by individuals (aged <= 19 years) with >= 1 of the following respiratory conditions: difficulty breathing, respiratory distress, wheezing, asthma, or cough were regressed on daily, community-level exposure to wildfire-specific PM2.5 and PM2.5 from ambient sources (eg, traffic emissions). RESULTS: A 10-unit increase in PM2.5 (from nonsmoke sources) was estimated to increase the number of admissions by 3.7% (95% confidence interval: 1.2% to 6.1%). In contrast, the effect of PM2.5 attributable to wildfire was estimated to be a 30.0% (95% confidence interval: 26.6% to 33.4%) increase in visits. CONCLUSIONS: Wildfire-specific PM2.5 was found to be similar to 10 times more harmful on children’s respiratory health than PM2.5 from other sources, particularly for children aged 0 to 5 years. Even relatively modest wildfires and associated PM2.5 resolved on our record produced major health impacts, particularly for younger children, in comparison with ambient PM2.5.
Major wildfires starting in the summer of 2020 along the west coast of the United States made PM2.5 concentrations in this region rank among the highest in the world. Washington was impacted both by active wildfires in the state and aged wood smoke transported from fires in Oregon and California. This study aims to estimate the magnitude and disproportionate spatial impacts of increased PM2.5 concentrations attributable to these wildfires on population health. Daily PM2.5 concentrations for each county before and during the 2020 Washington wildfire episode (September 7-19) were obtained from regulatory air monitors. Utilizing previously established concentration-response function (CRF) of PM2.5 (CRF of total PM2.5) and odds ratio (OR) of wildfire smoke days (OR of wildfire smoke days) for mortality, we estimated excess mortality attributable to the increased PM2.5 concentrations in Washington. On average, daily PM2.5 concentrations increased 97.1 mu g/m(3) during the wildfire smoke episode. With CRF of total PM2.5, the 13-day exposure to wildfire smoke was estimated to lead to 92.2 (95% CI: 0.0, 178.7) more all-cause mortality cases; with OR of wildfire smoke days, 38.4 (95% CI: 0.0, 93.3) increased all-cause mortality cases and 15.1 (95% CI: 0.0, 27.9) increased respiratory mortality cases were attributable to the wildfire smoke episode. The potential impact of avoiding elevated PM2.5 exposures during wildfire events significantly reduced the mortality burden. Because wildfire smoke episodes are likely to impact the Pacific Northwest in future years, continued preparedness and mitigations to reduce exposures to wildfire smoke are necessary to avoid excess health burden.
Increases in wildfire activity across the Western US pose a significant public health threat. While there is evidence that wildfire smoke is detrimental for respiratory health, the impacts on cardiovascular health remain unclear. This study evaluates the association between fine particulate matter (PM(2.5)) from wildfire smoke and unscheduled cardiorespiratory hospital visits in California during the 2004-2009 wildfire seasons. We estimate daily mean wildfire-specific PM(2.5) with Goddard Earth Observing System-Chem, a global three-dimensional model of atmospheric chemistry, with wildfire emissions estimates from the Global Fire Emissions Database. We defined a “smoke event day” as cumulative 0-1-day lag wildfire-specific PM(2.5) ≥ 98th percentile of cumulative 0-1 lag day wildfire PM(2.5). Associations between exposure and outcomes are estimated using negative binomial regression. Results indicate that smoke event days are associated with a 3.3% (95% CI: [0.4%, 6.3%]) increase in visits for all respiratory diseases and a 10.3% (95% CI: [2.3%, 19.0%]) increase for asthma specifically. Stratifying by age, we found the largest effect for asthma among children ages 0-5 years. We observed no significant association between exposure and overall cardiovascular disease, but stratified analyses revealed increases in visits for all cardiovascular, ischemic heart disease, and heart failure among non-Hispanic white individuals and those older than 65 years. Further, we found a significant interaction between smoke event days and daily average temperature for all cardiovascular disease visits, suggesting that days with high wildfire PM(2.5) concentrations and high temperatures may pose greater risk for cardiovascular disease. These results suggest substantial increases in adverse outcomes from wildfire smoke exposure and indicate the need for improved prevention strategies and adaptations to protect vulnerable populations.
This study proposes an approach to improve the spatial resolution of ground-level concentrations of PM2.5 that is required to assess health risks associated with exposure to pollutants released during wildfires. We use this approach to analyze the impact on air quality of the wildfire complex consisting of the Atlas, Nuns, Tubbs, Pocket, and Redwood Valley fires in northern California that started on October 8, 2017 and the Camp Fire in northern California that was first reported on November 8, 2018. The PM2.5 concentrations measured in populated areas downwind of these fires were well above the 24-h standard of 35 mu g/m3 during several days of both fires. To estimate health risks at locations where ground-based monitors did not provide sufficient spatial coverage we first estimate the emissions from the fires by fitting concentration estimates from two models, a Lagrangian model and a segmented plume dispersion model, to corresponding concentrations from ground monitors. We also use a power law model to fit the measured PM2.5 concentrations to the ratio of aerosol optical depth (AOD) to planetary boundary layer measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried by NASA’s Terra and Aqua satellites. Dispersion model estimates are then combined with estimates from the AOD model to compute ground-level concentrations at a resolution of 1 km. Kriged residuals between estimates from the combined model and measured PM2.5 concentrations are then added to obtain high resolution maps that can be used for exposure studies.
Background: Wildfire smoke is responsible for around 20% of all particulate emissions in the U.S. and affects millions of people worldwide. Children are especially vulnerable, as ambient air pollution exposure during early childhood is associated with reduced lung function. Most studies, however, have focused on the short-term impacts of wildfire smoke exposures. We aimed to identify long-term baseline epigenetic changes associated with early-life exposure to wildfire smoke. We collected nasal epithelium samples for whole genome bisulfite sequencing (WGBS) from two groups of adult female rhesus macaques: one group born just before the 2008 California wildfire season and exposed to wildfire smoke during early-life (n = 8), and the other group born in 2009 with no wildfire smoke exposure during early-life (n = 14). RNA-sequencing was also performed on a subset of these samples. Results: We identified 3370 differentially methylated regions (DMRs) (difference in methylation ≥5%, empirical p < 0.05) and 1 differentially expressed gene (FLOT2) (FDR < 0.05, fold of change ≥ 1.2). The DMRs were annotated to genes significantly enriched for synaptogenesis signaling, protein kinase A signaling, and a variety of immune processes, and some DMRs significantly correlated with gene expression differences. DMRs were also significantly enriched within regions of bivalent chromatin (top odds ratio = 1.46, q-value < 3 x 10^(-6)) that often silence key developmental genes while keeping them poised for activation in pluripotent cells. Conclusions: These data suggest that early-life exposure to wildfire smoke leads to long-term changes in the methylome over genes impacting the nervous and immune systems. Follow-up studies will be required to test whether these changes influence transcription following an immune/respiratory challenge.
Objective: The California Emergency Medical Services Authority manages and deploys California Medical Assistance Teams (CAL-MAT) to disaster medical incidents in the state. This analysis reviews diagnoses for ambulatory medical visits at multiple wildland fire incident base camp field sites in California during the 2020 fire season. Methods: Clinical data without personal health information were extracted retrospectively from patient care records from all patients seen by a provider. Results were entered into Excel spreadsheets with calculation of summary statistics. Results: During the 2020 fire season, CAL-MAT teams deployed 21 times for a total of 327 days to base camps supporting large fire incidents and cared for 1756 patients. Impacts of heat and environmental smoke are a constant factor near wildfires; however, our most common medical problem was rhus dermatitis (54.5%) due to poison oak. All 2020 medical missions were further complicated by prevention and management of coronavirus disease (COVID-19). Conclusions: There is very little literature regarding the acute medical needs facing responders fighting wildland fires. Ninety-five percent of clinical conditions presenting to a field medical team at the wildfire incident base camp during a severe fire season in California can be managed by small teams operating in field tents.
Driven by climate change, wildfires are increasing in frequency, duration, and intensity across the Western United States. Outdoor workers are being exposed to increasing wildfire-related particulate matter and smoke. Recognizing this emerging risk, Washington adopted an emergency rule and is presently engaged in creating a permanent rule to protect outdoor workers from wildfire smoke exposure. While there are growing bodies of literature on the exposure to and health effects of wildfire smoke in the general public and wildland firefighters, there is a gap in knowledge about wildfire smoke exposure among outdoor workers generally and construction workers specifically-a large category of outdoor workers in Washington totaling 200,000 people. Several data sources were linked in this study-including state-collected employment data and national ambient air quality data-to gain insight into the risk of PM2.5 exposure among construction workers and evaluate the impacts of different air quality thresholds that would have triggered a new Washington emergency wildfire smoke rule aimed at protecting workers from high PM2.5 exposure. Results indicate the number of poor air quality days has increased in August and September in recent years. Over the last decade, these months with the greatest potential for particulate matter exposure coincided with an annual peak in construction employment that was typically 9.4-42.7% larger across Washington counties (one county was 75.8%). Lastly, the ‘encouraged’ threshold of the Washington emergency rule (20.5 mu g m(-3)) would have resulted in 5.5 times more days subject to the wildfire rule on average across all Washington counties compared to its ‘required’ threshold (55.5 mu g m(-3)), and in 2020, the rule could have created demand for 1.35 million N-95 filtering facepiece respirators among construction workers. These results have important implications for both employers and policy makers as rules are developed. The potential policy implications of wildfire smoke exposure, exposure control strategies, and data gaps that would improve understanding of construction worker exposure to wildfire smoke are also discussed.
Frequent and widespread wildfires in the northwestern United States and Canada have become the “new normal” during the Northern Hemisphere summer months, which significantly degrades particulate matter air quality in the United States. Using the mid-visible Multi Angle Implementation of Atmospheric Correction (MAIAC) satellitederived aerosol optical depth (AOD) with meteorological information from the European Centre for Medium-Range Weather Forecasts (ECMWF) and other ancillary data, we quantify the impact of these fires on fine particulate matter concentration (PM2.5) air quality in the United States. We use a geographically weighted regression (GWR) method to estimate surface PM2.5 in the United States between low (2011) and high (2018) fire activity years. Our results indicate an overall leave-one-out cross-validation (LOOCV) R-2 value of 0.797 with root mean square error (RMSE) between 3 and 5 mu gm(-3). Our results indicate that smoke aerosols caused significant pollution changes over half of the United States. We estimate that nearly 29 states have increased PM2.5 during the fire-active year and that 15 of these states have PM2.5 concentrations more than 2 times that of the inactive year. Furthermore, these fires increased the daily mean surface PM2.5 concentrations in Washington and Oregon by 38 to 259 mu gm(-3), posing significant health risks especially to vulnerable populations. Our results also show that the GWR model can be successfully applied to PM2.5 estimations from wildfires, thereby providing useful information for various applications such as public health assessment.
Introduction: Wildfire smoke (WFS) exposure is a growing threat to human health, and lower socioeconomic position (SEP) has been shown to increase pollution susceptibility. Studies of SEP-related susceptibility, however, are often compromised due to spatial confounding between lower-SEP and pollution. Here we examine outdoorhoused nonhuman primates, living in natural social hierarchy in a common location, born during years of high vs. low WFS, to examine the separate and combined effects of WFS and social rank, an analog to SEP, on lung and immune function. Methods: Twenty-one females were born during extreme WFS events in summer 2008; 22 were born in summer 2009, during low WFS. Pulmonary function and circulating cytokines were measured three years later, in adolescence. We estimated fine particulate (PM2.5) and ozone exposures during each animal’s first 90 days and three years of age using regulatory data. Early-life social status was estimated using maternal rank at birth, as rank in females is relatively stable throughout life, and closely approximates mother’s rank. We tested associations among WFS exposure, rank, and endpoints using linear regression and ANOVA. Results: Higher WFS exposure in infancy was, on average, associated with lower functional residual capacity (FRC), residual volume (RV), tissue compliance (Ct), and IL-8 secretion in adolescence. Higher social rank conferred significantly higher expiratory reserve volume (ERV) and functional residual capacity (FRC) solely among those born in the high-WFS year (2008). Differences in effects of rank between years were not significant after adjustment for multiple comparisons. Conclusions: Exposure to WFS in infancy generally conferred lower adolescent respiratory volumes and inflammatory cytokines. Higher rank conferred higher respiratory volumes only among females born during WFS, suggesting the possibility that the health benefits of rank may be more apparent under environmental challenge.
BACKGROUND: Global climate change has led to an increase in the prevalence and severity of wildfires. Pollutants released into air, soil and groundwater from wildfires may impact embryo development leading to gastroschisis. OBJECTIVE: The objective of this study was to determine the association between wildfire exposure before and during pregnancy and the risk of foetal gastroschisis development. METHODS: This was a retrospective cohort study using The California Office of Statewide Health Planning and Development Linked Birth File linked to The California Department of Forestry and Fire Protection data between 2007 and 2010. Pregnancies complicated by foetal gastroschisis were identified by neonatal hospital discharge ICD-9 code. Pregnancies were considered exposed to wildfire if the mother’s primary residence zip code was within 15 miles to the closest edge of a wildfire. The exposure was further stratified by trimester or if exposed within 30 days prior to pregnancy. Multivariable log-binomial regression analyses were performed to estimate the association between wildfire exposure in each pregnancy epoch and foetal gastroschisis. RESULTS: Between 2007 and 2010, 844,348 (40%) births were exposed to wildfire in California. Compared with births without wildfire exposure, those with first-trimester exposure were associated with higher rates of gastroschisis, 7.8 vs. 5.7 per 10,000 births (adjusted relative risk [aRR] 1.28, 95% confidence interval [CI] 1.07, 1.54). Furthermore, those with prepregnancy wildfire exposure were also found to have higher rates of gastroschisis, 12.5 vs. 5.7 per 10,000 births, (aRR 2.17, 95% CI 1.42, 3.52). In contrast, second- and third-trimester wildfire exposures were not associated with foetal gastroschisis. CONCLUSIONS: Wildfire exposure within 30 days before pregnancy was associated with more than two times higher risk of foetal gastroschisis, whereas a 28% higher risk was demonstrated if exposure was in the first trimester.
The increased risk of wildfires and associated smoke exposure in the United States is a growing public health problem, particularly along the Wildland-Urban Interface (WUI). Using the measure of fire danger, the Energy Release Component, we define fire danger as the onset and duration of fire season, in the continental US, between 1979 and 2016. We then combine the measure of fire danger with census data to quantify changes in population fire exposure across the WUI. We determined that the largest increases in fire danger were observed in the Southwest, Intermountain, and Pacific Southwest regions. The increased fire danger, specifically during peak fire season, accounted for 6.1 more fires each year and 78,000 more acres burned each year, underscoring the link between fire danger and the risks of large fire occurrence and burn acreage. Finally, we observed significant population growth (121.2% between 1990 and 2010) within high-danger WUI areas, further implying significant increases in potential fire exposure.
Alaskan wildfires have major ecological, social, and economic consequences, but associated health impacts remain unexplored. We estimated cardiorespiratory morbidity associated with wildfire smoke (WFS) fine particulate matter with a diameter less than 2.5 μm (PM(2.5)) in three major population centers (Anchorage, Fairbanks, and the Matanuska-Susitna Valley) during the 2015-2019 wildfire seasons. To estimate WFS PM(2.5), we utilized data from ground-based monitors and satellite-based smoke plume estimates. We implemented time-stratified case-crossover analyses with single and distributed lag models to estimate the effect of WFS PM(2.5) on cardiorespiratory emergency department (ED) visits. On the day of exposure to WFS PM(2.5), there was an increased odds of asthma-related ED visits among 15-65 year olds (OR = 1.12, 95% CI = 1.08, 1.16), people >65 years (OR = 1.15, 95% CI = 1.01, 1.31), among Alaska Native people (OR = 1.16, 95% CI = 1.09, 1.23), and in Anchorage (OR = 1.10, 95% CI = 1.05, 1.15) and Fairbanks (OR = 1.12, 95% CI = 1.07, 1.17). There was an increased risk of heart failure related ED visits for Alaska Native people (Lag Day 5 OR = 1.13, 95% CI = 1.02, 1.25). We found evidence that rural populations may delay seeking care. As the frequency and magnitude of Alaskan wildfires continue to increase due to climate change, understanding the health impacts will be imperative. A nuanced understanding of the effects of WFS on specific demographic and geographic groups facilitates data-driven public health interventions and fire management protocols that address these adverse health effects.
Context: Wildfire events are increasing in prevalence and intensity in the Pacific Northwest. Effective communication of health risks and actions to reduce exposure to wildfire smoke is imperative. Objective: We assessed the content of wildfire smoke risk messages from government organizations and mainstream media during a major wildfire smoke event in August 2018. Design: We conducted a content analysis of wildfire smoke risk information communicated by local and state government organizations and the mainstream media. Setting: Eight Washington State counties during a statewide wildfire smoke event in August 2018. Main Outcome Measure: Leveraging the Extended Parallel Process Model and information in the existing literature on wildfire smoke and health, we assessed messages for the presence of information regarding health risk, personal interventions, administrative interventions, vulnerable populations, and trusted sources of information. Summary statistics were calculated to identify common messages about recommended interventions, vulnerable populations cited, and trusted sources of public health information. Results: Of the 273 identified government and media messages on wildfire smoke, the majority (71% and 66%) contained information about health risks. However, only 46% and 33% of government and media messages contained information about personal interventions to reduce risk, and 37% and 14% of government and media messages contained information about administrative interventions to reduce risk. Less than half of government and media messages (28% and 31%) contained information specific to vulnerable populations, and 58% and 46% of government and media messages contained any reference to a trusted source of information. Conclusions: While information about wildfire smoke and health risks was communicated during Washington’s August 2018 wildfire smoke event, there remains considerable opportunity to include additional information about interventions, vulnerable populations, and trusted sources of information. We recommend several opportunities to improve and evaluate risk communication and risk reduction before, during, and after future wildfire smoke events.
Background: The modular British Columbia Asthma Prediction System (BCAPS) is designed to reduce information burden during wildfire smoke events by automatically gathering, integrating, generating, and visualizing data for public health users. The BCAPS framework comprises five flexible and geographically scalable modules: (1) historic data on fine particulate matter (PM2.5) concentrations; (2) historic data on relevant health indicator counts; (3) PM2.5 forecasts for the upcoming days; (4) a health forecasting model that uses the relationship between (1) and (2) to predict the impacts of (3); and (5) a reporting mechanism. Methods: The 2018 wildfire season was the most extreme in British Columbia history. Every morning BCAPS generated forecasts of salbutamol sulfate (e.g., Ventolin) inhaler dispensations for the upcoming days in 16 Health Service Delivery Areas (HSDAs) using random forest machine learning. These forecasts were compared with observations over a 63-day study period using different methods including the index of agreement (IOA), which ranges from 0 (no agreement) to 1 (perfect agreement). Some observations were compared with the same period in the milder wildfire season of 2016 for context. Results: The mean province-wide population-weighted PM2.5 concentration over the study period was 22.0 mu g/m(3), compared with 4.2 mu g/m(3) during the milder wildfire season of 2016. The PM2.5 forecasts underpredicted the severe smoke impacts, but the IOA was relatively strong with a population-weighted average of 0.85, ranging from 0.65 to 0.95 among the HSDAs. Inhaler dispensations increased by 30% over 2016 values. Forecasted dispensations were within 20% of the observed value in 71% of cases, and the IOA was strong with a population-weighted average of 0.95, ranging from 0.92 to 0.98. All measures of agreement were correlated with HSDA population, where BCAPS performance was better in the larger populations with more moderate smoke impacts. The accuracy of the health forecasts was partially dependent on the accuracy of the PM2.5 forecasts, but they were robust to over- and underpredictions of PM2.5 exposure. Conclusions: Daily reports from the BCAPS framework provided timely and reasonable insight into the population health impacts of predicted smoke exposures, though more work is necessary to improve the PM2.5 and health indicator forecasts.
Wildfire smoke exposure is associated with a range of acute health outcomes, which can be more severe in individuals with underlying health conditions. Currently, there is limited information on the susceptibility of healthcare facilities to smoke infiltration. As part of a larger study to address this gap, a rehabilitation facility in Vancouver, Canada was outfitted with one outdoor and seven indoor low-cost fine particulate matter (PM2.5) sensors in Air Quality Eggs (EGG) during the summer of 2020. Raw measurements were calibrated using temperature, relative humidity, and dew point derived from the EGG data. The infiltration coefficient was quantified using a distributed lag model. Indoor concentrations during the smoke episode were elevated throughout the building, though non-uniformly. After censoring indoor-only peaks, the average infiltration coefficient (range) during typical days was 0.32 (0.22-0.39), compared with 0.37 (0.31-0.47) during the smoke episode, a 19% increase on average. Indoor PM2.5 concentrations quickly reflected outdoor conditions during and after the smoke episode. It is unclear whether these results will be generalizable to other years due to COVID-related changes to building operations, but some of the safety protocols may offer valuable lessons for future wildfire seasons. For example, points of building entry and exit were reduced from eight to two during the pandemic, which likely helped to protect the building from wildfire smoke infiltration. Overall, these results demonstrate the utility of indoor low-cost sensors in understanding the impacts of extreme smoke events on facilities where highly susceptible individuals are present. Furthermore, they highlight the need to employ interventions that enhance indoor air quality in such facilities during smoke events.
The negative synergistic effects of air pollution and sensible heat on public health have been noted in numerous studies. While separate, simplified, and public-facing indices have been developed to communicate the risks of unhealthful levels of air pollution and extreme heat, a combined index containing elements of both has rarely been investigated. Utilizing air quality, meteorology, and mortality data in Monterrey, Mexico, we investigated whether the association between the air quality index (AQI) and mortality was improved by considering elements of the heat index (HI). We created combined indices featuring additive, multiplicative, and either/or formulations and evaluated their relationship to mortality. Results showed increased associations with mortality for models employing indices that combined the AQI and the HI in an additive or multiplicative manner, with increases in the interquartile relative risk of 3-5% over that resulting from models employing the AQI alone.
Extreme heat and ozone are co-occurring exposures that independently and synergistically increase the risk of respiratory disease. To our knowledge, no joint warning systems consider both risks; understanding their interactive effect can warrant use of comprehensive warning systems to reduce their burden. We examined heterogeneity in joint effects (on the additive scale) between heat and ozone at small geographical scales. A within-community matched design with a Bayesian hierarchical model was applied to study this association at the zip code level. Spatially varying relative risks due to interaction (RERI) were quantified to consider joint effects. Determinants of the spatial variability of effects were assessed using a random effects metaregression to consider the role of demographic/neighborhood characteristics that are known effect modifiers. A total of 817,354 unscheduled respiratory hospitalizations occurred in California from 2004 to 2013 in the May to September period. RERIs revealed no additive interaction when considering overall joint effects. However, when considering the zip code level, certain areas observed strong joint effects. A lower median income, higher percentage of unemployed residents, and exposure to other air pollutants within a zip code drove stronger joint effects; a higher percentage of commuters who walk/bicycle, a marker for neighborhood wealth, showed decreased effects. Results indicate the importance of going beyond average measures to consider spatial variation in the health burden of these exposures and predictors of joint effects. This information can be used to inform early warning systems that consider both heat and ozone to protect populations from these deleterious effects in identified areas.
Wildfires can be detrimental to urban and rural communities, causing impacts in the form of psychological stress, direct physical injury, and smoke-related morbidity and mortality. This study examined the area burned by wildfires over the entire state of California from the years 2000 to 2020 in order to quantify and identify whether burned area and fire frequency differed across Census tracts according to socioeconomic indicators over time. Wildfire data were obtained from the California Fire and Resource Assessment Program (FRAP) and National Interagency Fire Center (NIFC), while demographic data were obtained from the American Community Survey. Results showed a doubling in the number of Census tracts that experienced major wildfires and a near doubling in the number of people residing in wildfire-impacted Census tracts, mostly due to an over 23,000 acre/year increase in the area burned by wildfires over the last two decades. Census tracts with a higher fire frequency and burned area had lower proportions of minority groups on average. However, when considering Native American populations, a greater proportion resided in highly impacted Census tracts. Such Census tracts also had higher proportions of older residents. In general, high-impact Census tracts tended to have higher proportions of low-income residents and lower proportions of high-income residents, as well as lower median household incomes and home values. These findings are important to policymakers and state agencies as it relates to environmental justice and the allocation of resources before, during, and after wildfires in the state of California.
The health impacts of wildfire smoke are an important and growing global issue, as extreme wildfire events are expected to increase in frequency and intensity throughout this century due to climate change. Research into individual protective health decision-making can elucidate how wildfire smoke exposure contributes to adverse health outcomes and aid in public health interventions to mitigate risks. In this study we investigate the role of psychological factors (threat and efficacy perceptions) and social processes (social norms and social support) in shaping protective behavior in response to wildfire smoke. Through semi-structured interviews of forty-five individuals in Northern California, we explore perceptions of threat and efficacy, social processes, and protective behaviors in response to wildfire smoke events between 2018 and 2020. We found that for many participants sensory experiences and engagement with wildfire smoke information were instrumental in forming perceptions of threat and efficacy. Three themes related to social processes emerged: interpreting information together, protecting vulnerable others, and questioning protective actions. Through these themes we show how social norms and social support interact in complex, non-linear ways to influence threat and efficacy perceptions, and directly affect protective health behavior. Finally, we propose a conceptual framework of wildfire smoke protective behavior. This study contributes to a growing body of knowledge within the disaster risk and protective health literatures related to wildfire smoke response. Our findings demonstrate how the study of psychological factors and social processes during natural hazards, like wildfire smoke events, is essential to understanding individual protective health decision-making pathways and ultimately, to developing a more comprehensive view of how individual actions affect exposure.
Background We studied the impact of fine particulate matter (PM2.5) exposure due to a remote wildfire event in the Pacific Northwest on daily outpatient respiratory and cardiovascular physician visits during wildfire (24-31 August, 2015) and post-wildfire period (1-30 September, 2015) relative to the pre-wildfire period (1-23 August, 2015) in the city of Calgary, Canada. Methods A quasi-Poisson regression model was used for modelling daily counts of physician visits due to PM2.5 while adjusting for day of the week (weekday versus weekend or public holiday), wildfire exposure period (before, during, after), methane, relative humidity, and wind direction. A subgroup analysis of those with pre-existing diabetes or hypertension was performed. Results An elevated risk of respiratory disease morbidity of 33% (relative risk: RR) [95% confidence interval (CI): 10%-59%] and 55% (95% CI: 42%-69%) was observed per 10 mu g/m(3) increase in PM2.5 level during and after wildfire, respectively, relative to the pre-wildfire time period. Increased risk was observed for children aged 0-9 years during (RR = 1.57, 95% CI: 1.21-2.02) and after the wildfire (RR = 2.11, 95% CI: 1.86-2.40) especially for asthma, acute bronchitis and acute respiratory infection. The risk of physician visits among seniors increased by 11% (95% CI: 3%-21%), and 19% (95% CI: 7%-33%) post-wildfire for congestive heart failure and ischaemic heart disease, respectively. Individuals with pre-existing diabetes had an increased risk of both respiratory and cardiovascular morbidity in the post-wildfire period (RR = 1.35, 95% CI: 1.09-1.67; RR = 1.22, 95% CI: 1.01-1.46, respectively). Conclusions Wildfire-related PM2.5 exposure led to increased respiratory condition-related outpatient physician visits during and after wildfires, particularly for children. An increased risk of physician visits for congestive heart failure and ischaemic heart disease among seniors in the post-wildfire period was also observed.
The increasing incidence of extreme wildfire is becoming a concern for public health. Although long-term exposure to wildfire smoke is associated with respiratory illnesses, reports on the association between short-term occupational exposure to wildfire smoke and lung function remain scarce. In this cross-sectional study, we analyzed data from 218 Royal Canadian Mounted Police officers (mean age: 38 & PLUSMN; 9 years) deployed at the Fort McMurray wildfires in 2016. Individual exposure to air pollutants was calculated by integrating the duration of exposure with the air quality parameters obtained from the nearest air quality monitoring station during the phase of deployment. Lung function was measured using spirometry and body plethysmography. Association between exposure and lung function was examined using principal component linear regression analysis, adjusting for potential confounders. In our findings, the participants were predominantly male (71%). Mean forced expiratory volume in 1 s (FEV1), and residual volume (RV) were 76.5 & PLUSMN; 5.9 and 80.1 & PLUSMN; 19.5 (% predicted). A marginal association was observed between air pollution and higher RV [beta: 1.55; 95% CI: -0.28 to 3.37 per interquartile change of air pollution index], but not with other lung function indices. The association between air pollution index and RV was significantly higher in participants who were screened within the first three months of deployment (2.80; 0.91 to 4.70) than those screened later (-0.28; -2.58 to 2.03), indicating a stronger effect of air pollution on peripheral airways. Acute short-term exposure to wildfire-associated air pollutants may impose subtle but clinically important deleterious respiratory effects, particularly in the peripheral airways.
Western North American fires have been increasing in magnitude and severity over the last few decades. The complex coupling of fires with the atmospheric energy budget and meteorology creates short-term feedbacks on regional weather altering the amount of pollution to which Americans are exposed. Using a combination of model simulations and observations, this study shows that the severe fires in the summer of 2017 increased atmospheric aerosol concentrations leading to a cooling of the air at the surface, reductions in sensible heat fluxes, and a lowering of the planetary boundary layer height over land. This combination of lower-boundary layer height and increased aerosol pollution from the fires reduces air quality. We estimate that from start of August to end of October 2017, ∼400 premature deaths occurred within the western US as a result of short-term exposure to elevated PM2.5 from fire smoke. As North America confronts a warming climate with more fires the short-term climate and pollution impacts of increased fire activity should be assessed within policy aimed to minimize impacts of climate change on society.
Background and purpose: We describe a novel, interprofessional, experiential training involving pharmacy students in response to a health emergency in rural Montana (MT). Educational activity and setting: Fourth-year pharmacy students on clinical rotations were recruited to participate in screening events assessing effects of wildfire smoke in Seeley Lake, MT. Students were required to fulfill at least two hours of supplementary training in addition to education on human research guidelines. Students assisted with patient surveys (demographics, health, and respiratory), physiological testing with biomedical researchers, blood pressure and medication counseling, and spirometry specialists. Findings: At least 20 pharmacy students have participated in this project in addition to nursing (n = 8), public health (n = 1), and social work (n = 1) students. In initial and subsequent screenings, students worked alongside a team of biomedical researchers and faculty from the University of Montana. An initial cohort of 95 patients was recruited. Summary: This unique experiential training opportunity has affordedpharmacy students access to rural community patient interaction and exposure to and performance of a variety of tests in response to an environmental health emergency. Furthermore, it enabled health professionals and researchers to assess individual and overall community health following an extreme wildfire smoke event, providing the groundwork for utilization of pharmacy students in healthcare responses to public health emergencies. (c) 2021 Elsevier Inc. All rights reserved.
The increased frequency of wildfires in the Western United States has raised public awareness of the impact of wildfire smoke on air quality and human health. Exposure to wildfire smoke has been linked to an increased risk of cancer and cardiorespiratory morbidity. Evidence-driven interventions can alleviate the adverse health impact of wildfire smoke. During wildfires, public health guidance is based on regional air quality data with limited spatiotemporal resolution. Recently, low-cost air quality sensors have been used in air quality studies, given their ability to capture high-resolution spatiotemporal data. We demonstrate the use of a network of low-cost particulate matter (PM) sensors to gather indoor and outdoor PM2.5 data from seven locations in the urban Seattle area, along with a personal exposure monitor worn by a resident living in one of these locations during the 2020 Washington wildfire event. The data were used to determine PM concentration indoor/outdoor (I/O) ratios, PM reduction, and personal exposure levels. The result shows that locations equipped with high-efficiency particulate air (HEPA) filters and HVAC filtration systems had significantly lower I/O ratios (median I/O = 0.43) than those without air filtration (median I/O = 0.82). The median PM2.5 reduction for the locations with HEPA is 58% compared to 20% for the locations without HEPA. The outdoor PM sensor showed a high correlation to the nearby regional air quality monitoring stations (pre-calibration R-2 = 0.92). The personal monitor showed higher variance in PM measurements as the user moved through different microenvironments and could not be fully characterized by the network of indoor or outdoor monitors. The findings imply that evidence-based interventions can be developed to reduce pollution exposure when combining data from indoor and outdoor sensors. Personal exposure monitoring captured temporal spikes in PM exposure.
Exceptional events occur when air pollution in a specific location exceeds the National Ambient Air Quality Standards (NAAQS) due to an event that cannot be reasonably attributed to human activities, such as a wildland fire. Ground-level ozone (O-3) and particulate matter (PM) are Environmental Protection Agency (EPA) criteria pollutants regulated under the NAAQS. Smoke from wildland fires can increase PM and O-3 concentrations downwind of fire and impact air quality, visibility, and health. Our analysis shows that the frequency of exceptional event reporting for PM with aerodynamic diameters smaller than 2.5 mu m or 10 mu m (PM2.5 and PM10) had increased since 2007 when the air quality standards became more stringent. We also show that wildland fires and windblown dust drive many exceptional events in several EPA regions. We note the importance of growth in the number of exceptional event days due to wildfire smoke in the future due to climate change and point to possible changes to the NAAQS and implementations.
Increased wildland fire activity is producing extreme fine particulate matter (PM2.5) concentrations impacting millions of people every year, especially in the western United States (US). Recommendations for limiting exposure to PM2.5 and associated adverse health outcomes focus on staying inside, closing windows and doors, and increasing filtration; however, relatively little is known about indoor air quality (IAQ) during major smoke events. Indoor and outdoor hourly PM2.5 (µg m–3) measurements from the publicly available PurpleAir sensor (PAS) network were analyzed for 42 sites (26 residential, 6 school, 10 commercial) across the western US during a September 2020 period of heavy wildfire smoke influence. The fraction of ambient PM2.5 that penetrates indoors and remains airborne (Fin), as well as the ratio (I/O) and correlation coefficient (R2) of indoor to outdoor PM2.5 concentrations, were lower in residential compared to commercial and school buildings. Interventions to improve IAQ were highly influential in PM2.5 infiltration in residential case studies, with multiple, continuously run filter units associated with lower Fin, I/O, and R2. A low-cost PM2.5 filtration method consisting of a Minimum Efficiency Rating Value-13 (MERV-13) filter attached to a box fan is evaluated as an alternative for improving IAQ during wildland fire smoke events. The MERV-13 fan filter unit proved highly effective at reducing indoor PM2.5 and particles 0.3–1.0 µm measured by PAS and a particle counter, respectively, when recirculating air in a single room. Low-cost filtration methods can have significant benefit for filtering submicron smoke particles and may reduce exposure to PM2.5 during wildfire smoke events.
Objective(s): This study explored the feasibility, acceptability, preliminary impact, and functionality of two risk reduction mobile application (app) interventions on asthma outcomes as compared to a control arm during wildfire season. Design: Three-arm, 8-week randomized clinical trial. Sample: Sixty-seven young adults with asthma were enrolled. Measurements: The Asthma Control Test, forced expiratory volume in one second (FEV1) and the System Usability Scale were measured at baseline, 4, and 8 weeks. The Research Attitude Scale was administered at 8 weeks. Twenty participants from the two intervention arms completed an optional survey and six were interviewed after completing the study. Intervention: Both intervention arms could access Smoke Sense Urbanova, an app that supports reducing risks from breathing wildfire smoke. The Smoke Sense Urbanova Plus arm also monitored their daily FEV1, received air quality notifications, and accessed preventive tips and a message board. Results: Most participants agreed the app and spirometer were usable and their privacy and confidentiality were maintained. No adverse events were reported. Conclusions: Participant-identified recommendations will support intervention refinement and testing. This research supports asthma self-management tools that public health nurses and community health workers can recommend for at-risk populations.
Wildland fires are diminishing air quality on a seasonal and regional basis, raising concerns about respiratory health risks to the public and occupational groups. This American Thoracic Society (ATS) workshop was convened in 2019 to meet the growing health threat of wildland fire smoke. The workshop brought together a multidisciplinary group of 19 experts, including wildland fire managers, public health officials, epidemiologists, toxicologists, and pediatric and adult pulmonologists. The workshop examined the following four major topics: 1) the science of wildland fire incidence and fire management, 2) the respiratory and cardiovascular health effects of wildland fire smoke exposure, 3) communication strategies to address these health risks, and 4) actions to address wildland fire health impacts. Through formal presentations followed by group discussion, workshop participants identified top priorities for fire management, research, communication, and public policy to address health risks of wildland fires. The workshop concluded that short-term exposure to wildland smoke causes acute respiratory health effects, especially among those with asthma and chronic obstructive pulmonary disease. Research is needed to understand long-term health effects of repeated smoke exposures across fire seasons for children, adults, and highly exposed occupational groups (especially firefighters). Other research priorities include fire data collection and modeling, toxicology of different fire fuel sources, and the efficacy of health protective measures to prevent respiratory effects of smoke exposure. The workshop committee recommends a unified federal response to the growing problem of wildland fires, including investment in fire behavior and smoke air quality modeling, research on the health impacts of smoke, and development of robust clinical and public health communication tools.
Recent dramatic and deadly increases in global wildfire activity have increased attention on the causes of wildfires, their consequences, and how risk from wildfire might be mitigated. Here we bring together data on the changing risk and societal burden of wildfire in the United States. We estimate that nearly 50 million homes are currently in the wildland-urban interface in the United States, a number increasing by 1 million houses every 3 y. To illustrate how changes in wildfire activity might affect air pollution and related health outcomes, and how these linkages might guide future science and policy, we develop a statistical model that relates satellite-based fire and smoke data to information from pollution monitoring stations. Using the model, we estimate that wildfires have accounted for up to 25% of PM (2.5) (particulate matter with diameter <2.5 μm) in recent years across the United States, and up to half in some Western regions, with spatial patterns in ambient smoke exposure that do not follow traditional socioeconomic pollution exposure gradients. We combine the model with stylized scenarios to show that fuel management interventions could have large health benefits and that future health impacts from climate-change-induced wildfire smoke could approach projected overall increases in temperature-related mortality from climate change-but that both estimates remain uncertain. We use model results to highlight important areas for future research and to draw lessons for policy.
Smoke impacts from large wildfires are mounting, and the projection is for more such events in the future as the one experienced October 2017 in Northern California, and subsequently in 2018 and 2020. Further, the evidence is growing about the health impacts from these events which are also difficult to simulate. Therefore, we simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling with WRF-CMAQ, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses. To demonstrate these analyses, we estimated the health impacts from smoke impacts during wildfires in October 8-20, 2017, in Northern California, when over 7 million people were exposed to Unhealthy to Very Unhealthy air quality conditions. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ system. Interestingly, this approach did not necessarily improve overall results, however it was key to simulating the initial 12-hr explosive fire activity and smoke impacts. To improve these results, we applied one data fusion and three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across all cases, the best Pearson correlation was 0.5. Overall, WRF-CMAQ simulations were biased high and the geostatistical methods were biased low. Finally, we applied the optimized PM2.5 exposure estimate in an exposure-response function. Estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% CI: 0, 196) with 47% attributable to wildland fire smoke.Implications: Large wildfires in the United States and in particular California are becoming increasingly common. Associated with these large wildfires are air quality and health impact to millions of people from the smoke. We simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses from the October 2017 Northern California wildfires. Temporary monitors deployed for the wildfires provided an important model evaluation dataset. Total estimated regional mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to the wildland fire smoke. This illustrates the profound effect that even a 12-day exposure to wildland fire smoke can have on human health.
Wildland fire smoke contains hazardous levels of fine particulate mat-ter (PM2.5), a pollutant shown to adversely effect health. Estimating fire at-tributable PM2.5 concentrations is key to quantifying the impact on air quality and subsequent health burden. This is a challenging problem since only to-tal PM2.5 is measured at monitoring stations and both fire-attributable PM2.5 and PM2.5 from all other sources are correlated in space and time. We propose a framework for estimating fire-contributed PM2.5 and PM2.5 from all other sources using a novel causal inference framework and bias-adjusted chemical model representations of PM2.5 under counterfactual scenarios. The chemical model representation of PM2.5 for this analysis is simulated using Commu-nity Multiscale Air Quality Modeling System (CMAQ), run with and without fire emissions across the contiguous U.S. for the 2008-2012 wildfire seasons. The CMAQ output is calibrated with observations from monitoring sites for the same spatial domain and time period. We use a Bayesian model that ac-counts for spatial variation to estimate the effect of wildland fires on PM2.5 and state assumptions under which the estimate has a valid causal interpreta-tion. Our results include estimates of the contributions of wildfire smoke to PM2.5 for the contiguous U.S. Additionally, we compute the health burden associated with the PM2.5 attributable to wildfire smoke.
Wildfire smoke is a growing public health concern in the United States. Numerous studies have documented associations between ambient smoke exposure and severe patient outcomes for single-fire seasons or limited geographic regions. However, there are few national-scale health studies of wildfire smoke in the United States, few studies investigating Intensive Care Unit (ICU) admissions as an outcome, and few specifically framed around hospital operations. This study retrospectively examined the associations between ambient wildfire-related PM2.5 at a hospital ZIP code with total hospital ICU admissions using a national-scale hospitalization data set. Wildfire smoke was characterized using a combination of kriged PM2.5 monitor observations and satellite-derived plume polygons from National Oceanic and Atmospheric Administration’s Hazard Mapping System. ICU admissions data were acquired from Premier, Inc. and encompass 15%-20% of all U.S. ICU admissions during the study period. Associations were estimated using a distributed-lag conditional Poisson model under a time-stratified case-crossover design. We found that a 10 mu g/m(3) increase in daily wildfire PM2.5 was associated with a 2.7% (95% CI: 1.3, 4.1; p = 0.00018) increase in ICU admissions 5 days later. Under stratification, positive associations were found among patients aged 0-20 and 60+, patients living in the Midwest Census Region, patients admitted in the years 2013-2015, and non-Black patients, though other results were mixed. Following a simulated severe 7-day 120 mu g/m(3) smoke event, our results predict ICU bed utilization peaking at 131% (95% CI: 43, 239; p < 10(-5)) over baseline. Our work suggests that hospitals may need to preposition vital critical care resources when severe smoke events are forecast. Plain Language Summary Wildfire smoke negatively affects people's health. Heavy smoke has been linked to higher rates of hospital admissions, emergency room, admissions, and death. However, we do not know the impact of smoke on Intensive Care Unit (ICU) admissions or on limited hospital resources like ICU beds. To fill this knowledge gap, we linked hospital ICU admissions to smoke levels near those hospitals. We also predicted how many ICU admissions would occur during a simulated severe week-long smoke event and how many ICU beds would be needed to care for the patients. We found that the link between smoke and ICU admissions was relatively modest, but a severe smoke event could more than double the number of ICU beds needed.
Wildfires are natural ecological processes that generate high levels of fine particulate matter (PM2.5) that are dispersed into the atmosphere. PM2.5 could be a potential health problem due to its size. Having adequate numerical models to predict the spatial and temporal distribution of PM2.5 helps to mitigate the impact on human health. The compositional data approach is widely used in the environmental sciences and concentration analyses (parts of a whole). This numerical approach in the modelling process avoids one common statistical problem: the spurious correlation. PM2.5 is a part of the atmospheric composition. In this way, this study developed an hourly spatio-temporal PM2.5 model based on the dynamic linear modelling framework (DLM) with a compositional approach. The results of the model are extended using a Gaussian-Mattern field. The modelling of PM2.5 using a compositional approach presented adequate quality model indices (NSE = 0.82, RMSE = 0.23, and a Pearson correlation coefficient of 0.91); however, the correlation range showed a slightly lower value than the conventional/traditional approach. The proposed method could be used in spatial prediction in places without monitoring stations.
We developed daily maps of surface fine particulate matter (PM(2.5)) for the western United States. We used geographically weighted regression fit to air quality station observations with Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) data, and meteorological data to produce daily 1-kilometer resolution PM(2.5) concentration estimates from 2003-2020. To account for impacts of stagnant air and inversions, we included estimates of inversion strength based on meteorological conditions, and inversion potential based on human activities and local topography. Model accuracy based on cross-validation was R(2) = 0.66. AOD data improve the model in summer and fall during periods of high wildfire activity while the stagnation terms capture the spatial and temporal dynamics of PM(2.5) in mountain valleys, particularly during winter. These data can be used to explore exposure and health outcome impacts of PM(2.5) across spatiotemporal domains particularly in the intermountain western United States where measurements from monitoring station data are sparse. Furthermore, these data may facilitate analyses of inversion impacts and local topography on exposure and health outcome studies.
We estimated cardiopulmonary morbidity and mortality associated with wildfire smoke (WFS) fine particulate matter (PM2.5) in the Front Range of Colorado from 2010 to 2015. To estimate WFS PM2.5, we developed a daily kriged PM2.5 surface at a 15 x 15 km resolution based on the Environmental Protection Agency Air Quality System monitors for the western United States; we subtracted out local seasonal-average PM2.5 of nonsmoky days, identified using satellite-based smoke plume estimates, from the local daily estimated PM2.5 if smoke was identified by National Oceanic and Atmospheric Administration’s Hazard Mapping System. We implemented time-stratified case-crossover analyses to estimate the effect of a 10 mu g/m(3) increase in WFS PM2.5 with cardiopulmonary hospitalizations and deaths using single and distributed lag models for lags 0-5 and distinct annual impacts based on local and long-range smoke during 2012, and long-range transport of smoke in 2015. A 10 mu g/m(3) increase in WFS was associated with all respiratory, asthma, and chronic obstructive pulmonary disease hospitalizations for lag day 3 and hospitalizations for ischemic heart disease at lag days 2 and 3. Cardiac arrest deaths were associated with WFS PM2.5 at lag day 0. For 2012 local wildfires, asthma hospitalizations had an inverse association with WFS PM2.5 (OR: 0.716, 95% CI: 0.517-0.993), but a positive association with WFS PM2.5 during the 2015 long-range transport event (OR: 1.455, 95% CI: 1.093-1.939). Cardiovascular mortality was associated with the 2012 long-range transport event (OR: 1.478, 95% CI: 1.124-1.944).
Wildfire activity in the western United States (US) has been increasing, a trend that has been correlated with changing patterns of temperature and precipitation associated with climate change. Health effects associated with exposure to wildfire smoke and fine particulate matter (PM(2.5)) include short- and long-term premature mortality, hospital admissions, emergency department visits, and other respiratory and cardiovascular incidents. We estimate PM(2.5) exposure and health impacts for the entire continental US from current and future western US wildfire activity projected for a range of future climate scenarios through the 21st century. We use a simulation approach to estimate wildfire activity, area burned, fine particulate emissions, air quality concentrations, health effects, and economic valuation of health effects, using established and novel methodologies. We find that climatic factors increase wildfire pollutant emissions by an average of 0.40% per year over the 2006-2100 period under Representative Concentration Pathway (RCP) 4.5 (lower emissions scenarios) and 0.71% per year for RCP8.5. As a consequence, spatially weighted wildfire PM(2.5) concentrations more than double for some climate model projections by the end of the 21st century. PM(2.5) exposure changes, combined with population projections, result in a wildfire PM2.5-related premature mortality excess burden in the 2090 RCP8.5 scenario that is roughly 3.5 times larger than in the baseline period. The combined effect of increased wildfire activity, population growth, and increase in the valuation of avoided risk of premature mortality over time results in a large increase in total economic impact of wildfire-related PM(2.5) mortality and morbidity in the continental US, from roughly $7 billion per year in the baseline period to roughly $36 billion per year in 2090 for RCP4.5, and $43 billion per year in RCP8.5. The climate effect alone accounts for a roughly 60% increase in wildfire PM2.5-related premature mortality in the RCP8.5 scenario, relative to baseline conditions.
BACKGROUND: Rising temperatures due to climate change are expected to impact human adaptive response, including changes to home cooling and ventilation patterns. These changes may affect air pollution exposures via alteration in residential air exchange rates, affecting indoor infiltration of outdoor particles. We conducted a field study examining associations between particle infiltration and temperature to inform future studies of air pollution health effects. METHODS: We measured indoor fine particulate matter (PM(2.5)) in Atlanta in 60 homes (810 sampling-days). Indoor-outdoor sulfur ratios were used to estimate particle infiltration, using central site outdoor sulfur concentrations. Linear and mixed-effects models were used to examine particle infiltration ratio-temperature relationships, based on which we incorporated projected meteorological values (Representative Concentration Pathways intermediate scenario RCP 4.5) to estimate particle infiltration ratios in 20-year future (2046-2065) and past (1981-2000) scenarios. RESULTS: The mean particle infiltration ratio in Atlanta was 0.70 ± 0.30, with a 0.21 lower ratio in summer compared to transition seasons (spring, fall). Particle infiltration ratios were 0.19 lower in houses using heating, ventilation, and air conditioning (HVAC) systems compared to those not using HVAC. We observed significant associations between particle infiltration ratios and both linear and quadratic models of ambient temperature for homes using natural ventilation and those using HVAC. Future temperature was projected to increase by 2.1 °C in Atlanta, which corresponds to an increase of 0.023 (3.9%) in particle infiltration ratios during cooler months and a decrease of 0.037 (6.2%) during warmer months. DISCUSSION: We estimated notable changes in particle infiltration ratio in Atlanta for different 20-year periods, with differential seasonal patterns. Moreover, when stratified by HVAC usage, increases in future ambient temperature due to climate change were projected to enhance seasonal differences in PM(2.5) infiltration in Atlanta. These analyses can help minimize exposure misclassification in epidemiologic studies of PM(2.5), and provide a better understanding of the potential influence of climate change on PM(2.5) health effects.
Air pollution, climate change, and other environmental factors contribute to increasing asthma in many cities, including Washington, DC. This work provides a case study of how community input, neighborhood-level health surveys, and air quality monitoring can inform the understanding of asthma and air pollution. A partnership between residents, concerned citizens, scientists, and educators has been working for environmental health in a DC neighborhood located on a major roadway, next to concrete batch plants and close to several construction projects. A 2016 Community Health and Safety Study by the DC Department of Health, Office of Health Equity, recognized this particular neighborhood as more vulnerable to health impacts from recent construction in the area, compared with the surrounding areas, due to lower average income and higher percentage of seniors and children. This work presents neighborhood health surveys and air quality monitoring data at a more granular, local level than available from DC government agencies. The health surveys documented residents’ experiences around air pollution, asthma, and other health concerns. A key finding was evidence that asthma might be undercounted in this neighborhood; among residents who did not indicate a diagnosis of asthma, many discussed having symptoms that could reflect asthma. Air quality monitoring (particulate matter [PM]) did not indicate that federal air quality standards have been violated. Real-time PM data, however, illustrated how current PM standards, such as 1- and 24-hour averages, may fail to capture shorter duration high PM events that are consistent with resident concerns.
BACKGROUND: While ozone levels in the USA have decreased since the 1980s, the Denver Metro North Front Range (DMNFR) region remains in nonattainment of the National Ambient Air Quality Standard (NAAQS). OBJECTIVE: To estimate the warm season ozone climate penalty to characterize its impact on Colorado Front Range NAAQS attainment and health equity. METHODS: May to October ozone concentrations were estimated using spatio-temporal land-use regression models accounting for climate and weather patterns. The ozone climate penalty was defined as the difference between the 2010s concentrations and concentrations predicted using daily 2010s weather adjusted to match the 1950s climate, holding constant other factors affecting ozone formation. RESULTS: The ozone climate penalty was 0.5-1.0 ppb for 8-h max ozone concentrations. The highest penalty was around major urban centers and later in the summer. The penalty was positively associated with census tract-level percentage of Hispanic/Latino residents, children living within 100-200% of the federal poverty level, and residents with asthma, diabetes, fair or poor health status, or lacking health insurance. SIGNIFICANCE: The penalty increased the DMNFR ozone NAAQS design values, delaying extrapolated future attainment of the 2008 and 2015 ozone standards by approximately 2 years each, to 2025 and 2035, respectively.
BACKGROUND: Air pollution is linked to preterm birth (PTB), but existing studies are primarily focused on chronic exposures, conducted in areas with moderate pollution, and/or subject to confounding. OBJECTIVES: We investigated short-term associations between two pollutants [particulate matter <2.5 microns (PM(2.5) ) and ozone] and PTB, and estimated excess PTB cases potentially attributed to these pollutants. METHODS: This time-stratified case-crossover study includes 196,970 singleton pregnancies affected by PTB and early term birth from the San Joaquin Valley (SJV), California, USA (2007-2015). Daily ozone and PM(2.5) concentrations were estimated by the SJV Air Pollution Control District and geospatially linked to maternal zip code. We used conditional logistic regression models to estimate the odds ratio (OR) and 95% confidence intervals (CI) for the associations between an interquartile range (IQR) increase in pollutants and very preterm (VPTB, 20-34 weeks), moderate preterm (MPTB, 34-36 weeks) and early term births (ETB, 37-38 weeks). We adjusted all models for co-pollutants and meteorological factors. RESULTS: During warm seasons (May-October), an IQR increase in ozone was associated with 9-11% increased odds of VPTB from lag 0 (OR(lag0) 1.09, 95% CI 1.04,1.16) to lag 7 (OR(lag7) 1.11, 95% CI 1.04,1.16). Findings were consistent for MPTB and ETB. Ozone was potentially responsible for an excess of 3-6 VPTBs, 7-9 PTBs and 24-42 ETBs per 1,000 singleton deliveries. During cold seasons (November-April), increased PM(2.5) exposure was associated with 5-6% increased odds of VPTB beginning at lag 3 (OR(lag3) 1.06, 95% CI 1.02,1.11). PM(2.5) was associated with an excess of 1-3 VPTBs, 0-3 MPTBs and 6-18 ETBs per 1,000 singleton deliveries. CONCLUSIONS: PM(2.5) and ozone are associated with increased risk of VPTB, MPTB and ETB within one week of exposure and are potential contributors to the increasing PTB trend. More research is needed to further understand the role of air pollution on PTB risk.
Wildfires and meteorological conditions influence the co-occurrence of multiple harmful air pollutants including fine particulate matter (PM2.5) and ground-level ozone. We examine the spatiotemporal characteristics of PM2.5/ozone co-occurrences and associated population exposure in the western United States (US). The frequency, spatial extent, and temporal persistence of extreme PM2.5/ozone co-occurrences have increased significantly between 2001 and 2020, increasing annual population exposure to multiple harmful air pollutants by similar to 25 million person-days/year. Using a clustering methodology to characterize daily weather patterns, we identify significant increases in atmospheric ridging patterns conducive to widespread PM2.5/ozone co-occurrences and population exposure. We further link the spatial extent of co-occurrence to the extent of extreme heat and wildfires. Our results suggest an increasing potential for co-occurring air pollution episodes in the western US with continued climate change.
BACKGROUND: Long-term exposures to air pollution has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood. OBJECTIVES: We aimed to determine the changes in the blood metabolome and thus the metabolic pathways associated with long-term exposure to outdoor air pollution and ambient temperature. METHODS: We quantified metabolites using mass-spectrometry based global untargeted metabolomic profiling of plasma samples among men from the Normative Aging Study (NAS). We estimated the association between long-term exposure to PM(2.5), NO(2), O(3), and temperature (annual average of central site monitors) with metabolites and their associated metabolic pathways. We used multivariable linear mixed-effect regression models (LMEM) while simultaneously adjusting for the four exposures and potential confounding and correcting for multiple testing. As a reduction method for the intercorrelated metabolites (outcome), we further used an independent component analysis (ICA) and conducted LMEM with the same exposures. RESULTS: Men (N = 456) provided 648 blood samples between 2000 and 2016 in which 1158 metabolites were quantified. On average, men were 75.0 years and had an average body mass index of 27.7 kg/m(2). Almost all men (97%) were not current smokers. The adjusted analysis showed statistically significant associations with several metabolites (58 metabolites with PM(2.5), 15 metabolites with NO(2), and 6 metabolites with temperature) while no metabolites were associated with O(3). One out of five ICA factors (factor 2) was significantly associated with PM(2.5). We identified eight perturbed metabolic pathways with long-term exposure to PM(2.5) and temperature: glycerophospholipid, sphingolipid, glutathione, beta-alanine, propanoate, and purine metabolism, biosynthesis of unsaturated fatty acids, and taurine and hypotaurine metabolism. These pathways are related to inflammation, oxidative stress, immunity, and nucleic acid damage and repair. CONCLUSIONS: Using a global untargeted metabolomic approach, we identified several significant metabolites and metabolic pathways associated with long-term exposure to PM(2.5), NO(2) and temperature. This study is the largest metabolomics study of long-term air pollution, to date, the first study to report a metabolomic signature of long-term temperature exposure, and the first to use ICA in the analysis of both.
Exposure to fine particulate matter (PM(2.5)) is associated with asthma development as well as asthma exacerbation in children. PM(2.5) can be directly emitted or can form in the atmosphere from pollutant precursors. PM(2.5) emitted and formed in the atmosphere is influenced by meteorology; future changes in climate may alter the concentration and distribution of PM(2.5). Our aim is to estimate the future burden of climate change and PM(2.5) on new and exacerbated cases of childhood asthma. Projected concentrations of PM(2.5) are based on the Geophysical Fluid Dynamics Laboratory Coupled Model version 3 climate model, the Representative Concentration Pathway 8.5 greenhouse gas scenario, and two air pollution emissions datasets: a 2011 emissions dataset and a 2040 emissions dataset that reflects substantial reductions in emissions of PM(2.5) as compared to the 2011 inventory. We estimate additional PM(2.5)-attributable asthma as well as PM(2.5)-attributable albuterol inhaler use for four future years (2030, 2050, 2075, and 2095) relative to the year 2000. Exacerbations, regardless of the trigger, are counted as attributable to PM(2.5) if the incident disease is attributable to PM(2.5). We project 38 thousand (95% CI 36, 39 thousand) additional PM(2.5)-attributable incident childhood asthma cases and 29 million (95% CI 27, 31 million) additional PM(2.5)-attributable albuterol inhaler uses per year in 2030, increasing to 200 thousand (95% CI 190, 210 thousand) additional incident cases and 160 million (95% CI 150, 160 million) inhaler uses per year by 2095 relative to 2000 under the 2011 emissions dataset. These additional PM(2.5)-attributable incident asthma cases and albuterol inhaler use would cost billions of additional U.S. dollars per year by the late century. These outcomes could be mitigated by reducing air pollution emissions.
Particulate matter 2.5 (PM2.5) exposure induces oxidative stress associated with many negative health outcomes such as respiratory disorders, cardiovascular disease and neurodegenerative disease. Research shows that diet and exercise can improve antioxidant defense against oxidative stress. This study is the first to use an Arctic animal model to investigate the cumulative effects of two lifestyle interventions on the antioxidant response before, during, and after ambient PM 2.5 exposure from wildfire: antioxidant supplementation (Arthrospira platensis) and exercise. In a two-factorial, longitudinal design, this study divided sled dogs (n = 48) into four groups (exercise and supplemented, exercise, supplemented, and control) to (1) test the effects of a 30-day exercise and antioxidant supplementation protocol on antioxidant response; and (2) measure the antioxidant response of all groups during and after a natural wildfire event. Commercial assays for total antioxidant power (TAP) and the enzymatic antioxidant superoxide dismutase (SOD) were used as markers for antioxidant status and response. During the forest fire, SOD was increased 5- to 10-fold over pre/post-exposure levels in all groups suggesting an endogenous upregulation of defense systems in response to the acute environmental stress. TAP was lower in all groups at peak PM2.5 exposure compared to 48 h after peak exposure in all groups except the exercise alone group which may indicate that exercise offers improved endogenous defense.
Decarbonizing power systems is a critical component of climate change mitigation, which can have public health cobenefits by reducing air pollution. Many studies have examined strategies to decarbonize power grids and quantified their health cobenefits. However, few of them focus on near-term cobenefits at community levels, while comparing various decarbonization pathways. Here, we use a coupled power system and air quality modeling framework to quantify the costs and benefits of decarbonizing the Texas power grid through a carbon tax; replacing coal with natural gas, solar, or wind; and internalizing human health impacts into operations. Our results show that all decarbonization pathways can result in major reductions in CO(2) emissions and public health impacts from power sector emissions, leading to large net benefits when considering the costs to implement these strategies. Operational changes with existing infrastructure can serve as a transitional strategy during the process of replacing coal with renewable energy, which offers the largest benefits. However, we also find that Black and lower-income populations receive disproportionately higher air pollution damages and that none of the examined decarbonization strategies mitigate this disparity. These findings suggest that additional interventions are necessary to mitigate environmental inequity while decarbonizing power grids.
Local and state policymakers have become increasingly interested in developing policies that both reduce greenhouse gas (GHG) emissions and improve local air quality, along with public health. Interest in developing transportation-related policies has grown as transportation became the largest contributing sector to GHG emissions in the United States in 2017. Information on current emissions and health impacts, along with trends over time, is helpful to policymakers who are developing strategies to reduce emissions and improve public health, especially in areas with high levels of transportation-related emissions. Here, we provide a comprehensive assessment of the public health and climate social costs of on-road emissions by linking emissions data generated by the U.S. Environmental Protection Agency to reduced complexity models that provide impacts per ton emitted for pollutants which contribute to ambient fine particulate matter, and the social costs of GHG emissions from on-road transportation. For 2017, social costs totaled $184 billion (min: $78 billion; max: $280 billion) for all on-road emissions from the eight health and climate pollutants that we assessed in the continental U.S. (in $2017 USD). Within this total social cost estimate, health pollutants constituted $93 billion of the social costs (min: $52 billion; max: $146 billion), and climate pollutants constituted $91 billion (min: $26 billion; max: $134 billion). The majority of these social costs came from CO2 followed by NO (x) emissions from privately owned individual vehicles in urban counties (CO2 contributed $51 billion and NO (x) contributed $16 billion in social costs from individual vehicles in urban counties). However, it is important to note that not all the attention should be placed solely on individual vehicles. Although the climate social costs of individual vehicle emissions are higher than those from commercial vehicles in urban counties (by two to eight times depending on the climate pollutant), the health social costs of individual vehicle emissions are roughly equal to those from commercial vehicles in urban counties. Regardless of each pollutant’s contributions to the social costs, the highest social benefits from reducing 1 ton of CO2 and its co-pollutants would occur in urban counties, given their high population density.
Pollution from wildfires constitutes a growing source of poor air quality globally. To protect health, governments largely rely on citizens to limit their own wildfire smoke exposures, but the effectiveness of this strategy is hard to observe. Using data from private pollution sensors, cell phones, social media posts and internet search activity, we find that during large wildfire smoke events, individuals in wealthy locations increasingly search for information about air quality and health protection, stay at home more and are unhappier. Residents of lower-income neighbourhoods exhibit similar patterns in searches for air quality information but not for health protection, spend less time at home and have more muted sentiment responses. During smoke events, indoor particulate matter (PM(2.5)) concentrations often remain 3-4× above health-based guidelines and vary by 20× between neighbouring households. Our results suggest that policy reliance on self-protection to mitigate smoke health risks will have modest and unequal benefits.
The increasing number and severity of wildfires is negatively impacting air quality for millions of California residents each year. Community exposure to PM(2.5) in two main population centers (San Francisco Bay area and Los Angeles County area) was assessed using the low-cost PurpleAir sensor network for the record-setting 2020 California wildfire season. Estimated PM(2.5) concentrations in each study area were compared to census tract-level environmental justice vulnerability indicators, including environmental, health, and demographic data. Higher PM(2.5) concentrations were positively correlated with poverty, cardiovascular emergency department visits, and housing inequities. Sensors within 30 km of actively burning wildfires showed statistically significant increases in indoor (~800 %) and outdoor (~540 %) PM(2.5) during the fires. Results indicate that wildfire emissions may exacerbate existing health disparities as well as the burden of pollution in disadvantaged communities, suggesting a need to improve monitoring and adaptive capacity among vulnerable populations.
As wildfires increase in prevalence and intensity across California and globally, it is anticipated that more children will be exposed to wildfire smoke, and thus face associated adverse health outcomes. Here, we provide a concise summary of the respiratory effects of California’s wildfires on pediatric healthcare utilization, examine global examples of wildfire smoke exposure within the pediatric population and associated physiological effects, and assess the efficacy of metrics used to measure and communicate air quality during wildfires within the United States and elsewhere.
Climate change and human activities have drastically altered the natural wildfire balance in the Western US and increased population health risks due to exposure to pollutants from fire smoke. Using dynamically downscaled climate model projections, we estimated additional asthma emergency room visits and hospitalizations due to exposure to smoke fine particulate matter (PM2.5) in the Western US in the 2050s. Isolating the amount of PM2.5 from wildfire smoke is both difficult to estimate and, thus, utilized by relatively few studies. In this study, we use a sophisticated modeling approach to estimate future increase in wildfire smoke exposure over the reference period (2003-2010) and subsequent health care burden due to asthma exacerbation. Average increases in smoke PM2.5 during future fire season ranged from 0.05 to 9.5 mu g m(-3) with the highest increases seen in Idaho, Montana, and Oregon. Using the Integrated Climate and Land-Use Scenarios (ICLUS) A2 scenario, we estimated the smoke-related asthma events could increase at a rate of 15.1 visits per 10 000 persons in the Western US, with the highest rates of increased asthma (25.7-41.9 per 10 000) in Idaho, Montana, Oregon, and Washington. Finally, we estimated healthcare costs of smoke-induced asthma exacerbation to be over $1.5 billion during a single future fire season. Here we show the potential future health impact of climate-induced wildfire activity, which may serve as a key tool in future climate change mitigation and adaptation planning.
Biomass burning emits a wide range of carbona-ceous particles into the atmosphere and has negative impacts on human health and the Earth’s radiative balance. Nonvolatile spherical organic aerosol particles, commonly known as tar balls, represent one of the most abundant particles in aged biomass burning smoke. However, the detailed molecular level composition of ambient tar balls is largely unknown but critical to assess their environmental impacts. Ambient aerosol samples collected during a wildfire event, which were similar to 90% tar balls by number fraction, were analyzed using ultrahigh-resolution Orbitrap Elite mass spectrometry with four complementary ionization modes. Our results show the molecular composition of tar balls to be complex, composed of over 10,000 molecular formulas. Model estimated saturation mass concentrations and relative humidity-dependent glass-transition temperatures were consistent with low volatility and solid morphology as expected for tar balls. Room-temperature evaporation kinetics showed that these particles retained similar to 90% of their volume after 24 h of evaporation. The molecular complexity detected here signifies a continuum of carbonaceous species, ranging from C-3 to C-45 with continuous ranges of oxygenation and hydrogen saturation for each Cn. Approximately 24% of molecular formulas were estimated to be highly aromatic, which could indicate chemical compounds with negative health effects and which may contribute to visible light absorption. The carbon continuum observed here has significant implications for the molecular characterization of atmospheric organic matter. The level of complexity detected here should not be ignored in future studies, and we demonstrate that multiple analytical methods may be required to suitably interpret this complexity on a molecular level.
This paper presents findings from an online survey that explored public experiences of wildfire smoke, public health advisory information, risk perceptions, and protective actions in response to wildfire smoke in western Canada. Most respondents had wildfire smoke experiences lasting several days with decreased visibility, and many had difficulty breathing and changes to their health. While a majority of respondents were aware of the Air Quality Health Index and how to respond on a high risk day, some did not. Most respondents perceived the risk from wildfire smoke during their most recent experience to be extreme, severe, or moderate, with only 20% perceiving low risk from wildfire smoke. Wildfire smoke experiences affected risk perceptions, and female respondents perceived the risk from wildfire smoke to be higher in comparison to male respondents. Most respondents took protective actions during their most recent exposure to wildfire smoke, with the most popular measures including keeping windows and doors shut, and limiting time spent outdoors. Perceptions of wildfire smoke risks, experiencing health impacts from wildfire smoke, sex and highest level of education, and firefighting experience influenced protective actions. Recommendations to improve public health during wildfire smoke events and future research are included.
First Nation reserves in Canada are at high risk from wildfires, with many evacuated every year. There is a need to understand how First Nations are affected by wildfire evacuations to identify ways to reduce negative impacts. The First Nations Wildfire Evacuation Partnership has conducted research to explore evacuation experiences of seven First Nations in three Canadian provinces. This paper presents findings from research across the seven First Nations. Results show that few participating First Nations had an up to date emergency plan tailored to their community, which contributed to challenges during the evacuation. Family separation, insufficient information, and worries about losing their house caused considerable distress for evacuees. Wildfire smoke health impacts occurred, particularly for those who had pre-existing health conditions. Social and financial support, if available, helped evacuees during and after their evacuation. Several years after First Nations return home after a wildfire evacuation, lingering distress continues and some First Nations were still experiencing fiscal challenges as a result of the evacuation. Recommendations for reducing negative impacts of wildfire evacuations on First Nations people are discussed.
Mexico is expected to become the 6th largest economy in 2050. According to EDGAR database, in 2019 it was the largest polluting country in Latin America and the 13th in the world, regarding Greenhouse Gas (GHG) emissions. Lately, the new Administration has shifted its energy strategy from a renewable path into the reinforcement of conventional energy sources. In this context, new policies have to be deployed to meet the Paris Agreement goals. In such scenario, carbon capture and storage (CCS) technology may contribute reducing CO2 emissions as a way to transform Mexico into a low-carbon economy in the long term. However, the construction and operation and maintenance phases will embody environmental impacts that should be considered. This paper assesses the carbon capture investments required for the expected increasing capacity of natural gas power plants up to 2050 and their impact on production, value added, employment, climate change, acidification, water consumption and human health effects. An environmentally extended multi-regional the input-output analysis (EMRIO) is used to address Mexican policies for the period 2020-2050. Results show that the investment in capture technologies in Mexico allows a net reduction of the carbon emissions in Mexico that is pursued at a low cost (33 EUR/tCO(2)). This mitigation policy has important additional co-benefits in terms of domestic value added and employment creation of medium and high qualification. As for the environmental impacts, most of them are produced in the power plant due to the burning of the natural gas consumed.
BACKGROUND: Short-term exposure to ambient nitrogen dioxide (NO(2)) is associated with adverse respiratory and cardiovascular outcomes. Supplementation of omega-3 polyunsaturated fatty acids (PUFA) has shown protection against exposure to fine particulate matter. This study aims to investigate whether habitual omega-3 PUFA intake differentially modify the associations between respiratory and cardiovascular responses and short-term exposure to ambient NO(2). METHODS: Sixty-two healthy participants were enrolled into low or high omega-3 groups based on their habitual omega-3 PUFA intake. Each participant was repeatedly assessed for lung function, blood lipids, markers of coagulation and fibrinolysis, vascular function, and heart rate variability (HRV) in up to five sessions, each separated by at least 7 days. This study was carried out in the Research Triangle area of North Carolina, USA between October 2016 and September 2019. Daily ambient NO(2) concentrations were obtained from an area air quality monitoring station on the day of outcome assessment (Lag0), 4 days prior (Lag1-4), as well as 5-day moving average (5dMA). The associations between short-term exposure to NO(2) and the measured indices were evaluated using linear mixed-effects models stratified by omega-3 levels and adjusted by covariates including relative humidity and temperature. RESULTS: The average concentration of ambient NO(2) during the study periods was 5.3??3.8 ppb which was below the National Ambient Air Quality Standards (NAAQS). In the high omega-3 group, an interquartile range (IQR) increase in short-term NO(2) concentrations was significantly associated with increased lung function [e.g. 1.2% (95%CI: 0.2%, 2.2%) in FVC at lag1, 2.6% (95%CI: 0.4%, 4.8%) in FEV1 at 5dMA], decreased blood lipids [e.g. -2.6% (95%CI: -4.4%, -0.9%) in total cholesterol at lag2, -3.1% (95%CI: -6.1%, 0.0%) in HDL at 5dMA, and -3.1% (95%CI: -5.5%, -0.7%) in LDL at lag2], improved vascular function [e.g. 8.9% (95%CI: 0.6%, 17.2%) increase in FMD and 43.1% (95%CI: -79.8%, -6.3%) decrease in endothelin-1 at 5dMA], and changed HRV parameters [e.g. -7.2% (95%CI: -13.6%, -0.8%) in HFn and 13.4% (95%CI: 0.2%, 28.3%) in LF/HF ratio at lag3]. In the low omega-3 group, an IQR increase in ambient NO(2) was associated with elevations in coagulation markers (von Willebrand Factor, D-dimer) and a decrease in HRV (very-low frequency); however, null associations were observed between short-term NO(2) exposure and changes in lung function, blood lipids, and vascular function. CONCLUSIONS: The results in this study imply that dietary omega-3 PUFA consumption may offer respiratory and vascular benefits in response to short-term exposure of healthy adults to NO(2) levels below the NAAQS. TRIAL REGISTRATION: ClinicalTrials.gov ( NCT02921048 ).
Heavy-duty trucks and buses continue to contribute significantly to air pollution at the local, regional, and national level, often disproportionally affecting communities of color and low-income populations.
To ensure the progress needed on cleaning trucks and buses and to harness improvements in vehicle technologies, EPA will issue two major regulations over the next three years—the “Clean Trucks Plan” that will result in decreasing emissions from new heavy-duty vehicles, including long-haul tractors, buses, commercial delivery trucks, and many other types of trucks. These new rules will be major steps towards improving air quality and addressing the climate crisis.
Carbon monoxide (CO) is a colorless, odorless gas that can cause injury or death if inhaled. CO is a frequent secondary hazard induced by the aftereffects of natural hazards as individuals, families, and communities often seek alternative power sources for heating, cooking, lighting, and cleanup during the emergency and recovery phases of a disaster. These alternative power sources-such as portable generators, petroleum-based heaters, and vehicles-exhaust CO that can ultimately build to toxic levels in enclosed areas. Ever-increasing environmental and societal changes combined with an aging infrastructure are growing the odds of power failures during hazardous weather events, which, in turn, are increasing the likelihood of CO exposure, illness, and death. This study analyzed weather-related CO fatalities from 2000 to 2019 in the United States using death-certificate data, providing one of the longest assessments of this mortality. Results reveal that over 8300 CO fatalities occurred in the United States during the 20-yr study period, with 17% of those deaths affiliated with weather perils. Cool-season perils such as ice storms, snowstorms, and extreme cold were the leading hazards that led to situations causing CO fatalities. States in the Southeast and Northeast had the highest CO fatality rates, with winter having the greatest seasonal mortality. In general, these preventable CO poisoning influxes are related to a deficiency of knowledge on generator safety and the absence of working detectors and alarms in the enclosed locations where poisonings occur. Education and prevention programs that target the most vulnerable populations will help prevent future weather-related CO fatalities. Significance StatementCarbon monoxide exposure is common after weather disasters when individuals, families, and communities seek alternative power sources-such as portable generators, petroleum-based heaters, and vehicles-that exhaust this deadly, colorless, and odorless gas. Initially, we catalog carbon monoxide fatalities associated with weather events in the United States over two decades; thereafter, we illustrate the characteristics and patterns affiliated with these deaths. Results will assist public officials, first responders, and individuals in their decision-making and response before, during, and after weather events so that these deaths may be prevented in the future.
Many studies project that climate change can cause a significant number of excess deaths. Yet, in integrated assessment models (IAMs) that determine the social cost of carbon (SCC) and prescribe optimal climate policy, human mortality impacts are limited and not updated to the latest scientific understanding. This study extends the DICE-2016 IAM to explicitly include temperature-related mortality impacts by estimating a climate-mortality damage function. We introduce a metric, the mortality cost of carbon (MCC), that estimates the number of deaths caused by the emissions of one additional metric ton of CO2. In the baseline emissions scenario, the 2020 MCC is 2.26 × 10(‒4) [low to high estimate -1.71× 10(‒4) to 6.78 × 10(‒4)] excess deaths per metric ton of 2020 emissions. This implies that adding 4,434 metric tons of carbon dioxide in 2020-equivalent to the lifetime emissions of 3.5 average Americans-causes one excess death globally in expectation between 2020-2100. Incorporating mortality costs increases the 2020 SCC from $37 to $258 [-$69 to $545] per metric ton in the baseline emissions scenario. Optimal climate policy changes from gradual emissions reductions starting in 2050 to full decarbonization by 2050 when mortality is considered.
Research has shown that the healthcare sector is among the least green sectors and constitutes one of the largest contributors to greenhouse gas (GHG) emissions, posing risks to human health. This review discusses the development of a knowledge translation tool that aims to compare a range of interventions that can be applied in hospital settings to reduce the local GHG emissions and associated financial costs. It discusses several interventions that potentially have the most impact on GHG reduction and compares these to interventions that are commonly used in different hospital departments. The authors propose opportunities to advance the implementation of these interventions within hospital operations across many other geographic locations.
OBJECTIVE: Ongoing environmental changes increasingly require public health nurses to understand how environmental factors impact the health of populations. One approach to researching these impacts is incorporating environmental research methods to determine associations between harmful exposures and health. We use the Salton Sea in Southern California as a demonstration of how environmental exposure can be examined using air parcel trajectory analysis. DESIGN: We demonstrate a methodology for public health nurses to better understand and apply data from the Hybrid Single-Particle Lagrangian Integrated Trajectory meteorological model to estimate the effect of airborne particulate matter from a single source. MEASUREMENTS: We explain a method for tracking air parcel trajectories to populations: selection of meterological data to identify air parcels, geographic identification of population centers, generation of trajectories, classification of trajectory dispersions, adjusting for atmospheric stability, and merging environmental variables with health data. CONCLUSIONS: Climate change-related environmental events are expected to become more commonplace and disproportionately affect those populations impacted by health disparities. Public health nurses can identify communities at risk so that public health nursing researchers can use these techniques in collaboration with environmental science to robustly examine health effects of proximal air pollution sources for communities at risk.
Nitrogen dioxide (NO2) is responsible for aggravating respiratory diseases, particularly asthma. The aim of this study is to investigate the association between NO2 exposure and asthma emergency department (ED) visits during the cold season (November-February) in five populated locations (Sacramento, San Francisco, Fresno, Los Angeles, and San Diego) of California from 2005 to 2015 (1320 Days). Conditional logistic regression models were used to obtain the odds ratio (OR) and 95% confidence interval Cl)( associated with a 5 ppb increase in NO2 concentration for the 19,735 ED visits identified. An increase in NO2 exposure increased the odds of having asthma ED visits for the studied population. The potential effect modification by sex (female and male), race (White, Black, Hispanic, and Asian), and age (2-5, 6-18, 19-40, 41-64, and ?65) was explored. A 5 ppb increase in the concentration of NO2 during lag 0-30 was associated with a 56% increase in the odds of having an asthma ED visit (OR 1.560, Cl: 1.428-1.703). Sex was not found lo be a modifier. Asthma ED visits among all the racesiehnicities (except Asians) were associated with NO2 exposure. Whiles had the highest OR 75% (OR 1.750, CI: 1A17-2.160) at lag 0-30 in response to NO2 exposure. The association between NO2 exposure and asthma ED visits was positive among all age groups except fur 19 to 40 years old; the OR was higher among 2 to 18 year old (al lag 0-30: age group 2-5 (OR – 1.699, CI: 1.399-2.062), and age group 6-18 (OR – 1.568, CII.348-1.825)). For stratification by location, San Diego and Fresno were found to have the highest OR, compared lo the other studied locations. (C) 2020 Elsevier B.V. All rights reserved.
BACKGROUND: Hurricane Harvey made landfall along the Texas Gulf Coast as a Category 4 hurricane on August 25, 2017, producing unprecedented precipitation that devastated coastal areas. Catastrophic flooding in the City of Houston inundated industrial and residential properties resulting in the displacement and transfer of soil, sediment, and debris and heightening existing environmental justice (EJ) concerns. OBJECTIVES: The primary aim of this study was to evaluate the presence, distribution, and potential human health implications of polycyclic aromatic hydrocarbons (PAHs) in a residential neighborhood of Houston, Texas following a major hurricane. METHODS: Concentrations of PAHs in 40 soil samples collected from a residential neighborhood in Houston, Texas were measured. Spatial interpolation was applied to determine the distribution of PAHs. Potential human health risks were evaluated by calculating toxicity equivalency quotients (TEQs) and incremental excess lifetime cancer risk (IELCR). RESULTS: Total priority PAH concentrations varied across samples (range: 9.7 × 10(1) ng/g-1.6 × 10(4) ng/g; mean: 3.0 × 10(3) ng/g ± 3.6 × 10(3) standard deviation). Spatial analysis indicated a variable distribution of PAH constituents and concentrations. The IELCR analysis indicated that nine of the 40 samples were above minimum standards. CONCLUSIONS: Findings from this study highlight the need for fine scale soil testing in residential areas as well as the importance of site-specific risk assessment. COMPETING INTERESTS: The authors declare no competing financial interests.
Unprecedented inland precipitation and catastrophic flooding associated with Hurricane Harvey potentially redistributed contaminants from industrial sites and transportation infrastructure to recreational areas that make up networks of green infrastructure, creeks, and waterways used for flood control throughout the Greater Houston Area. Sediment samples were collected in parks located near the Buffalo Bayou watershed 1 week after Hurricane Harvey made landfall and again 7 weeks later. Total concentrations of the U.S. Environmental Protection Agency’s (EPA’s) 16 priority polycyclic aromatic hydrocarbons (PAHs) were measured in each sample at both time points. Diagnostic ratios were calculated to improve understanding of potential sources of PAHs after flooding. Diagnostic ratios suggest vehicular traffic to be a potential source for PAHs in parks. Although the concentrations of PAHs in all samples were below EPA actionable levels, given that no background values were available for comparison, it is difficult to quantify the impact flooding from Hurricane Harvey had on PAH concentrations in Houston parks. However, given the high frequency of flooding in Houston, and the concentration of industrial facilities and transportation infrastructure adjacent to recreation areas, these data demonstrate that PAHs were still present after unprecedented flooding. This study may also serve as a baseline for future efforts to understand the environmental health impacts of disasters.
Hurricane Harvey was a category four storm that induced catastrophic flooding in the Houston metropolitan area. Following the hurricane there was increased concern regarding chemical exposures due to damage caused by flood waters and emergency excess emissions from industrial facilities. This study utilized personal passive samplers in the form of silicone wristbands in Houston, TX to both assess chemical exposure to endocrine disrupting chemicals (EDCs) immediately after the hurricane and determine participant characteristics associated with higher concentrations of exposure. Participants from the Houston-3H cohort (n = 172) wore a wristband for seven days and completed a questionnaire to determine various flood-related and demographic variables. Bivariate and multivariate analysis indicated that living in an area with a high Area Deprivation Index (ADI) (indicative of low socioeconomic status), identifying as Black/African American or Latino, and living in the Houston neighborhoods of Baytown and East Houston were associated with increased exposure to EDCs. These results provide evidence of racial/ethnic and socioeconomic injustices in exposure to EDCs in the Houston Metropolitan Area. Since the multiple regression models conducted did not fully explain exposure (0.047 < R2 < 0.34), more research is needed on the direct sources of EDCs within this area to create effective exposure mitigation strategies.
Pollen grains may contain allergens that exacerbate allergic respiratory diseases like asthma and rhinitis. In the presence of water, pollen grains (10-100 μm) can rupture to produce sub-pollen particles (SPP) with diameters <2.5 μm, which in comparison to intact pollen grains, have longer atmospheric lifetimes and greater penetration to the lower lung. The current study examines SPP, fungal spores, and bacteria in size-resolved atmospheric particulate matter (PM) using chemical and biological tracers. During springtime tree pollen season in Iowa City, Iowa, fine particle (PM(2.5)) concentrations of fructose (a pollen chemical tracer) increased on rainy sampling periods, especially during severe thunderstorms, and peaked when a tornado struck nearby. Submicron fluorescent particles, measured by single-particle fluorescence spectroscopy, were also enhanced during rain events, particularly thunderstorms in agreement with the chemical tracer measurements. PM(2.5) sucrose (a pollen chemical tracer) concentrations were higher in early spring when nighttime temperatures were closer to freezing, while fructose concentrations were higher in late spring with warmer temperatures, consistent with chemical tracers being sensitive to seasonal temperature influences. The first co-located measurements of fructose and Bet v 1 (birch pollen allergen), indicated that SPP ranged in diameter from <0.25 to 2.5 μm during rainy sampling periods and that allergens and carbohydrates exhibited distinct size distributions. Meanwhile, mannitol (a fungal spore tracer) peaked on warm, dry days following rain and was primarily in supermicron particles (>1.0 μm), which is consistent with intact fungal spore diameters (1-30 μm). Bacterial endotoxins in PM also increased during extreme weather events, primarily in supermicron particles. While the concentrations of fructose, mannitol, and endotoxin all increased in PM(2.5) μm during thunderstorms, the greatest relative increase in concentration was observed for fructose. Together, these observations suggest that SPP containing starch granules and allergens (Bet v 1) were released during rainy sampling periods. This study advances the use of chemical tracers to track SPP and other bioaerosols in the atmosphere, by providing new insight to their size distribution and response to extreme weather conditions.
This study focused on the measurement of BTEX (benzene, toluene, ethylbenzene and xylene) concentrations in the air of various regions and indoor-outdoor environments in Bandar Abbas, Iran. Air samples were taken actively and analyzed by gas chromatography-mass spectrometry (GC-MS) during two one-month periods i.e., Feb 2020 (period I) and Sep/Oct 2020 (period II). The mean air temperature and the levels of all BTEX compounds were higher in period II. The highest total BTEX (t-BTEX) levels (median [min-max]) were found in the urban region (18.00 [5.21-67.24] μg m(-3)), followed by industrial region (7.00 [2.05-14.76] μg m(-3)) and rural region (2.81 [ND-7.38] μg m(-3)). The significant positive correlations between all BTEX compounds and T/B ratio >1 indicated the vehicular traffic as the main source of emission. At 95th percentile probability, the non-cancer risk of t-BTEX in urban region was only less than one order of magnitude below the threshold level of unity (1.91E-01) and the cancer risk of benzene exceeded the recommended level of 1.0E-06 by U.S. EPA in urban (7.69E-06) and industrial (2.97E-06) regions. It was found that the indoor/outdoor ratio of BTEX concentration in beauty salon and hospital was greater than 1. Overall, the current levels of BTEX in the ambient air of study area, especially near urban roadside and in some indoor environments, should not be overlooked and appropriate mitigation actions should be undertaken.
The generation and emission of volatile organic compounds (VOCs) affects the environment and air quality, playing an important role in global warming, depletion of atmospheric ozone and emission of unpleasant odors, but also directly affect human health. This study investigated the health risks of benzene, toluene, ethylbenzene, xylene (BTEX) compounds and biogas released in and around the municipal landfill. Sampling of the VOCs was carried out by the 1501NIOSH method from 8 points over 5 months. The samples were analyzed for BTEX in the ambient air of the landfill, resulting in 0.03-18.09 ppm concentrations, while for biogases a 0.08-25.2 ppm range was found. Assessment of definite health and potential risks showed that the lifetime cancer risk (LCR) for benzene and hazard quotient (HQ) for the BTEX components in all studied sampling sites are higher than the acceptable standard. The high concentration of benzene measured in ambient air indicated that petroleum compounds containing benzene and its derivatives have the highest value in the category of BTEX compounds among all emissions. Therefore, high concentrations of volatile compounds derived from VOCs, especially benzene, should be reduced at the site with control engineering measures.
Polycyclic aromatic hydrocarbons (PAHs) represent one of the major toxic pollutants associated with PM(2.5) with significant human health and climate effects. Because of local and long-range transport of atmospheric PAHs to receptor sites, higher global attentions have been focused to improve PAHs pollution emission management. In this study, PM(2.5) samples were collected at three urban sites located in the capital of Iran, Tehran, during the heating and non-heating periods (H-period and NH-period). The US EPA 16 priority PAHs were analyzed and the data were processed to the following detailed aims: (i) investigate the H-period and NH-period variations of PM(2.5) and PM(2.5)-bound PAHs concentrations; (ii) identify the PAHs sources and the source locations during the two periods; (iii) carry out a source-specific excess cancer risk (ECR) assessment highlighting the potential source locations contributing to the ECR using a hybrid approach. Total PAHs (TPAHs) showed significantly higher concentrations (1.56-1.89 times) during the H-period. Among the identified PAHs compounds, statistically significant periodical differences (p-value < 0.05) were observed only between eight PAHs species (Nap, BaA, Chr, BbF, BkF, BaP, IcdP, and DahA) at all three sampling sites which can be due to the significant differences of PAHs emission sources during H and NH-periods. High molecular weight (HMW) PAHs accounted for 52.7% and 46.8% on average of TPAHs during the H-period and NH-period, respectively. Positive matrix factorization (PMF) led to identifying four main PAHs sources including industrial emissions, petrogenic emissions, biomass burning and natural gas emissions, and vehicle exhaust emissions. Industrial and petrogenic emissions exhibited the highest contribution (19.8%, 27.2%, respectively) during the NH-period, while vehicle exhaust and biomass burning-natural gas emissions showed the largest contribution (40.7%, 29.6%, respectively) during the H-period. Concentration weighted trajectory (CWT) on factor contributions was used for tracking the potential locations of the identified sources. In addition to local sources, long-range transport contributed to a significant fraction of TPHAs in Tehran both during the H- and NH-periods. Source-specific carcinogenic risks assessment apportioned vehicle exhaust (44.2%, 2.52 × 10(-4)) and biomass burning-natural gas emissions (33.9%, 8.31 × 10(-5)) as the main cancer risk contributors during the H-period and NH-period, respectively. CWT maps pointed out the different distribution patterns associated with the cancer risk from the identified sources. This will allow better risk management through the identification of priority PAHs sources.
BACKGROUND: In recent years, the prevalence of dust events has increased in the region and the world. According to the Meteorological Organization, the most frequent days with dust events are on stations located in Khuzestan province. Objective: Assessment of the effects of dust events and meteorological elements on stroke morbidity in health in Iran: a health promotion approach. MATERIALS AND METHODS: The present study was a retrospective cohort study 2020 and 2013 provided between based on ecological data-based on population. Information about patients with stroke was obtained from the hospital. Information on the dust events and meteorological elements was also from the data center of the Meteorological Organization of Iran. Using STATA the correlation between the diseases and the, 14 statistical software version occurrence of dust events and changes in meteorological elements was obtained and the statistical model (Spearman correlation coefficient) individually estigate the equation was used inv modified by Poisson regression simultaneous effect of variables. RESULTS: the results of adjusted statistical models show that increasing the severity of dust event increases the risk of stroke in males (lag 0-21 confidence interval [CI] 95% = 1.496-1.0067 relative risk [RR] = 1.03 P = 0.01). Increasing the average wind speed also increases the risk of stroke in males (lag 0-3 CI 95% = 1.0491-0.9996 RR = 1.02 P = 0.05). Increased rainfall and average relative humidity increase the risk of stroke in people under 60 years (lag 0-7 CI 95% = 1.0012-0.9058 RR = 1.95 P = 0.05). Increasing the average daily temperature reduces the risk of stroke in males (lag 0-3 CI 95% = 0.9874-0.9254 RR = 0.51 P < 0.001). CONCLUSION: Increasing the intensity of dust storms along with meteorological elements has increased the risk of stroke. However, increasing the average temperature has had a protective effect on the risk of stroke.
Recife is recognized as the 16th most vulnerable city to climate change in the world. In addition, the city has levels of air pollutants above the new limits proposed by the World Health Organization (WHO) in 2021. In this sense, the present study had two main objectives: (1) To evaluate the health (and economic) benefits related to the reduction in mean annual concentrations of PM(10) and PM(2.5) considering the new limits recommended by the WHO: 15 µg/m(3) (PM(10)) and 5 µg/m(3) (PM(2.5)) and (2) To simulate the behavior of these pollutants in scenarios with increased temperature (2 and 4 °C) using machine learning. The averages of PM(2.5) and PM(10) were above the limits recommended by the WHO. The scenario simulating the reduction in these pollutants below the new WHO limits would avoid more than 130 deaths and 84 hospital admissions for respiratory or cardiovascular problems. This represents a gain of 15.2 months in life expectancy and a cost of almost 160 million dollars. Regarding the simulated temperature increase, the most conservative (+ 2 °C) and most drastic (+ 4 °C) scenarios predict an increase of approximately 6.5 and 15%, respectively, in the concentrations of PM(2.5) and PM(10), with a progressive increase in deaths attributed to air pollution. The study shows that the increase in temperature will have impacts on air particulate matter and health outcomes. Climate change mitigation and pollution control policies must be implemented for meeting new WHO air quality standards which may have health benefits.
BACKGROUND: There is currently a scarcity of air pollution epidemiologic data from low- and middle-income countries (LMICs) due to the lack of air quality monitoring in these countries. Additionally, there is limited capacity to assess the health effects of wildfire smoke events in wildfire-prone regions like Brazil’s Amazon Basin. Emerging low-cost air quality sensors may have the potential to address these gaps. OBJECTIVES: We investigated the potential of PurpleAir PM2.5 sensors for conducting air pollution epidemiologic research leveraging the United States Environmental Protection Agency’s United States-wide correction formula for ambient PM(2.5). METHODS: We obtained raw (uncorrected) PM(2.5) concentration and humidity data from a PurpleAir sensor in Rio Branco, Brazil, between 2018 and 2019. Humidity measurements from the PurpleAir sensor were used to correct the PM(2.5) concentrations. We established the relationship between ambient PM(2.5) (corrected and uncorrected) and daily all-cause respiratory hospitalization in Rio Branco, Brazil, using generalized additive models (GAM) and distributed lag non-linear models (DLNM). We used linear regression to assess the relationship between daily PM(2.5) concentrations and wildfire reports in Rio Branco during the wildfire seasons of 2018 and 2019. RESULTS: We observed increases in daily respiratory hospitalizations of 5.4% (95%CI: 0.8%, 10.1%) for a 2-day lag and 5.8% (1.5%, 10.2%) for 3-day lag, per 10 μg/m(3) PM(2.5) (corrected values). The effect estimates were attenuated when the uncorrected PM(2.5) data was used. The number of reported wildfires explained 10% of daily PM2.5 concentrations during the wildfire season. DISCUSSION: Exposure-response relationships estimated using corrected low-cost air quality sensor data were comparable with relationships estimated using a validated air quality modeling approach. This suggests that correcting low-cost PM(2.5) sensor data may mitigate bias attenuation in air pollution epidemiologic studies. Low-cost sensor PM(2.5) data could also predict the air quality impacts of wildfires in Brazil’s Amazon Basin.
One of the central problems in large cities is air pollution, mainly caused by vehicular emissions. Tropospheric ozone is an atmospheric oxidizing gas that forms in minimal amounts naturally, affecting peoples’ health. This pollutant is formed by the NO2 photolysis, creating a main peak during the day. Nighttime secondary peaks occur in several parts of the world, but their intensity and frequency depend on the local condition. In this sense, this works aims to study the local characteristics for tropospheric nocturnal ozone levels in the Metropolitan Area of Sao Paulo, in Brazil, using the Simple Photochemical Module coupled to the Brazilian Developments on the Regional Atmospheric Modeling System. For this, three different situations of nocturnal occurrence were studied. The results show that the nocturnal maximum of ozone concentrations is related to the vertical transport of this pollutant from higher levels of the atmosphere to the surface and is not related to the synoptic condition.
BACKGROUND: Long-term exposure to fine particles ≤2.5 μm in diameter (PM2.5) has been linked to cancer mortality. However, the effect of wildfire-related PM2.5 exposure on cancer mortality risk is unknown. This study evaluates the association between wildfire-related PM2.5 and site-specific cancer mortality in Brazil, from 2010 to 2016. METHODS AND FINDINGS: Nationwide cancer death records were collected during 2010-2016 from the Brazilian Mortality Information System. Death records were linked with municipal-level wildfire- and non-wildfire-related PM2.5 concentrations, at a resolution of 2.0° latitude by 2.5° longitude. We applied a variant difference-in-differences approach with quasi-Poisson regression, adjusting for seasonal temperature and gross domestic product (GDP) per capita. Relative risks (RRs) and 95% confidence intervals (CIs) for the exposure for specific cancer sites were estimated. Attributable fractions and cancer deaths were also calculated. In total, 1,332,526 adult cancer deaths (age ≥ 20 years), from 5,565 Brazilian municipalities, covering 136 million adults were included. The mean annual wildfire-related PM2.5 concentration was 2.38 μg/m3, and the annual non-wildfire-related PM2.5 concentration was 8.20 μg/m3. The RR for mortality from all cancers was 1.02 (95% CI 1.01-1.03, p < 0.001) per 1-μg/m3 increase of wildfire-related PM2.5 concentration, which was higher than the RR per 1-μg/m3 increase of non-wildfire-related PM2.5 (1.01 [95% CI 1.00-1.01], p = 0.007, with p for difference = 0.003). Wildfire-related PM2.5 was associated with mortality from cancers of the nasopharynx (1.10 [95% CI 1.04-1.16], p = 0.002), esophagus (1.05 [95% CI 1.01-1.08], p = 0.012), stomach (1.03 [95% CI 1.01-1.06], p = 0.017), colon/rectum (1.08 [95% CI 1.05-1.11], p < 0.001), larynx (1.06 [95% CI 1.02-1.11], p = 0.003), skin (1.06 [95% CI 1.00-1.12], p = 0.003), breast (1.04 [95% CI 1.01-1.06], p = 0.007), prostate (1.03 [95% CI 1.01-1.06], p = 0.019), and testis (1.10 [95% CI 1.03-1.17], p = 0.002). For all cancers combined, the attributable deaths were 37 per 100,000 population and ranged from 18/100,000 in the Northeast Region of Brazil to 71/100,000 in the Central-West Region. Study limitations included a potential lack of assessment of the joint effects of gaseous pollutants, an inability to capture the migration of residents, and an inability to adjust for some potential confounders. CONCLUSIONS: Exposure to wildfire-related PM2.5 can increase the risks of cancer mortality for many cancer sites, and the effect for wildfire-related PM2.5 was higher than for PM2.5 from non-wildfire sources.
We quantified the impacts of wildfire-related PM2.5 on 2 million hospital admissions records due to cardiorespiratory diseases in Brazil between 2008 and 2018. The national analysis shows that wildfire waves are associated with an increase of 23% (95%CI: 12%-33%) in respiratory hospital admissions and an increase of 21% (95%CI: 8%-35%) in circulatory hospital admissions. In the North (where most of the Amazon region is located), we estimate an increase of 38% (95%CI: 30%-47%) in respiratory hospital admissions and 27% (95%CI: 15%-39%) in circulatory hospital admissions. Here we report epidemiological evidence that air pollution emitted by wildfires is significantly associated with a higher risk of cardiorespiratory hospital admissions. Brazil is a wildfire-prone region, and few studies have investigated the health impacts of wildfire exposure. Here, the authors show that wildfire waves are associated with an increase of 23% in respiratory hospital admissions and an increase of 21% in circulatory hospital admissions in Brazil.
Background Birth defects are a major cause of poor health outcomes during both childhood and adulthood. A growing body of evidence demonstrated associations between air pollution exposure during pregnancy and birth defects. To date, there is no study looking at birth defects and exposure to wildfire-related air pollution, which is suggested as a type of air pollution source with high toxicity for reproductive health. Objective Our study addresses this gap by examining the association between birth defects and wildfire smoke exposure in Brazil between 2001 and 2018. Based on known differences of impacts of wildfires across different regions of Brazil, we hypothesized differences in risks of birth defects for different regions. Methods We used a logistic regression model to estimate the odds ratios (ORs) for individual birth defects (12 categories) associated with wildfire exposure during each trimester of pregnancy. Results Among the 16,825,497 birth records in our study population, there were a total of 7595 infants born in Brazil between 2001 and 2018 with birth defects in any of the selected categories. After adjusting for several confounders in the primary analysis, we found statistically significant OR for three birth defects, including cleft lip/cleft palate [OR: 1.007 (95% CI: 1.001; 1.013)] during the second trimester of exposure, congenital anomalies of the respiratory system [OR: 1.013 (95% CI: 1.002; 1.023)] in the second trimester of exposure, and congenital anomalies of the nervous system [OR: 1.002 (95% CI: 1.001; 1.003)] during the first trimester of exposure for the regions South, North, and Midwest, respectively. Significance Our results suggest that maternal exposure to wildfire smoke during pregnancy may increase the risk of an infant being born with some congenital anomaly. Considering that birth defects are associated with long-term disability, impacting families and the healthcare system (e.g., healthcare costs), our findings should be of great concern to the public health community. Impact statement Our study focused on the association between maternal exposure to wildfire smoke in Brazil during pregnancy and the risk of an infant being born with congenital anomalies, which presents serious public health and environmental challenges.
Air pollution from Amazon fires has adverse impacts on human health. The number of fires in the Amazon has increased in recent years, but whether this increase was driven by deforestation or climate has not been assessed. We analyzed relationships between fire, deforestation, and climate for the period 2003 to 2019 among selected states across the Brazilian Legal Amazon (BLA). A statistical model including deforestation, precipitation and temperature explained ∼80% of the variability in dry season fire count across states when totaled across the BLA, with positive relationships between fire count and deforestation. We estimate that the increase in deforestation since 2012 increased the dry season fire count in 2019 by 39%. Using a regional chemistry-climate model combined with exposure-response associations, we estimate this increase in fire resulted in 3,400 (95UI: 3,300-3,550) additional deaths in 2019 due to increased exposure to particulate air pollution. If deforestation in 2019 had increased to the maximum recorded during 2003-2019, the number of active fire counts would have increased by an additional factor of 2 resulting in 7,900 (95UI: 7,600-8,200) additional premature deaths. Our analysis demonstrates the strong benefits of reduced deforestation on air quality and public health across the Amazon.
BACKGROUND: In the context of climate change and deforestation, Brazil is facing more frequent and unprecedented wildfires. Wildfire-related PM(2·5) is associated with multiple adverse health outcomes; however, the magnitude of these associations in the Brazilian context is unclear. We aimed to estimate the association between daily exposure to wildfire-related PM(2·5) and cause-specific hospital admission and attributable health burden in the Brazilian population using a nationwide dataset from 2000 to 2015. METHODS: In this nationwide time-series analysis, data for daily all-cause, cardiovascular, and respiratory hospital admissions were collected through the Brazilian Unified Health System from 1814 municipalities in Brazil between Jan 1, 2000, and Dec 31, 2015. Daily concentrations of wildfire-related PM(2·5) were estimated using the 3D chemical transport model GEOS-Chem at a 2·0° latitude by 2·5° longitude resolution. A time-series analysis was fitted using quasi-Poisson regression to quantify municipality-specific effect estimates, which were then pooled at the regional and national levels using random-effects meta-analyses. Analyses were stratified by sex and ten age groups. The attributable fraction and attributable cases of hospital admissions due to wildfire-related PM(2·5) were also calculated. FINDINGS: At the national level, a 10 μg/m(3) increase in wildfire-related PM(2·5) was associated with a 1·65% (95% CI 1·51-1·80) increase in all-cause hospital admissions, a 5·09% (4·73-5·44) increase in respiratory hospital admissions, and a 1·10% (0·78-1·42) increase in cardiovascular hospital admissions, over 0-1 days after the exposure. The effect estimates for all-cause hospital admission did not vary by sex, but were particularly high in children aged 4 years or younger (4·88% [95% CI 4·47-5·28]), children aged 5-9 years (2·33% [1·77-2·90]), and people aged 80 years and older (3·70% [3·20-4·20]) compared with other age groups. We estimated that 0·53% (95% CI 0·48-0·58) of all-cause hospital admissions were attributable to wildfire-related PM(2·5), corresponding to 35 cases (95% CI 32-38) per 100 000 residents annually. The attributable rate was greatest for municipalities in the north, south, and central-west regions, and lowest in the northeast region. Results were consistent for all-cause and respiratory diseases across regions, but remained inconsistent for cardiovascular diseases. INTERPRETATION: Short-term exposure to wildfire-related PM(2·5) was associated with increased risks of all-cause, respiratory, and cardiovascular hospital admissions, particularly among children (0-9 years) and older people (≥80 years). Greater attention should be paid to reducing exposure to wildfire smoke, particularly for the most susceptible populations. FUNDING: Australian Research Council and Australian National Health and Medical Research Council.
The March 2015 extraordinary hydrometeomlogical event in the Andes cordillera caused severe floods in the southern Atacama Desert. One of the most affected cities was CopiapO (northern Chile) located downstream of the junction between the CopiapO river and its ephemeral tributary Quebrada Paipote. This work analyses the features of this catastrophic flood and relates them with the identified impacts. A large volume of water mixed with fine sediments overflowed the tributary channel generating a flood that affected 72% of the urban area. The rheological (velocity, density and flow regime) and sedimentary features of the flow reveal the occurrence of massive mudflows that infilled the space available inside the buildings, buried the streets with a sandy mud deposit of more than 30 cm medium thickness and collapsed the sewer network. The post-event survey carried out by the Ministry of Housing and Urban Planning (MINVU) was used for the development of fragility curves that allows modelling the probability of damage. Results indicate that the greatest probability of building damage is generated by the accumulation of sediments instead of by the flow depth. On the other hand, once the very fine grain sediments of the top of the deposit dried up, it increased the concentration of post-event suspension particulate matter, causing a health issue. This work highlights the need to understand mudflow processes and their consequences in arid environments to improve urban planning and mitigate future damages since their impacts strongly affect infrastructures and communities.
Health risks associated with heatwaves and ozone pollution are projected to rise significantly under the effects of climate change. Although the literature has considered the future health risks of heatwaves and ozone pollution separately, the compound effects remain unexplored, and this could potentially impair risk-prevention plans. Here, using a model from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and four shared socioeconomic pathway (SSPs) scenarios, we explore the global tempo-spatial trend and country disparity of compound-event days and population-exposure person-days. We find that compared with the baseline of 1995-2014, by 2071-2090 under the high-emission scenario of SSP3-7.0, an increased annual mean of 34.6 compound-event days and mean population-exposure of 93.5 million person-days is expected. Furthermore, lower-income countries are facing dramatically higher exposure compared with higher-income countries. These projections could contribute to developing targeted mitigation and adaptation plans.
INTRODUCTION: There is an increasing interest in understanding whether air pollutants modify the quantitative relationships between temperature and health outcomes. The results of available studies were, however, inconsistent. This study aims to sum up the current evidence and provide a comprehensive understanding of this topic. METHODS: We conducted an electronic search in PubMed (MEDLINE), EMBASE, Web of Science Core Collection, and ProQuest Dissertations and Theses. The modified Navigation Guide was applied to evaluate the quality and strength of evidence. We calculated pooled temperature-related mortality at low and high pollutant levels respectively, using the random-effects model. RESULTS: We identified 22 eligible studies, eleven of which were included in the meta-analysis. Significant effect modification was observed on heat effects for all-cause and non-accidental mortality by particulate matter with an aerodynamic diameter of <10 μm (PM(10)) and ozone (O(3)) (p < 0.05). The excess risks (ERs) for all-cause and non-accidental mortality were 5.4% (4.4%, 6.4%) and 6.3% (4.8%, 7.8%) at the low PM(10) level, 8.8% (7.5%, 10.1%) and 11.4% (8.7%, 14.2%) at the high PM(10) level, respectively. As for O(3), the ERs for all-cause and non-accidental mortality were 5.1% (3.9%, 6.3%) and 3.6% (0.1%, 7.2%) at the low O(3) level, 7.6% (6.3%, 9.0%) and 12.5% (4.7%, 20.9%) at the high O(3) level, respectively. Surprisingly, the heat effects on cardiovascular mortality were found to be lower at high carbon monoxide (CO) levels [ERs = 5.4% (3.9%, 6.9%)] than that at low levels [ERs = 9.4% (7.0%, 11.9%)]. The heterogeneity varied, but the results of sensitivity analyses were generally robust. Significant effect modification by air pollutants was not observed for heatwave or cold effects. CONCLUSIONS: PM(10) and O(3) modify the heat-related all-cause and non-accidental mortality, indicating that policymakers should consider air pollutants when establishing heat-health warning systems. Future studies with comparable designs and settings are needed.
Evidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM(10), PM(2.5)), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m(3) increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM(2.5) and PM(10) respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19.
Air pollution is widely viewed as a serious threat to human health and a contributor to deaths. Air pollution appears to be linked to the progression of emphysema, according to epidemiological data. The objective of this study was to examine associations between air pollution and the progression of emphysema using a meta-analysis. A meta-analysis was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol. A systematic literature search was conducted using the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Medline, Embase, PubMed, and Web of Science bibliographic databases. A random-effects model for the meta-analysis was implemented to summarize effect estimates of sufficiently comparable outcomes and pollutants (e.g.: particulate matter, nitrogen oxides and ozone), and the results were visualized in forest plots. We observed that a 1-ppb rise in O3 was associated with a 0.30 increase in the percent emphysema progression (95% CI: 0.02, 0.57, p < 0.05). In contrast, no significant association was found between PM2.5 or NO2 exposure and the percent change in emphysema. Increasing O-3 concentrations may have an impact on and exacerbate human health conditions such as emphysema and respiratory diseases. Air quality and climate change should be concerns for future environmental policies and protection measures.
Surface ozone (O(3)) is an oxidizing gaseous pollutant; long-term exposure to high O(3) concentrations adversely affects human health. Based on daily surface O(3) concentration data, the spatiotemporal characteristics of O(3) concentration, exposure risks, and driving meteorological factors in 347 cities and 10 major countries (China, Japan, India, South Korea, the United States, Poland, Spain, Germany, France, and the United Kingdom) worldwide were analyzed using the MAKESENS model, Moran’ I analysis, and Generalized additive model (GAM). The results indicated that: in the boreal spring season from 2015 to 2020, the global O(3) concentration exhibited an increasing trend at a rate of 0.6 μg/m(3)/year because of the volatile organic compounds (VOCs) and NOx changes caused by human activities. Due to the lockdown policies after the outbreak of COVID-19, the average O(3) concentration worldwide showed an inverted U-shaped growth during the study period, increasing from 21.9 μg/m(3) in 2015 to 27.3 μg/m(3) in 2019, and finally decreasing to 25.9 μg/m(3) in 2020. According to exposure analytical methods, approximately 6.32% of the population (31.73 million people) in the major countries analyzed reside in rapidly increasing O(3) concentrations. 6.53% of the population (32.75 million people) in the major countries were exposed to a low O(3) concentration growth environment. Thus, the continuous increase of O(3) concentration worldwide is an important factor leading to increasing threats to human health. Further we found that mean wind speed, maximum temperature, and relative humidity are the main factors that determine the change of O(3) concentration. Our research results are of great significance to the continued implementation of strict air quality policies and prevention of population hazards. However, due to data limitations, this research can only provide general trends in O(3) and human health, and more detailed research will be carried out in the follow-up. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12403-022-00463-7.
In this article we review the physical and chemical properties of methane (CH4) relevant to impacts on climate, ecosystems, and air pollution, and examine the extent to which this is reflected in climate and air pollution governance. Although CH4 is governed under the UNFCCC climate regime, its treatment there is limited to the ways in which it acts as a “CO2 equivalent” climate forcer on a 100-year time frame. The UNFCCC framework neglects the impacts that CH4 has on near-term climate, as well its impacts on human health and ecosystems, which are primarily mediated by methane’s role as a precursor to tropospheric ozone. Frameworks for air quality governance generally address tropospheric ozone as a pollutant, but do not regulate CH4 itself. Methane’s climate and air quality impacts, together with its alarming rise in atmospheric concentrations in recent years, make it clear that mitigation of CH4 emissions needs to be accelerated globally. We examine challenges and opportunities for further progress on CH4 mitigation within the international governance landscapes for climate change and air pollution.
PURPOSE OF REVIEW: Fine particulate matter (PM(2.5)) and ground-level ozone (O(3)) pose a significant risk to human health. The World Health Organization (WHO) has recently revised healthy thresholds for both pollutants. The formation and evolution of PM(2.5) and O(3) are however governed by complex physical and multiphase chemical processes, and therefore, it is extremely challenging to mitigate both pollutants simultaneously. Here, we review mechanisms and discuss the science-informed pathways for effective and simultaneous mitigation of PM(2.5) and O(3). RECENT FINDINGS: Global warming has led to a general increase in biogenic emissions, which can enhance the formation of O(3) and secondary organic aerosols. Reductions in anthropogenic emissions during the COVID-19 lockdown reduced PM(2.5); however, O(3) was enhanced in several polluted regions. This was attributed to more intense sunlight due to low aerosol loading and non-linear response of O(3) to NO (x) . Such contrasting physical and chemical interactions hinder the formulation of a clear roadmap for clean air over such regions. SUMMARY: Atmospheric chemistry including the role of biogenic emissions, aerosol-radiation interactions, boundary layer, and regional-scale transport are the key aspects that need to be carefully considered in the formulation of mitigation pathways. Therefore, a thorough understanding of the chemical effects of the emission reductions, changes in photolytic rates and boundary layer due to perturbation of solar radiation, and the effect of meteorological/seasonal changes are needed on a regional basis. Statistical emulators and machine learning approaches can aid the cumbersome process of multi-sector multi-species source attribution.
Global air pollution and climate change are major threats to planetary health. These threats are strongly linked through the short-lived climate forcers (SLCFs); ozone (O(3)), aerosols, and methane (CH(4)). Understanding the impacts of ambitious SLCF mitigation in different source emission sectors on planetary health indicators can help prioritize international air pollution control strategies. A global Earth system model is applied to quantify the impacts of idealized 50% sustained reductions in year 2005 emissions in the eight largest global anthropogenic source sectors on the SLCFs and three indicators of planetary health: global mean surface air temperature change (∆GSAT), avoided PM(2.5)-related premature mortalities and gross primary productivity (GPP). The model represents fully coupled atmospheric chemistry, aerosols, land ecosystems and climate, and includes dynamic CH(4). Avoided global warming is modest, with largest impacts from 50% cuts in domestic (-0.085 K), agriculture (-0.034 K), and waste/landfill (-0.033 K). The 50% cuts in energy, domestic, and agriculture sector emissions offer the largest opportunities to mitigate global PM(2.5)-related health risk at around 5%-7% each. Such small global impacts underline the challenges ahead in achieving the World Health Organization aspirational goal of a 2/3 reduction in the number of deaths from air pollution by 2030. Uncertainty due to natural climate variability in PM(2.5) is an important underplayed dimension in global health risk assessment that can vastly exceed uncertainty due to the concentration-response functions at the large regional scale. Globally, cuts to agriculture and domestic sector emissions are the most attractive targets to achieve climate and health co-benefits through SLCF mitigation.
The global food system is essential for the health and wellbeing of society, but is also a major cause of environmental damage. Some impacts, such as on climate change, have been the subject of intense recent inquiry, but others, such as on air quality, are not as well understood. Here, we systematically synthesize the literature to identify the impacts on ambient PM2.5 (particulate matter with diameter <= 2.5 mu m), which is the strongest contributor to premature mortality from exposure to air pollution. Our analysis indicates that the life-cycle of the global food system (pre-production, production, post-production, consumption and waste management) accounts for 58% of anthropogenic, global emissions of primary PM2.5, 72% of ammonia (NH3), 13% of nitrogen oxides (NO (x) ), 9% of sulfur dioxide (SO2), and 19% of non-methane volatile organic compounds (NMVOC). These emissions result in at least 890 000 ambient PM2.5-related deaths, which is equivalent to 23% of ambient PM2.5-related deaths reported in the Global Burden of Disease Study 2015. Predominant contributors include livestock and crop production, which contribute >50% of food-related NH3 emissions, and land-use change and waste burning, which contribute up to 95% of food-related primary PM2.5 emissions. These findings are largely underestimated given the paucity of data from the post-production and consumption stages, total underestimates in NH3 emissions, lack of sector-scale analysis of PM2.5-related deaths in South America and Africa, and uncertainties in integrated exposure-response functions. In addition, we identify mitigation opportunities-including shifts in food demand, changes in agricultural practices, the adoption of clean and low-energy technologies, and policy actions-that can facilitate meeting food demand with minimal PM2.5 impacts. Further research is required to resolve sectoral-scale, region-specific contributions to PM2.5-related deaths, and assess the efficiency of mitigation strategies. Our review is positioned to inform stakeholders, including scientists, engineers, policymakers, farmers and the public, of the health impacts of reduced air quality resulting from the global food system.
Particulate matter with aerodynamic diameter ≤2.5 μm (PM(2.5)) concentrations vary between countries with similar carbon dioxide (CO(2)) emissions, which can be partially explained by differences in air pollution control efficacy. However, no indicator of air pollution control efficacy has yet been developed. We aimed to develop such an indicator, and to evaluate its global and temporal distribution and its association with country-level health metrics. A novel indicator, ambient population-weighted average PM(2.5) concentration per unit per capita CO(2) emission (PM(2.5)/CO(2)), was developed to assess country-specific air pollution control efficacy (abbreviated as APCI). We estimated and mapped the global average distribution of APCI and its changes during 2000-2016 across 196 countries. Pearson correlation coefficients and Generalized Additive Mixed Model (GAMM) were used to evaluate the relationship between APCI and health metrics. APCI varied by country with an inverse association with economic development. APCI showed an almost stable trend globally from 2000 to 2016, with the low-income groups increased and several countries (China, India, Bangladesh) decreased. The Pearson correlation coefficients between APCI and life expectancy at birth (LE), infant-mortality rate (IMR), under-five year of age mortality rate (U5MR) and logarithm of per capita GDP (LPGDP) were -0.57, 0.65, 0.66, -0.59 respectively (all P values < 0.001). APCI could explain international variation of LE, IMR and U5MR. The associations between APCI and LE, IMR, U5MR were independent of per capita GDP and climatic factors. We consider APCI to be a good indicator for air pollution control efficacy given its relation to important population health indicators. Our findings provide a new metric to interpret health inequity across the globe from the point of climate change and air pollution control efficacy.
Accumulating evidence underscores the large role played by the environment in the health of communities and individuals. We review the currently known contribution of environmental exposures and pollutants on kidney disease and its associated morbidity. We review air pollutants, such as particulate matter; water pollutants, such as trace elements, per- and polyfluoroalkyl substances, and pesticides; and extreme weather events and natural disasters. We also discuss gaps in the evidence that presently relies heavily on observational studies and animal models, and propose using recently developed analytic methods to help bridge the gaps. With the expected increase in the intensity and frequency of many environmental exposures in the decades to come, an improved understanding of their potential effect on kidney disease is crucial to mitigate potential morbidity and mortality.
Previous research demonstrates that low-income countries face higher risks than high-income countries from toxic pollution and climate change. However, the relationship between these two risks is little explored or tested, and efforts to address the risks are often independent and uncoordinated. We argue that the global risks from toxic pollution and climate change are highly correlated and should be jointly analyzed in order to inform and better target efforts to reduce or mitigate both risks. We provide such analysis for 176 countries and found a strong (rs = -0.798;95%CI -0.852, -0.727) and significant (p<0.0001) relationship between the distribution of climate risk and toxic pollution. We also found that inequities in pollution production, economic status, and institutional readiness are interconnected and exacerbate risk for countries already in the highest risk categories for both toxic and non-toxic (greenhouse gas) pollution. The findings have policy implications, including the use of the proposed Target assessment to decide where best to address toxic and non-toxic pollution simultaneously, based on the need to minimize human suffering and maximize return on effort.
The coronavirus disease 2019 (COVID-19) pandemic has significantly disrupted global metal mining and associated supply chains. Here we analyse the cascading effects of the metal mining disruption associated with the COVID-19 pandemic on the economy, climate change, and human health. We find that the pandemic reduced global metal mining by 10-20% in 2020. This reduction subsequently led to losses in global economic output of approximately 117 billion US dollars, reduced CO(2) emissions by approximately 33 million tonnes (exceeding Hungary’s emissions in 2015), and reduced human health damage by 78,192 disability-adjusted life years. In particular, copper and iron mining made the most significant contribution to these effects. China and rest-of-the-world America were the most affected. The cascading effects of the metal mining disruption associated with the pandemic on the economy, climate change, and human health should be simultaneously considered in designing green economic stimulus policies.
During wildfire smoke events public health agencies release advisories to stay indoors, close doors and windows, and operate a portable air cleaner (PAC). The do-it-yourself (DIY) air cleaner consisting of a box fan and a furnace filter is a widely used low-cost alternative to commercial PACs because of its increased accessibility. In this study, we evaluate the clean air delivery rate (CADR) of different DIY air cleaner designs for reducing simulated wildfire smoke and identify operating parameters that may impact their performance and use. The simplest formulation of a DIY air cleaner (box fan with taped on minimum effectiveness reporting value – [MERV] 13 furnace filter) had a CADR of 111.2 ± 1.3 ft(3) /min (CFM). Increasing the fan flow by changing the fan type, increasing the fan setting, or reducing the pressure drop across the filtering surface increased the CADR. Large increases in CADR could be obtained by using a shroud (40%), using a 4″ thick filter (123%) using two filters in a wedge shape (137%), or using four filters in a Corsi-Rosenthal (CR) box design (261%). The CADR was greatly reduced with filters heavily loaded with smoke, pointing to the need for frequent filter changes during smoke events.
In recent years, wildland fires have occurred more frequently and with increased intensity in many fire-prone areas. In addition to the direct life and economic losses attributable to wildfires, the emitted smoke is a major contributor to ambient air pollution, leading to significant public health impacts. Wildfire smoke is a complex mixture of particulate matter (PM), gases such as carbon monoxide, nitrogen oxide, and volatile and semi-volatile organic compounds. PM from wildfire smoke has a high content of elemental carbon and organic carbon, with lesser amounts of metal compounds. Epidemiological studies have consistently found an association between exposure to wildfire smoke (typically monitored as the PM concentration) and increased respiratory morbidity and mortality. However, previous reviews of the health effects of wildfire smoke exposure have not established a conclusive link between wildfire smoke exposure and adverse cardiovascular effects. In this review, we systematically evaluate published epidemiological observations, controlled clinical exposure studies, and toxicological studies focusing on evidence of wildfire smoke exposure and cardiovascular effects, and identify knowledge gaps. Improving exposure assessment and identifying sensitive cardiovascular endpoints will serve to better understand the association between exposure to wildfire smoke and cardiovascular effects and the mechanisms involved. Similarly, filling the knowledge gaps identified in this review will better define adverse cardiovascular health effects of exposure to wildfire smoke, thus informing risk assessments and potentially leading to the development of targeted interventional strategies to mitigate the health impacts of wildfire smoke.
Due to climate change, bushfires are becoming a more frequent and more severe phenomenon which contributes to poor health effects associated with air pollution. In pregnancy, environmental exposures can have lifelong consequences for the fetus, but little is known about these consequences in the context of bushfire smoke exposure. In this review we summarise the current knowledge in this area, and propose a potential mechanism linking bushfire smoke exposure in utero to poor perinatal and respiratory outcomes in the offspring. Bushfire smoke exposure is associated with poor pregnancy outcomes including reduced birth weight and an increased risk of prematurity. Some publications have outlined the adverse health effects on young children, particularly in relation to emergency department presentations and hospital admissions for respiratory problems, but there are no studies in children who were exposed to bushfire smoke in utero. Prenatal stress is likely to occur as a result of catastrophic bushfire events, and stress is known to be associated with poor perinatal and respiratory outcomes. Changes to DNA methylation are potential epigenetic mechanisms linking both smoke particulate exposure and prenatal stress to poor childhood respiratory health outcomes. More research is needed in large pregnancy cohorts exposed to bushfire events to explore this further, and to design appropriate mitigation interventions, in this area of global public health importance.
BACKGROUND: Fine particulate matter (PM(2.5)) produced by landscape fires is thought to be more toxic than that from non-fire sources. However, the effects of “fire-sourced” PM(2.5) on acute respiratory infection (ARI) are unknown. METHODS: We combined Demographic and Health Survey (DHS) data from 48 countries with gridded global estimates of PM(2.5) concentrations from 2003 to 2014. The proportions of fire-sourced PM(2.5) were assessed by a chemical transport model using a variety of PM(2.5) source data. We tested for associations between ARI and short-term exposure to fire- and “non-fire-sourced” PM(2.5) using a bidirectional case-crossover analysis. The robustness and homogeneity of the associations were examined by sensitivity analyses. We also established a nonlinear exposure-response relationship between fire- and non-fire-sourced PM(2.5) and ARI using a two-dimensional spline function. RESULTS: The study included 36,432 children under 5 years who reported ARI symptoms. Each 1 µg/m(3) increment of fire-sourced PM(2.5) was associated with a 3.2 % (95 % confidence interval [CI] 0.2, 6.2) increment in the risk of ARI. This effect was comparable to that of each ∼5 µg/m(3) increment in PM(2.5) from non-fire sources (3.1 %; 95 % CI 2.4, 3.7). The association between ARI and total PM(2.5) concentration was significantly mediated by the proportion of fire-sourced particles. Nonlinear analysis showed that the risk of ARI was increased by both fire- and non-fire-sourced PM(2.5), but especially by the former. CONCLUSIONS: PM(2.5) produced by landscape fire was more strongly associated to ARI among children under 5 years than that from non-fire sources.
Exposures to ambient fine particulate matter (PM(2.5)) and cold ambient temperatures have been identified as important risk factors in contributing towards the global mortality from chronic obstructive pulmonary disease (COPD). Despite China currently being the country with the largest population in the world, previous relative risk (RR) models have considered little or no information from the ambient air pollution related cohort studies in the country. This likely provides a less accurate picture of the trend in air pollution attributable mortality in the country over time. A novel relative risk model called pollutant-temperature exposure (PTE) model is proposed to estimate the RR attributable to the combined effect of air pollution and ambient temperature in a population. In this paper, the pollutant concentration-response curve was extrapolated from the cohort studies in China, whereas the temperature response curve was extracted from a study in Yangtze River Delta (YRD) region. The performance of the PTE model was compared with the integrated exposure-response (IER) model using the data of YRD region, which revealed that the estimated relative risks of the PTE model were noticeably higher than the IER model during the winter season. Furthermore, the predictive ability of the PTE model was validated using actual data of Ningbo city, which showed that the estimated RR using the PTE model with 1-month moving average data showed a good result with the trend of actual COPD mortality, indicated by a lower root mean square error (RMSE = 0.956). By considering the combined effect of ambient air pollutant and ambient temperature, the PTE model is expected to provide more accurate relative risk estimates for the regions with high levels of ambient PM(2.5) and seasonal variation of ambient temperature.
Climate change and air pollution can interact to amplify risks to human health and crop production. This has significant implications for our ability to reach the Sustainable Development Goals (e.g. SDGs 2, 3, 13, 15) and for the design of effective mitigation and adaptation policies and risk management. To be able to achieve the SDG targets, closer integration of climate change and air pollution both in terms of impact assessment for human health and agricultural productivity and respective policy development is needed. Currently, studies estimating the impacts of climate and air pollutants on human health and crops mostly treat these stressors separately, and the methods used by the health and agricultural science communities differ. Better insights into the methods applied in the different communities can help to improve existing and develop new methods to advance our knowledge about the combined impacts of climate change and air pollution on human health and crops. This topical review provides an overview of current methodologies applied in the two fields of human health and agricultural crop impact studies, ranging from empirical regression-based and experimental methods to more complex process-based models. The latter are reasonably well developed for estimating impacts on agricultural crops, but not for health impacts. We review available literature addressing the combined effects of climate and air pollution on human health or agricultural productivity to provide insights regarding state-of-the-art knowledge and currently available methods in the two fields. Challenges to assess the combined effect of climate and air pollution on human health and crops, and opportunities for both fields to learn from each other, are discussed.
New epidemiological studies acknowledge the detrimental effects of dust storms on health. The aim of this study was to systematically review the effects of dust storms on the morbidity and mortality rates of cardiovascular and respiratory diseases. The results of this study were obtained based on articles published in English-language journals. For the purpose of this study, all articles published until the end of 2020 based on the search in the “Scopus,” “Web of Science,” and “PubMed” databases were selected. Articles were searched independently by two trained researchers. Dust storms are the cause of many diseases and health-related complications, of which cardiovascular and respiratory diseases are common. It is necessary to recognize and investigate the harmful effects of dust storms to prevent serious harms to human societies. In the reviewed articles, the impact of dust storms on several diseases, including cardiovascular and respiratory diseases, has been analyzed. Most of these articles acknowledge the effect of dust storms on increasing the incidence and mortality rate of these diseases, although in some articles this effect is not statistically significant. Many studies conducted around the world confirm the harmful effects of dust storms on cardiovascular and respiratory diseases, including increase in the number and duration of hospitalizations, as well as increase in mortality and exacerbation of these diseases. However, some studies do not consider the harmful effects of dust storms on the above diseases to be statistically significant.
Climate change and obesity were considered threats to our planet long before the onset of COVID-19. The recent pandemic has enhanced the global burden of both pre-existing crises. The aim of this narrative review is to explore the interaction between the three concurrent crises and the future of our planet should they not be dealt with accordingly. A PubMed and Google Scholar literature search was performed using different combinations of search strategies and using the keywords obesity , climate/temperature change , cold/hot temperatures , and COVID-19 . High global greenhouse gas (GHG) emissions link obesity and climate change as a result of the interplay between biological and behavioural factors. COVID-19 mitigation measures have indirectly impacted obesity and GHG emissions through the shift in dietary habits, restricted mobility, the impact on healthcare services, and enhanced psychological stress. Furthermore, COVID-19 has a more detrimental effect if acquired by an obese individual, with a higher chance of hospitalization and mechanical ventilation. This leads to higher GHG emissions and negative repercussions on the climate. A tri-directional relationship exists between obesity, climate change, and COVID-19. Various factors contribute to this relationship, but unless urgent global integrated action plans are implemented that target all three calamities, and not just COVID-19, a devastating and unsustainable future may ensue.
This review paper discusses the Stockholm Paradigm (SP) as a theoretical framework and practical computational instrument for studying and assessing the risk of emerging infectious diseases (EIDs) as a result of climate change. The SP resolves the long-standing parasite paradox and explains how carbon emissions in the atmosphere increase parasites’ generalization and intensify host switches from animals to humans. The SP argues that the growing rate of novel EID occurrence caused by mutated zoonotic pathogens is related to the following factors brought together as a unified issue of humanity: (a) carbon emissions and consequent climate change; (b) resettlement/migration of people with hyper-urbanization; (c) overpopulation; and (d) human-induced distortion of the biosphere. The SP demonstrates that, in an evolutionary way, humans now play a role migratory birds once played in spreading parasite pathogens between the three Earth megabiotopes (northern coniferous forest belt; tropical/equatorial rainforest areas; and hot/cold deserts), i.e., the role of “super-spreaders” of parasitic viruses, bacteria, fungi and protozoa. This makes humans extremely vulnerable to the EID threat. The SP sees the +1.0-+1.2 °C limit as the optimal target for the slow, yet feasible curbing of the EID hazard to public health (150-200 years). Reaching merely the +2.0 °C level will obviously be an EID catastrophe, as it may cause two or three pandemics each year. We think it useful and advisable to include the SP-based research in the scientific repository of the Intergovernmental Panel on Climate Change, since EID appearance and spread are indirect but extremely dangerous consequences of climate change.
Background: It is crucial to understand the benefits to human health from decarbonisation to galvanise action among decision makers. Most of our existing evidence comes from modelling studies and little is known about the extent to which the health co-benefits of climate change mitigation actions are realised upon implementation. We aim to analyse evidence from mitigation actions that have been implemented across a range of sectors and scales, to identify those that can improve and sustain health, while accelerating progress towards a zero-carbon economy. Objectives: To understand the implementation process of actions and the role of key actors; explain the contextual elements influencing these actions; summarise what effects, both positive and negative, planned and unplanned they may have on emissions of greenhouse gases and health; and to summarise environmental, social, or economic co-benefits. Data: We will review evidence collected through partnership with existing data holders and an open call for evidence. We will also conduct a hand search of reference lists from systematic reviews and websites of organisations relevant to climate change mitigation. Screening: Screening will be done by two reviewers according to a pre-defined inclusion and exclusion criteria. Analysis: We will identify gaps where implementation or evaluation of implementation of mitigation actions is lacking. We will synthesise the findings to describe how actions were implemented and how they achieved results in different contexts, identifying potential barriers and facilitators to their design, implementation, and uptake. We will also synthesise their effect on health outcomes and other co-benefits. Quantitative synthesis will depend on the heterogeneity of outcomes and metrics. Conclusions: Findings will be used to identify lessons that can be learned from successful and unsuccessful mitigation actions, to make inferences on replicability, scalability, and transferability and will contribute to the development of frameworks that can be used by policy makers.
Polycyclic aromatic hydrocarbons (PAHs) are a large group of organic compounds that have 2-7 benzene rings. PAHs causes many complications in humans, including respirations and increased risk of cancer. The most important fixed and mobile sources (PAHs) include food, industrial pollution, and car exhaust. The most common ways of entering the body (PAHs) are through direct contact, seafood, grilled meat, inhalation of PAHs, and contaminated water. From various studies and many publications in the field, the major issue with PAHs is increased risk of cancer, such as cancer of lungs if inhaled or skin if in contact with skin, cancer of stomach or gastrointestinal in smoked or barbecued fish and meat products. The purpose of this review study was to the epidemiological literature on the side effect of Polycyclic aromatic hydrocarbons (PAHs) on respiratory diseases and the risk factors related to Cancer. Six hundred and fifty-five articles according to different databases: Google Scholar, PubMed, Web of Science, BMJ, Springer, and Science Direct were retrieved. Forty-two studies were screened after review and, 27 full-text articles were entered into the analysis process. Finally, 15 articles were selected for this study. Studies have shown the effects of PAHs in increasing the risk of infection in the respiratory system, including asthma, lung dysfunction, and various cancers, such as skin, digestive tract, lung, and blood. The results showed that polycyclic aromatic hydrocarbons could increase the probability and risk incidence of cancers of the lung, skin, bladder, and respiratory diseases, such as asthma and lung dysfunction. Reducing the emission of polycyclic aromatic hydrocarbons (PAHs) due to activities, such as cooking, car exhaust, wildfire, and power plant can be a very influential factor in reducing the health endpoint of this pollutant, especially respiratory diseases, and Cancer.
Climate change can have economic consequences, affecting the nutritional intake of populations and increasing food insecurity, as it negatively affects diet quality parameters. One way to mitigate these consequences is to change the way we produce and consume our food. A healthy and sustainable diet aims to promote and achieve the physical, mental, and social well-being of the populations at all life stages, while protecting and safeguarding the resources of the planet and preserving biodiversity. Over the past few years, several indexes have been developed to evaluate dietary sustainability, most of them based on the EAT-Lancet reference diet. The present review explains the problems that arise in human nutrition as a result of climate change and presents currently available diet sustainability indexes and their applications and limitations, in an effort to aid researchers and policy actors in identifying aspects that need improvement in the development of relevant indexes. Overall, great heterogeneity exists among the indicators included in the available indexes and their methodology. Furthermore, many indexes do not adequately account for the diets’ environmental impact, whereas others fall short in the economic impact domain, or the ethical aspects of sustainability. The present review reveals that the design of one environmentally friendly diet that is appropriate for all cultures, populations, patients, and geographic locations is a difficult task. For this, the development of sustainable and healthy diet recommendations that are region-specific and culturally specific, and simultaneously encompass all aspects of sustainability, is required.
Climate change can cause multiply potential health issues in urban areas, which is the most susceptible environment in terms of the presently increasing climate volatility. Urban greening strategies make an important part of the adaptation strategies which can ameliorate the negative impacts of climate change. It was aimed to study the potential impacts of different kinds of greenings against the adverse effects of climate change, including waterborne, vector-borne diseases, heat-related mortality, and surface ozone concentration in a medium-sized Hungarian city. As greening strategies, large and pocket parks were considered, based on our novel location identifier algorithm for climate risk minimization. A method based on publicly available data sources including satellite pictures, climate scenarios and urban macrostructure has been developed to evaluate the health-related indicator patterns in cities. The modelled future- and current patterns of the indicators have been compared. The results can help the understanding of the possible future state of the studied indicators and the development of adequate greening strategies. Another outcome of the study is that it is not the type of health indicator but its climate sensitivity that determines the extent to which it responds to temperature rises and how effective greening strategies are in addressing the expected problem posed by the factor.
Air pollution is responsible for many adverse effects on human beings. Thermal discomfort, on the other hand, is able to overload the human body and eventually provoke health implications due to the heat imbalance. Methods: The aim of the presented work is to study the behavior of two bio-climatic indices and statistical characteristics of the air quality index for Sofia city-the capital of Bulgaria for the period 2008-2014. The study is based on the WRF-CMAQ model system simulations with a spatial resolution of 1 km. The air quality is estimated by the air quality index, taking into account the influence of different pollutants and the thermal conditions by two indices, respectively, for hot and cold weather. It was found that the recurrence of both the heat and cold index categories and of the air quality categories have heterogeneous space distribution and well manifested diurnal and seasonal variability. For all of the situations, only O-3 and PM10 are the dominant pollutants-these which determine the AQI category. It was found that AQI1, AQI2, and AQI3, which fall in the “Low” band, have the highest recurrence during the different seasons, up to more than 70% in some places and situations. The recurrence of AQI10 (very high) is rather small-no more than 5% and concentrated in small areas, mostly in the city center. The Heat index of category “Danger” never appears, and the Heat index of category “Extreme caution” appears only in the spring and summer with the highest recurrence of less than 5% in the city center. For the Wind-chill index category, “Very High Risk” never appears, and the category “High Risk” appears with a frequency of about 1-2%. The above leads to the conclusion that both from a point of view of bioclimatic and air quality indices, the human health risks in the city of Sofia are not as high.
Urbanization, anthropogenic activities, and social determinants such as poverty and literacy rate greatly contribute to heat-related mortalities. The 2003 strong heat wave (Lucifer) in France resulted in catastrophic health consequences in the region that may be attributed to urbanization and other anthropogenic activities. Amiens is a medium-sized French city, where the average temperature has increased since the year 2000. In this study, we evaluated the Heat Vulnerability Index (HVI) in Amiens for extreme heat days recorded during three years (2018-2020). We used the principal component analysis (PCA) technique for fine-scale vulnerability mapping. The main types of considered data included (a) socioeconomic and demographic data, (b) air pollution, (c) land use and cover, (d) elderly heat illness, (e) social vulnerability, and (f) remote sensing data (land surface temperature (LST), mean elevation, normalized difference vegetation index (NDVI), and normalized difference water index (NDWI)). The output maps identified the hot zones through comprehensive GIS analysis. The resultant maps showed that high HVI exists in three typical areas: (1) areas with dense population and low vegetation, (2) areas with artificial surfaces (built-up areas), and (3) industrial zones. Low-HVI areas are in natural landscapes such as rivers and grasslands. Our analysis can be implemented in other cities to highlight areas at high risk of extreme heat and air pollution.
Cities are increasingly confronted with multiple environmental and climatic stressors. Especially during heatwaves, street canyons are both producers and sufferers of air pollution and urban heat island (UHI) effects, with severe risks on public health. To better design mitigation measures, it is important to consider both the microclimate behaviors as well as the perceptions of the local population. Therefore, this study examined pedestrian perceptions and microclimate modelings to understand outdoor thermal comfort conditions and air pollution dispersion in the case study neighborhood of Dortmund Marten, Germany. A field survey with measurement points at two street canyons for climatic variables and questionnaires on subjective thermal comfort and air pollution was conducted on a hot day during the heatwave period in August 2020. As a cost-effective method for modeling input generation, we extracted spatial and spectral data like albedo, roof materials and tree locations out of remote sensing imageries. Finally, we compared the modeling results of the physiological equivalent temperature (PET) index, particulate matter concentrations and air temperatures with empirical field measurement data and the questionnaire responses. Results indicate that during hot summer days with light winds from the east, the north-south orientated street canyon with tree arrangements tends to act as a tunnel for particulate matter accumulation. Coincidently, pedestrians show less thermal discomfort than calculated PET values in that particular area during morning and daytime, which underlines the dichotomy of such places. On the other hand, the low rise east-west orientated street canyon shows higher PET votes than predicted by the model. However, particulate matter concentrations were considerably underestimated by the model, while air temperature predictions provided meaningful results. The proposed workflow shows the potential to accelerate future preparations of input data for microclimate modelings, while the results can enhance wind-sensitive planning procedures and heat stress resilience in mid-latitude urban neighborhoods.
Monitoring microclimate variables within cities with high accuracy is an ongoing challenge for a better urban resilience to climate change. Assessing the intra-urban characteristics of a city is of vital importance for ensuring fine living standards for citizens. Here, a novel mobile microclimate station is applied for monitoring the main microclimatic variables regulating urban and intra-urban environment, as well as directionally monitoring shortwave radiation and illuminance and hence systematically map for the first time the effect of urban surfaces and anthropogenic heat. We performed day-time and night-time monitoring campaigns within a historical city in Italy, characterized by substantial urban structure differentiations. We found significant intra-urban variations concerning variables such as air temperature and shortwave radiation. Moreover, the proposed experimental framework may capture, for the very first time, significant directional variations with respect to shortwave radiation and illuminance across the city at microclimate scale. The presented mobile station represents therefore the key missing piece for exhaustively identifying urban environmental quality, anthropogenic actions, and data driven modelling toward risk and resilience planning. It can be therefore used in combination with satellite data, stable weather station or other mobile stations, e.g. wearable sensing techniques, through a citizens’ science approach in smart, livable, and sustainable cities in the near future.
BACKGROUND: Desert dust events in Mediterranean countries, originating mostly from the Sahara and Arabian deserts, have been linked to climate change and are associated with significant increase in mortality and hospital admissions from respiratory causes. The MEDEA clinical intervention study in children with asthma is funded by EU LIFE+ program to evaluate the efficacy of recommendations aiming to reduce exposure to desert dust and related health effects. METHODS: This paper describes the design, methods, and challenges of the MEDEA childhood asthma study, which is performed in two highly exposed regions of the Eastern Mediterranean: Cyprus and Greece-Crete. Eligible children are recruited using screening surveys performed at primary schools and are randomized to three parallel intervention groups: a) no intervention for desert dust events, b) interventions for outdoor exposure reduction, and c) interventions for both outdoor and indoor exposure reduction. At baseline visits, participants are enrolled on MEDena® Health-Hub, which communicates, alerts and provides exposure reduction recommendations in anticipation of desert dust events. MEDEA employs novel environmental epidemiology and telemedicine methods including wearable GPS, actigraphy, health parameters sensors as well as indoor and outdoor air pollution samplers to assess study participants’ compliance to recommendations, air pollutant exposures in homes and schools, and disease related clinical outcomes. DISCUSSION: The MEDEA study evaluates, for the first time, interventions aiming to reduce desert dust exposure and implement novel telemedicine methods in assessing clinical outcomes and personal compliance to recommendations. In Cyprus and Crete, during the first study period (February-May 2019), a total of 91 children participated in the trial while for the second study period (February-May 2020), another 120 children completed data collection. Recruitment for the third study period (February-May 2021) is underway. In this paper, we also present the unique challenges faced during the implementation of novel methodologies to reduce air pollution exposure in children. Engagement of families of asthmatic children, schools and local communities, is critical. Successful study completion will provide the knowledge for informed decision-making both at national and international level for mitigating the health effects of desert dust events in South-Eastern Europe. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03503812 , April 20, 2018.
BACKGROUND: The evidence is sparse regarding the associations between serious mental illnesses (SMIs) prevalence and environmental factors in adulthood as well as the geographic distribution and variability of these associations. In this study, we evaluated the association between availability and proximity of green and blue space with SMI prevalence in England as a whole and in its major conurbations (Greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle). METHODS AND FINDINGS: We carried out a retrospective analysis of routinely collected adult population (≥18 years) data at General Practitioner Practice (GPP) level. We used data from the Quality and Outcomes Framework (QOF) on the prevalence of a diagnosis of SMI (schizophrenia, bipolar affective disorder and other psychoses, and other patients on lithium therapy) at the level of GPP over the financial year April 2014 to March 2018. The number of GPPs included ranged between 7,492 (April 2017 to March 2018) to 7,997 (April 2014 to March 2015) and the number of patients ranged from 56,413,719 (April 2014 to March 2015) to 58,270,354 (April 2017 to March 2018). Data at GPP level were converted to the geographic hierarchy unit Lower Layer Super Output Area (LSOA) level for analysis. LSOAs are a geographic unit for reporting small area statistics and have an average population of around 1,500 people. We employed a Bayesian spatial regression model to explore the association of SMI prevalence in England and its major conurbations (greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle) with environmental characteristics (green and blue space, flood risk areas, and air and noise pollution) and socioeconomic characteristics (age, ethnicity, and index of multiple deprivation (IMD)). We incorporated spatial random effects in our modelling to account for variation at multiple scales. Across England, the environmental characteristics associated with higher SMI prevalence at LSOA level were distance to public green space with a lake (prevalence ratio [95% credible interval]): 1.002 [1.001 to 1.003]), annual mean concentration of PM2.5 (1.014 [1.01 to 1.019]), and closeness to roads with noise levels above 75 dB (0.993 [0.992 to 0.995]). Higher SMI prevalence was also associated with a higher percentage of people above 24 years old (1.002 [1.002 to 1.003]), a higher percentage of ethnic minorities (1.002 [1.001 to 1.002]), and more deprived areas. Mean SMI prevalence at LSOA level in major conurbations mirrored the national associations with a few exceptions. In Birmingham, higher average SMI prevalence at LSOA level was positively associated with proximity to an urban green space with a lake (0.992 [0.99 to 0.998]). In Liverpool and Manchester, lower SMI prevalence was positively associated with road traffic noise ≥75 dB (1.012 [1.003 to 1.022]). In Birmingham, Liverpool, and Manchester, there was a positive association of SMI prevalence with distance to flood zone 3 (land within flood zone 3 has ≥1% chance of flooding annually from rivers or ≥0.5% chance of flooding annually from the sea, when flood defences are ignored): Birmingham: 1.012 [1.000 to 1.023]; Liverpool and Manchester: 1.016 [1.006 to 1.026]. In contrast, in Leeds, there was a negative association between SMI prevalence and distance to flood zone 3 (0.959 [0.944 to 0.975]). A limitation of this study was because we used a cross-sectional approach, we are unable to make causal inferences about our findings or investigate the temporal relationship between outcome and risk factors. Another limitation was that individuals who are exclusively treated under specialist mental health care and not seen in primary care at all were not included in this analysis. CONCLUSIONS: Our study provides further evidence on the significance of socioeconomic associations in patterns of SMI but emphasises the additional importance of considering environmental characteristics alongside socioeconomic variables in understanding these patterns. In this study, we did not observe a significant association between green space and SMI prevalence, but we did identify an apparent association between green spaces with a lake and SMI prevalence. Deprivation, higher concentrations of air pollution, and higher proportion of ethnic minorities were associated with higher SMI prevalence, supporting a social-ecological approach to public health prevention. It also provides evidence of the significance of spatial analysis in revealing the importance of place and context in influencing area-based patterns of SMI.
Desert dust storms (DDS) are natural events that impact not only populations close to the emission sources but also populations many kilometers away. Countries located across the main dust sources, including countries in the Eastern Mediterranean, are highly affected by DDS. In addition, climate change is expanding arid areas exacerbating DDS events. Currently, there are no intervention measures with proven, quantified exposure reduction to desert dust particles. As part of the wider “MEDEA” project, co-funded by LIFE 2016 Programme, we examined the effectiveness of an indoor exposure-reduction intervention (i.e., decrease home ventilation during DDS events and continuous use of air purifier during DDS and non-DDS days) across homes and/or classrooms of schoolchildren with asthma and adults with atrial fibrillation in Cyprus and Crete-Greece. Participants were randomized to a control or intervention groups, including an indoor intervention group with exposure reduction measures and the use of air purifiers. Particle sampling, PM(10) and PM(2.5,) was conducted in participants’ homes and/or classrooms, between 2019 and 2022, during DDS-free weeks and during DDS days for as long as the event lasted. In indoor and outdoor PM(10) and PM(2.5) samples, mass and content in main and trace elements was determined. Indoor PM(2.5) and PM(10) mass concentrations, adjusting for premise type and dust conditions, were significantly lower in the indoor intervention group compared to the control group (PM(2.5-intervention)/PM(2.5-control) = 0.57, 95% CI: 0.47, 0.70; PM(10-intervention)/PM(10-control) = 0.59, 95% CI: 0.49, 0.71). In addition, the PM(2.5) and PM(10) particles of outdoor origin were significantly lower in the intervention vs. the control group (PM(2.5) infiltration intervention-to-control ratio: 0.49, 95% CI: 0.42, 0.58; PM(10) infiltration intervention-to-control ratio: 0.68, 95% CI: 0.52, 0.89). Our findings suggest that the use of air purifiers alongside decreased ventilation measures is an effective protective measure that reduces significantly indoor exposure to particles during DDS and non-DDS in high-risk population groups.
The cold season is usually accompanied by an increased incidence of respiratory infections and increased air pollution from combustion sources. As we are facing growing numbers of COVID-19 cases caused by the novel SARS-CoV-2 coronavirus, an understanding of the impact of air pollutants and meteorological variables on the incidence of respiratory infections is crucial. The incidence of influenza-like illness (ILI) can be used as a close proxy for the circulation of influenza viruses. Recently, SARS-CoV-2 has also been detected in patients with ILI. Using distributed lag nonlinear models, we analyzed the association between ILI, meteorological variables and particulate matter concentration in Bialystok, Poland, from 2013-2019. We found an exponential relationship between cumulative PM(2.5) pollution and the incidence of ILI, which remained significant after adjusting for air temperatures and a long-term trend. Pollution had the greatest effect during the same week, but the risk of ILI was increased for the four following weeks. The risk of ILI was also increased by low air temperatures, low absolute humidity, and high wind speed. Altogether, our results show that all measures implemented to decrease PM(2.5) concentrations would be beneficial to reduce the transmission of SARS-CoV-2 and other respiratory infections.
This study examines whether climate change-associated environmental stressors, including air and noise pollution, local heat levels, as well as a lack of surrounding greenspace, mediate the effects of local poverty on mental health, using the 28-item General Health Questionnaire. We recruited 478 adults who were representative of eleven of Berlin’s inner-city neighborhoods. The relationship of individual-level variables, neighborhood-level sociodemographic and environmental data from the Berlin Senate (Department for Urban Development, Building and Housing) to mental health was assessed in a multilevel model using SPSS. We found that neither local exposure to environmental stressors, nor available greenspace as a protective factor, mediated the effects of local poverty on variance in mental health (all p values > 0.2). However, surrounding greenspace (r = -0.24, p < 0.001), nitrogen dioxide levels (r = 0.10, p < 0.05), noise pollution (rho = 0.15, p < 0.01), and particle pollution (r = 0.12, p < 0.001) were associated with local poverty, which, more strongly than individual factors, accounted for variance in mental health (β = 0.47, p < 0.001). Our analysis indicates that the effects of local poverty on mental health are not mediated by environmental factors. Instead, local poverty was associated with both an increased mental health burden and the exposure to climate-related environmental stressors.
Ultrafine particles (UFP), harmful to human health, are emitted at high levels from motorized traffic. Bicycle commuting is increasingly encouraged to reduce traffic emissions and increase physical activity, but higher breathing rates increase inhaled UFP concentrations while in traffic. We assessed exposure to UFP while cycling along a fixed 8.5 km inner-city route in Copenhagen, on weekdays over six weeks (from September to October 2020), during morning and afternoon rush-hour, as well as morning non-rush-hour, traffic time periods starting from 07:45, 15:45, and 09:45 h, respectively. Continuous measurements were made (each second) of particle number concentration (PNC) and location. PNC levels were summarized and compared across time periods. We used generalized additive models to adjust for meteorological factors, weekdays and trends. A total of 61 laps were completed, during 28 days (∼20 per time period). Overall mean PNC was 18,149 pt/cm^(3) (range 256-999,560 pt/cm^(3)) with no significant difference between morning rush-hour (18003 pt/cm^(3)), afternoon rush-hour (17560 pt/cm^(3)) and late morning commute (17560 pt/cm^(3)) [p = 0.85]. There was substantial spatial variation of UFP exposure along the route with highest PNC levels measured at traffic intersections (∼38,000-42000 pt/cm^(3)), multiple lane roads (∼38,000-40000 pt/cm^(3)) and construction sites (∼44,000-51000 pt/cm^(3)), while lowest levels were measured at smaller streets, areas with open built environment (∼12,000 pt/cm^(3)), as well as at a bus-only zone (∼15,000 pt/cm^(3)). UFP exposure in inner-city Copenhagen did not differ substantially when bicycling in either rush-hour or non-rush-hour, or morning or afternoon, traffic time periods. UFP exposure varied substantially spatially, with highest concentrations around intersections, multiple lane roads, and construction sites. This suggests that exposure to UFP is not necessarily reduced by avoiding rush-hours, but by avoiding sources of pollution along the bicycling route.
BACKGROUND: The chronic effects of ozone have only rarely been investigated in disease burden studies to date. Our goal was to determine this disease burden in Germany over the period 2007-2016, with particular attention to estimation based on effect estimates adjusted for particulate matter (PM2.5) and nitrogen dioxide (NO2). METHODS: The nationwide, high-spatial-resolution (2 km × 2 km), population-based exposure to ozone in the summer months (“summer ozone”) was calculated on the basis of modeled ozone data and population counts in Germany. Next, risk estimates derived from cohort studies were used to quantify the burden of chronic obstructive pulmonary disease (COPD). Data on population counts, life expectancy, and mortality in Germany were used to reflect the situation across the country as accurately as possible. RESULTS: The estimates of years of life lost (YLL) due to summer ozone ranged from 18.33 per 100 000 people (95% confidence interval [14.02; 22.08]) in 2007 to 35.77 per 100 000 people [27.45; 42.98] in 2015. These findings indicate that ozone affects the COPD burden independently of other harmful components of the air. No clear secular trend in the COPD burden can be seen over the period 2007 to 2016. CONCLUSION: Long-term exposure to ozone contributes to the COPD burden among the general population in Germany. As climate change may lead to a rise in the ozone concentration, more intensive research is required on the effects of ozone on health.
While many authors have described the adverse health effects of poor air quality and meteorological extremes, there remain inconsistencies on a regional scale as well as uncertainty about the single and joint effects of atmospheric predictors. In this context, we investigated the short-term impacts of weather and air quality on moderate extreme cancer-related mortality events for the urban area of Augsburg, Southern Germany, during the period 2000-2017. First, single effects were uncovered by applying a case-crossover routine. The overall impact was assessed by performing a Mann-Whitney U testing scheme. We then compared the results of this procedure to extreme noncancer-related mortality events. In a second step, we found periods with contemporaneous significant predictors and carried out an in-depth analysis of these joint-effect periods. We were interested in the atmospheric processes leading to the emergence of significant conditions. Hence, we applied the Principal Component Analysis to large-scale synoptic conditions during these periods. The results demonstrate a strong linkage between high-mortality events in cancer patients and significantly above-average levels of nitrogen dioxide (NO(2)) and particulate matter (PM(2.5)) during the late winter through spring period. These were mainly linked to northerly to easterly weak airflow under stable, high-pressure conditions. Especially in winter and spring, this can result in low temperatures and a ground-level increase and the accumulation of air pollution from heating and traffic as well as eastern lateral advection of polluted air. Additionally, above-average temperatures were shown to occur on the days before mortality events from mid-summer through fall, which was also caused by high-pressure conditions with weak wind flow and intense solar radiation. Our approach can be used to analyse medical data with epidemiological as well as climatological methods while providing a more vivid representation of the underlying atmospheric processes.C
BACKGROUND: Previous studies reported a link between short-term exposure to environmental stressors (air pollution and air temperature) and atherothrombotic cardiovascular diseases. However, only few of them reported consistent associations with venous thromboembolism (VTE). Our aim was to estimate the association between daily air temperature and particulate matter (PM) air pollution with hospital admissions for pulmonary embolism (PE) and venous thrombosis (VT) at national level in Italy. METHODS: We collected daily hospital PE and VT admissions from the Italian Ministry of Health during 2006-2015 in all the 8,084 municipalities of Italy, and we merged them with air temperature and daily PM10 concentrations estimated by satellite-based spatiotemporal models. First, we applied multivariate Poisson regression models at province level. Then, we obtained national overall effects by random-effects meta-analysis. RESULTS: This analysis was conducted on 219,952 PE and 275,506 VT hospitalizations. Meta-analytical results showed weak associations between the two exposures and the study outcomes in the full year analysis. During autumn and winter, PE hospital admissions increased by 1.07% (95% confidence intervals [CI]: 0.21%; 1.92%) and 0.96% (95% CI: 0.07%; 1.83%) respectively, per 1 °C decrement of air temperature in the previous 10 days (lag 0-10). In summer we observed adverse effects at high temperatures, with a 1% (95% CI: 0.10%; 1.91%) increasing risk per 1 °C increment. We found no association between VT and cold temperatures. CONCLUSION: Results show a significant effect of air temperature on PE hospitalizations in the cold seasons and summer. No effect of particulate matter was detected.
BACKGROUND: The impact of nitrogen dioxide (NO2) and particulate matter with an aerodynamic diameter of less than or equal to 2.5. microns (PM2.5) exposures on lung function has been investigated mainly in children and less in adults. Furthermore, it is unclear whether short-term deviations of air pollutant concentration need to be considered in long-term exposure models. OBJECTIVES: The aims of this study were to investigate the association between short-term air pollution exposure and lung function and to assess whether short-term deviations of air pollutant concentration should be integrated into long-term exposure models. METHODS: Short-term (daily averages 0-7 d prior) and long-term (1- and 4-y means) NO2 and PM2.5 concentrations were modeled using satellite, land use, and meteorological data calibrated on ground measurements. Forced expiratory volume within the first second (FEV1) of forced exhalation and forced vital capacity (FVC) were measured during a LuftiBus assessment (2003-2012) and linked to exposure information from the Swiss National Cohort for 36,085 adults (ages 18-95 y). We used multiple linear regression to estimate adjusted associations, and additionally adjusted models of long-term exposures for short-term deviations in air pollutant concentrations. RESULTS: A 10 μg/m3 increase in NO2 and PM2.5 on the day of the pulmonary function test was associated with lower FEV1 and FVC (NO2: FEV1 – 8.0 ml [95% confidence interval: – 13.4, – 2.7], FVC – 16.7 ml [ – 23.4, – 10.0]; PM2.5: FEV1 – 15.3 ml [ – 21.9, – 8.7], FVC – 18.5 ml [ – 26.5, – 10.5]). A 10 μg/m3 increase in 1-y mean NO2 was also associated with lower FEV1 ( – 7.7 ml; – 15.9, 0.5) and FVC ( – 21.6 ml; – 31.9, – 11.4), as was a 10 μg/m3 increase in 1-y mean PM2.5 (FEV1: – 42.2 ml; – 56.9, – 27.5; FVC: – 82.0 ml; – 100.1, – 63.9). These associations were robust to adjustment for short-term deviations in the concentration of each air pollutant. CONCLUSIONS: Short- and long-term air pollution exposures were negatively associated with lung function, in particular long-term PM2.5 exposure with FVC. Our findings contribute substantially to the evidence of adverse associations between air pollution and lung function in adults. https://doi.org/10.1289/EHP7529.
The short- and long-term impacts of air pollution on human health are well documented and include cardiovascular, neurological, immune system and developmental damage. Additionally, the irritant qualities of air pollutants can cause respiratory and cardiovascular distress. This can be heightened during exercise and especially so for those with respiratory conditions such as asthma. Meteorological conditions have also been shown to adversely impact athletic performance; but research has mostly examined the impact of pollution and meteorology on marathon times or running under laboratory settings. This study focuses on the half marathon distance (13.1 miles/21.1 km) and utilises the Great North Run held in Newcastle-upon-Tyne, England, between 2006 and 2019. Local meteorological (temperature, relative humidity, heat index and wind speed) and air quality (ozone, nitrogen dioxide and PM(2.5)) data is used in conjunction with finishing times of the quickest and slowest amateur participants, along with the elite field, to determine the extent to which each group is influenced in real-world conditions. Results show that increased temperatures, heat index and ozone concentrations are significantly detrimental to amateur half marathon performances. The elite field meanwhile is influenced by higher ozone concentrations. It is thought that the increased exposure time to the environmental conditions contributes to this greater decrease in performance for the slowest participants. For elite athletes that are performing closer to their maximal capacity (VO(2) max), the higher ozone concentrations likely results in respiratory irritation and decreased performance. Nitrogen dioxide and PM(2.5) pollution showed no significant relationship with finishing times. These results provide additional insight into the environmental effects on exercise, which is particularly important under the increasing effects climate change and regional air pollution. This study can be used to inform event organisation and start times for both mass participation and major elite events with the aim to reduce heat- and pollution-related incidents.
The health impacts of global climate change mitigation will affect local populations differently. However, most co-benefits analyses have been done at a global level, with relatively few studies providing local level results. We aimed to quantify the local health impacts due to fine particles (PM(2.5)) under the governance arrangements embedded in the Shared Socioeconomic Pathways (SSPs1-5) under two greenhouse gas concentration scenarios (Representative Concentration Pathways (RCPs) 2.6 and 8.5) in local populations of Mozambique, India, and Spain. We simulated the SSP-RCP scenarios using the Global Change Analysis Model, which was linked to the TM5-FASST model to estimate PM(2.5) levels. PM(2.5) levels were calibrated with local measurements. We used comparative risk assessment methods to estimate attributable premature deaths due to PM(2.5) linking local population and mortality data with PM(2.5)-mortality relationships from the literature, and incorporating population projections under the SSPs. PM(2.5) attributable burdens in 2050 differed across SSP-RCP scenarios, and sensitivity of results across scenarios varied across populations. Future attributable mortality burden of PM(2.5) was highly sensitive to assumptions about how populations will change according to SSP. SSPs reflecting high challenges for adaptation (SSPs 3 and 4) consistently resulted in the highest PM(2.5) attributable burdens mid-century. Our analysis of local PM(2.5) attributable premature deaths under SSP-RCP scenarios in three local populations highlights the importance of both socioeconomic development and climate policy in reducing the health burden from air pollution. Sensitivity of future PM(2.5) mortality burden to SSPs was particularly evident in low- and middle- income country settings due either to high air pollution levels or dynamic populations.
Frequent and severe PM2.5 pollution over China seriously harms natural environment and human health. Changes in meteorological conditions in recent decades have been recognized to contribute to the long-term increase in PM2.5 pollution in North China (NC). However, the dominant climatic factors driving the interdecadal changes of the weather conditions conducive to PM2.5 pollution remain unclear. Here we identify a potential global teleconnection mechanism: the decadal reduction in European aerosol emissions since the 1980s may have partially contributed to the interdecadal increase in weather conditions conducive to PM2.5 pollution in NC, measured by an Emission-weighted Air Stagnation Index (ASI(E)) that increases at a rate of 6.2% decade(-1) (relative to the 1981-1985 level). By regression analysis, we show that the decreased European aerosol loadings can warm the lower atmosphere and induce anomalous ascending motion in Europe, which potentially stimulates two anomalous Rossby wave trains in the upper troposphere travelling eastward across Eurasia. The teleconnection patterns project on NC by weakening the near-surface horizontal dispersion, which may be favorable to the increase in local ASI(E) and air pollution build-up. The suggested mechanism is further supported by the results from a set of large-ensemble simulations, showing that the European aerosol emission decline since the 1980s excites similar local heating and ascending motion and leads to increasing trends of 0.1-0.5 mu g m(-3) (38 year)(-1) in surface sulfate concentrations over most of NC. This proposed ‘West-to-East Aerosol-to-Aerosol’ teleconnection mechanism helps resolve opposite views on the impact of global versus local aerosol forcing on PM2.5 pollution weather in NC. The policy implication is that the sustained decline in European aerosol emissions in coming decades, in conjunction with unabated global and regional warming, could further exacerbate air pollution in NC, thus imposing stronger pressure to reduce local emission sources quicker and deeper.
BACKGROUND: Ground-level ozone is a major public health issue worldwide. An accurate assessment of ozone exposure is necessary. Modeling tools have been developed to tackle this issue in large areas. However, these models could present inaccuracies at the local scale. OBJECTIVES: The objective of this study was i) to assess whether O(3) concentrations estimated by transnational modeling at the kilometric scale (9 km(2)) could be improved, ii) to propose a potential correction of these downscaled ozone concentrations and iii) to evaluate the efficiency and applicability of such a correction. METHOD: The present work was carried out in three phases. First, the performance of a transnational modeling platform (PREV’EST) was assessed at 6 geographic points by comparison with data from 6 air quality monitoring stations. Performance indicators were used for this purpose (MBE (mean bias error), MAE (mean absolute error), RMSE (root mean square error), r (Pearson correlation coefficient), and target plots). Second, several corrections were developed using MARS (multivariate adaptive regression splines) and integrating different sets of variables (mean temperature, relative humidity, rainfall amount, wind speed, elevation, and date). Their performance was evaluated. Third, external validation of the corrections was conducted using the data from six additional air quality monitoring stations. RESULTS: The uncorrected PREV’EST model presented a lack of exactitude and precision. These concentrations did not reproduce the interday variability of the measurements, leading to a lack of temporal contrast in exposure data. For the best performance enhancement, the correction applied improved MBE, MAE, RMSE and r from 14.67, 19.23, 23.18 and 0.67 to 0.00, 8.00, 10.19 and 0.91, respectively. External validation confirmed the efficiency of the corrections at the regional scale. CONCLUSIONS: We propose a validated and efficient methodology integrating local environmental variables. The methodology is adaptable according to the context, needs and data available.
Air pollution is the fourth greatest overall risk factor for human health. Despite declining levels in Europe, air pollution still represents a major health and economic burden. We collected data from the Global Burden of Disease Study 2019 regarding overall, as well as ischemic heart disease (IHD), stroke, and tracheal, bronchus and lung cancer-specific disability adjusted life years (DALYs), years of life lost (YLL) and mortality attributable to air pollution for 43 European countries between 1990 and 2019. Concentrations of ambient particulate matter (aPM(2.5)), ozone, and household air pollution from solid fuels were obtained from State of Global Air 2020. We analysed changes in air pollution parameters, as well as DALYs, YLL, and mortality related to air pollution, also taking into account gross national income (GNI) and socio-demographic index (SDI). Using a novel calculation, aPM(2.5) ratio (PMR) change and DALY rate ratio (DARR) change were used to assess each country’s ability to decrease its aPM(2.5) pollution and DALYs to at least the extent of the European median decrease within the analysed period. Finally, we created a multiple regression model for reliably predicting YLL using aPM(2.5) and household air pollution. The average annual population-weighted aPM(2.5) exposure in Europe in 1990 was 20.8 μg/m(3) (95% confidence interval (CI) 18.3-23.2), while in 2019 it was 33.7% lower at 13.8 μg/m(3) (95% CI 12.0-15.6). There were in total 368 006 estimated deaths in Europe in 2019 attributable to air pollution, a 42.4% decrease compared to 639 052 in 1990. The majority (90.4%) of all deaths were associated with aPM(2.5). IHD was the primary cause of death making up 44.6% of all deaths attributable to air pollution. The age-standardised DALY rate and YLL rate attributable to air pollution were more than 60% lower in 2019 compared to 1990. There was a strong positive correlation (r=0.911) between YLL rate and aPM(2.5) pollution in 2019 in Europe. Our multiple regression model predicts that for 10% increase in aPM(2.5), YLL increases by 16.7%. Furthermore, 26 of 43 European countries had a positive DARR change. 31 of 43 European countries had a negative PMR change, thus not keeping up with the European median aPM(2.5) concentration decrease. When categorising countries by SDI and GNI, countries in the higher brackets had significantly lower aPM(2.5) concentration and DALY rate for IHD and stroke. Overall, air pollution levels, air pollution-related morbidity and mortality have decreased considerably in Europe in the last three decades. However, with the growing European population, air pollution remains an important public health and economic issue. Policies targeting air pollution reduction should continue to be strongly enforced to further reduce one of the greatest risk factors for human health.
Reduced telomere length (TL) has been associated with increased risk of age-related diseases, most likely through oxidative stress and inflammation, which have also been claimed as mechanisms underlying health effects of air pollution exposure. We aimed to verify whether exposure to particulate matter with diameter ≤10 µm (PM(10)) affects TL. We recruited 1792 participants with overweight/obesity in Milan (Italy) in 2010-2015 who completed a structured questionnaire on sociodemographic data, gave a blood sample for TL measurement by real-time PCR, and were assigned air pollution and meteorological data of their residential address. In multivariate mixed-effects linear models (with a random intercept on PCR plate), we observed a -0.51% change in TL (95% confidence interval (CI): -0.98; -0.05)) per 10 µg/m(3) increase in PM(10) at the day of recruitment. A similar decreasing trend in TL was observed up to two weeks before withdrawal, with percentage changes as low as -1.53% (average exposure of the 12 days before recruitment). Mean annual exposure to PM(10) was associated with -2.57% TL reduction (95%CI: -5.06; -0.08). By showing consistent associations between short- and long-term PM(10) exposures and reduced TL, our findings shed light on the potential mechanisms responsible for the excess of age-related diseases associated with air pollution exposure.
The scientific literature is scarce when referring to the influence of atmospheric pollutants on neurodegenerative diseases for present and future climate change scenarios. In this sense, this contribution evaluates the incidence of dementia (Alzheimer’s disease, AD, and dementia from unspecified cause, DU) occurring in Europe associated with the exposure to air pollution (essentially NO(2) and PM2.5) for the present climatic period (1991-2010) and for a future climate change scenario (RCP8.5, 2031-2050). The GEMM methodology has been applied to air pollution simulations using the chemistry/climate regional model WRF-Chem. Present population data were obtained from NASA’s Center for Socioeconomic Data and Applications (SEDAC); while future population projections for the year 2050 were derived from the United Nations (UN) Department of Economic and Social Affairs-Population Dynamics. Overall, the estimated incidence rate (cases per year) of AD and DU associated with exposure to air pollution over Europe is 498,000 [95% confidence interval (95% CI) 348,600-647,400] and 314,000 (95% CI 257,500-401,900), respectively. An important increase in the future incidence rate is projected (around 72% for both types of dementia) when considering the effect of climate change together with the foreseen changes in the future population, because of the expected aging of European population. The climate penalty (impacts of future climate change alone on air quality) has a limited effect on the total changes of dementia (approx. 0.5%), because the large increase in the incidence rate over southern Europe is offset by its decrease over more northern countries, favored by an improvement of air pollution caused by the projected enhancement of rainfall.
Wildland fires release substantial amounts of hazardous contaminants, contributing to a decline in air quality and leading to serious health risks. Thus, this study aimed to understand the contributions of the 2017 extreme wildland fires in Portugal on children health, compared to 2016 (with burned area, in accordance with the average of the previous 15 years). The impact of long-term exposure to PM(10) and NO(2) concentrations, associated with wildland fires, on postneonatal mortality, bronchitis prevalence, and bronchitis symptoms in asthmatic children was estimated, as well as the associated costs. The excess health burden in children attributable to exposure to PM(10) and NO(2), was calculated based on WHO HRAPIE relative risks. Fire emissions were obtained from the Fire INventory from NCAR (FINN). The results obtained indicate that the smoke from wildfires negatively impacts children’s lung function (PM(10) exposure: increase of 320 and 648 cases of bronchitis in 2016 and 2017; NO(2) exposure: 24 and 40 cases of bronchitis symptoms in asthmatic children in 2016 and 2017) and postneonatal mortality (PM(10) exposure: 0.2 and 0.4 deaths in 2016 and 2017). Associated costs were increased in 2017 by around 1 million € for all the evaluated health endpoints, compared to 2016.
Wildland fires, increasing in recent decades in the Mediterranean region due to climate change, can contribute to PM levels and composition. This study aimed to investigate biological effects of PM(2.5) (Ø < 2.5 µm) and PM(10) (Ø < 10 µm) collected near a fire occurred in the North-West of Italy in 2017 and in three other areas (urban and rural areas). Organic extracts were assessed for mutagenicity using Ames test (TA98 and TA100 strains), cell viability (WST-1 and LDH assays) and genotoxicity (Comet assay) with human bronchial cells (BEAS-2B) and estrogenic activity using a gene reporter assay (MELN cells). In all sites, high levels of PM(10) and PM(2.5) were measured during the fire suggesting that near and distant sites were influenced by fire pollutants. The PM(10) and PM(2.5) extracts induced a significant mutagenicity in all sites and the mutagenic effect was increased with respect to historical data. All extracts induced a slight increase of the estrogenic activity but a possible antagonistic activity of PM samples collected near fire was observed. No cytotoxicity or DNA damage was detected. Results confirm that fires could be relevant for human health, since they can worsen the air quality increasing PM concentrations, mutagenic and estrogenic effects.
Uncontrolled wildfires have a substantial impact on the environment, the economy and local populations. According to the European Forest Fire Information System (EFFIS), between 2000 and 2013 wildfires burned up to 740 000 ha of land annually in the south of Europe, Portugal being the country with the highest percentage of burned area per square kilometre. However, there is still a lack of knowledge regarding the impacts of the wildfire-related pollutants on the mortality of the country’s population. All wildfires occurring during the fire season (June-July-AugustSeptember) from 2001 and 2016 were identified, and those with a burned area above 1000 ha (large fires) were considered for the study. During the studied period (2001-2016), more than 2 million ha of forest (929 766 ha from June to September alone) were burned in mainland Portugal. Although large fires only represent less than 1% of the number of total fires, in terms of burned area their contribution is 46% (53% from June to September). To assess the spatial impact of the wildfires, burned areas in each region of Portugal were correlated with PM10 concentrations measured at nearby background air quality monitoring stations. Associations between PM10 and all-cause (excluding injuries, poisoning and external causes) and cause-specific mortality (circulatory and respiratory) were studied for the affected populations using Poisson regression models. A significant positive correlation between burned area and PM10 was found in some regions of Portugal, as well as a significant association between PM10 concentrations and mortality, these being apparently related to large wildfires in some of the regions. The north, centre and inland of Portugal are the most affected areas. The high temperatures and long episodes of drought expected in the future will increase the probabilities of extreme events and therefore the occurrence of wildfires.
INTRODUCTION: Fine particulate matter with an aerodynamic diameter < 2.5 μm (PM(2.5)) in the ambient air has been associated with increased blood pressure (BP) levels and new-onset hypertension. However, the association of BP with a sudden upsurge of PM(2.5) in extreme conditions has not yet been demonstrated. AIM: To evaluate the association between PM(2.5) pollutants the week before, during, and the week after the 2021 wildfires in Athens (Greece) and home BP measurements. METHODS: Home BP measurements were performed, and the readings were transferred to the doctor's office through a telemonitoring system on the patient's Smartphone application. Data from a calibrated, sensor-based PM(2.5) monitoring network assessed PM(2.5) exposure. RESULTS: PM(2.5) pollutants demonstrated a gradual surge while the particle concentration was not different in the selected air pollution measurement stations. A total of 20 consecutive patients with controlled hypertension, mean age 61 ± 9 years, were included in the analysis. For one unit in μg/m(3) increase of PM(2.5) particle concentration, an average of 2.1 mmHg increment in systolic BP was observed after adjustment for confounders (P = 0.023). CONCLUSIONS: Our findings raise the hypothesis that short-term exposure to raised PM(2.5) concentrations in the air appears to be associated with increases in systolic home BP." Telemonitoring systems of home BP recordings may provide important information for the clinical management of hypertensive patients, at least in conditions of major environmental disturbances, such as wildfires.
Wildfires are a complex environmental problem worldwide. The ashes produced during the fire bear metals and PAHs with high toxicity and environmental persistence. These are mobilized into downhill waterbodies, where they can impair water quality and human health. In this context, the present study aimed at assessing the toxicity of mimicked wildfire runoff to human skin cells, providing a first view on the human health hazardous potential of such matrices. Human keratinocytes (HaCaT) were exposed to aqueous extracts of ashes (AEA) prepared from ash deposited in the soil after wildfires burned a pine or a eucalypt forest stand. Cytotoxicity (MTT assay) and changes in cell cycle dynamics (flow cytometry) were assessed. Cell viability decreased with increasing concentrations of AEA, regardless of the ash source, the extracts preparation method (filtered or unfiltered to address the dissolved or the total fractions of contaminants, respectively) or the exposure period (24 and 48 h). The cells growth was also negatively affected by the tested AEA matrices, as evidenced by a deceleration of the progress through the cell cycle, namely from phase G0/G1 to G2. The cytotoxicity of AEA could be related to particulate and dissolved metal content, but the particles themselves may directly affect the cell membrane. Eucalypt ash was apparently more cytotoxic than pine ash due to differential ash metal burden and mobility to the water phase. The deceleration of the cell cycle can be explained by the attempt of cells to repair metal-induced DNA damage, while if this checkpoint and repair pathways are not well coordinated by metal interference, genomic instability may occur. Globally, our results trigger public health concerns since the burnt areas frequently stand in slopes of watershed that serve as recreation sites and sources of drinking water, thus promoting human exposure to wildfire-driven contamination.
Heat and cold temperatures associated with exposure to poor air quality lead to increased mortality. Using a generalized linear model with Poisson regression for overdispersion, this study quantifies the natural-caused mortality burden attributable to heat/cold temperatures and PM(10) and O(3) air pollutants in Rome and Milan, the two most populated Italian cities. We calculate local-specific mortality relative risks (RRs) for the period 2004-2015 considering the overall population and the most vulnerable age category (≥85 years). Combining a regional climate model with a chemistry-transport model under future climate and air pollution scenarios (RCP2.6 and RCP8.5), we then project mortality to 2050. Results show that for historical mortality the burden is much larger for cold than for warm temperatures. RR peaks during wintertime in Milan and summertime in Rome, highlighting the relevance of accounting for the effects of air pollution besides that of climate, in particular PM(10) for Milan and O(3) for Rome. Overall, Milan reports higher RRs while, in both cities, the elderly appear more susceptible to heat/cold and air pollution events than the average population. Two counterbalancing effects shape mortality in the future: an increase associated with higher and more frequent warmer daily temperatures – especially in the case of climate inaction – and a decrease due to declining cold-mortality burden. The outcomes highlight the urgent need to adopt more stringent and integrated climate and air quality policies to reduce the temperature and air pollution combined effects on health.
Urban Built Environments (UBE) are increasingly prone to SLow-Onset Disasters (SLODs) such as air pollution and heatwaves. The effectiveness of sustainable risk-mitigation solutions for the exposed individuals’ health should be defined by considering the effective scenarios in which emergency conditions can appear. Combining environmental (including climatic) conditions and exposed users’ presence and behaviors is a paramount task to support decision-makers in risk assessment. A clear definition of input scenarios and related critical conditions to be analyzed is needed, especially while applying simulation-based approaches. This work provides a methodology to fill this gap, based on hazard and exposure peaks identification. Quick and remote data-collection is adopted to speed up the process and promote the method application by low-trained specialists. Results firstly trace critical conditions by overlapping air pollution and heatwaves occurrence in the UBE. Exposure peaks (identified by remote analyses on the intended use of UBEs) are then merged to retrieve critical conditions due to the presence of the individuals over time and UBE spaces. The application to a significant case study (UBE in Milan, Italy) demonstrates the approach capabilities to identify key input scenarios for future human behavior simulation activities from a user-centered approach.
INTRODUCTION: Climate change is one of the 21st century’s biggest public health issues and health care contributes up to 10% of the emissions of greenhouse gases in developed countries. About 15 million laparoscopic procedures are performed annually worldwide and single-use medical equipment is increasingly used during these procedures. Little is known about costs and environmental footprint of this change in practice. METHODS: We employed Life Cycle Assessment method to evaluate and compare the environmental impacts of single-use, reusable, and mixed trocar systems used for laparoscopic cholecystectomies at three hospitals in southern Sweden. The environmental impacts were calculated using the IMPACT 2002+ method and a functional unit of 500 procedures. Monte Carlo simulations were used to estimate differences between trocar systems. Data are presented as medians and 2.5th to 97.5th percentiles. Financial costs were calculated using Life Cycle Costing. RESULTS: The single-use system had a 182% higher impact on resources than the reusable system [difference: 5160 MJ primary (4400-5770)]. The single-use system had a 379% higher impact on climate change than the reusable system [difference: 446 kg CO2eq (413-483)]. The single-use system had an 83% higher impact than the reusable system on ecosystem quality [difference: 79 PDF*m2*yr (24-112)] and a 240% higher impact on human health [difference: 2.4×10-4 DALY/person/yr (2.2×10-4-2.6×10-4)]. The mixed and single-use systems had a similar environmental impact. Differences between single-use and reusable trocars with regard to resource use and ecosystem quality were found to be sensitive to lower filling of machines in the sterilization process. For ecosystem quality the difference between the two were further sensitive to a 50% decrease in number of reuses, and to using a fossil fuel intensive electricity mix. Differences regarding effects on climate change and human health were robust in the sensitivity analyses. The reusable and mixed trocar systems were approximately half as expensive as the single-use systems (17360 € and 18560 € versus 37600 €, respectively). CONCLUSION: In the Swedish healthcare system the reusable trocar system offers a robust opportunity to reduce both the environmental impact and financial costs for laparoscopic surgery.
BACKGROUND: Unhealthy diets, the rise of non-communicable diseases, and the declining health of the planet are highly intertwined, where food production and consumption are major drivers of increases in greenhouse gas emissions, substantial land use, and adverse health such as cancer and mortality. To assess the potential co-benefits from shifting to more sustainable diets, we aimed to investigate the associations of dietary greenhouse gas emissions and land use with all-cause and cause-specific mortality and cancer incidence rates. METHODS: Using data from 443 991 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) study, a multicentre prospective cohort, we estimated associations between dietary contributions to greenhouse gas emissions and land use and all-cause and cause-specific mortality and incident cancers using Cox proportional hazards regression models. The main exposures were modelled as quartiles. Co-benefits, encompassing the potential effects of alternative diets on all-cause mortality and cancer and potential reductions in greenhouse gas emissions and land use, were estimated with counterfactual attributable fraction intervention models, simulating potential effects of dietary shifts based on the EAT-Lancet reference diet. FINDINGS: In the pooled analysis, there was an association between levels of dietary greenhouse gas emissions and all-cause mortality (adjusted hazard ratio [HR] 1·13 [95% CI 1·10-1·16]) and between land use and all-cause mortality (1·18 [1·15-1·21]) when comparing the fourth quartile to the first quartile. Similar associations were observed for cause-specific mortality. Associations were also observed between all-cause cancer incidence rates and greenhouse gas emissions, when comparing the fourth quartile to the first quartile (adjusted HR 1·11 [95% CI 1·09-1·14]) and between all-cause cancer incidence rates and land use (1·13 [1·10-1·15]); however, estimates differed by cancer type. Through counterfactual attributable fraction modelling of shifts in levels of adherence to the EAT-Lancet diet, we estimated that up to 19-63% of deaths and up to 10-39% of cancers could be prevented, in a 20-year risk period, by different levels of adherence to the EAT-Lancet reference diet. Additionally, switching from lower adherence to the EAT-Lancet reference diet to higher adherence could potentially reduce food-associated greenhouse gas emissions up to 50% and land use up to 62%. INTERPRETATION: Our results indicate that shifts towards universally sustainable diets could lead to co-benefits, such as minimising diet-related greenhouse gas emissions and land use, reducing the environmental footprint, aiding in climate change mitigation, and improving population health. FUNDING: European Commission (DG-SANCO), the International Agency for Research on Cancer (IARC), MRC Early Career Fellowship (MR/M501669/1).
In the current era of globalization, a clean environment remains a crucial factor for the health of the population. Thus, improving air quality is a major focus of environmental policies, as it affects all aspects of nature, including humans. For these reasons, it is appropriate to take into account the health risks posed by greenhouse gas (GHG) emissions released into the atmosphere. With regard to global GHG emissions, there are concerns about the loss of protection of the ozone layer and it is very likely that climate change can be expected, which multiplies the environmental threat and has potentially serious global consequences. In this regard, it is important to pay increased attention to emissions that enter the atmosphere, which include countless toxic substances. The aim of this study was to examine the associations between selected GHG emissions and the health of the European Union (EU) population represented by disability-adjusted life years (DALYs). This aim was achieved using several analytical procedures (descriptive analysis, correlation analysis, cluster analysis, and panel regression analysis), which included five environmental variables (carbon dioxide (CO(2)), methane (CH(4)) in CO(2) equivalent, nitrous oxide (N(2)O) in CO(2) equivalent, hydrofluorocarbons (HFC) in CO(2) equivalent, sulfur hexafluoride (SF(6)) in CO(2) equivalent) and one health variable (DALYs). An emphasis was placed on the use of quantitative methods. The results showed that CO(2) emissions have a dominant position among selected GHG emissions. The revealed positive link between CO(2) and DALYs indicated that a decrease in CO(2) may be associated with a decrease in DALYs, but it is also true that this cannot be done without reducing emissions of other combustion products. In terms of CO(2), the least positive scores were observed in Luxembourg and Estonia. Germany had the lowest score of DALYs, representing the most positive health outcome in the EU. In terms of total GHG emissions, Ireland and Luxembourg were considered to be less positive countries compared to the other analyzed countries. Countries should focus on reducing GHG emissions in general, but from a health point of view, reducing CO(2) emissions seems to be the most beneficial.
BACKGROUND: Evidence of the role of interactions between air pollution and pollen exposure in subjects with allergic asthma is limited and need further exploration to promote adequate preventive measures. The objective of this study was to assess effects of exposure to ambient air pollution and birch pollen on exacerbation of respiratory symptoms in subjects with asthma and allergy to birch. METHODS: Thirty-seven subjects from two Swedish cities (Gothenburg and Umeå) with large variation in exposure to both birch-pollen and air pollutants, participated in the study. All subjects had confirmed allergy to birch and self-reported physician-diagnosed asthma. The subjects recorded respiratory symptoms such as rhinitis or eye irritation, dry cough, dyspnoea, the use of any asthma or allergy medication and peak respiratory flow (PEF), daily for five consecutive weeks during two separate pollen seasons and a control season without pollen. Nitrogen oxides (NO(x)), ozone (O(3)), particulate matter (PM(2.5)), birch pollen counts, and meteorological data were obtained from an urban background monitoring stations in the study city centres. The data were analysed using linear mixed effects models. RESULTS: During pollen seasons all symptoms and medication use were higher, and PEF was reduced in the subjects. In regression analysis, exposure to pollen at lags 0 to 2 days, and lags 0 to 6 days was associated with increased ORs of symptoms and decreased RRs for PEF. Pollen and air pollution interacted in some cases; during low pollen exposure, there were no associations between air pollution and symptoms, but during high pollen exposure, O(3) concentrations were associated with increased OR of rhinitis or eye irritation, and PM(2.5) concentrations were associated with increased ORs of rhinitis or eye irritation, dyspnea and increased use of allergy medication. CONCLUSIONS: Pollen and air pollutants interacted to increase the effect of air pollution on respiratory symptoms in allergic asthma. Implementing the results from this study, advisories for individuals with allergic asthma could be improved, minimizing the morbidities associated with the condition.
BACKGROUND: Common ragweed has been spreading as a neophyte in Europe. Elevated CO(2) levels, a hallmark of global climate change, have been shown to increase ragweed pollen production, but their effects on pollen allergenicity remain to be elucidated. METHODS: Ragweed was grown in climate-controlled chambers under normal (380 ppm, control) or elevated (700 ppm, based on RCP4.5 scenario) CO(2) levels. Aqueous pollen extracts (RWE) from control- or CO(2) -pollen were administered in vivo in a mouse model for allergic disease (daily for 3-11 days, n = 5) and employed in human in vitro systems of nasal epithelial cells (HNECs), monocyte-derived dendritic cells (DCs), and HNEC-DC co-cultures. Additionally, adjuvant factors and metabolites in control- and CO(2) -RWE were investigated using ELISA and untargeted metabolomics. RESULTS: In vivo, CO(2) -RWE induced stronger allergic lung inflammation compared to control-RWE, as indicated by lung inflammatory cell infiltrate and mediators, mucus hypersecretion, and serum total IgE. In vitro, HNECs stimulated with RWE increased indistinctively the production of pro-inflammatory cytokines (IL-8, IL-1β, and IL-6). In contrast, supernatants from CO(2) -RWE-stimulated HNECs, compared to control-RWE-stimulated HNECS, significantly increased TNF and decreased IL-10 production in DCs. Comparable results were obtained by stimulating DCs directly with RWEs. The metabolome analysis revealed differential expression of secondary plant metabolites in control- vs CO(2) -RWE. Mixes of these metabolites elicited similar responses in DCs as compared to respective RWEs. CONCLUSION: Our results indicate that elevated ambient CO(2) levels elicit a stronger RWE-induced allergic response in vivo and in vitro and that RWE increased allergenicity depends on the interplay of multiple metabolites.
There is limited knowledge about how crises are framed on different social media platforms specifically in a non-Western cultural context. This study compares how extreme environmental crises-Hurricane Maria and haze-were framed on Twitter and Weibo. Through word-cloud, co-occurrence, and thematic analyses with Hurricane Maria-related tweets, this study identified two major frames of this crisis: a disaster frame and a political frame. Similarly, by analyzing haze-related posts on Sina Weibo, two major frames emerged: an environmental frame and a health frame. Both crises were largely framed as environmental issues rather than health risks or crises. Such framing helps shape the existence of Hurricane Maria and haze as legitimate facts. The findings also reveal that cultural variances, eg, power distance, collectivist-individualist culture, and uncertainty avoidance, impact crisis framing. This study indicates the importance of designing culture-fit messages and incorporating social media strategies in crisis communication while developing emergency management plans and adds knowledge to the limited literature on social-mediated crisis communication in different cultural contexts. Such knowledge will provide theoretical and practical implications for crisis scholars, emergency management practitioners, and policymakers.
This study examines point and non-point sources of air pollution and particulate matter and their associated socioeconomic and health impacts in South Asian countries, primarily India, China, and Pakistan. The legislative frameworks, policy gaps, and targeted solutions are also scrutinized. The major cities in these countries have surpassed the permissible limits defined by WHO for sulfur dioxide, carbon monoxide, particulate matter, and nitrogen dioxide. As a result, they are facing widespread health problems, disabilities, and causalities at extreme events. Populations in these countries are comparatively more prone to air pollution effects because they spend more time in the open air, increasing their likelihood of exposure to air pollutants. The elevated level of air pollutants and their long-term exposure increases the susceptibility to several chronic/acute diseases, i.e., obstructive pulmonary diseases, acute respiratory distress, chronic bronchitis, and emphysema. More in-depth spatial-temporal air pollution monitoring studies in China, India, and Pakistan are recommended. The study findings suggest that policymakers at the local, national, and regional levels should devise targeted policies by considering all the relevant parameters, including the country’s economic status, local meteorological conditions, industrial interests, public lifestyle, and national literacy rate. This approach will also help design and implement more efficient policies which are less likely to fail when brought into practice.
The consequences of climate change and global warming have become irrefutable. Scientists are working to change the alarming scenario awaiting humanity in the future. On the other hand, they have proved that the increasing trend of many life-threatening diseases, such as cancer, are caused by global warming. In this research, data collected from national and international databases were analysed and compared. The aim of this research is presenting the relationship between increasing temperature anomalies and rising cancer trend. As a result of the study, it is determined that the rising global surface temperature and increasing cancer rates are directly related. In the study, data related to Northern Cyprus were also examined. According to the findings; poor waste management and uncontrolled carbon dioxide emissions are responsible for raising cancer rates and cardiovascular diseases in North Cyprus.
BACKGROUND: Evidence from the scientific literature shows a significant variation in greenhouse gas (GHG) emissions from the diet, according to the type of food consumed. We aim to analyze the relationship between the daily dietary GHG emissions according to red meat, fruit and vegetables consumption and their relationship with risk of total mortality, and incident risk of chronic diseases. METHODS: We examined data on the EPIC-Spain prospective study, with a sample of 40 621 participants. Dietary GHG emission values were calculated for 57 food items of the EPIC study using mean emission data from a systematic review of 369 published studies. RESULTS: Dietary GHG emissions (kgCO2eq/day), per 2000 kcal, were 4.7 times higher in those with high red-meat consumption (>140 g/day) than those with low consumption (<70 g/day). The average dietary GHG emissions were similar in males and females, but it was significantly higher in youngest people and in those individuals with lower educational level, as well as for northern EPIC centers of Spain. We found a significant association with the risk of mortality comparing the third vs. the first tertile of dietary GHG emissions [hazard ratio (HR) 1.095; 95% confidence interval (CI) 1.007-1.19; trend test 0.037]. Risk of coronary heart disease (HR 1.26; 95% CI 1.08-1.48; trend test 0.003) and risk of type 2 diabetes (HR 1.24; 95% CI 1.11-1.38; trend test 0.002) showed significant association as well. CONCLUSIONS: Decreasing red-meat consumption would lead to reduce GHG emissions from diet and would reduce risk of mortality, coronary heart disease and type 2 diabetes.
The environmental pollution caused by climate change and global warming pose significant risks to health. This raises the question how environmental disturbances can affect health expenditures. Based on this, this study examines the asymmetric effect of environmental quality on health expenditures in Türkiye using the non-linear ARDL (NARDL) model for the 1975-2019 period. In addition to environmental quality, natural resources, economic growth, and trade openness variables are also included in the health expenditure model. The findings support the existence of an asymmetric cointegration relationship between the series. The findings also indicate that positive environmental pollution shocks affect health expenditures positively in the long run, while negative environmental pollution shocks do not have a statistically significant effect on health expenditures. Positive and negative natural resource shocks affect health expenditures negatively in the long run. Despite the effect of positive economic growth shocks on health expenditures is positive but statistically insignificant, the effect of negative economic growth shocks is positive and significant. Besides, positive trade openness shocks have a negative effect on health expenditures and negative trade openness shocks have a positive effect. The findings prove that the steps to be taken to protect the environment in the current period will increase the effectiveness of health expenditures in the future. This situation has a guiding feature for policy-makers in terms of policy decisions.
Air pollution and extreme heat have been responsible for more than a million deaths in China every year, especially in densely urbanized regions. While previous studies intensively evaluated air pollution episodes and extreme heat events, a limited number of studies comprehensively assessed atmospheric hot-and-polluted-episodes (HPE) – an episode with simultaneously high levels of air pollution and temperature – which have potential adverse synergic impacts on human health. This study focused on the Pearl River Delta (PRD) region of China due to its high temperature in summer and poor air quality throughout a year. We employed geostatistical downscaling to model meteorology at a spatial resolution of 1 km, and applied a machine learning algorithm (XGBoost) to estimate a high-resolution (1 km) daily concentration of particulate matter with an aerodynamic diameter ≤2.5 μm (PM(2.5)) and ozone (O(3)) for June to October over 20 years (2000-2019). Our results indicate an increasing trend (∼50%) in the frequency of HPE occurrence in the first decade (2000-2010). Conversely, the annual frequency of HPE occurrence reduced (16.7%), but its intensity increased during the second decade (2010-2019). The northern cities in the PRD region had higher levels of PM(2.5) and O(3) than their southern counterparts. During HPEs, regional daily PM(2.5) exceeded the World Health Organization (WHO) and Chinese guideline levels by 75% and 25%, respectively, while the O(3) exceeded the WHO O(3) standard by up to 69%. Overall, 567,063 (95% confidence interval (CI): 510,357-623,770) and 52,231 (95%CI: 26,116-78,346) excessive deaths were respectively attributable to exposure to PM(2.5) and O(3) in the PRD region. Our findings imply the necessity and urgency to formulate co-benefit policies to mitigate the region’s air pollution and heat problems.
INTRODUCTION: There is a large body of epidemiological evidence showing significantly increased mortality risks from air pollution and temperature. However, findings on the modification of the association between air pollution and mortality by temperature are mixed. METHODS: We used a varying coefficient distributed lag model to assess the complex interplay between air temperature and PM(2.5) on daily mortality in Guangzhou City from 2013 to 2020, with the aim of establishing the PM(2.5)-mortality association at different temperatures and exploring synergetic mortality risks from PM(2.5) and temperature on vulnerable populations. RESULTS: We observed near-linear concentration-response associations between PM(2.5) and mortality across different temperature levels. Each 10 μg/m³ increase of PM(2.5) in low, medium, and high temperature strata was associated with increments of 0.73% [95% confidence interval (CI): 0.38%, 1.09%], 0.12% (95% CI: -0.27%, 0.52%), and 0.46% (95% CI: 0.11%, 0.81%) in non-accidental mortality, with a statistically significant difference between low and medium temperatures (P=0.02). There were significant modification effects of PM(2.5) by low temperature for cardiovascular mortality and among individuals 75 years or older. CONCLUSIONS: Low temperatures may exacerbate physiological responses to short-term PM(2.5) exposure in Guangzhou, China.
Background: Preterm birth contributes to the morbidity and mortality of newborns and infants. Recent studies have shown that maternal exposure to particulate matter and extreme temperatures results in immune dysfunction, which can induce preterm birth. This study aimed to evaluate the association between fine particulate matter (PM(2.5)) exposure, temperature, and preterm birth in Seoul, Republic of Korea. Methods: We used 2010-2016 birth data from Seoul, obtained from the Korea National Statistical Office Microdata. PM(2.5) concentration data from Seoul were generated through the Community Multiscale Air Quality (CMAQ) model. Seoul temperature data were collected from the Korea Meteorological Administration (KMA). The exposure period of PM(2.5) and temperature were divided into the first (TR1), second (TR2), and third (TR3) trimesters of pregnancy. The mean PM(2.5) concentration was used in units of ×10 µg/m(3) and the mean temperature was divided into four categories based on quartiles. Logistic regression analyses were performed to evaluate the association between PM(2.5) exposure and preterm birth, as well as the combined effects of PM(2.5) exposure and temperature on preterm birth. Result: In a model that includes three trimesters of PM(2.5) and temperature data as exposures, which assumes an interaction between PM(2.5) and temperature in each trimester, the risk of preterm birth was positively associated with TR1 PM(2.5) exposure among pregnant women exposed to relatively low mean temperatures (<3.4 °C) during TR1 (OR 1.134, 95% CI 1.061-1.213, p < 0.001). Conclusions: When we assumed the interaction between PM(2.5) exposure and temperature exposure, PM(2.5) exposure during TR1 increased the risk of preterm birth among pregnant women exposed to low temperatures during TR1. Pregnant women should be aware of the risk associated with combined exposure to particulate matter and low temperatures during TR1 to prevent preterm birth.
This study aims to quantitatively identify the economic value of the comprehensive improvement of environmental degradations caused by climate change. The research method applied to that is the choice experiment. Fine particulate matter, algae bloom, and heat waves were selected as individual attributes constituting environmental problems. It was found that the willingness to pay could not be induced for any level of improvement in algal bloom. It was concluded that if heat waves improved to the medium level where the number of heat-related illnesses and estimated deaths decreased by 50% compared to the current level, there would be a loss in value by USD 13.33. The value of improving environmental problems is USD 7.69 per household per year, and the improvement of fine particulate matter was the highest value attributed by consumers. This study is significant in that it comprehensively evaluates severe environmental problems, reflects their priorities and importance, and assesses the value for each level. It provides important foundational data for establishing effective budget input strategies to maximize consumer benefits and aids in the preparation of effective policies by establishing more detailed goals to achieve net-zero carbon emissions and the Sustainable Development Goals.
Mounting studies have associated asthma with environmental and climatic factors, but their interaction during pregnancy on childhood asthma are unclear. This study aims to investigate the interaction of in utero air pollution and environmental temperature exposure on childhood asthma, to identify key timing windows for exposure. A retrospective cohort study with 2,598 pre-schoolers was conducted during 2011-2012 in Changsha, China. Maternal exposure to three critical ambient air pollutants (PM10, SO2 and NO2, as proxies of industrial and vehicular air pollution) and temperature (T), was assessed for the 40 gestational weeks, three trimesters of gestation, and entire pregnancy by an inverse distance weighted (IDW) method. Logistic regression analysis was used to examine the association of childhood asthma with air pollution and temperature exposure. Our results showed that pre-schooler’s asthma was significantly associated with SO2 and NO2 exposure in utero, ORs = 1.46 (95% CI: 1.12-1.89) and 1.67 (95% CI: 1.24-2.26) by inter quartile range (IQR) increase of their exposure respectively. Significant risk was observed for exposure of SO2 and NO2 particularly during the 1st and 2nd trimesters and their specific gestational weeks. Pre-schooler’s asthma was related with high temperature expo-sure during 1st trimester, OR = 2.33 (95% CI: 1.11-4.90) by IQR increase of T exposure. Low T and high T respectively increased the asthma risk of NO2 exposure in the 1st and 3rd trimester. Boys were more susceptible to the temperature-pollution interaction on asthma development. Our study indicates that low and high tem-perature respectively during early and late pregnancy significantly increased the impact of air pollution exposure in utero on pre-schooler’s asthma.
BACKGROUND: Though inconsistent, acute effects of ambient nitrogen oxides on cardiovascular mortality have been reported. Whereas, interactive roles of temperature on their relationships and joint effects of different indicators of nitrogen oxides were less studied. This study aimed to extrapolate the independent roles of ambient nitrogen oxides and temperature interactions on cardiovascular mortality. METHODS: Data on mortality, air pollutants, and meteorological factors in Shenzhen from 2013 to 2019 were collected. Three indicators including nitric oxide (NO), nitrogen dioxide (NO(2)), and nitrogen oxides (NO(X)) were studied. Adjusted generalized additive models (GAMs) were applied to analyse their associations with cardiovascular mortality in different groups. RESULTS: The average daily concentrations of NO, NO(2), and NO(X) were 11.7 μg/m^3, 30.7 μg/m^3, and 53.2 μg/m3, respectively. Significant associations were shown with each indicator. Cumulative effects of nitrogen oxides were more obvious than distributed lag effects. Males, population under 65 years old, and population with stroke-related condition were more susceptible to nitrogen oxides. Adverse effects of nitrogen oxides were more significant at low temperature. Impacts of NO(2) on cardiovascular mortality, and NO on stroke mortality were the most robust in the multi-pollutant models, whereas variations were shown in the other relationships. CONCLUSIONS: Low levels of nitrogen oxides showed acute and adverse impacts and the interactive roles of temperature on cardiovascular mortality. Cumulative effects were most significant and joint effects of nitrogen oxides required more attention. Population under 65 years old and population with stroke-related health condition were susceptible, especially days at lower temperature.
BACKGROUND: The concentration of air pollutants is affected by changes in climatic conditions. Air temperature is a main factor affecting the concentration of air pollutants. This study sought to examine the relationship between air temperature, air pollutants, and their interactions in elderly patients with coronary heart disease (CHD) in Liaoning Province, China. METHODS: The population data primarily comprised data on daily hospitalizations due to CHD between January 1, 2015 and December 31, 2019 at the Shengjing Hospital of China Medical University. A total of 25,461 patients, who were permanent residents of Liaoning Province, were included in the study. The meteorological data included data on the average daily temperature and air pollutant data of the average daily concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) over the hospitalization period. A multiple linear regression model was constructed to analyze the relationship between meteorological factors and CHD. RESULTS: The interaction between air temperature and SO2, NO2, and O3 concentrations was related to the number of daily CHD-related hospitalizations in elderly patients aged ≥65 years (P=0.0023); however, this correlation was lower than that of the interaction between SO2 and NO2 concentrations (P=0.0026). Additionally, age exerted a greater effect than air temperature and air pollutants. CONCLUSIONS: The incidence of CHD in elderly patients aged ≥65 years was found to be related to the interaction of SO2 and NO2 concentrations, and the interaction of air temperature and the concentrations of SO2, NO2, and O3.
No study has ever investigated how ambient temperature and PM(2.5) mediate rotavirus infection (RvI) in children. We used insurance claims data from Taiwan in 2006-2012 to evaluate the RvI characteristics in children aged ≤ 9. The RvI incidence rates were higher in colder months, reaching the highest in March (117.0/100 days), and then declining to the lowest in July (29.2/100 days). The age-sex-specific average incident cases were all higher in boys than in girls. Stratified analysis by temperature (<20, 20-24, and ≥25 °C) and PM(2.5) (<17.5, 17.5-31.4, 31.5-41.9, and ≥42.0 μg/m^3) showed that the highest incidence was 16.4/100 days at average temperatures of <20 °C and PM(2.5) of 31.5–41.9 μg/m^3, with Poisson regression analysis estimating an adjusted relative risk (aRR) of 1.26 (95% confidence interval (CI) = 1.11-1.43), compared to the incidence at the reference condition (<20 °C and PM2.5 < 17.5 μg/m^3). As the temperature increased, the incident RvI cases reduced to 4.84 cases/100 days (aRR = 0.40, 95% CI = 0.35-0.45) when it was >25 °C with PM(2.5) < 17.5 μg/m^3, or to 9.84/100 days (aRR = 0.81, 95% CI = 0.77-0.93) when it was >25 °C with PM2.5 > 42 μg/m^3). The seasonal RvI is associated with frequent indoor personal contact among children in the cold months. The association with PM(2.5) could be an alternative assessment due to temperature inversion.
Worldwide, over half of the global population is living in urban areas. The metropolitan areas are highly populated and environmentally non-green regions on the planet. In green space regions, plants, grass, and green vegetation prevent soil erosion, absorb air pollutants, provide fresh and clean air, and minimize the burden of diseases. Presently, the entire world is facing a turmoil situation due to the COVID-19 pandemic. This study investigates the effect of the green space environment on air pollutants particulate matter PM2.5, PM10, carbon monoxide (CO), ozone (O(3)), incidence and mortality of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) in environmentally highly green and less-green countries. We randomly selected 17 countries based on the Environmental Performance Index (EPI) data. The 60% of the EPI score is based on seven categories: biodiversity and habitat, ecosystem, fisheries, climate change, pollution emissions, agriculture, and water resources. However, 40% of the score is based on four categories: air quality, sanitation and drinking water, heavy metals, and waste management. The air pollutants and SARS-CoV-2 cases and deaths were recorded from 25 January 2020, to 11 July 2021. The air pollutants PM2.5, PM10, CO, and O(3) were recorded from the metrological websites, Air Quality Index-AQI, 2021. The COVID-19 daily cases and deaths were obtained from the World Health Organization. The result reveals that air pollutants mean values for PM2.5 110.73 ± 1.09 vs. 31.35 ± 0.29; PM10 80.43 ± 1.11 vs. 17.78 ± 0.15; CO 7.92 ± 0.14 vs. 2.35 ± 0.03 were significantly decreased (p < 0.0001) in environmentally highly green space countries compared to less-green countries. Moreover, SARS-CoV-2 cases 15,713.61 ± 702.42 vs. 3445.59 ± 108.09; and deaths 297.56 ± 11.27 vs. 72.54 ± 2.61 were also significantly decreased in highly green countries compared to less-green countries. The green environment positively impacts human wellbeing. The policymakers must implement policies to keep the living areas, surroundings, towns, and cities clean and green to minimize air pollution and combat the present pandemic of COVID-19.
Background: Existing evidence suggests that mumps epidemics, a global public health issue, are associated with meteorological factors and air pollutants at the population scale. However, the interaction effect of meteorological factors and air pollutants on mumps remains underexplored.Methods: Daily cases of mumps, meteorological factors, and air pollutants were collected in Ningxia, China, from 2015 to 2019. First, a distributed lag nonlinear model (DLNM) was employed to assess the confounding-adjusted relationship between meteorological factors, ambient air pollutants, and mumps incidences. According to the results of DLNM, stratification in both air pollutants and meteorological factors was adopted to further explore the interaction effect of particulate matter less than or equal to 2.5 mu m in aerodynamic diameter (PM2.5) and ground-level ozone (O-3) with temperature and relative humidity (RH).Results: We reported significant individual associations between mumps incidences and environmental factors, including temperature, relative humidity, PM2.5, and O-3. Evident multiplicate and additive interactions between meteorological factors and PM2.5 were found with interaction relative risk (IRR) of 1.14 (95%CI: 1.01, 1.29) and relative excess risk due to interaction (RERI) of 0.17 (95%CI: 0.02, 0.32) for a moderate level of temperature at 12 degrees C, and IRR of 1.37 (95%CI: 1.14, 1.66), RERI of 0.36 (95%CI: 0.11, 0.60) for a high level of temperature at 20 degrees C, respectively. These results indicated that PM2.5 and temperature have a significant synergistic effect on the cases of mumps, while no interaction between relative humidity and PM2.5 is observed. Regarding O-3 and meteorological factors (temperature = 12 degrees C, 20 degrees C), IRR and RERI were 1.33 (95%CI: 1.17, 1.52) and 0.30 (95%CI: 0.16, 0.45), 1.91 (95%CI: 1.46, 2.49) and 0.69 (95%CI: 0.32, 1.07), respectively. And IRR of 1.17 (95%CI: 1.06, 1.29), RERI of 0.13 (95%CI: 0.04, 0.21) for a middle level of relative humidity at 48%.Conclusion: Our findings indicated that meteorological factors and air pollutants imposed a significantly lagged and nonlinear effect on the incidence of mumps. The interaction between low temperature and O-3 showed antagonistic effects, while temperature (medium and high) with PM2.5 and O-3 presented synergistic effects. For relative humidity, the interaction with O-3 is synergistic. These results provide scientific evidence to relevant health authorities for the precise disease control and prevention of mumps in arid and semi-arid areas.
Big data can be used to correlate diseases and climatic factors. The prevalence of influenza (flu) virus, accounting for a large proportion of respiratory infections, suggests that the effect of climate variables according to seasonal dynamics of influenza virus infections should be investigated. Here, trends in flu virus detection were analyzed using data from 9,010 tests performed between January 2012 and December 2018 at Dankook University Hospital, Cheonan, Korea. We compared the detection of the flu virus in Cheonan area and its association with climate change. The flu virus detection rate was 9.9% (894/9,010), and the detection rate was higher for flu virus A (FLUAV; 6.9%) than for flu virus B (FLUBV; 3.0%). Both FLUAV and FLUBV infections are considered an epidemic each year. We identified 43.1% (n = 385) and 35.0% (n = 313) infections in children aged < 10 years and adults aged > 60 years, respectively. The combination of these age groups encompassed 78.1% (n = 698/894) of the total data. Flu virus infections correlated with air temperature, relative humidity, vapor pressure, atmospheric pressure, particulate matter, and wind chill temperature (P < 0.001). However, the daily temperature range did not significantly correlate with the flu detection results. This is the first study to identify the relationship between long-term flu virus infection with temperature in the temperate region of Cheonan.
BACKGROUND: Sentinel physician surveillance in communities has played an important role in detecting early signs of epidemics. The traditional approach is to let the primary care physician voluntarily and actively report diseases to the health department on a weekly basis. However, this is labor-intensive work, and the spatio-temporal resolution of the surveillance data is not precise at all. In this study, we built up a clinic-based enhanced sentinel surveillance system named “Sentinel plus” which was designed for sentinel clinics and community hospitals to monitor 23 kinds of syndromic groups in Taipei City, Taiwan. The definitions of those syndromic groups were based on ICD-10 diagnoses from physicians. METHODS: Daily ICD-10 counts of two syndromic groups including ILI and EV-like syndromes in Taipei City were extracted from Sentinel plus. A negative binomial regression model was used to couple with lag structure functions to examine the short-term association between ICD counts and meteorological variables. After fitting the negative binomial regression model, residuals were further rescaled to Pearson residuals. We then monitored these daily standardized Pearson residuals for any aberrations from July 2018 to October 2019. RESULTS: The results showed that daily average temperature was significantly negatively associated with numbers of ILI syndromes. The ozone and PM2.5 concentrations were significantly positively associated with ILI syndromes. In addition, daily minimum temperature, and the ozone and PM2.5 concentrations were significantly negatively associated with the EV-like syndromes. The aberrational signals detected from clinics for ILI and EV-like syndromes were earlier than the epidemic period based on outpatient surveillance defined by the Taiwan CDC. CONCLUSIONS: This system not only provides warning signals to the local health department for managing the risks but also reminds medical practitioners to be vigilant toward susceptible patients. The near real-time surveillance can help decision makers evaluate their policy on a timely basis.
The bacteria (including pathogenic bacteria) attached to road deposited sediments (RDS) may interrelate with the microbe in the atmosphere, soil and water through resuspension and wash-off, and is of great significance to human and ecological health. However, the characteristics of bacterial communities with different time scale on RDS were unknown to dates. Climate change prolonged the dry days between rain events in many areas, making the varied trend of bacterial communities might be more significant in short term. This study revealed the characteristics of bacterial communities on RDS in urban and suburban areas through seasonal and daily scale. The correlations between other factors (land use, particle size, and chemical components) and the bacterial communities were also analyzed. It was found that the season showed a higher association with the bacterial community diversity than land use and particle size in urban areas. The bacterial community diversity increased substantially throughout the short-term study period (41 days) and the variation of dominant bacteria could be fitted by quadratic function in suburbs. In addition, urbanization notably increased the bacterial community diversity, while the potential pathogenic bacteria were more abundant in the suburban areas, coarse RDS (>75 μm), and in spring. The chemical components on RDS showed special correlations with the relative abundance of dominant bacteria. The research findings would fill the knowledge gap on RDS bacterial communities and be helpful for the future research on the assembly process of bacterial communities.
This study proposed a novel ensemble analysis strategy to improve hand, foot and mouth disease (HFMD) prediction by integrating environmental data. The approach began by establishing a vector autoregressive model (VAR). Then, a dynamic Bayesian networks (DBN) model was used for variable selection of environmental factors. Finally, a VAR model with constraints (CVAR) was established for predicting the incidence of HFMD in Chengdu city from 2011 to 2017. DBN showed that temperature was related to HFMD at lags 1 and 2. Humidity, wind speed, sunshine, PM10, SO2 and NO2 were related to HFMD at lag 2. Compared with the autoregressive integrated moving average model with external variables (ARIMAX), the CVAR model had a higher coefficient of determination (R2, average difference: + 2.11%; t = 6.2051, P = 0.0003 < 0.05), a lower root mean-squared error (-24.88%; t = -5.2898, P = 0.0007 < 0.05) and a lower mean absolute percentage error (-16.69%; t = -4.3647, P = 0.0024 < 0.05). The accuracy of predicting the time-series shape was 88.16% for the CVAR model and 86.41% for ARIMAX. The CVAR model performed better in terms of variable selection, model interpretation and prediction. Therefore, it could be used by health authorities to identify potential HFMD outbreaks and develop disease control measures.
BACKGROUND: Although exposure to air pollution has been linked to many health issues, few studies have quantified the modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China. METHODS: The data of daily incidence of influenza and the relevant meteorological data and air pollution data in Ningbo from 2014 to 2017 were retrieved. Low, medium and high temperature layers were stratified by the daily mean temperature with 25th and 75th percentiles. The potential modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo was investigated through analyzing the effects of air pollutants stratified by temperature stratum using distributed lag non-linear model (DLNM). Stratified analysis by sex and age were also conducted. RESULTS: Overall, a 10 μg/m(3) increment of O(3), PM(2.5), PM(10) and NO(2) could increase the incidence risk of influenza with the cumulative relative risk of 1.028 (95% CI 1.007, 1.050), 1.061 (95% CI 1.004, 1.122), 1.043 (95% CI 1.003, 1.085), and 1.118 (95% CI 1.028, 1.216), respectively. Male and aged 7-17 years were more sensitive to air pollutants. Through the temperature stratification analysis, we found that temperature could modify the impacts of air pollution on daily incidence of influenza with high temperature exacerbating the impact of air pollutants. At high temperature layer, male and the groups aged 0-6 years and 18-64 years were more sensitive to air pollution. CONCLUSION: Temperature modified the relationship between air pollution and daily incidence of influenza and high temperature would exacerbate the effects of air pollutants in Ningbo.
Airborne bacteria have an important role in atmospheric processes and human health. However, there is still little information on the transmission and distribution of bacteria via the airborne route. To characterize the impact of foggy, haze, haze-fog (HF) and dust days on the concentration and viability of bacteria in atmospheric aerosols, size-segregated bioaerosol samples were collected in the Qingdao coastal region from March 2018 to February 2019. The total airborne microbes and viable/non-viable bacteria in the bioaerosol samples were measured using an epifluorescence microscope after staining with DAPI (4′, 6-diamidino-2-phenylindole) and a LIVE/DEAD® BacLight Bacterial Viability Kit. The average concentrations of total airborne microbes on haze and dust days were 6.75 × 10(5) and 1.03 × 10(6) cells/m(3), respectively, which increased by a factor of 1.3 and 2.5 (on average), respectively, relative to those on sunny days. The concentrations of non-viable bacteria on haze and dust days increased by a factor of 1.2 and 3.6 (on average), respectively, relative to those on sunny days. In contrast, the concentrations of viable bacteria on foggy and HF days were 7.13 × 10(3) and 5.74 × 10(3) cells/m(3), decreases of 38% and 50%, respectively, compared with those on sunny days. Foggy, haze, dust and HF days had a significant effect on the trend of the seasonal variation in the total airborne microbes and non-viable bacteria. Bacterial viability was 20.8% on sunny days and significantly higher than the 14.1% on foggy days, 11.2% on haze days, 8.6% during the HF phenomenon and 6.1% on dust days, indicating that special weather is harmful to some bacterial species. Correlation analysis showed that the factors that influenced the bacterial concentration and viability depended on different weather conditions. The main influential factors were temperature, NO(2) and SO(2) concentrations on haze days, and temperature, particulate matter (PM(2.5)) and NO(2) concentrations on foggy days. The median size of particles containing viable bacteria was 1.94 μm on sunny days and decreased to 1.88 μm and 1.74 μm on foggy and haze days, respectively, but increased to 2.18 μm and 2.37 μm on dust and HF days, respectively.
Although dust storms have been associated with adverse health outcomes, studies on the burden of dust storms on deaths are limited. As global warming has induced significant climate changes in recent decades, which have accelerated desertification worldwide, it is necessary to evaluate the burden of dust storm-induced premature mortality using a critical measure of disease burden, such as the years of life lost (YLL). The YLL attributable to dust storms have not been examined to date. This study investigated the association between Asian dust storms (ADS) and the YLL in Seoul, South Korea, during 2002-2013. We conducted a time-series study using a generalized additive model assuming a Gaussian distribution and applied a distributed lag model with a maximum lag of 5 days to investigate the delayed and cumulative effects of ADS on the YLL. We also conducted stratified analyses using the cause of death (respiratory and cardiovascular diseases) and sociodemographic status (sex, age, education level, occupation, and marital status). During the study period, 108 ADS events occurred, and the average daily YLL was 1511 years due to non-accidental causes. The cumulative ADS exposure over the 6-day lag period was associated with a significant increase of 104.7 (95% CI, 31.0-178.5 years) and 34.4 years (4.0-64.7 years) in the YLL due to non-accidental causes and cardiovascular mortality, respectively. Sociodemographic analyses revealed associations between ADS exposure and the YLL in males, both <65 and ≥65 years old, those with middle-level education, and the unemployed, unmarried, and widowed (26.5-83.8 years). This study provides new evidence suggesting that exposure to dust storms significantly increases the YLL. Our findings suggest that dust storms are a critical environmental risk affecting premature mortality. These results could contribute to the establishment of public health policies aimed at managing dust storm exposure and reducing premature deaths.
Ultra-fine dust refers to particulate matter from external sources, and modernization contributes toward increasing the presence of ultra-fine dust. Young children are particularly vulnerable to the ill effects of ultra-fine dust. Educational buildings, where young children spend the longest duration after their houses, are typically difficult to retrofit. Consequently, they are often used for a long time in the same state as they were when first completed. The buildings deteriorate due to long-term use, particularly because the openings are opened and closed frequently by occupants. Hence, architectural retrofits were performed during vacation, and the effects were evaluated. The evaluation factors include the temperature, relative humidity, and presence of ultra-fine dust. It was confirmed that the temperature and humidity inside the room decreased after the retrofit, while the airtightness performance was strengthened, thereby reducing the I/O ratio. To evaluate the sustainability of architectural remodeling with regard to not only the indoor air environment but also the enhancement of airtightness and insulation performance through the retrofit, a representative scenario was selected with reference to the Intergovernmental Panel on Climate Change’s Future Climate Report. Although it was found that improving both the main entrance and the outdoor window was appropriate, replacing only the outdoor window was the adjudged the optimal retrofit scenario in consideration of the recovery of the investment cost.
Biomass burning and dust storm have significant impacts on air pollution, aerosol properties and potential human health. In order to investigate the influences of them on the chemical component and sources of aerosols, PM2.5 are collected in spring and summer in Beijing. There are two special periods in the whole campaign. (1) Event I, from 16 to 18 April. Air quality is extremely poor during this period mainly affected by biomass burning. (2) Event II, from 4 to 5 May, the biggest dust storm happened on 4 May. In addition, we choose a relative clean period as (3) Event III, from 24 to 29 July, with the lowest PM2.5 levels (16-31 mu g m(-3)) in the whole campaign. Contributions of NO3, SO42-, and NH4+ to PM2.5 in Event I are 22.1%, 11.3%, and 8.3%, respectively, and decreased dramatically to 2.4%, 5.4%, and 0.9% in Event II, suggesting secondary aerosols are more significant in haze period. Both ratios of phytane & pristane and PAHs to OC in Event I and II are comparable, indicating contribution of local primary organic aerosols from fossil fuel combustions to PM2.5 are not significant differences between polluted and dust period. In contrast, ratio of levoglucosan to OC is much higher in Event I and ratio of trehalose to OC is much higher in Event II, suggesting the contribution of regional primary organic aerosols from biomass burning to PM2.5 is important during polluted period, while contribution of regional primary organic aerosols from dust to PM2.5 is significant in dust storm. Based on the organic markers, this work also estimates the source apportionment of PM2.5. Dust and biomass burning are the main contributors in polluted period, while vehicle and cooking are the main contributors in clean period.
OBJECTIVES: In April 2000, a series of wildfires occurred simultaneously in five adjacent small cities located on the eastern coast of Korea. These wildfires burned approximately 23,794 hectares of forestland over several days. We investigated the effects of prenatal exposure to the by-products generated by wildfire disasters on birth weight. METHODS: Birth weight data were obtained for 1999-2001 from the birth registration database of the Korean National Statistical Office and matched with the zip code and exposed/unexposed pregnancy week for days of the wildfires. Generalized linear models were then used to assess the associations between birth weight and exposure to wildfires after adjusting for fetal sex, gestational age, parity, maternal age, maternal education, paternal education, and average exposed atmospheric temperature. RESULTS: Compared with unexposed pregnancies before and after the wildfires, mean birth weight decreased by 41.4 g (95% confidence interval [CI], -72.4 to -10.4) after wildfire exposure during the first trimester, 23.2 g (95% CI, -59.3 to 13.0) for exposure during the second trimester, and 27.0 g (95% CI, -63.8 to 9.8) during the third trimester. In the adjusted model for infants exposed in utero during any trimester, the mean birth weight decreased by 32.5 g (95% CI, -53.2 to -11.7). CONCLUSIONS: We observed a 1% reduction in birth weight after wildfire exposure. Thus, exposure to by-products generated during a wildfire disaster during pregnancy may slow fetal growth and cause developmental delays.
BACKGROUND: Studies on the association between smoke haze (hereafter ‘haze’) and adverse health effects have increased in recent years due to extreme weather conditions and the increased occurrence of vegetation fires. The possible adverse health effects on under-five children (U5Y) is especially worrying due to their vulnerable condition. Despite continuous repetition of serious haze occurrence in Southeast Asia, epidemiological studies in this region remained scarce. Furthermore, no study had examined the association accounting for three important aspects (time lag, duration and intensity) concurrently. OBJECTIVE: This study aimed to examine the association between haze and U5Y mortality in Malaysia, considering time lag, duration and intensity of exposure. METHODS: We performed a time-stratified case-crossover study using a generalized additive model to examine the U5Y mortality related to haze in 12 districts in Malaysia, spanning from 2014 to 2016. A ‘haze day’ was characterized by intensity [based on concentrations of particulate matter (PM)] and duration (continuity of haze occurrence, up to 3 days). RESULTS: We observed the highest but non-significant odds ratios (ORs) of U5Y mortality at lag 4 of Intensity-3. Lag patterns revealed the possibility of higher acuteness at prolonged and intensified haze. Stratifying the districts by the 95th-percentile of PM distribution, the ‘low’ category demonstrated marginal positive association at Intensity-2 Duration-3 [OR: 1.210 (95% confidence interval: 1.000, 1.464)]. CONCLUSIONS: We found a null association between haze and U5Y mortality. The different lag patterns of the association observed over different duration and intensity suggest consideration of these aspects in future studies.
Interactions between climate change and anthropogenic activities result in increasing numbers of open fires, which have been shown to harm maternal health. However, few studies have examined the association between open fire and pregnancy loss. We conduct a self-comparison case-control study including 24,876 mothers from South Asia, the region with the heaviest pregnancy-loss burden in the world. Exposure is assessed using a chemical transport model as the concentrations of fire-sourced PM(2.5) (i.e., fire PM(2.5)). The adjusted odds ratio (OR) of pregnancy loss for a 1-μg/m(3) increment in averaged concentration of fire PM(2.5) during pregnancy is estimated as 1.051 (95% confidence intervals [CI]: 1.035, 1.067). Because fire PM(2.5) is more strongly linked with pregnancy loss than non-fire PM(2.5) (OR: 1.014; 95% CI: 1.011, 1.016), it contributes to a non-neglectable fraction (13%) of PM(2.5)-associated pregnancy loss. Here, we show maternal health is threaten by gestational exposure to fire smoke in South Asia.
Wildfires are increasing and cause health effects. The immediate and ongoing health impacts of prolonged wildfire smoke exposure in severe asthma are unknown. This longitudinal study examined the experiences and health impacts of prolonged wildfire (bushfire) smoke exposure in adults with severe asthma during the 2019/2020 Australian bushfire period. Participants from Eastern/Southern Australia who had previously enrolled in an asthma registry completed a questionnaire survey regarding symptoms, asthma attacks, quality of life and smoke exposure mitigation during the bushfires and in the months following exposure. Daily individualized exposure to bushfire particulate matter (PM(2.5)) was estimated by geolocation and validated modelling. Respondents (n = 240) had a median age of 63 years, 60% were female and 92% had severe asthma. They experienced prolonged intense PM(2.5) exposure (mean PM(2.5) 32.5 μg/m(3) on 55 bushfire days). Most (83%) of the participants experienced symptoms during the bushfire period, including: breathlessness (57%); wheeze/whistling chest (53%); and cough (50%). A total of 44% required oral corticosteroid treatment for an asthma attack and 65% reported reduced capacity to participate in usual activities. About half of the participants received information/advice regarding asthma management (45%) and smoke exposure minimization strategies (52%). Most of the participants stayed indoors (88%) and kept the windows/doors shut when inside (93%), but this did not clearly mitigate the symptoms. Following the bushfire period, 65% of the participants reported persistent asthma symptoms. Monoclonal antibody use for asthma was associated with a reduced risk of persistent symptoms. Intense and prolonged PM(2.5) exposure during the 2019/2020 bushfires was associated with acute and persistent symptoms among people with severe asthma. There are opportunities to improve the exposure mitigation strategies and communicate these to people with severe asthma.
Objective: Adults born either extremely preterm (EP, <28 weeks gestation) or extremely low birthweight (ELBW, <1000 g birthweight) have more obstructive airflow than controls of normal birthweight (>2499 g). We compared self-reported adverse respiratory health outcomes in young adults born EP/ELBW with controls following smoke exposure from the 2019/2020 wildfires in the Australian state of Victoria, and explored if any effects were mediated by airway obstruction, reflected in the forced expiratory volume in 1 second (FEV1). Methods: EP/ELBW participants were derived from all survivors born in the state of Victoria in 1991–92. Contemporaneous controls of normal birthweight (>2499 g) were recruited in the newborn period and matched for sociodemographic variables. Both groups had been assessed at intervals through childhood and into adulthood. Those who participated in the most recent follow-up assessment at 25 years of age, when FEV1 had been measured, were sent a survey when they were approximately 28 years of age asking about respiratory health related outcomes (respiratory symptoms, health services usage, medication uptake) following wildfire smoke exposure over the southern hemisphere summer of 2019–20. Results: A total of 296 participants (166 EP/ELBW; 130 controls) were sent the survey; 44% of the EP/ELBW group and 47% of the control group responded. Compared with controls, EP/ELBW respondents reported more overall respiratory problems (30%vs 20%) and specific respiratory symptoms (breathlessness, wheezing, cough and chest tightness) following wildfire smoke exposure, as well as higher health services usage (e.g. local health clinic, hospital emergency department) and medication uptake for respiratory-related problems. Higher FEV1 values were associated with lower odds of most self-reported respiratory symptoms; adjusting for FEV1 attenuated the differences between EP/ELW and control groups. Conclusion: Survivors born EP/ELBW may be at an increased risk of adverse respiratory health outcomes following wildfire smoke exposure in early adulthood, in part related to worse expiratory airflows.
INTRODUCTION: Numerous studies have reported the modification of particulate matters (PMs) on the association between cold temperature and health. However, it remains uncertain whether the modification effect may vary by size of PMs, especially in Shandong Province, China where the disease burdens associated with cold temperature and PMs are both substantial. This study aimed to examine various interactive effects of cold exposure and ambient PMs with diameters ≤1/2.5 μm (PM1 and PM2.5) on premature deaths in Shandong Province, China. METHODS: In the 2013-2018 cold seasons, data on daily mortality, PM1 and PM2.5, and weather conditions were collected from the 1822 sub-districts of Shandong Province. A time-stratified case-crossover study design was performed to quantify the cumulative association between ambient cold and mortality over lag 0-12 days, with a linear interactive term between temperature and PM1 and PM2.5 additionally added into the model. RESULTS: The mortality risk increased with temperature decline, with the cumulative OR of extreme cold (-16.9°C, the 1st percentile of temperature range) being 1.83 (95% CI: 1.66, 2.02), compared with the minimum mortality temperature. The cold-related mortality risk was 2.20 (95%CI: 1.83, 2.64) and 2.24 (95%CI: 1.78, 2.81) on high PM1 and PM2.5 days, which dropped to 1.60 (95%CI: 1.39, 1.84) and 1.60 (95%CI: 1.37, 1.88) on low PM1 and PM2.5 days. PM1 showed greater modification effect for per unit concentration increase than PM2.5. For example, for each 10?g/m3 increase in PM1 and PM2.5, the mortality risk associated with extreme cold temperature increased by 7.6% (95% CI: 1.3%, 14.2%) and 2.6% (95% CI: -0.7%, 5.9%), respectively. DISCUSSION: The increment of smaller PMs’ modification effect varied by population subgroups, which was particularly strong in the elderly aged over 75 years and individuals with middle school education and below. Specific health promotion strategies should be developed towards the greater modification effect of smaller PMs on cold effect.
Anxiety and depression are severe public health problems worldwide. The effects of ozone exposure on anxious and depressive symptoms remain largely unknown, especially in China. We evaluated the associations between ozone exposure and depression and anxiety among middle-aged and older adults across China. A multi-center community-based repeated measurement study among middle-aged and older adults was conducted from 2017 to 2018 in 11 provinces in China. The status of depression and anxiety was measured using Patient Health Questionnaire-9 (PHQ-9) and the generalized anxiety disorder seven-item (GAD-7) scale at the cut-off point of five, respectively. Concentrations of multiple ozone metrics were collected from real-time monitoring stations. The multilevel logistic regression model with random intercept was used to evaluate the effects of ambient ozone on anxiety and depression over different exposure windows. After adjusting for potential confounders, a 10 mu g /m(3) increase in the three months moving average of ozone was associated with the risk of anxiety [odds ratio (OR) = 1.25; 95% confidence interval (CI): 1.15; 1.37] and depression (OR = 1.17; 95% CI: 1.08; 1.27). A significantly positive modification effect of temperature on associations between ozone and anxiety was also found, while there is no interaction for depression. Exposure-response curves showed that there may be a threshold for the effect of ozone exposure on anxiety and depression over the three months moving average concentrations, with similar patterns observed at different temperature levels. People over 65 years old were at significantly higher risks of ozone-associated depression, while anxiety was more strongly associated with ozone in hypertensive patients. Our study supports the theory that anxiety and depression is associated with mid-term ozone exposure in China, and temperatures significantly enhanced their associations. These findings may have significant implications for promoting prevention activities regarding mental disorders and approaches in reducing the disease burden by simultaneously controlling air pollution and mitigating climate change.
WHAT IS ALREADY KNOWN ABOUT THIS TOPIC? Ozone (O(3)) is a weather-driven photochemical ambient pollutant, and its harm to human health may be affected by meteorological factors such as temperature. However, there is conflicting evidence regarding whether temperature can modify the effects of ozone on health. WHAT IS ADDED BY THIS REPORT? Short-term exposure to O(3) in the Beijing Municipality, Tianjin Municipality, Hebei Province, and surrounding areas was associated with an increased risk of human mortality and that association was positive modified by relatively higher (>75th 24 h-average temperature) or extreme cold temperature (<10th 24 h-average temperature). Under extreme temperatures (>90th 24 h-average temperature) modification, the associations were further increased. Cardiopulmonary diseases, as vulnerable diseases of air pollution, their mortality risks associated with O(3) were markedly strengthened by uncomfortable temperatures. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE? This study suggests that policymakers should pay attention to the synergistic effect between ozone and heat or extreme cold on human health, as well as provide evidence for establishing an integrated early-warning system to protect the public against both uncomfortable temperature and air pollution.
Heatwaves (HWs) paired with higher ozone (O-3) concentration at the surface level pose a serious threat to human health. Their combined modulation of synoptic patterns and urbanization remains unclear. Using 5 years of summertime temperature and O-3 concentration observation in Beijing, this study explored potential drivers of compound HWs and O-3 pollution events and their public health effects. Three favorable synoptic weather patterns were identified to dominate the compound HWs and O-3 pollution events. These weather patterns contributing to enhance those conditions are characterized by sinking air motion, low boundary layer height, and high temperatures. Under the synergy of HWs and O-3 pollution, the mortality risk from all non-accidental causes increased by approximately 12.31 % (95 % confidence interval: 4.66 %, 20.81 %). Urbanization caused a higher risk of HWs and O-3 in urban areas than at rural stations. Particularly, due to O(3 )depletion caused by NO titration at traffic and urban stations, the health risks related to O(3 )pollution in different regions are characterized as follows: suburban stations > urban stations > rural stations > traffic stations. In general, favorable synoptic patterns and urbanization enhanced the health risk of these compound events in Beijing by 33.09 % and 18.95 %, respectively. Our findings provide robust evidence and implications for forecasting compound HWs and O-3 pollution events and their health risks in Beijing or in other urban areas all over the world that have high concentrations of O-3 and high-density populations.
The 1.5 °C pathways initially promoted by the challenges presented by climate change could bring substantial air quality-related benefits. However, since there is a lack of comprehensive assessment on emissions of air pollutants, meteorology, air quality, and heatwave occurrences under different climate goals, how significant the clean air cobenefits compared with the direct climate-related impact is uncertain. In this study, we assess the cobenefits of 1.5 °C pathways for air quality in China by linking multiple shared socioeconomic pathways, ensembling simulations of regional climate-air quality dynamic downscaling and an air pollution and climate-related health assessment model, and compare different kinds of benefits: the health benefits from direct slowing climate (reduced heatwaves) versus the health cobenefits from air quality improvement (the improved air quality from reduced air pollutants versus meteorological changes). The benefit of reduced air pollution emissions associated with sustainable development under 1.5 °C pathways dominated the overall impact, which could avoid 1 589 000 PM(2.5)-related and 526 000 O(3)-related deaths in 2050. Correspondingly, the impact of changed meteorology on air quality would avoid additional 8000 PM(2.5)-related deaths in 2050 under 1.5 °C pathways yet would lead to 22 000 O(3)-related deaths. Also, the heatwave-related deaths could be avoided by 7000. The substantial anthropogenic emission reduction cobenefits of 1.5 °C pathways in improving air quality significantly exceed the direct climate (heatwave-related) benefits and completely offset the impact of meteorological changes’ impact on air pollution under climate change.
A multitude of epidemiological studies have demonstrated that both ambient temperatures and air pollution are closely related to health outcomes. However, whether temperature has modification effects on the association between ozone and health outcomes is still debated. In this study, three parallel time-series Poisson generalized additive models (GAMs) were used to examine the effects of modifying ambient temperatures on the association between ozone and mortality (including non-accidental, respiratory, and cardiovascular mortality) in Chengdu, China, from 2014 to 2016. The results confirmed that the ambient high temperatures strongly amplified the adverse effects of ozone on human mortality; specifically, the ozone effects were most pronounced at > 28 °C. Without temperature stratification conditions, a 10-μg/m(3) increase in the maximum 8-h average ozone (O(3-8hmax)) level at lag01 was associated with increases of 0.40% (95% confidence interval [CI] 0.15%, 0.65%), 0.61% (95% CI 0.27%, 0.95%), and 0.69% (95% CI 0.34%, 1.04%) in non-accidental, respiratory, and cardiovascular mortality, respectively. On days during which the temperature exceeded 28 °C, a 10-μg/m(3) increase in O(3-8hmax) led to increases of 2.22% (95% CI 1.21%, 3.23%), 2.67% (95% CI 0.57%, 4.76%), and 4.13% (95% CI 2.34%, 5.92%) in non-accidental, respiratory, and cardiovascular mortality, respectively. Our findings validated that high temperature could further aggravate the health risks of O(3-8hmax); thus, mitigating ozone exposure will be brought into the limelight especially under the context of changing climate.
Numerous epidemiological studies have reported that ozone (O(3)) and temperature are independently associated with health outcomes, but modification of the effects of O(3) on health outcomes by temperature, and vice versa, has not been fully described. This study aimed to investigate effect modification by temperature on the association between O(3) and emergency ambulance dispatches (EADs) in Japan. Data on daily air pollutants, ambient temperature, and EADs were obtained from eight Japanese cities from 2007 to 2015. A distributed lag non-linear model combined with Poisson regression was performed with temperature as a confounding factor and effect modifier to estimate the effects of O(3) on EADs at low (<25th percentile), moderate (25th-75th percentile), and high (>75th percentile) temperature for each city. The estimates obtained from each city were pooled by random-effects meta-analysis. When temperature was entered as a confounder, the estimated effects of O(3) on EADs for all acute, cardiovascular, and respiratory illnesses were largest at lag 0 (current-day lag). Therefore, this lag was used to further estimate the effects of O(3) on EADs in each temperature category. The estimated effects of O(3) on EADs for all acute, cardiovascular, and respiratory illnesses in all eight Japanese cities increased with increasing temperature. Specifically, a 10 ppb increase in O(3) was associated with 0.80 % (95 % CI: 0.25 to 1.35), 0.19 % (95 % CI: -0.85 to 1.25), and 1.14 % (95 % CI: -0.01 to 2.31) increases in the risk of EADs for all acute, cardiovascular, and respiratory illnesses, respectively, when city-specific daily temperature exceeded the 75th percentile. Our findings suggest that the association between O(3) and EADs for all acute, cardiovascular, and respiratory illnesses is the highest during high temperature. Finding of this study can be used to develop potential mitigation measures against O(3) exposure in high temperature environment to reduce its associated adverse health effects.
BACKGROUND: Numerous studies have confirmed the association of ambient temperature and air pollution with a higher risk of morbidities, yet few have addressed their effect on the ocular system. The purpose of this study was to assess the association between temperature, air pollution, and emergency room visits for conjunctivitis. METHODS: In this case-crossover study, the records of all emergency room visits to Soroka University Medical Center (SUMC) from 2009 to 2014 were reviewed for patients with conjunctivitis. Daily exposure to fine and coarse particulate matter and temperature were determined by a hybrid model involving satellite sensors. Mean relative humidity was obtained from the Ministry of Environmental Protection meteorological monitoring station located in Beer-Sheva. RESULTS: Six hundred one patients were diagnosed with conjunctivitis in the SUMC emergency room. We discovered a positive association between temperature increments and incidence of conjunctivitis. The strongest effect was found during summer and autumn, with an immediate (lag0) incidence increase of 8.1% for each 1 °C increase in temperature (OR = 1.088, 95%CI: 1.046-1.132) between 24 and 28 °C in the summer and 7.2% for each 1 °C increase in temperature (OR = 1.072, 95%CI: 1.036-1.108) between 13 and 23 °C in the autumn. There was no statistically significant association between fine and coarse particulate matter and conjunctivitis incidence. CONCLUSION: Temperature increases during summer and autumn are significantly associated with an increased risk of conjunctivitis. Conjunctivitis is not associated with non-anthropogenic air pollution. These findings may help community clinics and hospital emergency rooms better predict conjunctivitis cases and will hopefully lead to improved prevention efforts that will lower the financial burden on both the individual and the public.
The Australian 2019/2020 bushfires were unprecedented in their extent and intensity, causing a catastrophic loss of habitat, human and animal life across eastern-Australia. We use a regional air quality model to assess the impact of the bushfires on particulate matter with a diameter less than 2.5 μm (PM(2.5)) concentrations and the associated health impact from short-term population exposure to bushfire PM(2.5). The mean population Air Quality Index (AQI) exposure between September and February in the fires and no fires simulations indicates an additional ∼437,000 people were exposed to “Poor” or worse AQI levels due to the fires. The AQ impact was concentrated in the cities of Sydney, Newcastle-Maitland, Canberra-Queanbeyan and Melbourne. Between October and February 171 (95% CI: 66-291) deaths were brought forward due to short-term exposure to bushfire PM(2.5). The health burden was largest in New South Wales (NSW) (109 (95% CI: 41-176) deaths brought forward), Queensland (15 (95% CI: 5-24)), and Victoria (35 (95% CI: 13-56)). This represents 38%, 13% and 30% of the total deaths brought forward by short-term exposure to all PM(2.5). At a city-level 65 (95% CI: 24-105), 23 (95% CI: 9-38) and 9 (95% CI: 4-14) deaths were brought forward from short-term exposure to bushfire PM(2.5), accounting for 36%, 20%, and 64% of the total deaths brought forward from all PM(2.5.) Thus, the bushfires caused substantial AQ and health impacts across eastern-Australia. Climate change is projected to increase bushfire risk, therefore future fire management policies should consider this.
This study investigated the contributions of particulate matter (PM) from various emission sources during the dry season, which resulted from frequent fires occurring in degraded forests and peatlands in Indonesia. Samples of fine (PM2.5) and coarse (PM2.5-10) particles collected during the dry season in Riau, Indonesia were analyzed to determine the mass concentrations of metallic trace elements, ionic compound, black carbon (BC), and organic carbon (OC). The average concentrations of PM2.5 and PM2.5-10 at Riau, Indonesia were 63.85 +/- 3.22 mu g m(-3) and 27.72 +/- 2.40 mu g m(-3), respectively. The positive matrix factorization (PMF) model was adopted to identify possible PM sources and their contributions to the ambient PM level. The PMF results identified six major PM2.5 sources, including biomass burning (BB) (28.7%), secondary aerosols (SA) (26.9%), vehicle exhaust (VE) (12.8%), industrial emissions (IE) (12.3%), soil dust (SD) (11.9%), and sea salt (SS) (7.5%). Moreover, there were five primary PM2.5-10 sources, including VE (28.6%) and BB (24%), followed by IE (19.9%), SD (17.2%), and SA (15.3%). A conditional probability function (CPF) analysis revealed that the southeast sector dominated among source direction-dependent contributions. The noncarcinogenic health risks for both adults and children resulting from exposure to PM2.5 were mainly contributed by Co, Ni, and Mn, and carcinogenic risks were caused by the toxic metals Cr and Co. Both noncarcinogenic and carcinogenic health risks resulting from cumulative multielement exposure for both adults and children exceeded acceptable levels. Clearly, more attention should be devoted to reducing the noncarcinogenic and carcinogenic health risks caused by particulate-bound toxic elements through inhalation exposure.
Over the past 30 years, forest fire has been one of main ecological issues in Indonesia. Human-caused deforestation was accused to be the reason behind this matter, apart from the drastic changing in global climate. Palangkaraya is one of the citiesaffected by haze of the forest fire in 2015; considered to be the worst year of forest fire with the value of PM10 was above the normal threshold. As the impact to the community wellbeing, the prevalence of acute respiratory infection (ARI) in October 2015was increasing especially in children. The research aimed to analyse the spatial distribution of children with ARI in October 2015 at Palangkaraya City. Data onARI number were collected from Primary Care under Public Health Office of Palangkaraya City. The PM 10 value was collected bythe Environmental Agency of Palangkaraya City. The spatial analyse method was conducted using theAverage Nearest Neighbour (ANN) method. The result shows that the number of ANN ratio is 0.761801. It means that the distribution pattern of children with ARI in Central Kalimantan during the forest fire in October 2015 was in cluster form.
BACKGROUND: Climate change has resulted in an increase in ambient temperatures during the summer months as well as an increase in risk of associated air pollution and of potentially disastrous bushfires throughout much of the world. The increasingly frequent combination of elevated summer temperatures and bushfires may be associated with acute increases in risks of cardiovascular events, but this relationship remains unstudied. We evaluated the individual and cumulative impacts of daily fluctuations in temperature, fine particulate matter of less than 2.5 µm (PM(2.5)) pollution and presence of bushfires on incidence of acute coronary syndromes and Takotsubo syndrome. METHODS: From November 1, 2019, to February 28, 2020, all admissions with acute coronary syndromes or Takotsubo syndrome to South Australian tertiary public hospitals were evaluated. Univariate and combined associations were sought among each of 1) maximal daily temperature, 2) PM(2.5) concentrations, and 3) presence of active bushfires within 200 km of the hospitals concerned. RESULTS: A total of 504 patients with acute coronary syndromes and 35 with Takotsubo syndrome were studied. In isolation, increasing temperature was associated (r(s) = 0.26, P = .005) with increased incidence of acute coronary syndromes, while there were similar, but nonsignificant correlations for PM(2.5) and presence of bushfires. Combinations of all these risk factors were also associated with a doubling of risk of acute coronary syndromes. No significant associations were found for Takotsubo syndrome. CONCLUSION: The combination of high temperatures, presence of bushfires and associated elevation of atmospheric PM(2.5) concentrations represents a substantially increased risk for precipitation of acute coronary syndromes; this risk should be factored into health care planning including public education and acute hospital preparedness.
BACKGROUND: Air pollution including particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) increases the risk of acute myocardial infarction. However, whether short-term exposure to PM2.5 triggers the onset of myocardial infarction with nonobstructive coronary arteries, compared with myocardial infarction with coronary artery disease, has not been elucidated. This study aimed to estimate the association between short-term exposure to PM2.5 and admission for acute myocardial infarction, myocardial infarction with coronary artery disease, and myocardial infarction with nonobstructive coronary arteries. DESIGN: This was a time-stratified case-crossover study and multicenter validation study. METHODS: This study used a nationwide administrative database in Japan between April 2012-March 2016. Of 137,678 acute myocardial infarction cases, 123,633 myocardial infarction with coronary artery disease and 14,045 myocardial infarction with nonobstructive coronary arteries were identified by a validated algorithm combined with International Classification of Disease (10th revision), diagnostic, and procedure codes. Air pollutants and meteorological data were obtained from the monitoring station nearest to the admitting hospital. RESULTS: In spring (March-May), the short-term increase of 10 µg/m3 in PM2.5 2 days before admission was significantly associated with admission for acute myocardial infarction, myocardial infarction with nonobstructive coronary arteries, and myocardial infarction with coronary artery disease after adjustment for meteorological variables (odds ratio 1.060, 95% confidence interval 1.038-1.082; odds ratio 1.151, 1.079-1.227; odds ratio 1.049, 1.026-1.073, respectively), while the association was not significant in other variables. These associations were also observed after adjustment for other co-pollutants. The risk for myocardial infarction with nonobstructive coronary arteries (vs myocardial infarction with coronary artery disease) was associated with an even lower concentration of PM2.5 under the current environmental standards. CONCLUSIONS: This study showed the seasonal difference of acute myocardial infarction risk attributable to PM2.5 and the difference in the threshold of triggering the onset of acute myocardial infarction subtype.
BACKGROUND: Previous reports indicate an association between ambient temperature (Ta) and air pollution exposure during pregnancy and preterm birth (PTB). Nevertheless, information regarding the association between environmental factors and specific precursors of spontaneous preterm birth is lacking. We aimed to determine the association between Ta and air pollution during gestation and the precursors of spontaneous preterm parturition, i.e. preterm labor (PTL) and preterm prelabor rupture of membranes (PPROM). METHODS: From 2003 to 2013 there were 84,476 deliveries of singleton gestation that comprised the study cohort. Exposure data during pregnancy included daily measurements of temperature and particulate matter <2.5 μm and <10 μm, PM(2.5) and PM(10), respectively. Deliveries were grouped into PPROM, PTL and non-spontaneous preterm and term deliveries. Exposure effect was tested in windows of a week and two days prior to admission for delivery and adjusted to gestational age and socio-economic status. Poisson regression models were used for analyses. RESULTS: There is an association of environmental exposure with the precursors of spontaneous preterm parturition; PPROM was more sensitive to Ta fluctuations than PTL. This effect was modified by the ethnicity, Bedouin-Arabs were susceptible to elevated Ta, especially within the last day prior to admission with PPROM (Relative Risk (RR) =1.19 [95% CI, 1.03; 1.37]). Jews, on the other hand, were susceptible to ambient pollutants, two (RR=1.025 [1.010; 1.040]) and one (RR= 1.017 [1.002; 1.033]) days prior to spontaneous PTL with intact membranes resulting in preterm birth. CONCLUSION: High temperature is an independent risk factor for PPROM among Bedouin-Arabs; ambient pollution is an independent risk factor for spontaneous PTL resulting in preterm birth. Thus, the precursors of spontaneous preterm parturition differ in their association with environmental factors.
The differential effect of meteorological factors and air pollutants on pediatric epistaxis in younger and older children has not been evaluated. We evaluated the distribution of pediatric epistaxis cases between younger (0-5 years) and older children (6-18 years). Subsequently, we assessed and compared the effects of meteorological variables and the concentration of particulate matter measuring ≤ 10 μm in diameter (PM10) on hospital epistaxis presentation in younger and older children. This retrospective study included pediatric patients (n = 326) who presented with spontaneous epistaxis between January 2015 and August 2019. Meteorological conditions and PM10 concentration were the exposure variables, and data were obtained from Korea Meteorological Administration 75. The presence and cumulative number of epistaxis presentations per day were considered outcome variables. Air temperature, wind speed, sunshine duration, and PM10 concentration in younger children, and sunshine duration and air pressure in older children, significantly correlated with the presence of and cumulative number of epistaxis presentations per day. The PM10 concentration was not a significant factor in older children. Thus, meteorological factors and PM10 concentration may differentially affect epistaxis in younger (0-5-year-olds) and older (6-18-year-olds) children. Risk factors for pediatric epistaxis should be considered according to age.
BACKGROUND: Positive associations between ambient PM(2.5) and cardiorespiratory disease have been well demonstrated during the past decade. However, few studies have examined the adverse effects of PM(2.5) based on an entire population of a megalopolis. In addition, most studies in China have used averaged data, which results in variations between monitoring and personal exposure values, creating an inherent and unavoidable type of measurement error. METHODS: This study was conducted in Wuhan, a megacity in central China with about 10.9 million people. Daily hospital admission records, from October 2016 to December 2018, were obtained from the Wuhan Information center of Health and Family Planning, which administrates all hospitals in Wuhan. Daily air pollution concentrations and weather variables in Wuhan during the study period were collected. We developed a land use regression model (LUR) to assess individual PM(2.5) exposure. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate cardiorespiratory hospitalization risks associated with short-term exposure to PM(2.5). We also conducted stratification analyses by age, sex, and season. RESULTS: A total of 2,806,115 hospital admissions records were collected during the study period, from which we identified 332,090 cardiovascular disease admissions and 159,365 respiratory disease admissions. Short-term exposure to PM(2.5) was associated with an increased risk of a cardiorespiratory hospital admission. A 10 μg/m(3) increase in PM(2.5) (lag0-2 days) was associated with an increase in hospital admissions of 1.23% (95% CI 1.01-1.45%) and 1.95% (95% CI 1.63-2.27%) for cardiovascular and respiratory diseases, respectively. The elderly were at higher PM-induced risk. The associations appeared to be more evident in the cold season than in the warm season. CONCLUSIONS: This study contributes evidence of short-term effects of PM(2.5) on cardiorespiratory hospital admissions, which may be helpful for air pollution control and disease prevention in Wuhan.
Air Pollution is an emerging disaster and considered one of the biggest challenges of the world to effectively con-trol, mitigate and forecast due to abrupt variability, stochastic, and chaotic pattern of particulate matter (PM) in terms of time and space of the pollutants. Composition of ambient PM not only causes serious damage to public health but also emerging as a global hazard particularly for urban environment with negative impact on human health including morbidity. Mortality and ultimately towards unstable economy. In this study, hourly short-term trends of PM2.5 and air quality index (AQI) of Lahore city of Pakistan is monitored and mitigated by the design of fractional order Lorenz based physics informed hybrid computing paradigm SARFIMA-NARX for forecasting hourly pattern of next two days. The complex dynamics of earth system and its weather forecast are character-ized by combination of biological, physical, and chemical processes governed by the different laws of science that provides additional information for the climate variation in terms of physics inform intelligence. The perfor-mance index based on statistical indicator of RMSE confirmed the high accuracy and efficiency of designed model to predict the pattern. The early predictions based on computational intelligence paradigm may serve as a surveillance system to reduce the air pollution through cost-effectiveness planning by environmental monitor-ing agencies.(c) 2022 Elsevier Ltd. All rights reserved.
The rapid development of industrialization and urbanization has had a substantial impact on the increasing air pollution in many populated cities around the globe. Intensive research has shown that ambient aerosols, especially the fine particulate matter PM2.5, are highly correlated with human respiratory diseases. It is critical to analyze, forecast, and mitigate PM2.5 concentrations. One of the typical meteorological phenomena seducing PM2.5 concentrations to accumulate is temperature inversion which forms a warm-air cap to blockade the surface pollutants from dissipating. This paper analyzes the meteorological patterns which coincide with temperature inversion and proposes two machine learning classifiers for temperature inversion classification. A separate multivariate regression model is trained for the class with or without manifesting temperature inversion phenomena, in order to improve PM2.5 forecasting performance. We chose Puli township as the studied site, which is a basin city easily trapping PM2.5 concentrations. The experimental results with the dataset spanning from 1 January 2016 to 31 December 2019 show that the proposed temperature inversion classifiers exhibit satisfactory performance in F1-Score, and the regression models trained from the classified datasets can significantly improve the PM2.5 concentration forecast as compared to the model using a single dataset without considering the temperature inversion factor.
The impact of atmospheric concentration of particulate matter ≤10 μm in diameter (PM(10)) continues to attract research attention. This study aimed to evaluate the effects of meteorological factors, including PM(10) concentration, on epistaxis presentation in children and adults. We reviewed the data from 1557 days and 2273 cases of epistaxis between January 2015 and December 2019. Eligible patients were stratified by age into the children (age ≤17 years) and adult groups. The main outcome was the incidence and cumulative number of epistaxis presentations in hospital per day and month. Meteorological factors and PM(10) concentration data were obtained from the Korea Meteorological Administration. Several meteorological factors were associated with epistaxis presentation in hospital; however, these associations differed between children and adults. Only PM(10) concentration was consistently associated with daily epistaxis presentation in hospital among both children and adults. Additionally, PM(10) concentration was associated with the daily cumulative number of epistaxis presentations in hospital in children and adults. Furthermore, the monthly mean PM(10) concentration was significantly associated with the total number of epistaxis presentations in the corresponding month. PM(10) concentration should be regarded as an important environmental factor that may affect epistaxis in both children and adults.
OBJECTIVE: The associations between climate variables and diseases such as respiratory infections, influenza, pediatric seizure, and gastroenteritis have been long appreciated. Infection is the main reason for acute otitis media (AOM) incidence. However, few previous studies explored the correlation between climatic parameters and AOM infections. The most important meteorological factors, temperature, relative humidity, and fine particulate matter (PM2.5), were included in this study. We studied the relationship between these meteorological factors and the AOM visits. MATERIALS AND METHODS: It was a retrospective cross-sectional study. A linear correlation and a linear regression model were used to explore the AOM visits and meteorological factors. RESULTS: A total of 7075 emergency department visits for AOM were identified. Relative humidity was found an independent risk factor for the AOM visits in preschool children (regression coefficient = -10.841<0, P = .039 < .05), but not in infants and school-age children. Average temperature and PM2.5 were not correlated with AOM visits. CONCLUSION: Humidity may have a significant inverse impact on the incidence of AOM in preschool-age children.
Low-carbon pathways consistent with the 2 degrees C and 1.5 degrees C long-term climate goals defined in the Paris Agreement are likely to induce substantial co-benefits for air pollution and associated health impacts. In this analysis, using five global integrated assessment models, we quantify the emission reductions in key air pollutants resulting from the decarbonization of energy systems and the resulting changes in premature mortality attributed to the exposure to ambient concentrations of fine particulate matter. The emission reductions differ by sectors. Sulfur emissions are mainly reduced from power plants and industry, cuts in nitrogen oxides are dominated by the transport sector, and the largest abatement of primary fine particles is achieved in the residential sector. The analysis also shows that health benefits are the largest when policies addressing climate change mitigation and stringent air pollution controls are coordinated. We decompose the key factors that determine the extent of health co-benefits, focusing on Asia: changes in emissions, urbanization rates, population growth and ageing. Demographic processes, particularly due to ageing population, counteract in many regions the mortality reductions realized through lower emissions.
The objective of this study was to evaluate the influence of exposure to meteorological conditions, including air pollution, on thyroid cancer. A nested case-control study was conducted utilizing 4632 patients with thyroid cancer and 18,528 control subjects who were matched at a 1:4 ratio by age group, sex, income, and region of residence. Korean National Health Insurance Service-Health Screening Cohort data from 2002 to 2015 were used. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for thyroid cancer correlated with meteorological and air pollution exposure over a moving average of 3 years before the index dates. For all participants, the adjusted ORs associated with relative humidity (1.01, 95% CI 1.00-1.03, P value = 0.023), ambient atmospheric pressure (1.02, 95% CI 1.01-1.03, P value < 0.001), and sunshine duration (1.17, 95% CI 1.04-1.31, P value = 0.007) indicated correlations with the occurrence of thyroid cancer; however, these results were inconsistent in the subgroup analyses. Overall, exposure to nitrogen dioxide (NO(2)) (1.33, 95% CI 1.24-1.43, P value < 0.001) and particulate matter (PM(10)) (0.64, 95% CI 0.60-0.69, P value < 0.001) were related to thyroid cancer. These relationships persisted in the subgroup analyses. In conclusion, thyroid cancer occurrence was positively associated with NO(2) exposure and negatively associated with PM(10) exposure.
Meeting the Paris Agreement on climate change requires substantial investments in low-emissions energy and significant improvements in end-use energy efficiency. These measures can also deliver improved air quality and there is broad recognition of the health benefits of decarbonising energy. Monetising these health benefits is an important part of a robust assessment of the costs and benefits of renewable energy and energy efficiency programs (clean energy programs (CEP)) and a variety of methods have been used to estimate health benefits at national, regional, continental and global scales. Approaches, such as unit damage cost estimates and impact pathways, differ in complexity and spatial coverage and can deliver different estimates for air pollution costs/benefits. To date, the monetised health benefits of CEP in Australia have applied international and global estimates that can range from 2-229USD/tCO2 (USD 2016). Here, we calculate the current health damage costs of coal-fired power in New South Wales (NSW), Australia’s most populous state, and the health benefits of CEP. Focusing on PM2.5 pollution, we estimate the current health impacts of coal-fired power at 3.20USD/MWh, approximately 10% of the generation costs, and much lower than previous estimates. We demonstrate the need for locally specific assessment of the air pollution benefits of CEP and illustrate that without locally specific information, the relative costs/benefits of CEP may be significantly over- or understated. We estimate that, for NSW, the health benefits from CEP are 1.80USD/MWh and that the current air pollution health costs of coal-fired power in NSW represent a significant unpriced externality.
BACKGROUND: Bushfire smoke is a major ongoing environmental hazard in Australia. In the summer of 2019-2020 smoke from an extreme bushfire event exposed large populations to high concentrations of particulate matter (PM) pollution. In this study we aimed to estimate the effect of bushfire-related PM of less than 2.5 μm in diameter (PM(2.5)) on the risk of mortality in Sydney, Australia from 2010 to 2020. METHODS: We estimated concentrations of PM(2.5) for three subregions of Sydney from measurements at monitoring stations using inverse-distance weighting and cross-referenced extreme days (95th percentile or above) with satellite imagery to determine if bushfire smoke was present. We then used a seasonal and trend decomposition method to estimate the Non-bushfire PM(2.5) concentrations on those days. Daily PM(2.5) concentrations above the Non-bushfire concentrations on bushfire smoke days were deemed to be Bushfire PM(2.5). We used distributed-lag non-linear models to estimate the effect of Bushfire and Non-bushfire PM(2.5) on daily counts of mortality with sub-analyses by age. These models controlled for seasonal trends in mortality as well as daily temperature, day of week and public holidays. RESULTS: Within the three subregions, between 110 and 134 days were identified as extreme bushfire smoke days within the subregions of Sydney. Bushfire-related PM(2.5) ranged from 6.3 to 115.4 µg/m(3). A 0 to 10 µg/m(3) increase in Bushfire PM(2.5) was associated with a 3.2% (95% CI 0.3, 6.2%) increase in risk of all-cause death, cumulatively, in the 3 days following exposure. These effects were present in those aged 65 years and over, while no effect was observed in people under 65 years. CONCLUSION: Bushfire PM(2.5) exposure is associated with an increased risk of mortality, particularly in those over 65 years of age. This increase in risk was clearest at Bushfire PM(2.5) concentrations up to 30 µg/m(3) above background (Non-bushfire), with possible plateauing at higher concentrations of Bushfire PM(2.5).
We examine 512 Australian newspaper articles published over a five-year period (2016-2021) that report on air pollution due to bushfire smoke and resulting human health impacts. We analyze to what extent these articles provide information on the possible range of negative health impacts due to bushfire smoke pollution, and to what extent they report on climate change as a driver behind increased bushfire risk. A temporary surge in articles in our sample occurs during the unusually severe 2019/2020 Black Summer bushfires. However, most articles are limited to general statements about the health impacts of bushfire smoke, with only 50 articles in the sample (9%) mentioning an explicit link between bushfire smoke inhalation and cardiovascular and respiratory problems or increases in mortality risk. About 148 of the 512 articles in the sample (29%) established a connection between bushfire risk and climate change. We carry out a further keyword analysis to identify differences in reporting by Australia’s two main publishing groups (News Corp Australia and Nine Entertainment), which shows that articles in News Corp Australia outlets offered the lowest climate change coverage. We suggest that more detailed communication strategies are needed to strengthen public preparedness for future impacts.
Smoke from forest fires can reach hazardous levels for extended periods of time. We aimed to determine if there is an association between particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5) and living in a forest fire–prone province and cognitive function. We used data from the Indonesian Family and Life Survey. Cognitive function was assessed by the Ravens Colored Progressive Matrices (RCPM). We used regression models to estimate associations between PM2.5 and living in a forest fire–prone province and cognitive function. In multivariable models, we found very small positive relationships between PM2.5 levels and RCPM scores (PM2.5 level at year of survey: β = 0.1%; 95% confidence interval (CI) [0.01, 0.19%]). There were no differences in RCPM scores for children living in forest fire–prone provinces compared with children living in non-forest fire–prone provinces (mean difference = −1.16%, 95% CI [–2.53, 0.21]). RCPM scores were lower for children who had lived in a forest fire–prone province all their lives compared with children who lived in a non-forest fire–prone province all their life (β = −1.50%; 95% CI [–2.94, –0.07]). Living in a forest fire–prone province for a prolonged period of time negatively affected cognitive scores after adjusting for individual factors.
Smoke haze due to vegetation and peatland fires in Southeast Asia is a serious public health concern. Several approaches have been applied in previous studies; however, the concepts and interpretations of these approaches are poorly understood. In this scoping review, we addressed issues related to the application of epidemiology (EPI), health burden estimation (HBE), and health risk assessment (HRA) approaches, and discussed the interpretation of findings, and current research gaps. Most studies reported an air quality index exceeding the ‘unhealthy’ level, especially during smoke haze periods. Although smoke haze is a regional issue in Southeast Asia, studies on its related health effects have only been reported from several countries in the region. Each approach revealed increased health effects in a distinct manner: EPI studies reported excess mortality and morbidity during smoke haze compared to non-smoke haze periods; HBE studies estimated approximately 100,000 deaths attributable to smoke haze in the entire Southeast Asia considering all-cause mortality and all age groups, which ranged from 1,064-260,000 for specified mortality cause, age group, study area, and study period; HRA studies quantified potential lifetime cancer and non-cancer risks due to exposure to smoke-related chemicals. Currently, there is a lack of interconnection between these three approaches. The EPI approach requires extensive effort to investigate lifetime health effects, whereas the HRA approach needs to clarify the assumptions in exposure assessments to estimate lifetime health risks. The HBE approach allows the presentation of health impact in different scenarios, however, the risk functions used are derived from EPI studies from other regions. Two recent studies applied a combination of the EPI and HBE approaches to address uncertainty issues due to the selection of risk functions. In conclusion, all approaches revealed potential health risks due to smoke haze. Nonetheless, future studies should consider comparable exposure assessments to allow the integration of the three approaches.
Due to climate change, catastrophic events such as landscape fires are increasing in frequency and severity. However, relatively little is known about the longer-term mental health outcomes of such events. Follow-up was conducted of 709 adults exposed to smoke from the 2014 Hazelwood mine fire in Morwell, Victoria, Australia. Participants completed two surveys evaluating posttraumatic distress, measured using the Impact of Events Scale-Revised (IES-R), three and six years after the mine fire. Mixed-effects regression models were used to evaluate longitudinal changes in distress. IES-R total scores increased on average by 2.6 points (95%CI: 1.2 to 3.9 points) between the two survey rounds, with increases across all three posttraumatic distress symptom clusters, particularly intrusive symptoms. This increase in distress was evident across all levels of fine particulate matter (PM(2.5)) exposure to the mine fire smoke. Age was an effect modifier between mine fire PM(2.5) exposure and posttraumatic distress, with younger adults impacted more by exposure to the mine fire. Greater exposure to PM(2.5) from the mine fire was still associated with increased psychological distress some six years later, with the overall level of distress increasing between the two survey rounds. The follow-up survey coincided with the Black Summer bushfire season in south-eastern Australia and exposure to this new smoke event may have triggered distress sensitivities stemming from exposure to the earlier mine fire. Public health responses to disaster events should take into consideration prior exposures and vulnerable groups, particularly younger adults.
The 2019-20 bushfires that raged in eastern Australia were an overwhelming natural disaster leading to lives lost or upended, and communities destroyed. For almost a month, Canberra, Australia’s capital city in the Australian Capital Territory (ACT), was obscured by smoke from fires which threatened the outer suburbs. While smoke itself is experientially different from many natural disasters, it nevertheless poses a significant public health threat. As the impact of extended bushfire smoke in an urban setting is relatively unexplored we aimed to capture the individual and community-level experiences of the event and their importance for community and social functioning. We responded rapidly by conducting semi-structured interviews with a range of Canberra residents who, due to their personal or social circumstances, were potentially vulnerable to the effects of the smoke. Three major themes emerging from the narratives depicted disruption to daily life, physical and psychological effects, and shifting social connectedness. This study highlighted the ambiguous yet impactful nature of a bushfire smoke event, and identified four simple key messages that may be critically relevant to policy making in preparation for similar smoke events in the future.
The 2019-2020 summer wildfire event on the east coast of Australia was a series of major wildfires occurring from November 2019 to end of January 2020 across the states of Queensland, New South Wales (NSW), Victoria and South Australia. The wildfires were unprecedent in scope and the extensive character of the wildfires caused smoke pollutants to be transported not only to New Zealand, but also across the Pacific Ocean to South America. At the peak of the wildfires, smoke plumes were injected into the stratosphere at a height of up to 25 km and hence transported across the globe. The meteorological and air quality Weather Research and Forecasting with Chemistry (WRF-Chem) model is used together with the air quality monitoring data collected during the bushfire period and remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellites to determine the extent of the wildfires, the pollutant transport and their impacts on air quality and health of the exposed population in NSW. The results showed that the WRF-Chem model using Fire Emission Inventory (FINN) from National Center for Atmospheric Research (NCAR) to simulate the dispersion and transport of pollutants from wildfires predicted the daily concentration of PM2.5 having the correlation (R-2) and index of agreement (IOA) from 0.6 to 0.75 and 0.61 to 0.86, respectively, when compared with the ground-based data. The impact on health endpoints such as mortality and respiratory and cardiovascular diseases hospitalizations across the modelling domain was then estimated. The estimated health impact on each of the Australian Bureau of Statistics (ABS) census districts (SA4) of New South Wales was calculated based on epidemiological assumptions of the impact function and incidence rate data from the 2016 ABS and NSW Department of Health statistical health records. Summing up all SA4 census district results over NSW, we estimated that there were 247 (CI: 89, 409) premature deaths, 437 (CI: 81, 984) cardiovascular diseases hospitalizations and 1535 (CI: 493, 2087) respiratory diseases hospitalizations in NSW over the period from 1 November 2019 to 8 January 2020. The results are comparable with a previous study based only on observation data, but the results in this study provide much more spatially and temporally detailed data with regard to the health impact from the summer 2019-2020 wildfires.
Persistent and intensive wildland dense-fires (DFs) release substantial amounts of airborne pollutants, resulting in a sharp increase in emissions and leading to serious impacts on the environment and human health over extensive geographical areas. It is challenging to thoroughly investigate patterns of fire occurrence and fire distribution for predicting wildfire behaviour, and it is especially difficult to distinguish the characteristics of human-caused and climate-driven fires. Here, we identify and assess dense-fire (DF) from the perspective of spatiotemporally integrated processes using a machine-learning method based on a density-based clustering algorithm with noise constraint ratio. DFs represent collections of fires with homogenous behaviour and therefore allow the study of their internal features, which can reveal fixed patterns of fire occurrence and dis-tribution as well as the evolution of fires over time. We estimated and labelled thousands of fire clusters on the Indochina Peninsula between 2010 and 2020, most of which occurred between December and May. For large-scale DFs, the number of fires contained and amount of atmospheric pollutants emitted were accounted for throughout most of the region, and the time, location and scale of their occurrence each year were relatively stable and predictable. Furthermore, the results of a secondary cluster analysis of fire interactions over the past decade showed two extreme fire events, labelled “north ” and “south ” groups, whose activities significantly impacted the atmospheric environment of the Indochina Peninsula. Additionally, we predicted their start/end dates and daily emissions. The study also found that the recurrence of high-density fires and the correlation between the DF edge and administrative border suggested a positive anthropogenic influence. To the authors’ knowledge, this study is the first to analyze fires in a spatiotemporal Euclidean space by using density-based clustering, with high-density fires as independent subjects to study fire behaviour. The method proposed in this study can provide a reference for wildfire prediction and emission forecasting and fire control work.
Evidence of the acute effects of air pollutants on ischemic heart disease (IHD) hospitalizations based on the entire population of a megacity in central China is lacking. All IHD hospitalization records from 2017 to 2018 were obtained from the Wuhan Information Center of Health and Family Planning. Daily air pollutant concentrations and meteorological data were synchronously collected from the Wuhan Environmental Protection Bureau. A time-series study using generalized additive models was conducted to systematically examine the associations between air pollutants and IHD hospitalizations. Stratified analyses by gender, age, season, hypertension, diabetes, and hyperlipidemia were performed. In total, 139,616 IHD hospitalizations were included. Short-term exposure to air pollutants was positively associated with IHD hospitalizations. The age group ≥ 76 was at higher exposure risk, and the associations appeared to be more evident in cold seasons. PM(2.5) and PM(10) appeared to have greater effects on males and those without hypertension or diabetes, whereas NO(2) and SO(2) had greater effects on females and those with hypertension or diabetes. The risk of IHD hospitalization due to air pollutants was greater in people without hyperlipidemia. Our study provides new evidence of the effects of air pollution on the increased incidence of IHD in central China.
Recent evidence shows that carbon emissions in China are likely to peak ahead of 2030. However, the social and economic impacts of such an early carbon peak have rarely been assessed. Here we focus on the economic costs and health benefits of different carbon mitigation pathways, considering both possible socio-economic futures and varying ambitions of climate policies. We find that an early peak before 2030 in line with the 1.5 °C target could avoid ~118,000 and ~614,000 PM(2.5) attributable deaths under the Shared Socioeconomic Pathway 1, in 2030 and 2050, respectively. Under the 2 °C target, carbon mitigation costs could be more than offset by health co-benefits in 2050, bringing a net benefit of $393-$3,017 billion (in 2017 USD value). This study not only provides insight into potential health benefits of an early peak in China, but also suggests that similar benefits may result from more ambitious climate targets in other countries.
Background: Previous studies suggested that exposure to air pollution could increase risk of asthma attacks in children. The aim of this study is to investigate the short-term effects of exposure to ambient air pollution on asthma hospital admissions in children in Beijing, a city with serious air pollution and high-quality medical care at the same time. Methods: We collected hospital admission data of asthma patients aged ?ëñ 18 years old from 56 hospitals from 2013 to 2016 in Beijing, China. Time-stratified case-crossover design and conditional Poisson regression were applied to explore the association between risk of asthma admission in children and the daily concentration of six air pollutants [particulate matter ?ëñ 2.5 ??m (PM(2.5)), particulate matter ≤ μm (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), carbon monoxide (CO), and ozone (O(3))], adjusting for meteorological factors and other pollutants. Additionally, stratified analyses were performed by age, gender, and season. Results: In the single-pollutant models, higher levels of PM(2.5), SO(2), and NO(2) were significantly associated with increased risk of hospital admission for asthma in children. The strongest effect was observed in NO(2) at lag06 (RR = 1.25, 95%CI: 1.06-1.48), followed by SO(2) at lag05 (RR = 1.17, 95%CI: 1.05-1.31). The robustness of effects of SO(2) and NO(2) were shown in two-pollutant models. Stratified analyses further indicated that pre-school children (aged ≤ 6 years) were more susceptible to SO(2). The effects of SO(2) were stronger in the cold season, while the effects of NO(2) were stronger in the warm season. No significant sex-specific differences were observed. Conclusions: These results suggested that high levels of air pollution had an adverse effect on childhood asthma, even in a region with high-quality healthcare. Therefore, it will be significant to decrease hospital admissions for asthma in children by controlling air pollution emission and avoiding exposure to air pollution.
Electric vehicle (EV) adoption promises potential air pollutant and greenhouse gas (GHG) reduction co-benefits. As such, China has aggressively incentivized EV adoption, however much remains unknown with regard to EVs’ mitigation potential, including optimal vehicle type prioritization, power generation contingencies, effects of Clean Air regulations, and the ability of EVs to reduce acute impacts of extreme air quality events. Here, we present a suite of scenarios with a chemistry transport model that assess the potential co-benefits of EVs during an extreme winter air quality event. We find that regardless of power generation source, heavy-duty vehicle (HDV) electrification consistently improves air quality in terms of NO2 and fine particulate matter (PM2.5), potentially avoiding 562 deaths due to acute pollutant exposure during the infamous January 2013 pollution episode (similar to 1% of total premature mortality). However, HDV electrification does not reduce GHG emissions without enhanced emission-free electricity generation. In contrast, due to differing emission profiles, light-duty vehicle (LDV) electrification in China consistently reduces GHG emissions (similar to 2 Mt CO2), but results in fewer air quality and human health improvements (145 avoided deaths). The calculated economic impacts for human health endpoints and CO2 reductions for LDV electrification are nearly double those of HDV electrification in present-day (155M vs. 87M US$), but are within similar to 25% when enhanced emission-free generation is used to power them. Overall, we find only a modest benefit for EVs to ameliorate severe wintertime pollution events, and that continued emission reductions in the power generation sector will have the greatest human health and economic benefits.
The epidemiological evidence on relationships between air pollution, temperature, and stroke remains inconclusive. Limited evidence is available for the effect modification by apparent temperature, an indicator reflecting reactions to the thermal environment, on short-term associations between air pollution and hospital admissions for stroke. We used a generalized additive model with Poisson regression to estimate the relative risk (RR) of stroke admissions in Shanghai, China, between 2014 and 2016 associated with air pollutants, with subgroup analyses by age, sex, apparent temperature, and season. During the study period, changes in the daily number of stroke admissions per 10 μg/m(3) increase in nitrogen dioxide (at lags 0, 1, 0-1, and 0-2) ranged from 1.05 (95% CI: 0.82%, 2.88%) to 2.24% (95% CI: 0.84%, 3.65%). For each 10 μg/m(3) increase in sulfur dioxide concentrations at lags 1, 2, 0-1, and 0-2, the RR of daily stroke admissions increased by 3.34 (95% CI: 0.955%, 5.79%), 0.32 (95% CI: -1.97%, 2.67%), 3.33 (95% CI: 0.38%, 6.37%), and 2.86% (95% CI: -0.45%, 6.28%), respectively. The associations of same-day exposure to nitrogen dioxide with stroke admissions remained significant after adjustment for ozone levels. These associations were not modified by sex, age, apparent temperature, or season. More research is warranted to determine whether apparent temperature modifies the associations between air pollution and stroke admissions.
Chronic obstructive pulmonary disease (COPD) is the fourth major cause of mortality and morbidity worldwide and is projected to be the third by 2030. However, there is little evidence available on the associations of COPD hospitalizations with meteorological factors and air pollutants in developing countries/regions of Asia. In particular, no study has been done in western areas of China considering the nonlinear and lagged effects simultaneously. This study aims to evaluate the nonlinear and lagged associations of COPD hospitalizations with meteorological factors and air pollutants using time-series analysis. The modified associations by sex and age were also investigated. The distributed lag nonlinear model was used to establish the association of daily COPD hospitalizations of all 441 public hospitals in Chengdu, China from Jan/2015-Dec/2017 with the ambient meteorological factors and air pollutants. Model parameters were optimized based on quasi Akaike Information Criterion and model diagnostics was conducted by inspecting the deviance residuals. Subgroup analysis by sex and age was also performed. Temperature, relative humidity, wind and Carbon Monoxide (CO) have statistically significant and consistent associations with COPD hospitalizations. The cumulative relative risk (RR) was lowest at a temperature of 19℃ (relative humidity of 67%). Both extremely high and low temperature (and relative humidity) increase the cumulative RR. An increase of wind speed above 4 mph (an increase of CO above 1.44 mg/m(3)) significantly decreases (increases) the cumulative RR. Female populations were more sensitive to low temperature and high CO level; elderly (74+) populations are more sensitive to high relative humidity; younger populations (< = 74) are more susceptible to CO higher than 1.44 mg/m(3). Therefore, people with COPD should avoid exposure to adverse environmental conditions of extreme temperatures and relative humidity, low wind speed and high CO level, especially for female and elderly patients who were more sensitive to extreme temperatures and relative humidity.
South Korea had the highest annual average PM2.5 exposure levels in the Organization for Economic Co-operation and Development (OECD) in 2019, and air pollution is consistently ranked as citizens’ top environmental concern. South Korea is also one of the world’s top ten emitter countries of CO2. Co-benefit mitigation policies can address both air pollution and climate change. Utilizing an alternative co-benefit approach, which views air pollution reduction as the primary goal and climate change mitigation as secondary, this research conducts a scenario analysis to forecast the health and climate benefits of fuel substitution in South Korea’s electricity generation sector. Health benefits are calculated by avoided premature mortality and years of life lost (YLL) due to ischemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lung cancer, and acute lower respiratory infections (ALRI). The study finds that use of liquefied natural gas (LNG) instead of coal over the 2022-2050 period would result in an average of 116 fewer premature deaths (1152 YLL) and 80.8 MTCO(2)e fewer emissions per year. Over the same period, maintaining and maximizing the use of its nuclear energy capacity, combined with replacing coal use with LNG, would result in an average of 161 fewer premature deaths (1608 YLL) and 123.7 MTCO(2)e fewer emissions per year.
This article quantifies the environmental, health, and economic co-benefits from the use of solar electricity and heat generation in the Ger area (a sub-district of traditional residences and private houses) in Ulaanbaatar (UB), Mongolia. The quantification of the featured co-benefits is based on calculating emissions reductions from the installation of the solar photovoltaic (PV) and solar water heaters. A user-friendly spreadsheet tool is developed to shed much-needed light on the steps involved in estimating these co-benefits. The tool simulates the hourly electricity and thermal energy generation, taking into account local meteorological conditions, local geographical data, and technical specifications of the solar power and heat generation systems. The tool is then employed to evaluate two intervention scenarios: (1) Installing 100 MW solar electricity, including both rooftop PV and community grids, to reduce the peak-load burden on the grid; (2) Providing solar thermal heaters for 20,000 households to replace the heating load demand from the existing heat only boilers (HOBs) in UB. The modelling results reveal a significant reduction in GHG emissions and fine particulate matter (PM(2.5)) (PM that is 2.5 microns or less in diameter) by 311,000 tons and 767 tons, respectively, as well as nearly 6500 disability-adjusted life years (DALYs) and an annual saving of USD 7.7 million for the local economy. The article concludes that the mainstreaming spreadsheet-based estimation tools like the one used in this article into decision-making processes can fill important research gaps (e.g., usability of assessment tools) and help translate co-benefits analyses into action in Mongolia and beyond.
Pollution of the environment is increasing and threatens the health and wellbeing of adults and children around the globe. The impact of air pollution on pulmonary and cardiovascular disease has been well documented, but it also has a deleterious effect on reproductive health. Ulaanbaatar, the capital city of Mongolia, has one of the highest levels of air pollution in the world. During the extreme winters when temperatures routinely fall below -20 degrees C the level of air pollution can reach 80 times the WHO recommended safe levels. Heating mainly comes from coal, which is burned both in power stations, and in stoves in the traditional Ger housing. We studied the impact of air pollution on conception rates and birth outcomes in Ulaanbaatar using a retrospective analysis of health data collected from the Urguu Maternity hospital in Ulaanbaatar, Mongolia. Daily levels of SO2, NO2, PM10, and PM2.5 were collected from the government Air Quality Monitoring Stations in Ulaanbaatar for the same period as the study. In January, the month of highest pollution, there is a 3.2-fold decrease in conceptions that lead to the successfully delivered infants compared to October. The seasonal variations in conceptions resulting in live births in this study in Ulaanbaatar are shown to be 2.03 +/- 0.20 (10-sigma) times greater than those in the Denmark/North America study of Wesselink et al., 2020. The two obvious differences between Ulaanbaatar and Europe/North America are pollution and temperature both of which are extreme in Ulaanbaatar. The extreme low temperature is mitigated by burning coal, which is the main source of domestic heat especially in the ger districts. This drives the level of pollution so the two are inextricably linked. Infants conceived in the months of June-October had the greatest cumulative PM2.5 pollution exposure over total gestation, yet these were also the pregnancies with the lowest PM2.5 exposure for the month of conception and three months prior to conception. The delivered-infant conception rate shows a markedly negative association with exposure to PM2.5 prior to and during the first month of pregnancy. This overall reduction in fecundity of the population of Ulaanbaatar is therefore a preventable health risk. It is of great consequence that the air pollution in Ulaanbaatar affects health over an entire lifespan including reproductive health. This could be remedied with a clean source of heating.
OBJECTIVES: To investigate associations between long-term exposure to PM(2.5), NO(2), mortality and morbidity in New Zealand, a country with low levels of exposure. DESIGN: Retrospective cohort study. SETTING: The New Zealand resident population. METHOD: The main analyses included all adults aged 30 years and over with complete data on covariates: N = 2,223,507. People who died, or were admitted to hospital, (2013-2016) were linked anonymously to the 2013 census, and to estimates of ambient PM(2.5), and NO(2) concentration. We fitted Poisson regression models of mortality and morbidity in adults (≥30) for all natural causes of death, and by sub- group of major cause. Person-time of exposure, censored at the time of death, was included as an offset. We adjusted for confounding by age, sex, ethnicity, income, education, smoking status and ambient temperature. Further analyses stratified by ethnic group, and investigated respiratory hospital admissions in children. RESULTS: There were statistically significant positive associations between pollutants and natural causes of death: RR (per 10 μg/m(3)) for PM(2.5) 1.11 (1.07 to 1.15) and for NO(2) 1.10 (1.07 to 1.12). For morbidity, the strongest associations were for PM(2.5) and ischaemic heart disease in adults, RR: 1.29 (1.23 to 1.35) and for NO(2) and asthma in children, RR: 1.18 (1.09 to 1.28). In models restricted to specific ethnic groups, we found no consistent differences in any of the associations. CONCLUSIONS: The results for NO(2) are higher than those published previously. Other studies have reported that the dose-response for PM(2.5) may be higher at low concentrations, but less is known about NO(2). It is possible NO(2) is acting as a proxy for other traffic-related pollutants that are causally related to health impacts. This study underlines the importance of controlling pollution caused by motor vehicles.
This study examines how human capital develops in response to early-life weather and pollution exposures in the Philippines. Both pollution and weather are examined in relation to short- and long-term human capital outcomes. We combine a three-decade longitudinal survey measuring human capital development, a database of historical weather, and multiple databases characterizing carbon monoxide and ozone in the Philippines during the 1980s. We find evidence that extreme precipitation and temperature affect short-term anthropometric outcomes, but long-term outcomes appear unaffected. For long-term cognitive outcomes, we find that early-life pollution exposures negatively affect test scores and schooling. These long-term responses to early-life pollution exposures extend to the labor market with reduced hours worked and earnings. The implication is that a 25 per cent reduction in early-life ozone exposure would increase per person discounted lifetime earnings by $1,367, which would scale to $2.05 billion at the national level (or 2 per cent of 2005 GDP).
There is a dearth of research on the hourly risk of ambulance dispatches with respect to ambient conditions. We evaluated hourly relative risks (RR) and 95% confidence interval (CI) of ambulance dispatches in Taiwan to treat respiratory distress, coma and unconsciousness, and out-of-hospital cardiac arrest (OHCA), from 2006 to 2015. We considered island-wide ambient temperatures, fine particulate matter (PM(2.5)), and ozone (O(3)) at lag 0-180 h while using a distributed lag nonlinear model and meta-analysis. Results showed the pooled risks peaked at lag 16-18 h for all ambulance dispatches at 99th percentile of hourly temperature (32 °C, versus reference temperature of 25 °C), with significant excess risk of 0.11% (95% CI; 0.06, 0.17) for coma and unconsciousness, and 0.06% (95% CI; 0.01, 0.11) for OHCA. The risks of exposure to 90th percentile of hourly O(3) of 52.3 ppb relative to the Q1 level of 17.3 ppb peaked at lag 14 h, with excess risk of 0.17% (95% CI; 0.11, 0.23) for respiratory distress, 0.11% (95% CI; 0.06, 0.16) for coma and unconsciousness, and 0.07% (95% CI; 0.01, 0.14) for OHCA. The population exposed to reference temperatures of 28 °C, 20 °C, and 26 °C were exposed to the lowest levels of ambulance dispatches risk for respiratory distress, coma and unconsciousness, and OHCA, respectively; the highest cumulative 0-96 h RRs of ambulance dispatches were 1.27 (95% CI; 1.19, 1.35) for OHCA at 5th percentile temperatures and 1.25 (95% CI; 1.11, 1.41) for OHCA at 99th percentile temperatures. Following an accumulating lag of 0-96 h, no significant risk was identified for hourly levels of PM(2.5) and O(3). In conclusion, the analytical results of hourly data speak to immediate and real-time responses to environmental changes, rather than to short-term relationships. In our analyses, we emphasized health events in extreme heat; thus, we recommend a comparative study of daily versus hourly associations.
OBJECTIVE: To determine the association of meteorological factors and air pollutants (MFAPs) with fracture and to estimate the effect size/time lag. DESIGN: This is a nationwide population-based ecological study from 2008 to 2017. SETTING: Eight large metropolitan areas in Korea. PARTICIPANTS: Of 8 093 820 patients with fractures reported in the Korea National Health Insurance database, 2 129 955 were analysed after the data set containing patient data (age, sex and site of fractures) were merged with MFAPs. Data on meteorological factors were obtained from the National Climate Data Center of the Korea Meteorological Administration. Additionally, data on air pollutants (atmospheric particulate matter ≤2.5 µm in diameter (PM(2.5)), PM(10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide) were obtained from the Air Korea database. PRIMARY AND SECONDARY OUTCOME MEASURES: We hypothesised that there would be an association between MFAPs and the incidence of fracture. A generalised additive model was used while factoring in the non-linear relationship between MFAPs and fractures as well as a time lag ≤7 days. Multivariate analysis was performed. Backward elimination with an Akaike information criterion was used to fit the multivariate model. RESULTS: Overall, in eight urban areas, 2 129 955 patients with fractures were finally analysed. These included 370 344, 187 370, 173 100, 140 358, 246 775, 6501, 228 346, 57 183 and 719 978 patients with hip, knee, shoulder, elbow, wrist, hand, ankle, foot and spine fractures, respectively. Various MFAPs (average temperature, daily rain, wind speed, daily snow and PM(2.5)) showed significant association with fractures, with positive correlations at time lags 7, 5-7, 5-7, 3-7 and 6-7 days, respectively. CONCLUSIONS: Various MFAPs could affect the occurrence of fractures. The average temperature, daily rain, wind speed, daily snow and PM(2.5) were most closely associated with fracture. Thus, improved public awareness on these MFAPs is required for clinical prevention and management of fractures.
The biological mechanisms underlying the associations between atmospheric ozone exposure and adverse cardiometabolic outcomes are yet to be identified. Imbalanced autonomic nervous system (ANS) as well as activations of the sympatho-adrenomedullary (SAM) and hypothalamic-pituitary-adrenal (HPA) axes are among possible early biological responses triggered by ozone, and may eventually lead to cardiometabolic abnormalities. To determine whether acute ozone exposure causes ANS imbalance and increases the secretion of neuroendocrine stress hormones, we conducted a randomized, double-blind, crossover trial, under controlled 2-hour exposure to either ozone (200 ppb) or clean air with intermittent exercise among 22 healthy young adults. Here we found that, compared to clean air exposure, acute ozone exposure significantly decreased the high-frequency band of heart rate variability, even after adjusting for heart rate and pre-exposure to ambient air pollutants and meteorological factors. Ozone exposure also significantly increased the serum levels of stress hormones, including corticotrophin-releasing factor, adrenocorticotropic hormone, adrenaline, and noradrenaline. Metabolomics analysis showed that acute ozone exposure led to alterations in stress hormones, systemic inflammation, oxidative stress, and energy metabolism. Our results suggest that acute ozone exposure may trigger ANS imbalance and activate the HPA and SAM axes, offering potential biological explanations for the adverse cardiometabolic effects following acute ozone exposure.
Air pollution causes adverse effects not only on the environment but also on human health. This study evaluated the excess mortalities in continental Southeast Asia that are related to future O-3 and PM2.5 ambient concentration changes attributed to future climate change and emission change. The Environmental Benefits Mapping and Analysis Program -Community Edition (BenMAP-CE) was applied as a health impact assessment tool. In BenMAP-CE simulations, baseline scenarios presenting for the present year (2014) were compared against the control scenarios presenting for the future year (2050). The air pollutant concentrations for the simulations were collected from modeled data. The future population data and baseline incidence rates were as same as the 2014 levels. In four calculating countries namely Laos, Cambodia, Thailand, and Vietnam, on average, impacted by climate change alone, the avoided mortalities of -1164 and -3358 under Representative Concentration Pathway (RCP) 4.5 scenario and the additional mortalities of +758 and +2562 under RCP8.5 scenario were calculated for O-3 and PM2.5, respectively. Future emission change alone under Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants current legislation (ECLIPSE CLE) scenario induces +7113 and +11072 additional O-3 and PM2.5 related mortalities, respectively. Combined change in climate and emission produces additional O-3 and PM2.5 related mortalities of +6067 and +7830 under RCP4.5 and ECLIPSE CLE combined scenario and +8763 and +14580 under RCP8.5 and ECLIPSE CLE combined scenario, respectively. The results of this study provided meaningful information for understanding the public health attributed to air pollution in the region.
BACKGROUND/AIMS: Weather and air pollution are associated with the exacerbation of respiratory diseases. We investigated patterns of medical care use according to meteorological factors and air pollution in patients with asthma or chronic obstructive pulmonary disease (COPD). METHODS: We analyzed the medical care utilization patterns of patients with asthma or COPD registered in the Korea Health Insurance Review and Assessment database for the period 2007 to 2013. The patterns were divided into hospitalization and emergency department (ED) use. RESULTS: The medical care use of patients with asthma or COPD increased when the mean temperature and relative humidity were lower, and the temperature difference and atmospheric pressure were greater. Medical care use increased with the concentrations of particulate matter and ozone. Among age groups, sensitivity to pollutants was greatest in patients aged ≥ 65 years. The effect of being elderly was greater for asthma than for COPD, with a higher hospitalization rate. ED utilization affected by environmental factors was significantly greater for females and hospitalization was significantly more common for males. CONCLUSION: Meteorological factors and air pollutants were shown to contribute to increased medical care utilization by patients with asthma and COPD, particularly elderly patients. The overall effect was greater for COPD, but the effect in elderly patients was greater for asthma. In addition, the patterns of change in medical care use due to environmental factors differed according to sex.
With the development of the economy and the accumulation of social wealth, urban residents have begun to give more attention to quality of life than to material needs. Consequently, environmental factors that affect human health, such as air quality, have become a new focus when traveling. A travel scheme with relatively low pollutant exposure to travelers can not only improve their health and satisfy their goals but also benefit social stability and sustained progress. However, low spatiotemporal resolution and coarse spatial details of the distribution of PM2.5 (particles with an aerodynamic diameter of 2.5 mu m or less) educe the success rate of short distance healthy travel route planning. This paper proposes a short-distance healthy route planning approach that is based on PM2.5 retrieval with high spatiotemporal resolution and a dynamic Dijkstra algorithm. First, fine spatial resolution images, meteorological data, and socioeconomic data are used to retrieve the spatial distribution of PM2.5 concentration in hourly intervals via a back-propagation neural network (BPNN). Second, a PM2.5 concentration value is obtained for each road section, and the harm degree to the human body is calculated as the weight of each road section. Then, the healthiest route is obtained based on the Dijkstra algorithm. Finally, the route planning effectiveness is verified by comparing the PM2.5 potential dose descending rate between the healthy route and the shortest route. The results show that the coefficient of determination (R2) of the PM2.5 retrieval approach that is based on multisource data and BPNN is 0.85, which can ensure the accuracy of the PM2.5 data at the street level. On this basis, the potential dose reduction rate of the healthy route can reach up to 20%, which proves that our approach can perform well. It can effectively improve the safety of travel and alleviate the anxiety that is caused by air pollution. In addition, it provides an easy implementation strategy for software for health management.
Over the past few decades, due to human activities, industrialization, and urbanization, air pollution has become a life-threatening factor in many countries around the world. Among air pollutants, Particulate Matter with a diameter of less than 2.5 μm ( PM2.5 ) is a serious health problem. It causes various illnesses such as respiratory tract and cardiovascular diseases. Hence, it is necessary to accurately predict the PM2.5 concentrations in order to prevent the citizens from the dangerous impact of air pollution beforehand. The variation of PM2.5 depends on a variety of factors, such as meteorology and the concentration of other pollutants in urban areas. In this paper, we implemented a deep learning solution to predict the hourly forecast of PM2.5 concentration in Beijing, China, based on CNN-LSTM, with a spatial-temporal feature by combining historical data of pollutants, meteorological data, and PM2.5 concentration in the adjacent stations. We examined the difference in performances among Deep learning algorithms such as LSTM, Bi-LSTM, GRU, Bi-GRU, CNN, and a hybrid CNN-LSTM model. Experimental results indicate that our method hybrid CNN-LSTM multivariate enables more accurate predictions than all the listed traditional models and performs better in predictive performance.
BACKGROUND: Smaller sizes of ambient particulate matter (PM) can be more toxic and can be breathed into lower lobes of a lung. Children are particularly vulnerable to PM air pollution because of their adverse effects on both lung functions and lung development. However, it remains unknown whether a smaller PM has a greater short-term impact on childhood pneumonia. AIMS: We compared the short-term effects on childhood pneumonia from PM with aerodynamic diameters ≤1 μm (PM(1)), ≤2.5 μm (PM(2.5)), and ≤10 μm (PM(10)), respectively. METHODS: Daily time-series data (2016-2018) on pneumonia hospitalizations in children aged 0-17 years, records of air pollution (PM(1), PM(2.5), PM(10), and gaseous pollutants), and weather conditions were obtained for Hefei, China. Effects of different PM were quantified using a quasi-Poisson generalized additive model after controlling for day of the week, holiday, seasonality and long-term time trend, and weather variables. Stratified analyses (gender, age, and season) were also performed. RESULTS: For each 10 μg/m(3) increase in PM(1), PM(2.5), and PM(10) concentrations over the past three days (lag 0-2), the risk of pneumonia hospitalizations increased by 10.28% (95%CI: 5.88%-14.87%), 1.21% (95%CI: 0.34%-2.09%), and 1.10% (95%CI: 0.44%-1.76%), respectively. Additionally, both boys and girls were at risk of PM(1) effects, while PM(2.5) and PM(10) effects were only seen in boys. Children aged ≤12 months and 1-4 years were affected by PM(1), but PM(2.5) and PM(10) were only associated with children aged 1-4 years. Furthermore, PM(1) effects were greater in autumn and winter, while greater PM(2.5) and PM(10) effects were evident only in autumn. CONCLUSION: This study suggests a greater short-term impact on childhood pneumonia from PM(1) in comparison to PM(2.5) and PM(10). Given the serious PM pollution in China and other rapid developing countries due to various combustions and emissions, more investigations are needed to determine the impact of different PM on childhood respiratory health.
OBJECTIVE: Acute tonsillitis is a common disease in otorhinolaryngology. Meteorological factors can affect the incidence of many infectious diseases. This study aims to analyze the correlation between acute tonsillitis and meteorological conditions. MATERIALS AND METHODS: We collected the meteorological data, including daily temperature, humidity, and fine particulate matter (PM(2.5)) of Shanghai, China, from 2014 to 2015. The monthly number of acute tonsillitis cases in our hospital was also calculated and used as the outcome variable. The associations between them were evaluated, respectively. RESULTS: The average number of patients diagnosed with acute tonsillitis in our hospital per month was 68.67 ± 18.67 from 2014 to 2015. The average temperature, humidity, and PM(2.5) of Shanghai during the defined period was 16.84 °C ± 7.80 °C, 75.93% ± 5.45%, and 52.38 ± 14.23 μg/m(3), respectively. The temperature was significantly positively associated with the acute tonsillitis cases number both in Pearson correlation analysis (R = 0.423, P = .039) and in multivariate regression analysis (coefficient =2.194, P = .012). However, no correlation between the acute tonsillitis cases number and relative humidity or PM(2.5) was found through a multivariate regression model (P = .225 and P = .243), respectively. CONCLUSION: The high temperature was associated with an increased incidence of acute tonsillitis.
An outdoor solar assisted large-scale cleaning system (SALSCS) was constructed to mitigate the levels of fine particulate matter (PM(2.5)) in urban areas of Xi’an China, providing a quasi-experimental opportunity to examine the biologic responses to the changes in pollution level. We conducted this outdoor SALSCS based real-world quasi-interventional study to examine the associations of the SALSCS intervention and changes in air pollution levels with the biomarkers of systemic inflammation and oxidative stress in healthy elders. We measured the levels of 8-hydrox-2-deoxyguanosine (8-OHdG), Interlukin-6 (IL-6), as well as tumor necrosis factor alpha (TNF-α) from urine samples, and IL-6 from saliva samples of 123 healthy retired participants from interventional/control residential areas in two sampling campaigns. We collected daily 24-h PM(2.5) samples in two residential areas during the study periods using mini-volume samplers. Data on PM(10), gaseous pollutants and weather factors were collected from the nearest national air quality monitoring stations. We used linear mixed-effect models to examine the percent change in each biomarker associated with the SALSCS intervention and air pollution levels, after adjusting for time trend, seasonality, weather factors and personal characteristics. Results showed that the SALSCS intervention was significantly associated with decreases in the geometric mean of biomarkers by 47.6% (95% confidence interval: 16.5-67.2%) for 8-OHdG, 66% (31.0-83.3%) for TNF-α, 41.7% (0.2-65.9%) and 43.4% (13.6-62.9%) for urinary and salivary IL-6, respectively. An inter-quartile range increase of ambient PM(2.5) exposure averaged on the day of the collection of bio-samples and the day before (34.1 μg/m(3)) was associated, albeit non-significantly so, with 22.8%-37.9% increases in the geometric mean of these biomarkers. This study demonstrated that the SALSCS intervention and decreased ambient air pollution exposure results in lower burden of systemic inflammation and oxidative stress in older adults.
BACKGROUND: Evidences have shown that the stroke risk associated with long-term exposure to particulate matter with an aerodynamic diameter of ≤2.5 μm (PM(2.5)) varies among people in North America, Europe and Asia, but studies in Asia rarely evaluated the association by stroke type. We examined whether long-term exposure to PM(2.5) is associated with developing all strokes, ischemic stroke and hemorrhagic stroke. METHODS: The retrospective cohort study consisted of 1,362,284 adults identified from beneficiaries of a universal health insurance program in 2011. We obtained data on air pollutants and meteorological measurements from air quality monitoring stations across Taiwan in 2010-2015. Annual mean levels of all environmental measurements in residing areas were calculated and assigned to cohort members. We used Cox proportional hazards models to estimate hazard ratio (HR) and 95% confidence interval (CI) of developing stroke associated with 1-year mean levels of PM(2.5) at baseline in 2010, and yearly mean levels from 2010 to 2015 as the time-varying exposure, adjusting for age, sex, income and urbanization level. RESULTS: During a median follow-up time of 6.0 years, 12,942 persons developed strokes, 9919 (76.6%) were ischemic. The adjusted HRs (95% CIs) per interquartile range increase in baseline 1-year mean PM(2.5) were 1.03 (1.00-1.06) for all stroke, 1.06 (1.02-1.09) for ischemic stroke, and 0.95 (0.89-1.10) for hemorrhagic stroke. The concentration-response curves estimated in the models with and without additional adjustments for other environmental measurements showed a positively linear association between baseline 1-year mean PM(2.5) and ischemic stroke at concentrations greater than 30 μg/m(3), under which no evidence of association was observed. There was an indication of an inverse association between PM(2.5) and hemorrhagic stroke, but the association no longer existed after controlling for nitrogen dioxide or ozone. We found similar shape of the concentration-response association in the Cox regression models with time-varying PM(2.5) exposures. CONCLUSION: Long-term exposure to PM(2.5) might be associated with increased risk of developing ischemic stroke. The association with high PM(2.5) concentrations remained significant after adjustment for other environmental factors.
What is already known about this topic? Climate change and air pollution are two important environmental issues in China. It is important to investigate particulate matter with aerodynamic diameter less than 2.5 μm (PM(2.5))-related health impacts from climate change and air pollution emission control. What is added by this report? Deaths and years of life lost related to PM(2.5) would increase in climate change scenario, although emission control would outweigh the influence of climate change. What are the implications for public health practice? More targeted actions should be taken to meet challenges of exacerbated PM(2.5) pollutions and its health impacts related to climate change in the future.
BACKGROUND: Scientific studies have identified various adverse effects of particulate matter (PM) on respiratory disease (RD) and type 2 diabetes (T2D). However, whether short-term exposure to PM triggers the onset of RD with T2D, compared with RD without T2D, has not been elucidated. METHODS: A two-stage time-series study was conducted to evaluate the acute adverse effects of PM on admission for RD and for RD with and without T2D in Beijing, China, from 2014 to 2020. District-specific effects of PM(2.5) and PM(10) were estimated using the over-dispersed Poisson generalized addictive model after adjusting for weather conditions, day of the week, and long-term and seasonal trends. Meta-analyses were applied to pool the overall effects on overall and cause-specific RD, while the exposure-response (E-R) curves were evaluated using a cubic regression spline. RESULTS: A total of 1550,154 admission records for RD were retrieved during the study period. Meta-analysis suggested that per interquartile range upticks in the concentration of PM(2.5) corresponded to 1.91% (95% CI: 1.33-2.49%), 2.16% (95% CI: 1.08-3.25%), and 1.92% (95% CI: 1.46-2.39%) increments in admission for RD, RD with T2D, and RD without T2D, respectively, at lag 0-8 days, lag 8 days, and lag 8 days. The effect size of PM(2.5) was statistically significantly higher in the T2D group than in the group without T2D (z = 3.98, P < 0.01). The effect sizes of PM(10) were 3.86% (95% CI: 2.48-5.27%), 3.73% (95% CI: 1.72-5.79%), and 3.92% (95% CI: 2.65-5.21%), respectively, at lag 0-13 days, lag 13 days, and lag 13 days, respectively, and no statistically significant difference was observed between T2D groups (z = 0.24, P = 0.81). Significant difference was not observed between T2D groups for the associations of PM and different RD and could be found between three groups for effects of PM(10) on RD without T2D. The E-R curves varied by sex, age and T2D condition subgroups for the associations between PM and daily RD admissions. CONCLUSIONS: Short-term PM exposure was associated with increased RD admission with and without T2D, and the effect size of PM(2.5) was higher in patients with T2D than those without T2D.
Most studies on the short-term local benefits of carbon mitigation technologies on air quality improvement and health focus on specific technologies such as biofuels or carbon sequestration technologies, while ignoring the overall role of the growing scale of low-carbon technologies. Based on STIRPAT model and EKC hypothesis, this paper takes 30 provinces in China from 2004 to 2016 as research samples. We builded the panel double fixed effect model to empirical analysis of climate change on carbon mitigation tech-innovation suppressing the influence of haze pollution, on this basis, the mediating effect model was used to explore the mediation function of industrial structure and energy structure. Meanwhile, we drawed on the existing studies on air quality and health benefits, and quantify the co-benefits of carbon mitigation tech-innovation on health through the equivalent substitution formula. It shows that a 1% increase in the number of low-carbon patent applications can reduce haze pollution by 0.066%. According to this estimate, to 2029, China’s carbon mitigation tech-innovation could reduce PM2.5 concentration to 15 μg/m(3) preventing 5.597 million premature deaths. Moreover, carbon mitigation tech-innovation can also indirectly inhibit haze pollution by triggering more systematic economic structure changes such as energy and industrial structure. Additionally, we found that the role of gray tech-innovation (GT) related to improving the efficiency of fossil energy is stronger than that of clean technology (CT) related to the use of renewable energy. This suggests that for a large economy such as China, where coal is still the dominant source of energy consumption, the short-term local benefits of improving air quality and health through the use of gray tech-innovation to improve energy and industrial structure are still important to balance the cost of carbon mitigation.
BACKGROUND: Pneumonia is one of the principal reasons for incidence and death in the world. The former research mainly concentrated on specific sources of patients. Besides, due to the heterogeneity among regions, there are inconsistencies in the outcome of these surveys. To explore the relationship between atmospheric pollution and hospital visits for pneumonia under the climate and pollution conditions in Qingdao, we carried out this study. METHODS: The medical records of pneumonia patients were gathered from the affiliated hospital of Qingdao University during Jan 1st, 2014, and Dec 31st,2018. Daily concentrations of PM(2.5), PM(10), SO(2), NO(2), as well as CO, were collected from the national air quality monitoring stations in Qingdao. Case-crossover study design and conditional logistic regression model were used to estimate the associations. Daily temperature, relative humidity, and atmospheric pressure were adjusted as the covariates in all models. A principal component analysis was used to solve the multicollinearity between atmospheric pollutants and investigate the relationship between various air pollutants and pneumonia occurs. RESULTS: In the single pollutant model, with interquartile range increment of the density of PM(2.5), PM(10), NO(2) and SO(2) at the lag2 days, the odds ratio of hospital visits for pneumonia patients increased by 6.4% (95%CI, 2.3-10.7%), 7.7% (95%CI, 3.2-12.4%), 6.7% (95%CI, 1.0-12.7%), and 7.2% (95%CI, 1.1-13.5%). Stratified analysis showed that pollutants were more significant in the cold period. Besides, the impact of atmospheric particulates on different ages mainly occurs in the young child (0 to 3-year-old). The odds ratio was 1.042 (95%CI, 1.012-1.072) when the principal components of atmospheric pollutants were included in the conditional logistic model. CONCLUSIONS: Our study found a significant relationship between short-term uncovering to PM(2.5), PM(10), NO(2), SO(2), and hospital visits for pneumonia in Qingdao. The effect of atmospheric pollutants mainly arose in a cold period. The particulate matter might be the principal reason in inducing hospital visits for pneumonia.
The national lockdown policies have drastically disrupted socioeconomic activities during the COVID-19 pandemic in China, which provides a unique opportunity to investigate the air quality response to such anthropogenic disruptions. And it is meaningful to evaluate the potential health impacts of air quality changes during the lockdown, especially for PM(2.5) with adverse health effects. In this study, by using PM(2.5) observations from 1388 monitoring stations nationwide in China, we examine the PM(2.5) variations between the COVID-19 lockdown (February and March in 2020) and the same period in 2015-2019, and find that the national average of PM(2.5) decreases by 18 μg/m(3), and mean PM(2.5) for most sites (about 75%) decrease by 30%-60%. The anthropogenic and meteorological contributions to these PM(2.5) variations are also determined by using a stepwise multiple linear regression (MLR) model combined with the Kolmogorov-Zurbenko filter. Our results show that the change of anthropogenic emissions is a leading contributor to those widespread PM(2.5) reductions, and meteorological conditions have the negative influence on PM(2.5) reductions for some regions, such as Beijing-Tianjin-Hebei (BTH). Additionally, the avoided premature death due to PM(2.5) reduction is estimated as a predicted number based on a log-linear concentration-response function. The total avoided premature death is 9952 in China, with dominant contribution (94%) from anthropogenic emission changes. For BTH, Yangtze River Delta, Pearl River Delta and Hubei regions, the reductions of PM(2.5) are 24.1, 24.3, 13.5 and 29.5 μg/m(3), with the avoided premature deaths of 1066, 1963, 454 and 583, respectively.
Interests in evaluation of the effect of air pollution and weather conditions on cardiovascular disease have increased. However, the relationship between short-term particulate matter (PM) exposure and first incident ST-elevation myocardial infarction (STEMI) remains unclear. Medical records were collected from December 2013 to December 2016. A total of 1354 patients with first incident STEMI were included. The daily average of air pollution and weather conditions were calculated. In this case-crossover study, conditional logistic regression was performed to assess the association between daily concentrations of PM and first incident STEMI. The daily average of PM(2.5) and PM(10) were 58.9 μg/m(3) and 80.2 μg/m(3), respectively. In this case-crossover study, single-pollutant models showed that each 10 μg/m(3) increase in PM(2.5) was associated with a percent change of 3.36, 95% confidence interval (CI): (1.01-5.77), or in PM(10) percent change of 2.1%, 95%CI: (0.2-4.04) for patients with first incident STEMI. The association remained stable after adjusting for ozone (O(3)). The results from subgroup analysis showed the association slightly enhanced in women, elder patients, patients with history of diabetes, patients without history of smoking, and cold seasons. The p values were not significant between these strata, which may be due to small sample size. This investigation showed that short-term PM exposure associated with first incident STEMI in Suzhou. Given the effect of PM on the first incident STEMI, strategies to decrease PM should be considered.
Purpose The association between atmospheric particulate matter and emergency room visits for cerebrovascular disease were evaluated in Beijing. Methods A generalized additive model was used to evaluate the associations between particulate matter and cerebrovascular disease, based on the daily data of meteorological elements, PM concentrations, and emergency room (ER) visits for cerebrovascular disease in Beijing from 2009 to 2012. Long-term trends and the effects of holidays, the day of the week, and confounding factors were controlled to determine the lag effect at 0-6 days. Single- and double-pollutant models were employed for different age and sex groups. Results The effect of PM2.5 concentration on the number of daily ER visits for cerebrovascular disease was much stronger than that of PM10 concentration. PM2.5 and PM10 had maximum RR values of 1.096 and 1.054 at lag 6 for patients aged 61-75 years. For each inter-quartile range (IQR) increase in PM10 concentration, the maximum RR values for the total, males, females, aged 15-60 years, aged 61-75 years, and aged > 75 years were 1.024, 1.044, 1.043, 1.038, 1.054, and 1.032, respectively. For each IQR increase in PM2.5 concentration, the maximum RR values for the total, males, females, aged 15-60 years, aged 61-75 years, and aged > 75 years were 1.038, 1.064, 1.076, 1.054, 1.096, and 1.049, respectively. The RR values of the double-pollutant models were lower than those of the single-pollutant models. Conclusion This study showed that the effects of PM pollution on cerebrovascular disease were different among different gender and age groups, and aged 61-75 years were mostly sensitive to particulate matters. The effects of PM2.5 on cerebrovascular disease were stronger than those of PM10. Our results can provide scientific evidence for the local government to take effective measures to improve air quality and the health of residents.
BACKGROUND: The hospitalization for asthma exacerbation has varied with seasons, however, the underlying weather reasons have not been fully explored yet. This study is aimed to explore the effect of weather factors on increased number of hospitalization due to worsening of asthma symptoms. This will provide more information to the relevant authorities to allocate appropriate medical resources as per the weather conditions in Qingdao, China. METHODS: All adult patients admitted for asthma exacerbation from 1 January, 2017 to 31 December, 2019 were enrolled from 13 main hospitals of Qingdao. The clinical data, including age, sex, smoking history, etc., were collected from the electronic medical record (EMR) systems. The hourly air quality of Qingdao from 2017-2019, including the air quality index (AQI), PM(2.5) and PM(10), was obtained from the China National Environmental Monitoring Centre. All these parameters during 2017-2019 were compared monthly. For meteorological data, the monthly horizontal wind at 850 hPa and vertical velocity at 500 hPa during 1960-2020 were obtained from National Center for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) global reanalysis dataset. The correlation analysis was applied to determine the association between asthma hospitalizations and the environmental factors, including atmospheric pressure, humidity, vertical visibility, and etc., monthly. RESULTS: In all, 10,549 asthmatic inpatients (45.7% males, 54.3% females) were included in the study. The inpatients number for asthma exacerbation had a plateau lasting from March to June of 2019, accompanied with high PM(2.5) and PM(10), as well as bad air quality from January to March of 2019, potentially governed by the El Niño event in 2018. However, there was no significance correlation between the number of asthma hospitalizations and the average value of all environmental factors. CONCLUSIONS: The high rate of hospitalization for asthma exacerbation in Qingdao during the spring of 2019 was associated with the unfavorable weather conditions, which might be linked to the atmospheric circulation in East Asia.
Particulate matter (PM) has been proved to be a risk factor for the development of circulatory system diseases (CSDs) around the world. In this study, we collected daily air pollutants, emergency room (ER) visits for CSDs, and meteorological data from 2009 to 2012 in Beijing, China. After controlling for the long-term trend and eliminating the influence of confounding factors, the generalized additive model (GAM) was used to evaluate the short-term effects of PM(10) on CSDs and cause-specific diseases. The results showed that for every 10 μg/m(3) increase in PM(10), the largest effect estimates in ER visits of total CSDs, arrhythmia, cerebrovascular diseases, high blood pressure, ischemic heart disease and other related diseases were 0.14% (95% CI: 0.06-0.23%), 0.37% (95% CI: – 0.23 to 0.97%), 0.20% (95% CI: 0.00-0.40%), 0.15% (95% CI: 0.02-0.27%), 0.18% (95% CI: 0.02-0.35%) and 0.35% (95% CI: – 0.04 to 0.79%), respectively. When NO(2) or SO(2) was added into the model, the effect estimates of PM(10) were mostly attenuated, while in those models with PM(2.5) added, the effect estimates of PM(10) were mostly increased. Stratified analysis indicated that PM(10) had a greater effect on males and the elderly.
BACKGROUND: Particulate matter (PM) pollution is a well-known risk factor of stroke. However, little is known about the association between PM(1) (aerodynamic diameter ≤ 1.0 μm) and stroke. We estimated the associations of short-term exposure to PM(1) with hospital admission and recurrence of stoke in China. METHODS: Stroke data were derived from the Chinese Stroke Center Alliance (CASA) program conducted in 1458 hospitals in 292 Chinese cities from 2015 to 2019. Daily air pollution and meteorological data were collected in the cities where studied hospitals were located. Daily PM(1) concentration was estimated by a generalized additive model (GAM) using PM(2.5) and meteorological variables. A time-stratified case-crossover design was applied to estimate the associations of short-term exposure to PM(1) with hospital admission of stroke. A GAM model was used to estimate the association between average PM(1) exposure during hospitalization and the recurrence of stroke. RESULTS: A total of 989,591 stroke cases were included in the study. Each 10 μg/m(3) increase in PM(1) (lag06-day) was associated with a 0.53% (95%CI, 0.39%, 0.67%) increment in hospital admission for stroke. The adverse effects of PM(1) on ischemic stroke was stronger than on intracerebral hemorrhage. We found the associations were significant in Northeast (0.94%, 95%CI, 0.51%, 1.38%), North (0.47%, 95%CI, 0.20%, 0.75%), Central (0.57%, 95%CI, 0.30%, 0.85%), and East China (0.63%, 95%CI, 0.27%, 0.99%). Of all stroke cases, 62,988 (6.4%) had recurrent stoke attack during their hospitalization. Each 10 μg/m(3) increase in PM(1) was associated with a 1.64% (95%CI, 1.28%, 2.01%) increment in recurrence of stroke during hospitalization. CONCLUSIONS: Short-term exposure to PM(1) may increase the risk of incidence and recurrence of stroke in China, and the effects varied across different types of stroke and regions. Geographically targeted strategies and measures are needed to control air pollution for reducing the burden of stroke from PM(1).
BACKGROUND: Nationwide studies that examine climatic modification effects on the association between air pollution and health outcome are limited in developing countries. Moreover, few studies focus on PM1 pollution despite its greater health effect. OBJECTIVES: This study aims to determine the modification effects of climatic factors on the associations between PM1 and the incidence rates of lung cancer for males and females in China. METHODS: We conducted a nationwide analysis in 345 Chinese counties (districts) from 2014 to 2015. Mean air temperature and relative humidity over the study period were used as the proxies of climatic conditions. In terms of the multivariable linear regression model, we examined climatic modification effects in the stratified and combined datasets according to the three-category and binary divisions of climatic factors. Moreover, we performed three sensitivity analyses to test the robustness of climatic modification effects. RESULTS: We found a stronger association between PM1 and the incidence rate of male lung cancer in counties with high levels of air temperature or relative humidity. If there is a 10 μg/m(3) shift in PM1, then the change in male incidence rate relative to its mean was higher by 4.39% (95% CI: 2.19, 6.58%) and 8.37% (95% CI: 5.18, 11.56%) in the middle and high temperature groups than in the low temperature group, respectively. The findings of climatic modification effects were robust in the three sensitivity analyses. No significant modification effect was discovered for female incidence rate. CONCLUSIONS: Male residents in high temperature or humidity counties suffer from a larger effect of PM1 on the incidence rate of lung cancer in China. Future research on air pollution-related health impact assessment should consider the differential air pollution effects across different climatic conditions.
RATIONALE & OBJECTIVE: Increasing evidence has linked ambient fine particulate matter (ie, particulate matter no larger than 2.5 μm [PM(2.5)]) to chronic kidney disease (CKD), but their association has not been fully elucidated, especially in regions with high levels of PM(2.5) pollution. This study aimed to investigate the long-term association of high PM(2.5) exposure with incident CKD in mainland China. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: 72,425 participants (age ≥18 years) without CKD were recruited from 121 counties in Hunan Province, China. EXPOSURE: Annual mean PM(2.5) concentration at the residence of each participant derived from a long-term, full-coverage, high-resolution (1 × 1 km(2)), high-quality dataset of ground-level air pollutants in China. OUTCOMES: Incident CKD during the interval between the baseline examination of each participant (2005-2017) and the end of follow-up through 2018. ANALYTICAL APPROACH: Cox proportional hazards models were used to estimate the independent association of PM(2.5) with incident CKD and the joint association of PM(2.5) with temperature or humidity on the development of PM(2.5)-related CKD. Restricted cubic splines were used to model exposure-response relationships. RESULTS: Over a median follow-up of 3.79 (IQR, 2.03-5.48) years, a total of 2,188 participants with incident CKD were identified. PM(2.5) exposure was associated with incident CKD with an adjusted hazard ratio of 1.71 (95% CI, 1.58-1.85) per 10-μg/m(3) greater long-term exposure. Multiplicative interactions between PM(2.5) and humidity or temperature on incident CKD were detected (all P < 0.001 for interaction), whereas an additive interaction was detected only for humidity (relative risk due to interaction, 3.59 [95% CI, 0.97-6.21]). LIMITATIONS: Lack of information on participants' activity patterns such as time spent outdoors. CONCLUSIONS: Greater long-term ambient PM(2.5) pollution is associated with incident CKD in environments with high PM(2.5) exposure. Ambient humidity has a potentially synergetic effect on the association of PM(2.5) with the development of CKD. PLAIN-LANGUAGE SUMMARY: Exposure to a form of air pollution known as fine particulate matter (ie, particulate matter ≤2.5 μm [PM(2.5)]) has been linked to an increased risk of chronic kidney disease (CKD), but little is known about how PM(2.5) affects CKD in regions with extremely high levels of PM(2.5) pollution. This longitudinal cohort study in China investigates the effect of PM(2.5) on the incidence of CKD and whether temperature or humidity interact with PM(2.5). Our findings suggest that long-term exposure to high levels of ambient PM(2.5) significantly increased the risk of CKD in mainland China, especially in terms of cumulative average PM(2.5). The associations of PM(2.5) and incident CKD were greater in high-humidity environments. These findings support the recommendation that reducing PM(2.5) pollution should be a priority to decrease the burden of associated health risks, including CKD.
Facing the dual challenges of air pollution and climate change, China has set ambitious goals and made decisive efforts to reduce its carbon emission and win the ‘Battle for Blue Sky’. However, how the low-carbon transition and air quality targets could be simultaneously achieved at the sub-national levels remains unclear. The questions arise whether province-level climate change mitigation strategies could help ease the air pollution and close the air quality gap, and how these co-benefits can be compared with the cost of the green transition. Here, using an integrated modeling framework, we combined with local air pollutant emission inventories and issued policy documents to quantitatively evaluated the current situation and targets of the air quality and health co-benefits of deep carbon mitigation in Sichuan, a fast-developing inland province in China. We found that by 2035, without system-wide energy transformation induced by carbon mitigation policies, the improvement in air quality in Sichuan Province might be limited, even under stringent end-of-pipe emission control measures. On the contrary, the co-benefits of low-carbon policies would be significant. On top of stringent end-of-pipe controls, the implementation of carbon mitigation policy in line with China’s enhanced climate target could further reduce the average PM2.5 concentration in Sichuan by as much as 2.8 mu g m(-3), or the population-weighted PM2.5 concentration by 5.9 mu g m(-3) in 2035. The monetized health co-benefits in Sichuan Province would amount to 23 billion USD under the stringent carbon mitigation scenario, exceeding 1.7 billion USD of the mitigation cost by 2035. The results indicate that significant air quality and health benefits could both be achieved from carbon mitigation at the provincial level. Both air-pollution or carbon-reduction oriented policies would be important for improving environmental quality and public health.
INTRODUCTION: PM(2.5) and climate change are two major public health concerns, with majority of the research on their interaction focused on the synergistic effect, particularly for extreme events such as hot or cold temperatures. The climate sustainability index (CLS) was introduced to comprehensively explore the impact of climate change and the interactive effect on human health with air pollution. METHODS: In this study, a county-level panel data in China was collected and used. The generalized additive model (GAM) and geographically and temporally weighted regression (GTWR) was used to explore the interactive and spatial effect on mortality between CLS and PM(2.5). RESULTS AND DISCUSSIONS: Individually, when CLS is higher than 150 or lower than 50, the mortality is higher. Moreover, when PM(2.5) is more than 35 μg/m(3), the influence on mortality is significantly increased as PM(2.5) concentration rises; when PM(2.5) is above 70 μg/m(3), the trend is sharp. A nonlinear antagonistic effect between CLS and PM(2.5) was found in this study, proving that the combined adverse health effects of climate change and air pollution, especially when CLS was lower (below 100) and PM(2.5) was higher (above 35 μg/m(3)), the antagonistic effect was much stronger. From a spatial perspective, the impact of CLS and PM(2.5) on mortality varies in different geographical regions. A negative and positive influence of CLS and PM(2.5) was found in east China, especially in the northeastern and northern regions, -which were heavily polluted. This study illustrated that climate sustainability, at certain level, could mitigate the adverse health influence of air pollution, and provided a new perspective on health risk mitigation from pollution reduction and climate adaptation.
In China, the rapid development of the economy and implementation of multiple emission control policies in recent decades have been accompanied by dramatic changes in air quality. In this study, PM(2.5) concentrations estimated by using MERRA-2 reanalysis data were integrated into the Global Exposure Mortality Model (GEMM) to explore the spatiotemporal variation of nationwide PM(2.5)-related premature mortality from 1990 to 2019, and the driving factors behind decadal changes were evaluated. Since 2000, as a result of PM(2.5) pollution, air quality in China has deteriorated substantially, especially in the fast-developing eastern and southern parts. In 2009, the nationwide population-weighted (PW) PM(2.5) concentration peaked at 41.4 μg/m(3) (95% confidence interval [CI], 36.7-46.2). Simultaneously, the GEMM results revealed that nationwide PM(2.5)-related deaths increased remarkably from 1089 (95% CI, 965-1210) thousand in 1990 to 1795 (1597-1986) thousand in 2009. The implementation of the toughest-ever Air Pollution Prevention and Control Action Plan (APPCAP) in 2013 effectively controlled PM(2.5) pollution in China. By 2018, the nationwide PW PM(2.5) concentration had decreased to 34.0 (29.2-38.9) μg/m(3). Dynamic trend prediction revealed that, although the APPCAP achieved substantial health benefits, the policy did not result in further remarkable reductions in PM(2.5)-related deaths; in 2019, deaths peaked at 1932 (1716-2140) thousand. PM(2.5)-related deaths in 2030 were projected for each of four emission control scenarios. The results of the driving factor analysis and the future projections indicated that the health benefits from improving air quality are likely to be counterbalanced by changes in the population age structure. Because population ageing is becoming more and more rapid in China and the challenge of climate change is increasing, the results of this study imply that policymakers need to implement more stringent measures and set more ambitious emission control targets to reduce nationwide PM(2.5)-related premature mortality in the future.
Exposure to fine particulate matter (PM(2.5)) has become a major global health concern. Although modeling exposure to PM(2.5) has been examined in China, accurate long-term assessment of PM(2.5) exposure with high spatiotemporal resolution at the national scale is still challenging. We aimed to establish a hybrid spatiotemporal modeling framework for PM(2.5) in China that incorporated extensive predictor variables (satellite, chemical transport model, geographic, and meteorological data) and advanced machine learning methods to support long-term and short-term health studies. The modeling framework included three stages: (1) filling satellite aerosol optical depth (AOD) missing values; (2) modeling 1 km × 1 km daily PM(2.5) concentrations at a national scale using extensive covariates; and (3) downscaling daily PM(2.5) predictions to 100-m resolution at a city scale. We achieved good model performances with spatial cross-validation (CV) R(2) of 0.92 and temporal CV R(2) of 0.85 at the air quality sites across the country. We then estimated daily PM(2.5) concentrations in China from 2013 to 2019 at 1 km × 1 km grid cells. The downscaled predictions at 100 m resolution greatly improved the spatial variation of PM(2.5) concentrations at the city scale. The framework and data set generated in this study could be useful to PM(2.5) exposure assessment and epidemiological studies.
Previous studies demonstrated that global warming can lead to deteriorated air quality even when anthropogenic emissions were kept constant, which has been called a climate change penalty on air quality. It is expected that anthropogenic emissions will decrease significantly in the future considering the aggressive emission control actions in China. However, the dependence of climate change penalty on the choice of emission scenario is still uncertain. To fill this gap, we conducted multiple independent model simulations to investigate the response of PM2.5 to future (2050) climate warming (RCP8.5) in China but with different emission scenarios, including the constant 2015 emissions, the 2050 CLE emissions (based on Current Legislation), and the 2050 MTFR emissions (based on Maximum Technically Feasible Reduction). For each set of emissions, we estimate climate change penalty as the difference in PM2.5 between a pair of simulations with either 2015 or 2050 meteorology. Under 2015 emissions, we find a PM2.5 climate change penalty of 1.43 mu g m(-3) in Eastern China, leading to an additional 35,000 PM2.5-related premature deaths [95% confidence interval (CI), 21,000-40,000] by 2050. However, the PM2.5 climate change penalty weakens to 0.24 mu g m(-3) with strict anthropogenic emission controls under the 2050 MTFR emissions, which decreases the associated PM2.5-related deaths to 17,000. The smaller MTFR climate change penalty contributes 14% of the total PM2.5 decrease when both emissions and meteorology are changed from 2015 to 2050, and 24% of total health benefits associated with this PM2.5 decrease in Eastern China. This finding suggests that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM2.5 and its associated premature deaths, even though a climate change penalty still occurs even under MTFR. Strengthened controls on anthropogenic emissions are key to attaining air quality targets and protecting human health in the context of future global climate change. (C) 2020 Elsevier B.V. All rights reserved.
OBJECTIVES: Evidence of childhood asthma hospitalizations associated with temperature variability (TV) and the attributable risk are limited in China. We aim to use a comprehensive index that reflected both intra- and inter-day TV to assess the TV-childhood asthma relationship and disease burden, further to identify seasonality vulnerable populations, and to explore the effect modification of PM(2.5). METHODS: A quasi-distributed lagged nonlinear model (DLNM) combined with a linear threshold function was applied to estimate the association between TV and childhood asthma hospitalizations during 2013-2016 in Hefei, China. Subgroup analysis was conducted by age and sex. Disease burden is reflected by the attributable fraction and attributable number. Besides, modifications of PM(2.5) were tested by introducing the cross-basis of TV and binary PM(2.5) as an interaction term. RESULTS: The risk estimates peaked at TV(0-3) and TV(0-4) in the cool and the warm season separately, with RR of 1.051 (95%CI: 1.021-1.081) and 1.072 (95%CI: 1.008-1.125), and the effects lasted longer in the cool season. The school-age children in the warm season and all subgroups except pre-school children in the cool season were vulnerable to TV. It is estimated that the disease burden related to TV account for 6.2% (95% CI: 2.7%-9.4%) and 4% (95% CI: 0.6%-7.1%) during the cool and warm seasons in TV(0-3). In addition, the risks of TV were higher under the high PM(2.5) level compared with the low PM(2.5) level in the cool season, although no significant differences between them. CONCLUSIONS: TV exposure significantly increases the risk and disease burden of childhood asthma hospitalizations, especially in the cool season. More medical resources should be allocated to school-age children. Giving priority to pay attention to TV in the cool season in practice could obtain the greatest public health benefits and those days with high TV and high PM(2.5) need more attention.
Global warming increases the probability of extreme events and heat waves triggering severe impacts on human health, especially the elderly. Taiwan is an aged society, so residential buildings, which cannot withstand extreme temperature events, increase the risk of harm for the elderly. Furthermore, Taiwanese prefer to open the windows to reduce indoor high temperatures, which causes high levels of outdoor PM2.5 to flow indoors, leading to health risks. Therefore, this research proposes a strategy to create a house with a low temperature and a low PM2.5 health risk for the elderly based on building envelope renovation and windows user behavior patterns. The risk day is demonstrated as an index to evaluate the indoor environment quality, which is based on the number of days that exceed the health risk threshold. The results show that the performance improvement of the building envelope and control of the window opening timing can effectively reduce the risk days by 48.5%. This means that passive strategies cannot fully control health risks, and the use of equipment is necessary. Finally, if the current situation is maintained without any adjustment or strategy improvement, an additional 41.3% energy consumption must be paid every year to control health risks.
Mental health conditions have the potential to be worsened by air pollution or other climate-sensitive factors. Few studies have empirically examined those associations when we faced to co-exposures, as well as interaction effects. There would be an urgent need to use deep learning to handle complex co-exposures that might interact in multiple ways, and the model performance reinforced by SHapely Additive exPlanations (SHAP) enabled our predictions interpretable and hence actionable. Here, to evaluate the mixed effect of short-term co-exposure, we conducted a time-series analysis using approximately 1.47 million hospital outpatient visits of mental disorders (i.e., depressive disorder-DD, Schizophrenia-SP, Anxiety Disorder-AD, Bipolar Disorder-BD, Attention Deficit and Hyperactivity Disorder-ADHD, Autism Spectrum Disorder-ASD), with matched meteorological observations from 2015 through 2019 in Nanjing, China. The global insights of gated recurrent unit model revealed that most of input features with similar effect size caused the illness risk of SP and ASD increase, and most markedly, 73% of relative humidity, 44.6 µg/m(3) of NO(2), and 14.1 µg/m(3) of SO(2) at 5-year average level associated with 2.27, 1.14, and 1.29 visits increase for DD, SP, and AD, respectively. Both synergic and antagonistic effect among informative paired-features were distinguished from local feature dependence. Interestingly, variation tendencies of excessive visits of bipolar disorder when atmospheric pressure, PM(2.5), and O(3) interacted with one another were inconsistent. Our results provided added qualitative and quantitative support for the conclusion that short-term co-exposure to ambient air pollutants and meteorological conditions posed threats to human mental health.
To examine Beijing residents’ risk perception of contracting smog-related diseases, we proposed a model in which air-pollution knowledge is a theoretical mechanism accounting for the influence on risk perception of exposure to environmental news and exposure to Under the Dome, an environmental documentary about smog in China, which has been censored. Data (N = 523) were collected from Beijing residents from February to March in 2017. We analyzed the data using Hayes’ PROCESS macro. Findings revealed that environmental-news exposure is positively associated with both air-pollution knowledge and risk perception. Exposure to environmental news has an indirect effect on risk perception through air-pollution knowledge. Exposure to Under the Dome is positively related to risk perception but is not related to air-pollution knowledge. We contributed to the literature by empirically testing the impact of Under the Dome, which has been largely studied via the critical theory approach. Implications included that Under the Dome is a successful risk communication model and that its impact goes beyond increasing public risk perception of smog.
The coupling effects of sandstorm and dust from coal bases themselves can have a major impact on the atmospheric environment as well as on human health. The typical coal resource city of Wuhai in Inner Mongolia was selected in order to study these impacts during a severe sandstorm event in March 2021. Particulate matter (PM1, PM2.5 and PM10) and total suspended particulate matter (TSP) samples were collected during the sandstorm event of 15-19 March 2021 and non-sandstorm weather (11-13 March 2021) and analyzed for their chemical composition. The concentrations of PM1, PM2.5, PM10 and TSP in Wuhai city during the sandstorm were 2.2, 2.6, 4.8 and 6.0 times higher than during non-sandstorm days, respectively. Trace metals concentrations in particles of different sizes generally increased during the sandstorm, while water-soluble ions decreased. Positive matrix fraction (PMF) results showed that the main sources of particles during both sandstorm and non-sandstorm days were industrial emissions, traffic emissions, combustion sources and dust. The proportion of industrial emissions and combustion sources increased compared with non-sandstorm days, while traffic emissions and dust decreased. The backward trajectory analysis results showed that airflows were mainly transported over short distances during non-sandstorm days, and high concentration contribution source areas were from southern Ningxia, southeast Gansu and western Shaanxi. The airflow was mainly transported over long distances during the sandstorm event, and high concentration contribution source areas were from northwestern Inner Mongolia, southern Russia, northern and southwestern Mongolia, and northern Xinjiang. A health risk analysis showed that the risk to human health during sandstorm days related to the chemical composition of particles was generally 1.2-13.1 times higher than during non-sandstorm days. Children were more susceptible to health risks, about 2-6.3 times more vulnerable than adults to the risks from heavy metals in the particles under both weather conditions.
BACKGROUND: Fine particulate matter (PM(2.5)) pollution is one of the most critical environmental and public health problems in China and has caused an enormous disease burden, especially long-term PM(2.5) exposure. Global climate change represents another environmental challenge in the coming decades and is also an essential factor affecting PM(2.5) pollution. Moreover, China has an aging population with a changing population size and falling age-standardized mortality rates. However, little evidence exists evaluating the potential impacts from climate change and population aging on the long-term PM(2.5) exposure-related disease burden. This study quantifies the impacts of climate and population changes on changes in the disease burden attributed to long-term PM(2.5) exposure from 2015 to 2030 in mainland China, which could add evidence for the revision of relevant environmental standards and health policies. METHODS: This modeling study investigated long-term PM(2.5) exposure-related mortality across China based on PM(2.5) projections under Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) and population scenarios from shared socioeconomic pathways (SSPs). PM(2.5) concentrations were simulated by the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) modeling systems. In addition, three types of population projections in 2030 relative to 2015 were set up as follows: (i) the population remained the same as that in 2015; (ii) the population size changed under SSPs, but the age structure remained the same; (iii) both the population size and age structure changed under SSPs. The global exposure mortality model (GEMM) was adopted to estimate PM(2.5)-related premature deaths. RESULTS: Ambient PM(2.5) concentrations decreased from 2015 to 2030 under the two climate and emission scenarios. Estimates of related premature mortality in 2030 declined compared with that in 2015 due to lower PM(2.5) concentrations (RCP4.5: -16.8%; RCP8.5: -16.4%). If the age structure of the population remained unchanged and the population size changed under SSPs, the nonaccidental premature mortality also showed a decrease ranging from -18.6% to -14.9%. When both population size and age structure changed under SSPs, the population in China would become older. Nonaccidental premature mortality would sharply increase by 35.7-52.3% (with a net increase of 666-977 thousand) in 2030. CONCLUSION: The PM(2.5) pollution in 2030 under both RCP4.5 and RCP8.5 would slightly improve. The population sizes in 2030 projected by SSPs are relatively stable compared with that in 2015. However, the modest decrease due to air pollution improvement and stable population size would be offset by population aging.
This study examines the impact of air pollution from straw burning on human cognitive health in China by linking household health surveys with PM2.5 emissions derived from remote sensing data on fire activity. The identification strategy leverages the spatial dispersion of air pollutants due to exogenous wind directions. The results indicate that PM2.5 emissions from upwind straw burning have a negative impact on cognitive functions of respondents aged 55 and above, but PM2.5 emissions from downwind fires do not. The impact is transitory and caused by contemporaneous PM2.5 emissions on the day of cognitive testing. Our findings demonstrate a link from air pollution to cognitive declines and suggest that through this link, climate change could result in additional health costs by increasing the risk of wildfires.
Hypertension (HTN) was a major preventable cause of cardiovascular disease (CVD), contributing to a huge disease burden. Ambient temperature, air pollution and green space were important influencing factors of HTN, and few studies have assessed the effects and interactions of ambient temperature, air pollution and green space on HTN in rural areas. In this study, we selected 8400 individuals randomly in rural areas of Anhui Province by a multi-stage stratified cluster sampling. A total of 8383 individuals were included in the final analysis. We collected particulate pollutants and meteorological data from the local air quality monitoring stations and National Center for Meteorological Science from January 1 to December 31, 2020, respectively. The normalized differential vegetation index (NDVI) of Anhui Province in 2020 was produced and processed by remote sensing inversion on the basis of medium resolution satellite images. The average annual mean exposure concentrations of air pollution, meteorological factors, and NDVI were calculated for each individual based on the geocoded residential address. HTN was defined according the Chinese Guidelines for Prevention and Treatment of HTN. The effects and interactions of ambient temperature, air pollution and green space on HTN were evaluated by generalized linear model and interaction model, respectively. In this study, the prevalence of HTN was 24.14%. The adjusted odd ratio of HTN for each 1 μg/m(3) increasing in PM(2.5) and PM(10), 1 °C of ambient temperature, and 0.1 of NDVI were:1.276 (1.013, 1.043), 1.012 (1.006, 1.018), 0.862 (0.862, 0.981) and 0.669 (0.611, 0.733), respectively. The results showed that air pollutants were positively correlated with HTN, while ambient temperature and green space were negatively correlated with HTN. Meanwhile, the negative associations of green space on HTN could decrease with the increasing concentrations of air pollution, but increase with the rising of ambient temperature.
BACKGROUND: While temperature changes have been confirmed as one of the contributory factors affecting human health, the association between high-frequency temperature variability (HFTV, i.e., temperature variation at short time scales such as 1, 2, and 5 days) and the hospitalization of chronic obstructive pulmonary disease (COPD) was rarely reported. OBJECTIVES: To evaluate the associations between high-frequency temperature variabilities (i.e., at 1, 2, and 5-day scales) and daily COPD hospitalization. METHODS: We collected daily records of COPD hospitalization and meteorological variables from 2013 to 2017 in 21 cities of Guangdong Province, South China. A quasi-Poisson regression with a distributed lag nonlinear model was first employed to quantify the effects of two HFTV measures, i.e., the day-to-day (DTD) temperature change and the intraday-interday temperature variability (IITV), on COPD morbidity for each city. Second, we used multivariate meta-analysis to pool the city-specific estimates, and stratified analyses were performed by age and sex to identify vulnerable groups. Then, the meta-regression with city-level characteristics was employed to detect the potential sources of the differences among 21 cities. RESULTS: A monotonic increasing curve of the overall exposure-response association was observed, suggesting that positive HFTV (i.e., increased DTD and IITV) will significantly increase the risk of COPD admission. Negative DTD was associated with reduced COPD morbidity while positive DTD elevated the COPD risk. An interquartile range (IQR) increase in DTD was associated with a 24% (95% CI: 12-38%) increase in COPD admissions. An IQR increase in IITV(0-1) was associated with 18% (95% CI: 7-27%) increase in COPD admissions. Males and people aged 0-64 years appeared to be more vulnerable to the DTD effect than others. Potential sources of the disparity among different cities include urbanization level, sex structure, industry structure, gross domestic product (GDP), health care services, and air quality. CONCLUSIONS: The increases of DTD and IITV have significant adverse impacts on COPD hospitalization. As climate change intensifies, precautions need to be taken to mitigate the impacts of high-frequency temperature changes.
OBJECTIVE: Most evidence comes from studies show that ambient ozone(O(3)) pollution has become a big issue in China. Few studies have investigated the impact of ozone spatiotemporal patterns on respiratory mortality and cardiovascular mortality in Nanchang city. Thus, this study aimed to explore the health effect of ozone exposure on respiratory mortality and cardiovascular mortality in Nanchang, Jiangxi Province. METHODS: Using the daily mortality data, atmospheric routine monitoring data and meteorological data in Nanchang from 2014 to 2020, we performed a generalized additive model (GAM) based on the poisson distribution in which time-series analysis to calculate the risk correlation between respiratory mortality and cardiovascular mortality and ozone exposure level (8h average ozone concentration, O(3)-8h). Besides, analyses were also stratified by season, age and sex. RESULTS: In the single-pollutant model, for every 10 μg/m(3) increase in ozone, respiratory mortality increased 1.04% with 95% confidence interval (CI) between 0.04 and 1.68%, and cardiovascular mortality increased 1.26% (95%CI: 0.68 ~ 1.83%). In the multi-day moving average lag model, the mortality of respiratory diseases and cardiovascular diseases reached a relative risk peak on the cumulative lag5 (1.77%,95%CI: 0.99 ~ 2.57%) and the cumulative lag3 (1.68%,95%CI: 0.93 ~ 2.45%), respectively. The differences were statistically significant (P < 0.05). Results of the stratified analyses showed the effect value of respiratory mortality in people aged ≥65 years was higher than aged <65 years, whereas the greatest effect of cardiovascular mortality in people aged <65 years than aged ≥65 years. Ozone had a more profound impact on females than males in respiratory diseases and cardiovascular diseases. In winter and spring, ozone had a obvious impact on respiratory mortality, and effects of ozone pollution on cardiovascular mortality were stronger in summer and winter. There was a statistically significant difference of respiratory mortality in winter and spring and of cardiovascular mortality in summer and winter (P < 0.05). CONCLUSIONS: In the long run, the more extreme the pollution of ozone exposure, the higher the health risk of residents' respiratory mortality and cardiovascular mortality. Therefore, the government should play an important role in the prevention and control ways of decreasing and eliminating the ozone pollution to protect the resident's health. The findings provide valuable data for further scientific research and improving environmental policies in Nanchang city.
Ambient ozone (O(3)) has emerged as an important public health issue worldwide. Previous studies found an association between O(3) and cardiorespiratory mortality. However, evidence was limited regarding the risk of O(3) on mortality from other diseases. In this study, we aimed to estimate the association between O(3) and mortality from a broad spectrum of diseases in Guangzhou, China, which has experienced a rapid increase in O(3) concentration over the past decades. Daily data were obtained on cause-specific mortality, air pollutant concentrations and weather conditions during 2013-2018. A generalized additive model with quasi-Poisson regression was applied to examine the association between O(3) and mortality from 10 broad causes and 26 refined subcategories, with adjustment of long-term and seasonal trends, weather conditions, public holidays and days of the week. We found that the threshold concentrations of O(3) were 40 μg/m(3) for all-cause, non-accidental, cardiovascular and respiratory mortality. Mortality risk increased monotonically with O(3) concentrations above the threshold. Per 10 μg/m(3) increase of O(3) at lag 0-3 days was associated with 0.54% (95%CI: 0.34-0.74%), 0.56% (95%CI: 0.36-0.76%), 0.59% (95%CI: 0.30-0.88%), 0.78% (95%CI: 0.33-1.24%) and 0.52% (95%CI: 0.21-0.83%) elevated risk of death from all causes, non-accidental causes, cardiovascular diseases, respiratory diseases and neoplasms, respectively. Among the subcategories, the largest effect estimate was observed in people with chronic obstructive pulmonary disease. The elderly suffered from a higher mortality risk from O(3). Stringent emission control strategies and multi-sectoral collaborations are needed to reduce the detrimental impact of O(3) on vulnerable populations.
Facing the dual challenges of climate change and air pollution, China has made great efforts to explore the co-control strategies for the both. We assessed the benefits of carbon and pollution control policies on air quality and human health, with an integrated framework combining an energy-economic model, an air quality model and a concentration-response model. With a base year 2015, seven combined scenarios were developed for 2030 based on three energy scenarios and three end-of-pipe control ones. Policy-specific benefits were then evaluated, indicated by the reduced emissions, surface concentrations of major pollutants, and premature deaths between scenarios. Compared to the 2030 baseline scenario, the nationwide PM(2.5)- and O(3)-related mortality was expected to decline 23% or 289 (95% confidence interval: 220-360) thousand in the most stringent scenario, and three quarters of the avoided deaths were attributed to the end-of-pipe control measures. Provinces in heavily polluted and densely populated regions would benefit more from carbon and pollution control strategies. The population fractions with PM(2.5) exposure under the national air quality standard (35 μg/m(3)) and WHO guideline (10 μg/m(3)) would be doubled from 2015 to 2030 (the most stringent scenario), while still very few people would live in areas with the WHO guideline achieved for O(3) (100 μg/m(3)). Increased health impact of O(3) suggested a great significance of joint control of PM(2.5) and O(3) in future policy-making.
Background This study investigated risks of mortality from and morbidity (emergency room visits (ERVs) and outpatient visits) of asthma and chronic obstructive pulmonary disease (COPD) associated with extreme temperatures, fine particulate matter (PM2.5), and ozone (O3) by sex, and age, from 2005 to 2016 in 6 metropolitan cities in Taiwan. Methods The distributed lag non-linear model was employed to assess age (0–18, 19–39, 40–64, and 65 years and above), sex-cause-specific deaths, ERVs, and outpatient visits associated with extreme high (99th percentile) and low (5th percentile) temperatures and PM2.5 and O3 concentrations at 90th percentile. Random-effects meta-analysis was adopted to investigate cause-specific pooled relative risk (RR) and 95% confidence intervals (CI) for the whole
studied areas. Results Only the mortality risk of COPD in the elderly men was significantly associated with the extreme low temperatures. Exposure to the 90th percentile PM2.5 was associated with outpatient visits for asthma in 0–18 years old boys [RR = 1.15 (95% CI: 1.09–1.22)]. Meanwhile, significant elevation of ERVs of asthma for females aged 40–64 years was associated with exposure to ozone, with the highest RR of 1.21 (95% CI: 1.05–1.39). Conclusions This study identified vulnerable subpopulations who were at risk to extreme events associated with ambient environments deserving further evaluation for adaptation.
BACKGROUND: The health effect of particulate matter pollution on stroke has been widely examined; however, the effect among patients with comorbid type 2 diabetes (T2D) in developing countries has remained largely unknown. METHODS: A time-series study was conducted to investigate the short-term effect of fine particulate matter (PM(2.5)) and inhalable particulate matter (PM(10)) on hospital admissions for stroke among patients with T2D in Beijing, China, from 2014 to 2018. An over-dispersed Poisson generalized additive model was employed to adjust for important covariates, such as weather conditions and long-term and seasonal trends. RESULTS: A total of 159,298 hospital admissions for stroke comorbid with T2D were reported. Approximately linear exposure-response curves were observed for PM(2.5) and PM(10) in relation to stroke admissions among T2D patients. A 10 μg/m(3) increase in the four-day moving average of PM(2.5) and PM(10) was associated with 0.14% (95% confidence interval [CI]: 0.05-0.23%) and 0.14% (95% CI: 0.06-0.22%) incremental increases in stroke admissions among T2D patients, respectively. A 10 μg/m(3) increase in PM(2.5) in the two-day moving average corresponded to a 0.72% (95% CI: 0.02-1.42%) incremental increase in hemorrhagic stroke, and a 10 μg/m(3) increase in PM(10) in the four-day moving average corresponded to a 0.14% (95% CI: 0.06-0.22%) incremental increase in ischemic stroke. CONCLUSIONS: High particulate matter might be a risk factor for stroke among patients with T2D. PM(2.5) and PM(10) have a linear exposure-response relationship with stroke among T2D patients. The study provided evidence of the risk of stroke due to particulate matter pollution among patients with comorbid T2D.
OBJECTIVE: To explore the relationship between ambient PM(2.5) level and outpatient visits of children with respiratory diseases in a megacity, Zhengzhou, in central China. METHODS: We collected daily outpatient visit data, air pollutant data, and meteorological data at the monitoring points of Zhengzhou from the time period 2018 to 2020 and used Spearman’s rank correlation to analyze the correlation between children’s respiratory outpatient visits and air pollutants and meteorological factors. Generalized additive models were used to analyze the association between PM(2.5) exposures and children’s respiratory outpatient visits. A stratified analysis was further carried out for the seasons. RESULTS: From 2018 to 2020, the total number of outpatients with children’s respiratory diseases was 79,1107, and the annual average concentrations of PM(2.5), PM(10), SO(2), NO(2), CO, and O(3)-8h in Zhengzhou were respectively 59.48 μg/m(3), 111.12 μg/m(3), 11.10 μg/m(3), 47.77 μg/m(3), 0.90 mg/m(3) and 108.81 μg/m(3). The single-pollutant model showed that the risk of outpatient visits for children with respiratory disease increased by 0.341% (95%CI: 0.274-0.407%), 0.532% (95%CI: 0.455-0.609%) and 0.233% (95%CI: 0.177-0.289%) for every 10 μg/m(3) increase in PM(2.5) with a 3-day lag, 1-day lag, and 1-day lag respectively for the whole year, heating period, and non-heating period. The multi-pollutant model showed that the risk of PM(2.5) on children’s respiratory disease visits was robust. The excess risk of PM(2.5) on children’s respiratory disease visits increased by 0.220% (95%CI: 0.147-0.294%) when SO(2) was adjusted. However, the PM(2.5) effects were stronger during the heating period than during the non-heating period. CONCLUSION: The short-term exposure to PM(2.5) was significantly associated with outpatient visits for children’s respiratory diseases. It is therefore necessary to strengthen the control of air pollution so as to protect children’s health.
Atmospheric coarse particulate matter (PM(10)) enriched with heavy metal(loid)s could pose potentially significant health risk to humans, while accurate health risk assessment calls for characterization of their bioaccessibility, besides the total contents. The health risk of major toxic heavy metal(loid)s in the PM(10) from four large cities in northern China via inhalation was investigated based on their total contents and bioaccessibility. The annual mean concentrations of PM-bound Zn, As, Pb, and Mn in the atmosphere of the four cities were 650, 305, 227, and 177 ng⋅m(-3), respectively. The levels of heavy metal(loid)s in the PM(10) were generally higher in winter but lower in summer in all four cities, which resulted primarily from the emissions associated with coal combustion for district and household heating and the unfavorable meteorological conditions in winter. The bioaccessibility of heavy metal(loid)s in the PM(10) ranged from 0.9 to 48.7%, following the general order of Mn > Co > Ni > Cd > Cu > As > Cr > Zn > Pb. Based on their total contents in the PM(10), most heavy metal(loid)s posed significant public health risk via inhalation exposure in the four cities. However, after accounting for the bioaccessibility of metal(loid)s, the non-carcinogenic risk of most metal(loid)s was negligible, except for As in the PM(10) of Jinzhong, while only the carcinogenic risk posed by Cr and As in the PM(10) exceeded the acceptable level. These findings demonstrate the importance of characterizing the bioaccessibility of airborne PM-bound heavy metal(loid)s in health risk assessment and could guide the on-going efforts on reducing the public health risk of PM(10) in northern China.
Air pollution has a serious fallout on human health, and the influences of the different urban morphological characteristics on air pollutants cannot be ignored. In this study, the relationship between urban morphology and air quality (wind speed, CO, and PM(2.5)) in residential neighborhoods at the meso-microscale was investigated. The changes in the microclimate and pollutant diffusion distribution in the neighborhood under diverse weather conditions were simulated by Computational Fluid Dynamics (CFD). This study identified five key urban morphological parameters (Building Density, Average Building Height, Standard Deviation of Building Height, Mean Building Volume, and Degree of Enclosure) which significantly impacted the diffusion and distribution of pollutants in the neighborhood. The findings of this study suggested that three specific strategies (e.g. volume of a single building should be reduced, DE should be increased) and one comprehensive strategy (the width and height of the single building should be reduced while the number of single buildings should be increased) could be illustrated as an optimized approach of urban planning to relief the air pollution. The result of the combined effects could provide a reference for mitigating air pollution in sustainable urban environments.
Evidence is still limited for the role of long-term PM(2.5) exposure in cerebrovascular diseases among residents in high pollution regions. The study is aimed to investigate the long-term effects of PM(2.5) exposure on stroke mortality, and further explore the effect modification of temperature variation on the PM(2.5)-mortality association in northern China. Based on a cohort data with an average follow-up of 9.8 years among 38,435 urban adults, high-resolution estimates of PM(2.5) derived from a satellite-based model were assigned to each participant. A Cox regression model with time-varying exposures and strata of geographic regions was employed to assess the risks of stroke mortality associated with PM(2.5), after adjusting for individual risk factors. The cross-product term of PM(2.5) exposure and annual temperature range was further added into the regression model to test whether the long-term temperature variation would modify the association of PM(2.5) with stroke mortality. Among the study participants, the annual mean level of PM(2.5) concentration was 66.3 μg/m(3) ranging from 39.0 μg/m(3) to 100.6 μg/m(3). For each 10 μg/m(3) increment in PM(2.5), the hazard ratio (HR) was 1.31 (95% CI: 1.04-1.65) for stroke mortality after multivariable adjustment. In addition, the HRs of PM(2.5) decreased gradually as the increase of annual temperature range with the HRs of 1.95 (95% CI: 1.36-2.81), 1.53 (95% CI: 1.06-2.22), and 1.11 (95% CI: 0.75-1.63) in the low, middle, and high group of annual temperature range, respectively. The findings provided further evidence of long-term PM(2.5) exposure on stroke mortality in high-exposure settings such as northern China, and also highlighted the view that assessing the adverse health effects of air pollution might not ignore the role of temperature variations in the context of climate change.
Ozone (O(3)) is a reactive oxidant exerting both inflammatory and oxidative damages to the respiratory system. With the ground-level O(3) progressively increasing in the past decade, the reevaluation of the pneumonia hospitalization risk from exposure to O(3) is of public health interest. We conducted an ecological time-series study to examine the city-specific association between short-term O(3) exposure and pneumonia hospitalizations in Hong Kong and Taipei, respectively. We linked the daily pneumonia hospitalization count to air pollution concentrations and weather conditions according to the date of admission during 2010-2017. We applied a generalized additive distributed lag model to examine the association while adjusting for time-varying covariates. Stratified analysis by age group and the potential harvesting effect of O(3) were evaluated. We observed the harvesting effects of O(3) on pneumonia hospitalizations in children in both cities and adults in Taipei. The short-term effect of O(3) lasted for around one week. An interquartile range (IQR) increment of daytime 8-hour mean concentration of O(3) distributed over 0-6 lag days in Hong Kong (42.4 μg/m(3)) was associated with a 7.04% (95% CI: 5.35-8.76%) increase in hospital admissions for elderly pneumonia, while the corresponding cumulative excess risk per IQR increment of O(3) in Taipei (38.7 μg/m(3)) was 3.41% (95% CI: 1.63-5.22%). Different O(3) metrics, varying degrees of freedom for filtering the temporal trend, and three-pollutant models supported the robustness of the associations. We concluded that short-term O(3) exposure was associated with pneumonia hospitalizations in the elderly population. Understanding the pneumonia hospitalization risk of O(3) will help to inform public health policies in the planning of ozone control strategies and intervention measures to prevent ozone-related pneumonia in vulnerable elderly populations.
Background: Health effects associated with extreme temperature and elevated air pollutants have been concerns. The present study examined mortality from and morbidity of chronic kidney disease (CKD) associated with extreme temperature and exposure to fine particulate matter (PM2.5) and ozone (O-3) by sex and age in 2005-2016 in metropolitans of Taiwan. Methods: The distributed lag non-linear model was applied to analyze roles of extreme high (99th percentile) and low (5th percentile) temperatures, and 90th percentile PM2.5 and ozone (O3) in association with CKD risks of deaths, emergency room visits (ERVs), and outpatient visits by age (40-64 and 65 years and above) and sex. Pooled relative risk (RR) and 95% confidence intervals (CI) for all studied areas were estimated using random -effects meta-analysis. Results: Cold spells (< 14 C) showed a higher risk on mortality from CKD for the elderly. Middle-aged population was more vulnerable to high temperature (31.3 C) with the highest risk for women admitted to outpatient visits [RR = 1.25; (95% CI; 1.17-1.34)]. Women aged 65 years and above had the highest risk after exposing to higher levels of PM2.5 (55 mu g/m(3)) [RR = 1.07; (95% CI; 1.03-1.12)] and O-3 (43 ppb) [RR = 1.07; (95% CI; 1.00-1.15)]. Conclusions: The elderly CKD patients were more prone to the adverse effect of low temperature and high levels of PM2.5 and O-3. Middle aged groups were more prone to health risks related to the high temperature. Men are more susceptible to the high temperature, meanwhile women are sensitive to higher levels of PM2.5 and O-3.
How to mitigate greenhouse gas emission and achieve human development remain major sustainability issues, particularly in China. Empirical research on the effects of climate warming and social change on human health and wellbeing is quite fragmented. This study examines the impact of environmental issues and social changes on health and human wellbeing using a time series data of China from 1991 to 2020. Findings show that environmental issues have a negative impact on health and human wellbeing in long run. While the internet is a form of social change that tends to improve health and human wellbeing in the long run. FDI exerts a positive effect on human health, but it does not improve wellbeing in the long run. In contrast, financial development does not improve human health but it has a significant positive impact on wellbeing in the long run. Our empirical insights have important implications for achieving human wellbeing through the pursuit of environmental sustainability and social change.
As the most common mental disorder, anxiety heavily damages human mental health and leads to heavy health burdens. However, evidence concerning the impact of NO2 on anxiety is limited. In this study, we aimed to further explore the association between short-term NO2 exposure and anxiety outpatient visits in Xi’an, a city located in Northwest China with relatively heavy air pollution. Daily data of anxiety outpatient visits, air pollutants (PM2.5, PM10, SO2, NO2, CO, and O-3), and meteorological conditions (daily mean temperature and relative humidity) from 2013 to 2019 were gathered. Then generalized additive models (GAM) was adopted to investigate the relationship between short-term NO2 exposure and the number of anxiety outpatient visits after controlling for long-term effects, holiday effects, day of the week, and weather conditions. The results showed that NO2 exposure was positively correlated with the number of daily anxiety outpatient visits: A 10 mu g/m(3) increase of NO2 concentration corresponded to 1.94% (95%CI: 1.19%, 2.68%) and 3.72% (95%CI: 2.35%, 5.08%) increase in anxiety outpatient visits at lag 1 and lag 07, respectively. Such a relationship showed gender differences (more obvious in females) but no age differences. More interestingly, the association between NO2 and anxiety outpatient visits showed to be more obvious during cool seasons than during warm seasons. In summary, short-term ambient NO2 exposure, especially during cool seasons, may be related to a higher risk of anxiety outpatient visits.
A reduction in the energy-related emissions of air pollutants would not only mitigate climate change but would also improve local air quality and public health. This paper aimed to analyze the trends of air quality index (AQI) and greenhouse gas (GHG) emissions in Taiwan by using the latest official statistics. In addition, this study also summarized regulatory measures for controlling air pollution from the energy sector with relevance to sustainable development goals (SDGs). With the joint efforts by the public and private sectors, the change in the total GHG emissions did not vary much with the exception of 2009, ranging from 250 to 272 million metric tons of CO2 equivalent from 2005 through 2019. Based on the data on AQI, the percentage of AQI by station-day with AQI > 100 has decreased from 18.1% in 2017 to 10.1% in 2020, indicating a decreasing trend for all criteria air pollutants. On the other hand, the coronavirus disease (COVID-19) lockdown, in 2019, has positively impacted Taiwan’s urban air quality, which was consistent with those observed in other countries. This consistent situation could be attributed to the climate change mitigation policies and promotional actions under the revised Air Pollution Control Act and the Greenhouse Gas Reduction and Management Act of 2015. In response to the SDGs launched by the Taiwan government in 2018, achieving the relevant targets by 2030 can be prospective.
The purpose of this paper is to evaluate the monetary GHG reduction benefits and health co-benefits for the industrial sector under the imposition of a carbon charge in Taiwan. The evaluation proceeds from 2023-2030 for different rates of carbon charge for the GHGs by a model of “Taiwan Economic Input Output Life Cycle Assessment and Environmental Value” constructed in this study. It is innovative in the literature to simulate the benefits of GHG reductions and health co-benefits of air pollutions for the industrial sector under the imposition of a carbon charge comprehensively. The results consistently show benefits whether the charge is imposed on the scope 1 and scope 2 GHG emissions or on the scope 1 emissions only. The health co-benefits are on average about 5 times those of GHG reductions benefits in 2023-2030. The average total benefits with the summation of GHG reduction benefits and health co-benefits are 821.9 million US dollars and 975.1 US million US dollars per year, respectively. However, both the GHG reduction benefits and health co-benefits are consistently increasing at a decreasing rate in 2023-2030. The increased multiple for the rate of the carbon charge is higher than the increased multiple of the total benefits and this result shows that the increase of the carbon charge becomes less effective.
Previous observational studies have shown that exposure to ambient temperature and air pollution were associated with the incidence of gestational diabetes mellitus (GDM). However, the susceptible time window of non-optimal temperature on GDM is still unknown, and the interaction with air pollution has not been examined. We conducted a prospective cohort study in Guangzhou, China to investigate the windows of susceptibility of temperature extremes and variability on the risk of GDM and to explore any interaction effect with air pollution. Daily maximum (T(max)), minimum temperature (T(min)) and diurnal temperature range (DTR) were obtained from Guangdong Meteorological Service. Distributed lag non-linear models with a logistic regression were applied to assess the effect of temperature extremes and DTR in different weeks of gestation on GDM. To examine the interaction effect, relative excess risk due to interaction index, attributable proportion and synergy index were calculated. There were 5,165 pregnant women enrolled, of which 604 were diagnosed with GDM (11.7%). Compared with a reference temperature (50th percentile of T(max)), we found that extreme high temperature (99th percentile of T(max)) exposure during 21st and 22nd gestational weeks was associated with an increased risk of GDM. Extreme low temperature (1st percentile of T(max)) exposure during 14th to 17th weeks increased the risk of GDM. We observed that per 1 °C increment of DTR during 21st to 24th weeks was associated with an elevated GDM risk. No interaction effect of temperature extremes or variability with air pollution on GDM were observed. Our results suggested that non-optimal temperature is an independent risk factor of GDM. The time window of susceptibility for extreme temperatures and DTR exposure on the risk of GDM generally occurred in second trimester of pregnancy. In the context of climate change, our study has important implications for reproductive health and justifies more research in different climate zones.
The independent associations of extreme temperature and ambient air pollutant with the admission to hospital and mortality of ischemic stroke have been widely investigated. However, knowledge about the modification effects of variation in season and temperature on the association between exposure to nitrogen dioxide (NO(2)) and ischemic stroke onset is still limited. This study purposed to explore the effect of NO(2) on daily ischemic stroke onset modified by season and ambient temperature, and identify the potential population that susceptible to ischemic stroke onset connected with NO(2) and ambient temperature. Data on daily ischemic stroke counts, weather conditions, and ambient air pollutant concentrations in Shenzhen were collected between January 1, 2008, and December 31, 2014. The seasonal effect on the NO(2)-associated onset was measured by a distributed-lag linear model. Furthermore, a generalized additive model that incorporated with stratification analyses was used to calculate the interactive effects between NO(2) and ambient temperature. During the winter, the average percentage increase in daily ischemic stroke onset for each 10 μg/m(3) increment in NO(2) concentration on lagged 2 days was 3.05% (95% CI: 1.31-4.82%), while there was no statistically significant effect of NO(2) during summer. And the low-temperature days ([Formula: see text] mean temperature), with a 2.23% increase in incidence (95% CI: 1.18-3.29%) for the same concentration increase in NO(2), were significant higher than high temperature days ([Formula: see text] mean temperature). The modification effects of temperature on the study association were more pronounced in individuals aged 65 years or more and in males. The adverse health effects of NO(2) on ischemic stroke are more pronounced during winter or low temperature periods. Elderly adults or males presented higher risks with these exposures.
BACKGROUND: The relationship between air pollution and meteorological factors on diseases has become a research hotspot recently. Nevertheless, few studies have touched the inferences of nitrogen dioxide (NO(2)) and atmospheric pressure (AP) on hospitalization risk for chronic obstructive pulmonary disease (COPD). OBJECTIVES: To investigate the short-term impact of particulate air pollutants and meteorology factors on hospitalizations for COPD and quantify the corresponding risk burden of hospital admission. METHODS: In our study, COPD cases were collected from Guangzhou Panyu Central Hospital (n = 11,979) from Dec of 2013 to Jun 2019. The 24-h average temperature, relative humidity (RH), wind speed (V), AP and other meteorological data were obtained from Guangzhou Meteorological Bureau. Air pollution data were collected from Guangzhou Air Monitoring Station. The influence of different NO(2) and AP values on COPD risk was quantified by a distributed lag nonlinear model (DLNM) combined with Poisson Regression and Time Series analysis. RESULTS: We found that NO(2) had a non-linear relationship with the incidence of COPD, with an approximate “M” type, appearing at the peaks of 126 μg/m³ (RR = 1.32, 95%CI, 1.07 to 1.64) and 168 μg/m³ (RR = 1.21, 95%CI, 0.94 to 1.55), respectively. And the association between AP and COPD incidence exhibited an approximate J-shape with a peak occurring at 1035 hPa (RR = 1.16, 95% CI, 1.02 to 1.31). CONCLUSIONS: The nonlinear relationship of NO(2) and AP on COPD admission risk in different periods of lag can be used to establish an early warning system for diseases and reduce the possible outbreaks and burdens of COPD in a sensitive population.
There are increasing concerns with regard to spontaneous abortion (SAB), the loss of pregnancy without external intervention before 20 weeks of gestation, among reproductive-aged women. To date, limited evidence is available concerning the association between SAB and air pollutants, especially in developing countries. Daily baseline outpatient data for SAB from January 1, 2014, to December 31, 2018 (1826 days) were obtained in Chongqing, a metropolis of southwest China. The over-dispersed Poisson generalized additive model with control of meteorological conditions and day of week was used to estimate the short-term effects of ambient air pollution on the daily number of SAB outpatients. A total of 42,334 SAB outpatient visits for SAB were recorded. No statistically significant association was observed between SAB and CO, PM(2.5), PM(10), O(3), and SO(2). The positive association only appeared for NO(2): positive associations between SAB and NO(2) were observed in both single-day models (lag 0, lag 1, lag 3, and lag 4) and cumulative exposure models (lag 01, lag 03, and lag 05) and the most significant effects were observed at lag 05 (3.289%; 95% CI: 1.568%, 5.011%). Moreover, the women with higher ages (30-39 and > 39) were more sensitive than those with lower ages (18-29), and the effect estimates were more evident in cool seasons. Collectively, our results suggested that short-term NO(2) exposure was associated with higher risk of SAB, especially in elder women and cool seasons, which may contribute to further understand the role of air pollution on SAB and other adverse obstetric outcomes.
Energy is considered a vital factor of economic growth that contributes to improve quality of life and health status. However, global warming, climate change, and environmental degradation are due primarily because of energy emissions, whereas environmental degradation is detrimental to health. Since one-fifth of the population lives in South Asia, it is necessary to analyze the impact of energy and environmental degradation on health status in this region. For this purpose, health status in South Asia is proxy with health expenditure, life expectancy, and infant mortality, and this study investigates the effect of energy intensity, income, and carbon emissions on health status, whereas urbanization is considered a control variable. The cointegration test indicates South Asia’s long-term health status factors are energy intensity, income, carbon emissions, and urbanization. Long-run results suggest that energy intensity and income improve health status as these factors reduce health expenditure, improve life expectancy, and decrease infant mortality. Environmental degradation not only increases health expenditure but also hinders life expectancy and increases mortality. Moreover, an increase in income diminishes health expenditure and is responsible for high life expectancy and low mortality in South Asia.
International trade’s impact on the pollution reduction, especially varied reduction effects dealing with global or local pollutants has not been thoroughly researched empirically. We explored effects of international trade participation on both the carbon dioxide emission intensity and sulfur dioxide emission intensity with a panel data of 179 major countries during 20 years when globalization thrived. Carbon dioxide causing climate change is a global concern. While sulfur dioxide is one major air pollutant causing local health problems. Empirically, international trade participation mainly reduces carbon dioxide emission intensity but not sulfur dioxide emission intensity. Also, trade in goods form is more effective than in service form. However, international trade participation does little to improving a country’s overall technology level, implying that regulation enhancement under international norm is the main mechanism. Compared with developed countries, developing countries can reduce both kinds of pollutant emission intensities more effectively by participating into international trade. A case study of China’s entering into World Trade Organization (WTO)’s impact on pollutant reduction can provide more evidence. Also, developing countries with higher industrialization level experiences a bigger improvement in cleaner production. And developing countries with higher democratization level pay more attention to reduce local environmental concerns.
Polycyclic aromatic hydrocarbons (PAHs) are hazardous compounds associated with respiratory disease and lung cancer. Increasing fossil fuel consumption, which causes climate change, has accelerated the emissions of PAHs. However, potential risks by PAHs have not been predicted for Korea, and appropriate PAH regulations under climate change have yet to be developed. This study assesses the potential risks posed by PAHs using climate change scenarios based on deep learning, and a multimedia fugacity model was employed to describe the future fate of PAHs. The multimedia fugacity model describes the dynamics of sixteen PAHs by reflecting inter-regional meteorological transportation. A deep neural network predicts future environmental and economic conditions, and the potential risks posed by PAHs, in the year 2050, using a prediction model and climate change scenarios. The assessment indicates that cancer risks would increase by more than 50%, exceeding the lower risk threshold in the southern and western regions. A mix of strategies for developing PAH regulatory policies highlighted the necessity of increasing PAHs monitoring stations and controlling fossil fuel usage based on the domestic and global conditions under climate change scenarios.
Exposure to polycyclic aromatic hydrocarbons (PAHs) are a cause of chronic cough occurrence in adult patients. In order to clear the relationship between transboundary transport of PAH and health effects, this study investigates the relationship between atmospheric particulate PAHs (p-PAHs), cough occurrence by epidemiological research, and meteorological conditions using a chemical transport model. Source receptor relationship (SRR) analysis revealed that a higher cough occurrence was caused by exposure to high p-PAH levels in air masses transported from central China (CCHN, 30-40 degrees N) under westerly conditions. The p-PAHs transported from northern China (NCHN, >40 degrees N) and the eastern part of Russia (ERUS) under north-westerly conditions also contributed to cough occurrence. The low equivalent potential temperature (ePT) and geopotential height anomaly suggested that the p-PAHs emitted near the surface were suppressed to upward transport under the colder air mass but were instead transported horizontally near the surface in the boundary layer, resulting in high p-PAH concentrations arriving in Kanazawa. Our study’s findings suggest that the air mass transport pattern associated with meteorology strongly influences the high p-PAH concentrations causing adult chronic cough occurrence.
BACKGROUND: Climate change models predict that atmospheric carbon dioxide [CO2] levels will be between 700 and 900 ppm within the next 80 y. Despite this, the direct physiological effects of exposure to slightly elevated atmospheric CO2 (as compared with ∼ 410 ppm experienced today), especially when exposures extend from preconception to adulthood, have not been thoroughly studied. OBJECTIVES: In this study we aimed to assess the respiratory structure and function effects of long-term exposure to 890 ppm CO2 from preconception to adulthood using a mouse model. METHODS: We exposed mice to CO2 ( ∼ 890 ppm) from prepregnancy, through the in utero and early life periods, until 3 months of age, at which point we assessed respiratory function using the forced oscillation technique, and lung structure. RESULTS: CO2 exposure resulted in a range of respiratory impairments, particularly in female mice, including higher tissue elastance, longer chord length, and lower lung compliance. Importantly, we also assessed the lung function of the dams that gave birth to our experimental subjects. Even though these mice had been exposed to the same level of increased CO2 for a similar amount of time ( ∼ 8 wk), we measured no impairments in lung function. This suggests that the early life period, when lungs are undergoing rapid growth and development, is particularly sensitive to CO2. DISCUSSION: To the best of our knowledge, this study, for the first time, shows that long-term exposure to environmentally relevant levels of CO2 can impact respiratory function in the mouse. https://doi.org/10.1289/EHP7305.
Severe volatile organic compound (VOC) pollution has become an urgent problem during the heating season in the North China Plain (NCP), as exposure to hazardous VOCs can lead to chronic or acute diseases. A campaign with online VOC measurements was conducted at a rural site in Wangdu, NCP during the 2018 heating season to characterize the compositions and associated sources of VOCs and to assess their potential health risks. The total concentration of VOCs with 94 identified species was 77.21 +/- 54.39 ppb. Seven source factors were identified by non-negative matrix factorization, including coal combustion (36.1%), LPG usage (21.1%), solvent usage (13.9%), biomass burning and secondary formation (142%), background (7.0%), industrial emissions (4.5%), and vehicle emissions (3.3%). The point estimate approach and Monte Carlo simulation were used to estimate the carcinogenic and non-carcinogenic risks of harzadous VOCs. The results showed that the cumulative health risk of VOCs was above the safety level. Acrolein, 1.2-dichlorprothane, 12-dichloropropane, chloroform, 1,3-butadiene, and benzene were identified as the key hazardous VOCs in Wangdu. Benzene had the highest average carcinogenic risk. Solvent usage and secondary formation were the dominant sources of adverse health effects. During the Spring Festival, most sources were sharply reduced; and VOC concentration declined by 49%. However, coal and biomass consumptions remained relatively large, probably due to heating demand. This study provides important references for the control strategies of VOCs during the heating season in heavily polluted rural areas in the NCP. (C) 2021 Elsevier B.V. All rights reserved.
Los productos suministrados son: concentraciones en superficie con salidas gráficas horarias de las concentraciones en superficie de NO2, NO, O3, SO2, CO, PM10 y PM2.5 expresadas en µg/m3; índice previsto diario de calidad del aire
calculado a partir de valores de concentración, utilizando la información procedente de las directivas vigentes relacionadas con los distintos contaminantes atmosféricos, e Índice previsto horario de calidad del aire con un horizonte temporal de 48 horas
Izmerjeni podatki o kakovosti zraka in napovedi
South African Air Quality Information System (SAAQIS) is a web based interactive air quality information system which seeks to provide the state of air quality information to citizens, and it is a research portal for strengthening policy development related to air quality issues.
The growing concerns over urbanization and climate change have resulted in an exponential growth in publications on urban climatology in recent decades. However, an advanced synthesis that characterizes the existing studies is lacking. In this review, we used citation network analysis and a text mining approach to identify research trends and extract common research topics and the emerging domains in urban climatology. Based on the clustered networks, we found that aerosols and ozone, and urban heat island are the most popular topics. Together with other clusters, four emerging topical fields were identified: secondary organic aerosols, urban precipitation, flood risk and adaptation, and greenhouse gas emissions. The city case studies’ geographical information was analyzed to explore the spatial-temporal patterns, especially in the emerging topical fields. Interdisciplinary research grew in recent years as the field of urban climatology expanded to interact with urban hydrology, health, energy issues, and social sciences. A few knowledge gaps were proposed: the lack of long-term high-temporal-resolution observational data of organic aerosols for model validation and improvements, the need for predictions of urban effects on precipitation and extreme flooding events under climate change, and the lack of a framework for cooperation between physical sciences and social sciences under urban settings. To fill these gaps, we call for more observational data with high spatial and temporal resolution, using high-resolution models that adequately represent urban processes to conduct scenario analyses for urban planning, and the development of intellectual frameworks for better integration of urban climatology and social-economical systems in cities. This article is categorized under: Climate, History, Society, Culture > Disciplinary Perspectives
Speciated ground-level aerosol concentrations are required to understand and mitigate health impacts from dust storms, wildfires, and other aerosol emissions. Globally, surface monitoring is limited due to cost and infrastructure demands. While remote sensing can help estimate respirable (i.e. ground level) concentrations, current observations are restricted by inadequate spatiotemporal resolution, uncertainty in aerosol type, particle size, and vertical profile. One key issue with current remote sensing datasets is that they are derived from reflectances observed by polar-orbiting imagers, which means that aerosol is only derived during the daytime and only once or twice per day. Newer quantification methods using geostationary infrared (IR) data have focussed on detecting the presence, or absence, of an event. The determination of aerosol composition or particle size using IR exclusively has received little attention. This manuscript summarizes four scientific papers, published as part of a larger study, and identifies requirements for (a) using infrared radiance observations to obtain continual (i.e. day and night) concentration estimates; (b) increasing temporal resolution by using geostationary satellites; (c) utilizing all infrared channels to maximize spectral differences due to compositional changes; and (d) applying a high-pass filter (brightness temperature differences) to identify compositional variability. Additionally, (e) a preliminary calibration methodology was tested against three severe air quality case study incidents, namely, a dust storm, smoke from prescribed burns, and an ozone smog incident, near Sydney in eastern Australia which highlighted the ability of the method to determine atmospheric stability, clouds, and particle size. Geostationary remote sensing provides near-continuous data at a temporal resolution comparable to monitoring equipment. The spatial resolution (~?4 km(2) at NADIR) is adequate for large sources but coarse for localized sources. The spectral sensitivity of aerosol is limited and appears to be dominated by humidity changes rather than concentration or compositional changes. Geostationary remote sensing can be used to determine the timing, duration, and spatial extent of an air quality event. Brightness temperature differences can assist in qualifying composition with an order of magnitude estimate of concentration.
Pollens are a major cause of seasonal allergic diseases. Weather may alter the production of pollens. Increased atmospheric temperatures lead to earlier pollination of many plants and longer duration of pollination, resulting in extended pollen seasons, with early spring or late winter. Longer pollen seasons increase duration of exposure, resulting in more sensitization, and higher pollen concentrations may lead to more severe symptoms. Climate changes in contact to pollens may affect both allergic sensitization and symptom prevalence with severity. The future consequences of climate change, however, are speculative, because the influence on humans, is complex.
Purpose of reviewThe purpose of this chapter is to review allergic disease and how it is potentially impacted by climate change. It is difficult to measure the direct impact climate change has on allergic disease. This is difficult because there are many variables impacting human health as well as what capacity humans have to adapt to these changes. Asthma is tightly associated with allergies and environmental factors, especially in children. In this review, we will explore evidence of environmental changes associated with climate change and the potential impacts on allergy and associated respiratory disease. Furthermore, this paper is to review the impact of climate change on allergy to atmospheric fungi which are known to cause a common allergic response. In this review, we will explore evidence of environmental changes associated with climate change and the potential impacts on allergy.Recent findingsThe climate has been measurably changing for the past 100 years and has been described as the most significant health threat of the twenty-first century. How climate change impacts human health is varied and coming more into focus. While direct effects, such as heatwaves, severe weather, drought, and flooding, are well reported, effects that are indirect or secondary impacts involving changes in ecosystems are less obvious, though the body of data is growing and becoming more robust. It is these changes in ecosystems that may have the greatest impact on allergic and respiratory diseases. Otherwise, the airborne pollens and spores have also been linked with upper and lower respiratory conditions. Atmospheric pollen and spore concentrations are influenced by a wide array of environmental, meteorological, and biological factors and various interspecies interactions. Pollen and spores underlie seasonal variations. Especially climatic factors and circadian patterns influence the spectrum of their species and their concentrations in the environment. It may have the greatest impact on respiratory allergic diseases.SummaryThis review will explore some of the impacts our changing climate, current and predicted, has which influences upper and lower respiratory allergic diseases. The discussion will focus on changing pollination with altered pollen patterns, as well as alteration of the composition and transformation of atmospheric allergic fungi with increased CO2 air pollution and heat stress. The sporulation of fungi is likely to be amplified as CO2 concentration increases with climate change, potentially contributing to the increasing prevalence and severity of asthma and other respiratory allergies.
BACKGROUND: Climate change is broadly affecting human health, with grave concern that continued warming of the earth’s atmosphere will result is serious harm. Since the mid-20th century, skin cancer incidence rates have risen at an alarming rate worldwide. OBJECTIVE: This review examines the relationship between climate change and cutaneous carcinogenesis. METHODS: A literature review used the National Institutes of Health databases (PubMed and Medline), the Surveillance, Epidemiology, and End Results and International Agency for Research on Cancer registries, and published reports by federal and international agencies and consortia, including the Australian Institute of Health and Welfare, Climate and Clean Air Coalition, U.S. Environmental Protection Agency, Intergovernmental Panel on Climate Change, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, United Nations Environment Programme, World Health Organization, and World Meteorological Organization. RESULTS: Skin cancer risk is determined by multiple factors, with exposure to ultraviolet radiation being the most important. Strong circumstantial evidence supports the hypothesis that factors related to climate change, including stratospheric ozone depletion, global warming, and ambient air pollution, have likely contributed to the increasing incidence of cutaneous malignancy globally and will continue to impose a negative on influence skin cancer incidence for many decades to come. CONCLUSION: Because much of the data are based on animal studies and computer simulations, establishing a direct and definitive link remains challenging. More epidemiologic studies are needed to prove causality in skin cancer, but the evidence for overall harm to human health as a direct result of climate change is clear. Global action to mitigate these negative impacts to humans and the environment is imperative.
The coronavirus disease 2019 (COVID-19) pandemic caused a crisis worldwide, due to both its public health impact and socio-economic consequences. Mental health was consistently affected by the pandemic, with the emergence of newly diagnosed psychiatric disorders and the exacerbation of pre-existing ones. Urban areas were particularly affected by the virus spread. In this review, we analyze how the urban environment may influence mental health during the COVID-19 pandemic, considering two factors that profoundly characterize urbanization: air pollution and migration. Air pollution serves as a possibly risk factor for higher viral spread and infection severity in the context of urban areas and it has also been demonstrated to play a role in the development of serious mental illnesses and their relapses. The urban environment also represents a complex social context where minorities such as migrants may live in poor hygienic conditions and lack access to adequate mental health care. A global rethinking of the urban environment is thus required to reduce the impact of these factors on mental health. This should include actions aimed at reducing air pollution and combating climate change, promoting at the same time a more inclusive society in a sustainable development perspective.
Extreme weather and climate events are likely to increase in frequency and severity as a consequence of global climate change. These are events that can include flooding rains, prolonged heat waves, drought, wildfires, hurricanes, severe thunderstorms, tornadoes, storm surge, and coastal flooding. It is important to consider these events as they are not merely meteorologic occurrences but are linked to our health. We aim to address how these events are interconnected with asthma outcomes associated with thunderstorm asthma, pollen production, mold infestation from flooding events, and poor air quality during wildfires.
PURPOSE OF REVIEW: Atopic dermatitis (AD) is a chronic inflammatory skin disorder affecting up to 20% of children and up to 5% of adults worldwide, contributing to significant disease-related morbidity in this patient cohort. Its aetiopathogenesis is underpinned by multiple factors, including genetic susceptibility, skin barrier defects, a skewed cutaneous immune response and microbiome perturbation in both the skin and the gut. In this review, we aim to examine the biological effects of key environmental exposures (the sum of which is termed the “exposome”) at the population, community and individual levels in order to describe their effect on AD pathogenesis. RECENT FINDINGS: It is now understood that as well as considering the type of environmental exposure with regard to its effect on AD pathogenesis, the dosage and timing of the exposure are both critical domains that may lead to either exacerbation or amelioration of disease. In this review, we consider the effects of population-wide exposures such as climate change, migration and urbanization; community-specific exposures such as air pollution, water hardness and allergic sensitisation; and individual factors such as diet, microbiome alteration, psychosocial stress and the impact of topical and systemic therapy. SUMMARY: This review summarises the interaction of the above environmental factors with the other domains of AD pathogenesis, namely, the inherent genetic defects, the skin barrier, the immune system and the cutaneous and gut microbiota. We specifically emphasise the timing and dosage of exposures and its effect on the cellular and molecular pathways implicated in AD.
Recent pandemic outbreak of the corona-virus disease 2019 (COVID-19) has raised widespread concerns about the importance of the bioaerosols. They are atmospheric aerosol particles of biological origins, mainly including bacteria, fungi, viruses, pollen, and cell debris. Bioaerosols can exert a substantial impact on ecosystems, climate change, air quality, and public health. Here, we review several relevant topics on bioaerosols, including sampling and detection techniques, characterization, effects on health and air quality, and control methods. However, very few studies have focused on the source apportionment and transport of bioaerosols. The knowledge of the sources and transport pathways of bioaerosols is essential for a comprehensive understanding of the role microorganisms play in the atmosphere and control the spread of epidemic diseases associated with them. Therefore, this review comprehensively summarizes the up to date progress on the source characteristics, source identification, and diffusion and transport process of bioaerosols. We intercompare three types of diffusion and transport models, with a special emphasis on a widely used mathematical model. This review also highlights the main factors affecting the source emission and transport process, such as biogeographic regions, land-use types, and environmental factors. Finally, this review outlines future perspectives on bioaerosols.
BACKGROUND: In the rapidly shifting Canadian climate, an ageing population, and increased migration, a greater understanding of how local climate and air pollution hazards impact older adults and immigrant populations will be necessary for mitigating and adapting to adverse health impacts. OBJECTIVES: To explore the reported health impacts of climate change and air pollution exposures in older adults and immigrant people living in Canada, identify known factors influencing risk and resilience in these populations and gaps in the literature. METHODS: We searched for research focused on older adults and immigrants living in Canada, published from 2010 onward, where the primary exposures were related to climate or air pollution. We extracted data on setting, exposures, health outcomes, and other relevant contextual factors. RESULTS AND DISCUSSION: We identified 52 eligible studies, most focused in Ontario and Quebec. Older people in Canada experience health risks due to climate and air pollution exposures. The extent of the risk depends on multiple factors. We found little information about the climate- and air pollution-related health impacts experienced by immigrant communities. CONCLUSIONS: Further research about climate- and air pollution-related exposures, health, and which factors promote or reduce resiliency in Canada’s older adults and immigrant communities is necessary.
Heart failure is a major contributor to healthcare expenditures. Many clinical risk factors for the development and exacerbation of heart failure had been reported, including diabetes, renal dysfunction, and respiratory disease. In addition to these clinical parameters, the effects of social factors, such as occupation or lifestyle, and environmental factors may have a great impact on disease development and progression of heart failure. However, the current understanding of social and environmental factors as contributors to the clinical course of heart failure is insufficient. To present the knowledge of these factors to date, this comprehensive review of the literature sought to identify the major contributors to heart failure within this context. Social factors for the risk of heart failure included occupation and lifestyle, specifically in terms of the effects of specific occupations, occupational exposure to toxicities, work style, and sleep deprivation. Socioeconomic factors focused on income and education level, social status, the neighborhood environment, and marital status. Environmental factors included traffic and noise, air pollution, and other climate factors. In addition, psychological stress and behavior traits were investigated. The development of heart failure may be closely related to these factors; therefore, these data should be summarized for the context to improve their effects on patients with heart failure. The present study reviews the literature to summarize these influences.
Climate change is one of the biggest challenges humanity is facing in the 21st century. Two recognized sequelae of climate change are global warming and air pollution. The gradual increase in ambient temperature, coupled with elevated pollution levels have a devastating effect on our health, potentially contributing to the increased rate and severity of numerous neurological disorders. The main aim of this review paper is to shed some light on the association between the phenomena of global warming and air pollution, and two of the most common and debilitating neurological conditions: stroke and neurodegenerative disorders. Extreme ambient temperatures induce neurological impairment and increase stroke incidence and mortality. Global warming does not participate in the etiology of neurodegenerative disorders, but it exacerbates symptoms of dementia, Alzheimer’s disease (AD) and Parkinson’s Disease (PD). A very close link exists between accumulated levels of air pollutants (principally particulate matter), and the incidence of ischemic rather than hemorrhagic strokes. People exposed to air pollutants have a higher risk of developing dementia and AD, but not PD. Oxidative stress, changes in cardiovascular and cerebrovascular haemodynamics, excitotoxicity, microglial activation, and cellular apoptosis, all play a central role in the overlap of the effect of climate change on neurological disorders. The complex interactions between global warming and air pollution, and their intricate effect on the nervous system, imply that future policies aimed to mitigate climate change must address these two challenges in unison.
Numerous studies have linked outdoor levels of PM2.5, PM10, NO2, O-3, SO2, and other air pollutants to significantly higher rates of Covid 19 morbidity and mortality, although the rate in which specific concentrations of pollutants increase Covid 19 morbidity and mortality varies widely by specific country and study. As little as a 1-mu g/m(3) increase in outdoor PM2.5 is estimated to increase rates of Covid 19 by as much as 0.22 to 8%. Two California studies have strongly linked heavy wildfire burning periods with significantly higher outdoor levels of PM2.5 and CO as well as significantly higher rates of Covid 19 cases and deaths. Active smoking has also been strongly linked significantly increased risk of Covid 19 severity and death. Other exposures possibly related to greater risk of Covid 19 morbidity and mortality include incense, pesticides, heavy metals, dust/sand, toxic waste sites, and volcanic emissions. The exact mechanisms in which air pollutants increase Covid 19 infections are not fully understood, but are probably related to pollutant-related oxidation and inflammation of the lungs and other tissues and to the pollutant-driven alternation of the angiotensin-converting enzyme 2 in respiratory and other cells.
Male fertility and semen quality have declined over recent decades. Among other causes, exposure to environmental and occupational pollution has been linked to adverse reproductive outcomes, but effects on male semen quality are still uncertain. Therefore, the aim of the present study was to conduct a systematic review and meta-analysis to assess current evidence regarding the impact of exposure to tobacco smoke and environmental and occupational pollution on sperm quality in humans. In the meta-analysis, 22 studies are included showing that environmental and occupational pollutants may affect sperm count, volume, concentration, motility, vitality and sperm DNA, and chromatin integrity. All included articles reported significant alterations in at least one of the outcomes studied in association with at least one of the pollutants studied. Considering that sperm quality can be considered a proxy for general health and that pollutants have a dramatic impact on climate change, it would be strongly recommended to better understand the role of pollutants on human, animal, and planetary health.
Anthropogenic climate change is adversely impacting people and contributing to suffering and increased costs from climate-related diseases and injuries. In responding to this urgent and growing public health crisis, mitigation strategies are in place to reduce future greenhouse gas emissions (GHGE) while adaptation strategies exist to reduce and/or alleviate the adverse effects of climate change by increasing systems’ resilience to future impacts. While these strategies have numerous positive benefits on climate change itself, they also often have other positive externalities or health co-benefits. This knowledge can be harnessed to promote and improve global public health, particularly for the most vulnerable populations. Previous conceptual models in mitigation and adaptation studies such as the shared socioeconomic pathways (SSPs) considered health in the thinking, but health outcomes were not their primary intention. Additionally, existing guidance documents such as the World Health Organization (WHO) Guidance for Climate Resilient and Environmentally Sustainable Health Care Facilities is designed primarily for public health professionals or healthcare managers in hospital settings with a primary focus on resilience. However, a detailed cross sectoral and multidisciplinary conceptual framework, which links mitigation and adaptation strategies with health outcomes as a primary end point, has not yet been developed to guide research in this area. In this paper, we briefly summarize the burden of climate change on global public health, describe important mitigation and adaptation strategies, and present key health benefits by giving context specific examples from high, middle, and low-income settings. We then provide a conceptual framework to inform future global public health research and preparedness across sectors and disciplines and outline key stakeholders recommendations in promoting climate resilient systems and advancing health equity.
PURPOSE OF REVIEW: Climate change remains a major threat to the health and well-being of children globally. This article reviews the myriad health effects of climate change on children throughout their lives and discusses ways in which the general pediatrician can be an advocate for climate solutions. RECENT FINDINGS: Rising atmospheric temperatures, increased air pollution, and destabilized weather patterns all lead to adverse health outcomes for children and adverse obstetric outcomes. However, the impact of climate change is not evenly distributed. Children living in poverty are more likely to be adversely impacted by the changing climate. SUMMARY: Ongoing and emerging research suggests that children are particularly vulnerable to the effects of climate change. The primary care pediatrician is encouraged to see this irrefutable evidence as a call to action for advocacy on behalf of our patients and the planet.
Climatic change will have an impact on production and release of pollen, with consequences for the duration and magnitude of aeroallergen seasonal exposure and allergic diseases. Evaluations of pollen aerobiology in the southern hemisphere have been limited by resourcing and the density of monitoring sites. This review emphasizes inconsistencies in pollen monitoring methods and metrics used globally. Research should consider unique southern hemisphere biodiversity, climate, plant distributions, standardization of pollen aerobiology, automation, and environmental integration. For both hemispheres, there is a clear need for better understanding of likely influences of climate change and comprehending their impact on pollen-related health outcomes.
Air pollution disproportionately affects marginalized populations of lower socioeconomic status. There is little literature on how socioeconomic status affects the risk of exposure to air pollution and associated health outcomes, particularly for children’s health. The objective of this article was to review the existing literature on air pollution and children’s health and discern how socioeconomic status affects this association. The concept of environmental injustice recognizes how underserved communities often suffer from higher air pollution concentrations in addition to other underlying risk factors for impaired health. This exposure then exerts larger effects on their health than it does in the average population, affecting the whole body, including the lungs and the brain. Children, whose organs and mind are still developing and who do not have the means of protecting themselves or creating change, are the most vulnerable to the detrimental effects of air pollution and environmental injustice. The adverse health effects of air pollution and environmental injustice can harm children well into adulthood and may even have transgenerational effects. There is an urgent need for action in order to ensure the health and safety of future generations, as social disparities are continuously increasing, due to social discrimination and climate change.
Background: Environmental health is a growing area of knowledge, continually increasing and updating the body of evidence linking the environment to human health. Aim: This study summarizes the epidemiological evidence on environmental risk factors from meta-analyses through an umbrella review. Methods: An umbrella review was conducted on meta-analyses of cohort, case-control, case-crossover, and time-series studies that evaluated the associations between environmental risk factors and health outcomes defined as incidence, prevalence, and mortality. The specific search strategy was designed in PubMed using free text and Medical Subject Headings (MeSH) terms related to risk factors, environment, health outcomes, observational studies, and meta-analysis. The search was limited to English, Spanish, and French published articles and studies on humans. The search was conducted on September 20, 2020. Risk factors were defined as any attribute, characteristic, or exposure of an individual that increases the likelihood of developing a disease or death. The environment was defined as the external elements and conditions that surround, influence, and affect a human organism or population’s life and development. The environment definition included the physical environment such as nature, built environment, or pollution, but not the social environment. We excluded occupational exposures, microorganisms, water, sanitation and hygiene (WASH), behavioral risk factors, and no-natural disasters. Results: This umbrella review found 197 associations among 69 environmental exposures and 83 diseases and death causes reported in 103 publications. The environmental factors found in this review were air pollution, environmental tobacco smoke, heavy metals, chemicals, ambient temperature, noise, radiation, and urban residential surroundings. Among these, we identified 65 environmental exposures defined as risk factors and 4 environmental protective factors. In terms of study design, 57 included cohort and/or case-control studies, and 46 included time-series and/or case-crossover studies. In terms of the study population, 21 included children, and the rest included adult population and both sexes. In this review, the largest body of evidence was found in air pollution (91 associations among 14 air pollution definitions and 34 diseases and mortality diagnoses), followed by environmental tobacco smoke with 24 associations. Chemicals (including pesticides) were the third larger group of environmental exposures found among the meta-analyses included, with 19 associations. Conclusion: Environmental exposures are an important health determinant. This review provides an overview of an evolving research area and should be used as a complementary tool to understand the connections between the environment and human health. The evidence presented by this review should help to design public health interventions and the implementation of health in all policies approach aiming to improve populational health.
Climate change (CC) is the most challenging environmental health (EH) concern. Air pollution is closely linked to CC. However, many CC-health-related conditions (i.e., allergic diseases, asthma, hypertension, fluid and electrolyte disorders, child and adult obesity, type 2 diabetes, vector-borne diseases) are not usually counted, either because they do not cause death or require hospital admission/emergency triage. They are the vast majority of health care seeking generally treated by family doctors (FDs) and family pediatricians (FPs). FDs/FPs are often not aware of CC-health-impacts. Their potential role in tackling such a global challenge through their local influence on individual and collective attitudes and policies is not considered. Proper FD training could fill these gaps, raise awareness of their role, and implement EH FDs/FPs-based surveillance networks to collect, analyze, interpret, and report EH data to inform EH-related Policy. FDs and FPs, organized in sentinel physicians’ networks, could play a key role in advising policymakers at the local and regional level in designing interventions adapted to climate-related issues. Such experiences are rare worldwide and not well known. We will describe and discuss them in detail to share successful local examples.
Pollen, a major causal agent of respiratory allergy, is mainly affected by weather conditions. In Korea, pollen and weather data are collected by the national observation network. Forecast models and operational services are developed and provided based on the national pollen data base. Using the pollen risk forecast information will help patients with respiratory allergy to improve their lives. Changes in temperature and CO(2) concentration by climate change affect the growth of plants and their capacity of producing more allergenic pollens, which should be considered in making the future strategy on treating allergy patients.
BACKGROUND: Although the frequency and magnitude of climate change-related health hazards (CCRHHs) are likely to increase, the population vulnerabilities and corresponding health impacts are dependent on a community’s exposures, pre-existing sensitivities, and adaptive capacities in response to a hazard’s impact. To evaluate spatial variability in relative vulnerability, we: 1) identified climate change-related risk factors at the dissemination area level; 2) created actionable health vulnerability index scores to map community risks to extreme heat, flooding, wildfire smoke, and ground-level ozone; and 3) spatially evaluated vulnerability patterns and priority areas of action to address inequity. METHODS: A systematic literature review was conducted to identify the determinants of health hazards among populations impacted by CCRHHs. Identified determinants were then grouped into categories of exposure, sensitivity, and adaptive capacity and aligned with available data. Data were aggregated to 4188 Census dissemination areas within two health authorities in British Columbia, Canada. A two-step principal component analysis (PCA) was then used to select and weight variables for each relative vulnerability score. In addition to an overall vulnerability score, exposure, adaptive capacity, and sensitivity sub-scores were computed for each hazard. Scores were then categorised into quintiles and mapped. RESULTS: Two hundred eighty-one epidemiological papers met the study criteria and were used to identify 36 determinant indicators that were operationalized across all hazards. For each hazard, 3 to 5 principal components explaining 72 to 94% of the total variance were retained. Sensitivity was weighted much higher for extreme heat, wildfire smoke and ground-level ozone, and adaptive capacity was highly weighted for flooding vulnerability. There was overall varied contribution of adaptive capacity (16-49%) across all hazards. Distinct spatial patterns were observed – for example, although patterns varied by hazard, vulnerability was generally higher in more deprived and more outlying neighbourhoods of the study region. CONCLUSIONS: The creation of hazard and category-specific vulnerability indices (exposure, adaptive capacity and sensitivity sub-scores) supports evidence-based approaches to prioritize public health responses to climate-related hazards and to reduce inequity by assessing relative differences in vulnerability along with absolute impacts. Future studies can build upon this methodology to further understand the spatial variation in vulnerability and to identify and prioritise actionable areas for adaptation.
The Fourth National Climate Assessment (NCA4) is the most comprehensive report to date assessing climate change science, impacts, risks, and adaptation in the United States. The 1,500 page report covers a breadth of topics, ranging from foundational physical science to climate change response options. Here we present information on indicators and impacts of climate change in the human environment featured in NCA4 Volume II, focusing on: air quality, forest disturbance and wildfire, energy systems, and water resources. Observations, trends, and impacts of these aspects of our changing climate will be discussed, along with implications for the future. Implications: People of the United States are already being affected by our changing climate. Information on observed changes and impacts that affect human welfare and society, along with projections for the future, is highly valuable for informing decision-makers, including utility managers, emergency planners, and other stakeholders, about climate risk assessment, adaptation, and mitigation options.
Converging data would indicate the existence of possible relationships between climate change, environmental pollution and epidemics/pandemics, such as the current one due to SARS-CoV-2 virus. Each of these phenomena has been supposed to provoke detrimental effects on mental health. Therefore, the purpose of this paper was to review the available scientific literature on these variables in order to suggest and comment on their eventual synergistic effects on mental health. The available literature report that climate change, air pollution and COVID-19 pandemic might influence mental health, with disturbances ranging from mild negative emotional responses to full-blown psychiatric conditions, specifically, anxiety and depression, stress/trauma-related disorders, and substance abuse. The most vulnerable groups include elderly, children, women, people with pre-existing health problems especially mental illnesses, subjects taking some types of medication including psychotropic drugs, individuals with low socio-economic status, and immigrants. It is evident that COVID-19 pandemic uncovers all the fragility and weakness of our ecosystem, and inability to protect ourselves from pollutants. Again, it underlines our faults and neglect towards disasters deriving from climate change or pollution, or the consequences of human activities irrespective of natural habitats and constantly increasing the probability of spillover of viruses from animals to humans. In conclusion, the psychological/psychiatric consequences of COVID-19 pandemic, that currently seem unavoidable, represent a sharp cue of our misconception and indifference towards the links between our behaviour and their influence on the “health” of our planet and of ourselves. It is time to move towards a deeper understanding of these relationships, not only for our survival, but for the maintenance of that balance among man, animals and environment at the basis of life in earth, otherwise there will be no future.
BACKGROUND: Climate change impacts are associated with dramatic consequences for human health and threaten physical activity (PA) behaviors. OBJECTIVE: The aims of this systematic review were to present the potential bidirectional associations between climate change impacts and PA behaviors in humans and to propose a synthesis of the literature through a conceptual model of climate change and PA. METHODS: Studies published before October 2020 were identified through database searches in PubMed, PsycARTICLES, CINAHL, SPORTDiscus, GreenFILE, GeoRef, Scopus, JSTOR and Transportation Research Information Services. Studies examining the associations between PA domains and climate change (e.g., natural disasters, air pollution, and carbon footprint) were included. RESULTS: A narrative synthesis was performed and the 74 identified articles were classified into 6 topics: air pollution and PA, extreme weather conditions and PA, greenhouse gas emissions and PA, carbon footprint among sport participants, natural disasters and PA and the future of PA and sport practices in a changing world. Then, a conceptual model was proposed to identify the multidimensional associations between climate change and PA as well as sport practices. Results indicated a consistent negative effect of air pollution, extreme temperatures and natural disasters on PA levels. This PA reduction is more severe in adults with chronic diseases, higher body mass index and the elderly. Sport and PA communities can play an important mitigating role in post-natural disaster contexts. However, transport related to sport practices is also a source of greenhouse gas emissions. CONCLUSION: Climate change impacts affect PA at a worldwide scale. PA is observed to play both a mitigation and an amplification role in climate changes. TRIAL REGISTRATION NUMBER: PROSPERO CRD42019128314.
Climate change is one of the major global health threats to the world’s population. It is brought on by global warming due in large part to increasing levels of greenhouse gases resulting from human activity, including burning fossil fuels (carbon dioxide), animal husbandry (methane from manure), industry emissions (ozone, nitrogen oxides, sulfur dioxide), vehicle/factory exhaust, and chlorofluorocarbon aerosols that trap extra heat in the earth’s atmosphere. Resulting extremes of weather give rise to wildfires, air pollution, changes in ecology, and floods. These in turn result in displacement of populations, family disruption, violence, and major impacts on water quality and availability, food security, public health and economic infrastructures, and limited abilities for civil society to maintain citizen safety. Climate change also has direct impacts on human health and well-being. Particularly vulnerable populations are affected, including women, pregnant women, children, the disabled, and the elderly, who comprise the majority of the poor globally. Additionally, the effects of climate change disproportionally affect disadvantaged communities, including low income and communities of color, and lower-income countries that are at highest risk of adverse impacts when disasters occur due to inequitable distribution of resources and their socioeconomic status. The climate crisis is tilting the risk balance unfavorably for women’s sexual and reproductive health and rights as well as newborn and child health. Obstetrician/gynecologists have the unique opportunity to raise awareness, educate, and advocate for mitigation strategies to reverse climate change affecting our patients and their families. This article puts climate change in the context of women’s reproductive health as a public health issue, a social justice issue, a human rights issue, an economic issue, a political issue, and a gender issue that needs our attention now for the health and well-being of this and future generations. FIGO joins a broad coalition of international researchers and the medical community in stating that the current climate crisis presents an imminent health risk to pregnant people, developing fetuses, and reproductive health, and recognizing that we need society-wide solutions, government policies, and global cooperation to address and reduce contributors, including fossil fuel production, to climate change.
Several climate change-related predictions and observations have been documented for the Australian continent. Extreme weather events such as cycles of severe drought and damaging flooding are occurring with greater frequency and have a severe impact on human health. Two specific aspects of climate change affecting allergic and other respiratory disorders are outlined: firstly, the consequences of extreme weather events and secondly, the change in distribution of airborne allergens that results from various climate change factors.
Climate and weather directly impact plant phenology, affecting airborne pollen. The objective of this systematic review is to examine the impacts of meteorological variables on airborne pollen concentrations and pollen season timing. Using PRISMA methodology, we reviewed literature that assessed whether there was a relationship between local temperature and precipitation and measured airborne pollen. The search strategy included terms related to pollen, trends or measurements, and season timing. For inclusion, studies must have conducted a correlation analysis of at least 5 years of airborne pollen data to local meteorological data and report quantitative results. Data from peer-reviewed articles were extracted on the correlations between seven pollen indicators (main pollen season start date, end date, peak date, and length, annual pollen integral, average daily pollen concentration, and peak pollen concentration), and two meteorological variables (temperature and precipitation). Ninety-three articles were included in the analysis out of 9,679 articles screened. Overall, warmer temperatures correlated with earlier and longer pollen seasons and higher pollen concentrations. Precipitation had varying effects on pollen concentration and pollen season timing indicators. Increased precipitation may have a short-term effect causing low pollen concentrations potentially due to “wash out” effect. Long-term effects of precipitation varied for trees and weeds and had a positive correlation with grass pollen levels. With increases in temperature due to climate change, pollen seasons for some taxa in some regions may start earlier, last longer, and be more intense, which may be associated with adverse health impacts, as pollen exposure has well-known health effects in sensitized individuals.
This paper highlights the important leadership role of the public health sector, working with other governmental sectors and nongovernmental entities, to advance environmental public health in Latin America and the Caribbean toward the achievement of 2030 Sustainable Development Goal 3: Health and Well-Being. The most pressing current and future environmental public health threats are discussed, followed by a brief review of major historical and current international and regional efforts to address these concerns. The paper concludes with a discussion of three major components of a regional environmental public health agenda that responsible parties can undertake to make significant progress toward ensuring the health and well-being of all people throughout Latin America and the Caribbean.
Allergic diseases are caused by the immune system’s response to innocent antigens called allergens. Recent decades have seen a significant increase in the prevalence of allergic diseases worldwide, which has imposed various socio-economic effects in different countries. Various factors, including genetic factors, industrialization, improved hygiene, and climate change contribute to the development of allergic diseases in many parts of the world. Moreover, changes in lifestyle and diet habits play pivotal roles in the prevalence of allergic diseases. Dietary changes caused by decreased intake of antioxidants such as vitamin E lead to the generation of oxidative stress, which is central to the development of allergic diseases. It has been reported in many articles that oxidative stress diverts immune responses to the cells associated with the pathogenesis of allergic diseases. The aim of this short review was to summarize current knowledge about the anti-allergic properties of vitamin E.
Corona virus is highly uncertain and complex in space and time. Atmospheric parameters such as type of pollutants and local weather play an important role in COVID-19 cases and mortality. Many studies were carried out to understand the impact of weather on spread and severity of COVID-19 and vice-versa. A review study is conducted to understand the impact of weather and atmospheric pollution on morbidity and mortality. Studies show that aerosols containing corona virus generated by sneezes and coughs are major route for spread of virus. Viability and virulence of SARS-CoV-2 stuck on the surface of particulate matter is not yet confirmed. Studies found that an increase in particulate matter concentration causes more COVID-19 cases and mortality. Gaseous pollutant and COVID-19 cases are positively correlated. Local meteorology plays crucial role in the spread of corona virus and thus mortality. Decline in number of cases with rising temperature observed. Few studies also find that lowest and highest temperatures were related to lesser number of cases. Similarly humidity shows negative or no relationship with COVID-19 cases. Rainfall was not related whilst wind-speed plays positive role in spread of COVID-19. Solar radiation threats survival of virus, areas with lower solar radiation showed high exposure rate. Air quality tremendously improved during lockdown. A significant reduction in PM10, PM2.5, BC, NOx, SO(2), CO and VOCs concentration were observed. Lockdown had a healing effect on ozone; significant increase in its concentration was observed. Aerosols Optical Depths were found to decrease up to 50%.
INTRODUCTION: Exacerbations of chronic obstructive pulmonary disease (COPD) are associated with a significant health burden both for patients and healthcare systems. Exposure to various environmental factors increases the risk of exacerbations. AREAS COVERED: We searched PubMed and assessed literature published within the last 10 years to include epidemiological evidence on the relationships between air pollution, temperature and COPD exacerbation risk as well as the implications of extreme weather events on exacerbations. EXPERT OPINION: Ongoing climate change is expected to increase air pollution levels, global temperature and the frequency and severity of extreme weather events, all of which are associated with COPD exacerbations. Further research is needed using patient-focused methodological approaches to better understand and quantify these relationships, so that effective mitigation strategies that decrease the risk of exacerbations can be developed.
Climate change is a crisis of vast proportions that has serious implications for pulmonary health. Increasing global temperatures influence respiratory health through extreme weather events, wildfires, prolonged allergy seasons, and worsening air pollution. Children, elderly patients, and patients with underlying lung disease are at elevated risk of complications from these effects of climate change. This paper summarizes the myriad ways in which climate change affects the respiratory health of patients at home and in outdoor environments and outlines measures for patients to protect themselves.
Background Air-pollution and weather exposure beyond certain thresholds have serious effects on public health. Yet, there is lack of information on wider aspects including the role of some effect modifiers and the interaction between air-pollution and weather. This article aims at a comprehensive review and narrative summary of literature on the association of air-pollution and weather with mortality and hospital admissions; and to highlight literature gaps that require further research. Methods We conducted a scoping literature review. The search on two databases (PubMed and Web-of-Science) from 2012 to 2020 using three conceptual categories of “environmental factors”, “health outcomes”, and “Geographical region” revealed a total of 951 records. The narrative synthesis included all original studies with time-series, cohort, or case cross-over design; with ambient air-pollution and/or weather exposure; and mortality and/or hospital admission outcomes. Results The final review included 112 articles from which 70 involved mortality, 30 hospital admission, and 12 studies included both outcomes. Air-pollution was shown to act consistently as risk factor for all-causes, cardiovascular, respiratory, cerebrovascular and cancer mortality and hospital admissions. Hot and cold temperature was a risk factor for wide range of cardiovascular, respiratory, and psychiatric illness; yet, in few studies, the increase in temperature reduced the risk of hospital admissions for pulmonary embolism, angina pectoris, chest, and ischemic heart diseases. The role of effect modification in the included studies was investigated in terms of gender, age, and season but not in terms of ethnicity. Conclusion Air-pollution and weather exposure beyond certain thresholds affect human health negatively. Effect modification of important socio-demographics such as ethnicity and the interaction between air-pollution and weather is often missed in the literature. Our findings highlight the need of further research in the area of health behaviour and mortality in relation to air-pollution and weather, to guide effective environmental health precautionary measures planning.
The impact of climate change on the environment, biosphere, and biodiversity has become more evident in the recent years. Human activities have increased atmospheric concentrations of carbon dioxide (CO(2) ) and other greenhouse gases. Change in climate and the correlated global warming affects the quantity, intensity, and frequency of precipitation type as well as the frequency of extreme events such as heat waves, droughts, thunderstorms, floods, and hurricanes. Respiratory health can be particularly affected by climate change, which contributes to the development of allergic respiratory diseases and asthma. Pollen and mold allergens are able to trigger the release of pro-inflammatory and immunomodulatory mediators that accelerate the onset the IgE-mediated sensitization and of allergy. Allergy to pollen and pollen season at its beginning, in duration and intensity are altered by climate change. Studies showed that plants exhibit enhanced photosynthesis and reproductive effects and produce more pollen as a response to high atmospheric levels of carbon dioxide (CO(2) ). Mold proliferation is increased by floods and rainy storms are responsible for severe asthma. Pollen and mold allergy is generally used to evaluate the interrelation between air pollution and allergic respiratory diseases, such as rhinitis and asthma. Thunderstorms during pollen seasons can cause exacerbation of respiratory allergy and asthma in patients with hay fever. A similar phenomenon is observed for molds. Measures to reduce greenhouse gas emissions can have positive health benefits.
Air pollution and climate change have a significant impact on human health and well-being and contribute to the onset and aggravation of allergic rhinitis and asthma among other chronic respiratory diseases. In Westernized countries, households have experienced a process of increasing insulation and individuals tend to spend most of their time indoors. These sequelae implicate a high exposure to indoor allergens (house dust mites, pets, molds, etc), tobacco smoke, and other pollutants, which have an impact on respiratory health. Outdoor air pollution derived from traffic and other human activities not only has a direct negative effect on human health but also enhances the allergenicity of some plants and contributes to global warming. Climate change modifies the availability and distribution of plant- and fungal-derived allergens and increases the frequency of extreme climate events. This review summarizes the effects of indoor air pollution, outdoor air pollution, and subsequent climate change on asthma and allergic rhinitis in children and adults and addresses the policy adjustments and lifestyle changes required to mitigate their deleterious effects.
BACKGROUND: Exposure to heat, air pollution, and pollen are associated with health outcomes, including cardiovascular and respiratory disease. Studies assessing the health impacts of climate change have considered increased exposure to these risk factors separately, though they may be increasing simultaneously for some populations and may act synergistically on health. Our objective is to systematically review epidemiological evidence for interactive effects of multiple exposures to heat, air pollution, and pollen on human health. METHODS: We systematically searched electronic literature databases (last search, April 29, 2019) for studies reporting quantitative measurements of associations between at least two of the exposures and mortality from any cause and cardiovascular and respiratory morbidity and mortality specifically. Following the Navigation Guide systematic review methodology, we evaluated the risk of bias of individual studies and the overall quality and strength of evidence. RESULTS: We found 56 studies that met the inclusion criteria. Of these, six measured air pollution, heat, and pollen; 39 measured air pollution and heat; 10 measured air pollution and pollen; and one measured heat and pollen. Nearly all studies were at risk of bias from exposure assessment error. However, consistent exposure-response across studies led us to conclude that there is overall moderate quality and sufficient evidence for synergistic effects of heat and air pollution. We concluded that there is overall low quality and limited evidence for synergistic effects from simultaneous exposure to (1) air pollution, pollen, and heat; and (2) air pollution and pollen. With only one study, we were unable to assess the evidence for synergistic effects of heat and pollen. CONCLUSIONS: If synergistic effects between heat and air pollution are confirmed with additional research, the health impacts from climate change-driven increases in air pollution and heat exposure may be larger than previously estimated in studies that consider these risk factors individually.
Since the publication of the last American Heart Association scientific statement on air pollution and cardiovascular disease in 2010, unequivocal evidence of the causal role of fine particulate matter air pollution (PM2.5, or particulate matter <= 2.5 mu m in diameter) in cardiovascular disease has emerged. There is a compelling case to provide the public with practical personalized approaches to reduce the health effects of PM2.5. Such interventions would be applicable not only to individuals in heavily polluted countries, high-risk or susceptible individuals living in cleaner environments, and microenvironments with higher pollution exposures, but also to those traveling to locations with high levels of PM2.5. The overarching motivation for this document is to summarize the current evidence supporting personal-level strategies to prevent the adverse cardiovascular effects of PM2.5, guide the use of the most proven/viable approaches, obviate the use of ineffective measures, and avoid unwarranted interventions. The significance of this statement relates not only to the global importance of PM2.5, but also to its focus on the most tested interventions and viable approaches directed at particulate matter air pollution. The writing group sought to provide expert consensus opinions on personal-level measures recognizing the current uncertainty and limited evidence base for many interventions. In doing so, the writing group acknowledges that its intent is to assist other agencies charged with protecting public health, without minimizing the personal choice considerations of an individual who may decide to use these interventions in the face of ongoing air pollution exposure.
PURPOSE OF REVIEW: Climate change will affect mortality associated with both ambient temperature and air pollution. Because older adults have elevated vulnerability to both non-optimal ambient temperature (heat and cold) and air pollution, population aging can amplify future population vulnerability to these stressors through increasing the number of vulnerable older adults. We aimed to review recent evidence on projections of temperature- or air pollution-related mortality burden (i.e., number of deaths) under combined climate change and population aging scenarios, with a focus on evaluating the role of population aging in assessing these health impacts of climate change. We included studies published between 2014 and 2019 with age-specific population projections. RECENT FINDINGS: We reviewed 16 temperature projection studies and 15 air pollution projection studies. Nine of the temperature studies and four of the air pollution studies took population aging into account by performing age-stratified analyses that utilized age-specific relationships between temperature or air pollution exposures and mortality (i.e., age-specific exposure-response functions (ERFs)). Population aging amplifies the projected mortality burden of temperature and air pollution under a warming climate. Compared with a constant population scenario, population aging scenarios lead to less reduction or even increases in cold-related mortality burden, resulting in substantial net increases in future overall (heat and cold) temperature-related mortality burden. There is strong evidence suggesting that to accurately assess the future temperature- and air pollution-related mortality burden of climate change, investigators need to account for the amplifying effect of population aging. Thus, all future studies should incorporate age-specific population size projections and age-specific ERFs into their analyses. These studies would benefit from refinement of age-specific ERF estimates.
The world is currently shadowed by the pandemic of COVID-19. Confirmed cases and the death toll has reached more than 12 million and more than 550,000 respectively as of 10 July 2020. In the unsettling pandemic of COVID-19, the whole Earth has been on an unprecedented lockdown. Social distancing among people, interrupted international and domestic air traffic and suspended industrial productions and economic activities have various far-reaching and undetermined implications on air quality and the climate system. Improvement in air quality has been reported in many cities during lockdown, while the death rate of COVID-19 has been found to be higher in more polluted cities. The relationship between the spread of the SARS-CoV-2 virus and air quality is under investigation. In addition, the battle against COVID-19 could bring short-lived and long-lasting and positive and negative impacts to the warming climate. The impacts on the climate system and the role of the climate in modulating the COVID-19 pandemic are the foci of scientific inquiry. The intertwined relationship among environment, climate change and public health is exemplified in the pandemic of COVID-19. Further investigation of the relationship is imperative in the Anthropocene, in particular, in enhancing disaster preparedness. This short article intends to give an up-to-date glimpse of the pandemic from air quality and climate perspectives and calls for a follow-up discussion.
Research on air quality and human health “co-benefits” from climate mitigation strategies represents a growing area of policy-relevant scholarship. Compared to other aspects of climate and energy policy evaluation, however, there are still relatively few of these co-benefits analyses. This sparsity reflects a historical disconnect between research quantifying energy and climate, and research dealing with air quality and health. The air quality co-benefits of climate, clean energy, and transportation electrification policies are typically assessed with models spanning social, physical, chemical, and biological systems. This review article summarizes studies to date and presents methods used for these interdisciplinary analyses. Studies in the peer-reviewed literature (n = 26) have evaluated carbon pricing, renewable portfolio standards, energy efficiency, renewable energy deployment, and clean transportation. A number of major findings have emerged from these studies: [1] decarbonization strategies can reduce air pollution disproportionally on the most polluted days; [2] renewable energy deployment and climate policies offer the highest health and economic benefits in regions with greater reliance on coal generation; [3] monetized air quality health co-benefits can offset costs of climate policy implementation; [4] monetized co-benefits typically exceed the levelized cost of electricity (LCOE) of renewable energies; [5] Electric vehicle (EV) adoption generally improves air quality on peak pollution days, but can result in ozone dis-benefits in urban centers due to the titration of ozone with nitrogen oxides. Drawing from these published studies, we review the state of knowledge on climate co-benefits to air quality and health, identifying opportunities for policy action and further research.
India is urbanizing at an alarming rate and the impact of climate change is becoming more visible each passing day. The rapid urbanization and climate change have severe direct and indirect consequences, such as increasing poverty, inequality, massive displacement, public health concerns, and challenges of urban governance, among others. This paper identifies some of the most pressing issues faced by urban India in the context of climate change. It also details the interventions undertaken at the local, national, and international levels to counter the effect of the climate change. In addition, it critically evaluates the role of government organizations, especially in terms of undertaking regulatory and planning functions. The paper argues that the implementation of institutional reforms would enable the government to reach out to the private sector to improve urban service delivery. It also provides examples of best practices from India and the world in combating climate change through adaptation and mitigation approaches.
Allergic rhinitis affects the quality of life of millions of people worldwide. Air pollution not only causes morbidity, but nearly 3 million people per year die from unhealthy indoor air exposure. Furthermore, allergic rhinitis and air pollution interact. This report summarizes the discussion of an International Expert Consensus on the management of allergic rhinitis aggravated by air pollution. The report begins with a review of indoor and outdoor air pollutants followed by epidemiologic evidence showing the impact of air pollution and climate change on the upper airway and allergic rhinitis. Mechanisms, particularly oxidative stress, potentially explaining the interactions between air pollution and allergic rhinitis are discussed. Treatment for the management of allergic rhinitis aggravated by air pollution primarily involves treating allergic rhinitis by guidelines and reducing exposure to pollutants. Fexofenadine a non-sedating oral antihistamine improves AR symptoms aggravated by air pollution. However, more efficacy studies on other pharmacological therapy of coexisting AR and air pollution are currently lacking.
Mesquite (Prosopis juliflora (Sw.) DC), is an medium-sized tree (family Fabaceae, subfamily Mimosoideae), that has been intorcuded around the world. It is a noxious invasive species in Africa, Asia, and the Arabian Peninsula and a source of highly allergenic pollen in. The present article reviews the adverse allergenic effects of P. juliflora pollen on human and animal health. Several studies have diagnosed that allergenic pollens from Prosopis spp. can provoke respiratory problems. Prosopis pollen extracts have 16 allergenic components of which nine proteins were recognized as major allergens with some of them showing cross-reactivity. Clinically, understanding Prosopis pollen production, flowering seasonality, pollen load, and dispersal in the atmosphere are important to avoid allergic consequences for local inhabitants. Climate change and other pollution can also help to further facilitate allergenic issues. Furthermore, we document other human and animal health problems caused by invasive Prosopis trees. This includes flesh injuries, dental and gastric problems, and the facilitation of malaria. This review summarizes and enhances the existing knowledge about Prosopis flowering phenology, aeroallergen, and other human and animal health risks associated with this noxious plant.
Future air quality will be driven by changes in air pollutant emissions, but also changes in climate. Here, we review the recent literature on future air quality scenarios and projected changes in effects on human health, crops and ecosystems. While there is overlap in the scenarios and models used for future projections of air quality and climate effects on human health and crops, similar efforts have not been widely conducted for ecosystems. Few studies have conducted joint assessments across more than one sector. Improvements in future air quality effects on human health are seen in emission reduction scenarios that are more ambitious than current legislation. Larger impacts result from changing particulate matter (PM) abundances than ozone burdens. Future global health burdens are dominated by changes in the Asian region. Expected future reductions in ozone outside of Asia will allow for increased crop production. Reductions in PM, although associated with much higher uncertainty, could offset some of this benefit. The responses of ecosystems to air pollution and climate change are long-term, complex, and interactive, and vary widely across biomes and over space and time. Air quality and climate policy should be linked or at least considered holistically, and managed as a multi-media problem. This article is part of a discussion meeting issue ‘Air quality, past present and future’.
Air pollution has broad effects on human health involving many organ systems. The ocular surface is an excellent model with which to study the effects of air pollution on human health as it is in constant contact with the environment, and it is directly accessible, facilitating disease monitoring. Effects of air pollutants on the ocular surface typically manifest as dry eye (DE) symptoms and signs. In this review, we break down air pollution into particulate matter (organic and inorganic) and gaseous compounds and summarize the literature regarding effects of various exposures on DE. Additionally, we examine the effects of weather (relative humidity, temperature) on DE symptoms and signs. To do so, we conducted a PubMed search using key terms to summarize the existing literature on the effects of air pollution and weather on DE. While we tried to focus on the effect of specific exposures on specific aspects of DE, environmental conditions are often studied concomitantly, and thus, there are unavoidable interactions between our variables of interest. Overall, we found that air pollution and weather conditions have differential adverse effects on DE symptoms and signs. We discuss these findings and potential mitigation strategies, such as air purifiers, air humidifiers, and plants, that may be instituted as treatments at an individual level to address environmental contributors to DE.
The recognition and documentation of climatic change effects on human health remains one of the most important challenges of the 21st century. While myriad in scope, one of the most recognised impacts is related to pollen, specifically its production, release and duration, and the consequences for allergic diseases, including asthma and allergic rhinitis. At present, the bulk of efforts to understand and document these links have been conducted by scientists in the Northern Hemisphere. However, the link between climate change and aeroallergenic pollen is global and international in scope. For this reason, more recent efforts to provide similar evaluations have been initiated by scientists in the Southern Hemisphere. The current review acknowledges northern enquiries, but also emphasises research gaps and inconsistencies which should be avoided by southern investigators. To remedy these deficiencies, some suggestions are offered, including a greater emphasis on plant demographics, the standardisation of pollen metrics, automation and environmental integration. It is hoped that this perspective will be able to provide support to efforts of scientists in the Southern Hemisphere to evaluate better climate shifts and aeroallergen consequences. Overall, there is a clear and pressing need to understand these likely changes while simultaneously comprehending their impact on pollen-related health outcomes – for both hemispheres.
Urban vegetation provides undeniable benefits to urban climate, health, thermal comfort and environmental quality of cities and represents one of the most considered urban heat mitigation measures. Despite the plethora of available scientific information, very little is known about the holistic and global impact of a potential increase of urban green infrastructure (GI) on urban climate, environmental quality and health, and their synergies and trade-offs. There is a need to evaluate globally the extent to which additional GI provides benefits and quantify the problems arising from the deployment of additional greenery in cities which are usually overlooked or neglected. The present paper has reviewed and analysed 55 fully evaluated scenarios and case studies investigating the impact of additional GI on urban temperature, air pollution and health for 39 cities. Statistically significant correlations between the percentage increase of the urban GI and the peak daily and night ambient temperatures are obtained. The average maximum peak daily and night-time temperature drop may not exceed 1.8 and 2.3 degrees C respectively, even for a maximum GI fraction. In parallel, a statistically significant correlation between the peak daily temperature decrease caused by higher GI fractions and heat-related mortality is found. When the peak daily temperature drops by 0.1 degrees C, then the percentage of heat-related mortality decreases on average by 3.0% The impact of additional urban GI on the concentration of urban pollutants is analysed, and the main parameters contributing to decrease or increase of the pollutants’ concentration are presented.
Children’s bodies are in dynamic stages of development that make them more susceptible to harm from exposure to environmental agents. Children’s physical, physiological and behavioral traits can lead to increased exposure to toxic chemicals or pathogens. In addition, the social determinants of health interact with this exposure and create an increasing risk for further disparities among children. In Indonesia, the fourth most populated country in the world, children are under threat of exposure to contaminated water, air, food and soil, which can cause gastrointestinal and respiratory diseases, birth defects and neurodevelopmental disorders. A safe and balanced nutrition is still an unmet need for too many children. At the same time, the prevalence of obesity and the risk of later development of metabolic diseases, including diabetes and cardiovascular diseases, are increasing as a consequence of both unhealthy diets and inadequate physical activity. The risks of potential long-term toxicity, including carcinogenic, neurotoxic, immunotoxic, genotoxic, endocrine-disrupting and allergenic effects of many chemicals, are also close to their lives. This paper provides an overview of common disease risks in Indonesian children, including: acute hepatitis A, diarrheal diseases, dengue and malaria due to lack of water supply and sanitation, vectors, and parasites; asthma, bronchopneumonia, chronic obstructive pulmonary disease (COPD) and acute respiratory infections (ARIs) due to air pollution and climate change; some chronic diseases caused by toxic and hazardous waste; and direct or indirect consequences due to the occurrence of disasters and health emergencies.
Since air pollutants are difficult and expensive to control, a strong scientific underpinning to policies is needed to guide mitigation aimed at reducing the current burden on public health. Much of the evidence concerning hazard identification and risk quantification related to air pollution comes from epidemiological studies. This must be reinforced with mechanistic confirmation to infer causality. In this review we focus on data generated from four contrasting sources of particulate air pollution that result in high population exposures and thus where there remains an unmet need to protect health: urban air pollution in developing megacities, household biomass combustion, wildfires and desert dust storms. Taking each in turn, appropriate measures to protect populations will involve advocating smart cities and addressing economic and behavioural barriers to sustained adoption of clean stoves and fuels. Like all natural hazards, wildfires and dust storms are a feature of the landscape that cannot be removed. However, many efforts from emission containment (land/fire management practices), exposure avoidance and identifying susceptible populations can be taken to prepare for air pollution episodes and ensure people are out of harm’s way when conditions are life-threatening. Communities residing in areas affected by unhealthy concentrations of any airborne particles will benefit from optimum communication via public awareness campaigns, designed to empower people to modify behaviour in a way that improves their health as well as the quality of the air they breathe.
In 2010, the American Heart Association published a statement concluding that the existing scientific evidence was consistent with a causal relationship between exposure to fine particulate matter and cardiovascular morbidity and mortality, and that fine particulate matter exposure is a modifiable cardiovascular risk factor. Since the publication of that statement, evidence linking air pollution exposure to cardiovascular health has continued to accumulate and the biological processes underlying these effects have become better understood. This increasingly persuasive evidence necessitates policies to reduce harmful exposures and the need to act even as the scientific evidence base continues to evolve. Policy options to mitigate the adverse health impacts of air pollutants must include the reduction of emissions through action on air quality, vehicle emissions, and renewable portfolio standards, taking into account racial, ethnic, and economic inequality in air pollutant exposure. Policy interventions to improve air quality can also be in alignment with policies that benefit community and transportation infrastructure, sustainable food systems, reduction in climate forcing agents, and reduction in wildfires. The health care sector has a leadership role in adopting policies to contribute to improved environmental air quality as well. There is also potentially significant private sector leadership and industry innovation occurring in the absence of and in addition to public policy action, demonstrating the important role of public-private partnerships. In addition to supporting education and research in this area, the American Heart Association has an important leadership role to encourage and support public policies, private sector innovation, and public-private partnerships to reduce the adverse impact of air pollution on current and future cardiovascular health in the United States.
Worldwide, diabetes mellitus (DM) represents a major public-health problem due to its increasing prevalence in tandem with the rising trend of obesity. However, climate change, with its associated negative health effects, also constitutes a worrisome problem. Patients with DM are experiencing more visits to emergency departments, hospitalizations, morbidity and mortality during heat waves at ever-increasing numbers. Such patients are particularly vulnerable to heat waves due to impaired thermoregulatory mechanisms in conjunction with impaired autonomous nervous system responses at high temperatures, electrolyte imbalances and rapid deterioration of kidney function, particularly among those aged > 80 years and with preexisting chronic kidney disease (CKD). Moreover, exposure to cold temperatures is associated with increased rates of acute myocardial infarction as well as poor glycaemic control, although results are conflicting regarding cold-related mortality among patients with DM. In addition to extremes of temperature, air pollution as a consequence of the climate crisis may also be implicated in the increased prevalence and incidence of DM, particularly gestational DM (GDM), and lead to deleterious effects in patients with DM. Thus, more large-scale studies are now required to elucidate the association between specific air pollutants and risk of DM. This review presents the currently available evidence for the detrimental effects of climate change, particularly those related to weather variables, on patients with DM (both type 1 and type 2) and GDM. Specifically, the effects of heat waves and extreme cold, and pharmaceutical and therapeutic issues and their implications, as well as the impact of air pollution on the risk for DM are synthesized and discussed here.
The preliminary determination of the article is to investigate the effects of pollution and climate change. In this regard, the authors want to highlight that this real and critical issue must take seriously because each of us contributes to pollution and climate change, which is very real, and which will be aggravated by not taking action. Global warming currently involves two major problems for humanity: on the one hand, the need to dramatically diminish greenhouse gas emissions to stabilize the concentration of these gases in the atmosphere to prevent anthropogenic influence on the climate system and enable ecosystems, contrastingly the need to accommodate to the consequence of climate change, given that these effects are already visible and inevitable due to the activity of the climate system, regardless of the outcome of emission reduction actions. The main problem with pollution is air quality, which has fallen considerably, especially in urban areas. The” World Health Organization” approximates, more than seven million people die each year from air pollution. The authors also conducted a case study on the local effects of climate change – Timisoara and its peri-urban area. Therefore, we concluded that if Timisoara is successful in reducing greenhouse gas emissions, this will create a test market for Romania’s ecological technologies and help the environmental industries to locate in Timisoara.
Featured Application The data and analysis can be applied to shipping emissions issues at five governmental levels: local (ports and port cities), subnational regional (port authorities), national (Italy and other countries), international regional (European Union and Mediterranean Sea coastal areas), and global (IMO). Ships’ emissions of air pollutants pose problems for local and regional public health and agricultural production, as well as global climate change. The Italian government’s endorsement in 2019 of the creation of a Mediterranean Emission Control Area is a reflection of increasing concern about the emissions. Also, ongoing developments in the International Maritime Organization and in the European Union add to the Italian government’s maritime shipping agenda and increase its complexity and uncertainty. In that context, this review paper addresses two central questions: What are the consequences for human health and agricultural production of ships’ emissions in Italian ports and coastal areas? How can their emissions be reduced? The approach to these questions is inter-disciplinary. It applies the results of studies in atmospheric chemistry and physics; maritime shipping engineering; public health; agriculture; economics; and international law and policymaking to assess current and prospective policy issues in Italy. The principal conclusions are that: (1) Black carbon emissions are threats to human health and agricultural production in Italy, as well as to the global climate. (2) It is important that black carbon emissions receive more serious attention in policymaking processes in order to reflect the significant analytic progress that has been made in terms of understanding the problems it poses and the technological and policy solutions. (3) There are cost-effective, emission-reducing measures that are readily available, as well as other measures needing more time before full-scale implementation. (4) Although existing multi-level governance systems pose complex analytic and policymaking challenges, they also offer opportunities to institute new policies with significant short-term and long-term co-benefits from reductions in emissions.
Our aim is to review current asthma epidemiology, achievements from the last 10 years, and persistent challenges of asthma management and control in low-middle income countries (LMICs). Despite global efforts, asthma continues to be an important public health problem worldwide, particularly in poorly resourced settings. Several epidemiological studies in the last decades have shown significant variability in the prevalence of asthma globally, but generally a marked increase in LMICs resulting in significant morbidity and mortality. Poverty, air pollution, climate change, exposure to indoor allergens, urbanization and diet are some of the factors that contribute to inadequate control and poor outcomes in developing countries. Although asthma guidelines have been developed to raise awareness and improve asthma diagnosis and treatment, problems with underdiagnosis and undertreatment are still common. In addition, important social, financial, cultural and healthcare barriers are common obstacles in LMICs in achieving control. Given the high burden of asthma in these countries, adaptation and implementation of national asthma guidelines tailored to local needs should be a public health priority. Governmental commitment, education, better health system infrastructure, access to care and effective asthma medications are the cornerstone of achieving success. CONCLUSION: Asthma poses significant challenges to LMICs. Whilst there are ongoing efforts in improving asthma diagnosis and decreasing asthma burden in LMICs; reasons for inadequate asthma control are also common and difficult to tackle. Improving asthma diagnosis, access to appropriate treatment and decreasing risk factors should be key goals to reduce asthma morbidity and mortality worldwide.
Since the 2003 heatwave in Europe, evidence has been rapidly increasing on the association between extreme temperature and all-cause mortality. Little is known, however, about cause-specific cardiovascular mortality, effect modification by air pollution and aircraft noise, and which population groups are the most vulnerable to extreme temperature. We conducted a time-stratified case-crossover study in Zurich, Switzerland, including all adult cardiovascular deaths between 2000 and 2015 with precise individual exposure estimates at home location. We estimated the risk of 24,884 cardiovascular deaths associated with heat and cold using distributed non-linear lag models. We investigated potential effect modification of temperature-related mortality by fine particles, nitrogen dioxide, and night-time aircraft noise and performed stratified analyses across individual and social characteristics. We found increased risk of mortality for heat (odds ratio OR = 1.28 [95% confidence interval: 1.11-1.49] for 99th percentile of daily Tmean (24 °C) versus optimum temperature at 20 °C) and cold (OR = 1.15 [0.95-1.39], 5th percentile of daily Tmean (-3 °C) versus optimum temperature at 20 °C). Heat-related mortality was particularly strong for myocardial infarctions and hypertension related deaths, and among older women (>75 years). Analysis of effect modification also indicated that older women with lower socio-economic position and education are at higher risk for heat-related mortality. PM(2.5) increased the risk of heat-related mortality for heart failure, but not all-cause cardiovascular mortality. This study provides useful information for preventing cause-specific cardiovascular temperature-related mortality in moderate climate zones comparable to Switzerland.
OBJECTIVE: The objective of the study was to explore the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures. METHODS: Outpatient and inpatient data from the National Health Insurance Database of Taiwan from 2009 to 2013, meteorological data from the Meteorological Bureau, and air pollution exposure data from the Taiwan Air Quality Monitoring Stations were collected and integrated into daily time series data. The following data processing and analysis results are based on the mean of the 7?days’ lag data of the 18 meteorological condition/air pollution exploratory factors to identify the critical meteorological conditions and air pollution exposure factors by executing univariate analysis. The average hospital visits for seizure per day by month were used as an index of observation. The effect of seasonality has also been examined. RESULTS: The average visits per day by month had a significant association with 10 variables. Overall, the number of visits due to these factors has been estimated to be 71.529 (13.7%). The most obvious factors affecting the estimated number of visits include ambient temperature, CH(4), and NO. Six air pollutants, namely CH(4), NO, CO, NO(2), PM2.5, and NMHC had a significantly positive correlation with hospital visits due to seizures. Moreover, the average daily number of hospital visits was significantly high in January and February (winter season in Taiwan) than in other months (R(2)?=?0.422). CONCLUSION: The prediction model obtained in this study indicates the necessity of rigorous monitoring and early warning of these air pollutants and climate changes by governments. Additionally, the study provided a firm basis for establishing prediction models to be used by other countries or for other diseases.
Epidemiological studies have suggested an association between particulate air pollution, increased temperatures, and morbidity related to pregnancy outcomes. However, the roles of desert dust storms and climatological factors have not been fully addressed. The objectives of the present study were to investigate the association between desert dust storms, particulate matter with a diameter ?10 ?m (PM(10)), daily temperatures, and toxemia of pregnancy and spontaneous abortion in Gaziantep, South East Turkey. The study was conducted retrospectively at emergency department of two hospitals in Gaziantep city. Data from January 1, 2009, to March 31, 2014, were collected. Patients, who were diagnosed with toxemia of pregnancy and spontaneous abortion by radiological imaging modalities, were included in the study. Daily temperature ranges, mean temperature values, humidity, pressure, wind speed, daily PM10 levels, and records of dust storms were collected. A generalized additive regression model was designed to assess variable effects on toxemia of pregnancy and spontaneous abortion, while adjusting for possible confounding factors. Our findings demonstrated that presence of dust storms was positively associated with the toxemia of pregnancy both in outpatient admissions (OR=1.543 95% CI=1.186-2.009) and inpatient hospitalizations (OR=1.534; 95% CI=1.162-2.027). However, neither PM(10) nor maximum temperature showed a marked association with spontaneous abortion or toxemia of pregnancy in our study population. Our findings suggest that desert dust storms may have an impact on the risk for adverse pregnancy outcomes such as toxemia of pregnancy. Health authorities should take necessary measures to protect pregnant women against detrimental effects of these storms.
Cold spells have been associated with mortality from a few broad categories of diseases or specific diseases. However, there is a lack of data about the health effects of cold spells on mortality from a wide spectrum of plausible diseases which can reveal a more comprehensive contour of the mortality burden of cold spells. We collected daily mortality data in Guangzhou during 2010-2018 from the Guangzhou Center for Disease Control and Prevention. The quasi-Poisson generalized linear regression model mixed with the distributed lag non-linear model (DLNM) was conducted to examine the health impacts of cold spells for 11 broad causes of death groupings and from 35 subcategories in Guangzhou. Then, we examined the effect modification by age group (0-64 and 65+ years) and sex. Effects of cold spells on mortality generally delayed for 3-5 d and persisted up to 27 d. Cold spells were significantly responsible for increased mortality risk for most categories of deaths, with cumulative relative risk (RR) over 0-27 lagged days of 1.57 [95% confidence interval (CI): 1.48-1.67], 1.95 (1.49-2.55), 1.58 (1.39-1.79), 1.54 (1.26-1.88), 1.92 (1.15-3.22), 1.75, (1.14-2.68), 2.02 (0.78-5.22), 1.92 (1.49-2.48), 1.48 (1.18-1.85), and 1.18 (1.06-1.30) for non-accidental causes, cardiovascular diseases, respiratory diseases, digestive diseases, nervous system diseases, genitourinary diseases, mental diseases, endocrine diseases, external cause and neoplasms, respectively. The magnitudes of the effects of cold spells on mortality varied remarkably among the 35 subcategories, with the largest cumulative RR of 2.87 (1.72-4.79) estimated for pulmonary heart diseases. The elderly and females were at a higher risk of mortality for most diseases after being exposed to cold spells. Increased mortality from a wide range of diseases was significantly linked with cold spells. Our findings may have important implications for formulating effective preventive strategies and early warning response plans that mitigate the health burden of cold spells.
Along with climate change, unstable weather patterns are becoming more frequent. However, the temporal trend associated with the effect of temperature variation on schizophrenia (SCZ) is not clear. Daily time-series data on SCZ and meteorological factors for 15-year between January 1, 2005 and December 31, 2019 were collected. And we used the Poisson regression model combined with the time-varying distribution lag nonlinear model (DLNM) to explore the temporal trend of the association between three temperature variation indicators (diurnal temperature range, DTR; temperature variability, TV; temperature change between neighboring days, TCN) and SCZ hospitalizations, respectively. Meanwhile, we also explore the temporal trend of the interaction between temperature and temperature variation. Stratified analyses were performed in different gender, age, and season. Across the whole population, we found a decreasing trend in the risk of SCZ hospitalizations associated with high DTR (from 1.721 to 1.029), TCN (from 1.642 to 1.066), and TV (TV0-1, from 1.034 to 0.994; TV0-2, from 1.041 to 0.994, TV0-3, from 1.044 to 0.992, TV0-4, from 1.049 to 0.992, TV0-5, from 1.055 to 0.993, TV0-6, from 1.059 to 0.991, TV0-7, from 1.059 to 0.990), but an increasing trend in low DTR (from 0.589 to 0.752). Subgroup analysis results further revealed different susceptible groups. Besides, the interactive effect suggests that temperature variation may cause greater harm under low-temperature conditions. There was a synergy between TCN and temperature on the addition and multiplication scales, which were 1.068 (1.007, 1.133) and 0.067 (0.009, 0.122), respectively. Our findings highlight public health interventions to mitigate temperature variation effects needed to focus not only on high temperature variations but also moderately low temperature variations. Future hospitalizations for SCZ associated with temperature variation may be more severely affected by temperature variability from low temperature environments. The temporal trend is associated with the effect of temperature variation on schizophrenia (SCZ).
Urban air pollution can have negative short- and long-term impacts on health, including cardiovascular, neurological, immune system and developmental damage. The irritant qualities of pollutants such as ozone (O(3)), nitrogen dioxide (NO(2)) and particulate matter (PM) can cause respiratory and cardiovascular distress, which can be heightened during physical activity and particularly so for those with respiratory conditions such as asthma. Previously, research has only examined marathon run outcomes or running under laboratory settings. This study focuses on elite 5-km athletes performing in international events at nine locations. Local meteorological and air quality data are used in conjunction with race performance metrics from the Diamond League Athletics series to determine the extent to which elite competitors are influenced during maximal sustained efforts in real-world conditions. The findings from this study suggest that local meteorological variables (temperature, wind speed and relative humidity) and air quality (ozone and particulate matter) have an impact on athletic performance. Variation between finishing times at different race locations can also be explained by the local meteorology and air quality conditions seen during races.
The effects of daily mean temperature on health outcomes have been discussed in many previous studies, but few have considered the adverse impacts on upper respiratory tract infection (URTI) due to variance of temperature in one day. Diurnal temperature range (DTR) was a novel indicator calculated as maximum temperature minus minimum temperature on the same day. In this study, generalized additive model (GAM) with quasi-Poisson distribution was used to investigate the association between DTR and the number of daily outpatient visits for URTI among college students. Data about meteorological factors and air pollutants were provided by Hubei Meteorological Bureau and Wuhan Environmental Protection Bureau, respectively. Outpatient visits data were collected from the Hospital of Wuhan University from January 1, 2016, to December 31, 2018. Short-term exposure to DTR was associated with the increased risk of outpatient for URTI among all college students. Per 1 °C increased in DTR was associated with 0.73% (95%CI: 0.24, 1.21) increased in outpatient visits of all college students for URTI at lag 0 day. The greatest effect values were observed in males [1.35% (95%CI: 0.33,2.39)] at lag 0-6 days, and in females [0.86% (95%CI: 0.24, 1.49)] at lag 0-1 days. DTR had more adverse health impact in autumn and winter. Public health departments should consider the negative effect of DTR to formulate more effective prevention and control measures for protecting vulnerable people.
PURPOSE: Diurnal temperature range (DTR) is a meteorological indicator closely associated with global climate change. Thus, we aim to explore the effects of DTR on the outpatient and emergency room (O&ER) admissions for cardiovascular diseases (CVDs), and related predictive research. METHODS: The O&ER admissions data for CVDs from three general hospitals in Jinchang of Gansu Province were collected from 2013 to 2016. A generalized additive model (GAM) with Poisson regression was employed to analyze the effect of DTR on the O&ER admissions for all cardiovascular diseases, hypertension, ischemic heart disease (IHD) and stoke. GAM was also used to preform predictive research of the effect of DTR on the O&ER admissions for CVDs. RESULTS: There were similar positive linear relationships between DTR and the O&ER visits with the four cardiovascular diseases. And the cumulative lag effects were higher than the single lag effects. A 1 °C increase in DTR corresponded to a 1.30% (0.99-1.62%) increase in O&ER admissions for all cardiovascular diseases. Males and elderly were more sensitivity to DTR. The estimates in non-heating season were higher than in heating season. The trial prediction accuracy rate of CVDs based on DTR was between 59.32 and 74.40%. CONCLUSIONS: DTR has significantly positive association with O&ER admissions for CVDs, which can be used as a prediction index of the admissions of O&ER with CVDs.
We herein report a 56-year-old woman who developed allergic bronchopulmonary aspergillosis (ABPA) possibly due to fungal exposure after disastrous heavy rainfall in Western Japan in 2018. She was diagnosed with ABPA complicated with asthma, increased peripheral blood eosinophil count, elevation of specific immunoglobulin E for Aspergillus fumigatus, positive Aspergillus fumigatus precipitation antibody reaction test results, and notable chest computed tomography findings. After treatment with benralizumab, her symptoms, peripheral blood eosinophil count, radiological findings, and respiratory function dramatically improved. The administration of benralizumab appears to be an effective treatment strategy for ABPA.
To date, research evidence suggests that extreme ambient temperatures may lead to preterm birth. Since the results of studies in subtropical humid monsoon climate are inconclusive, we investigated the association between extreme ambient temperatures and the risk of preterm birth in Xuzhou, China. We analyzed the association between the birth data of 103,876 singleton deliveries (from July 1, 2016 to June 30, 2019) and ambient temperature. We used a quasi-Poisson model with distributed lag nonlinear models (DLNM) to investigate the delay and nonlinear effects of temperature, taking into account the effects of air pollutants and relative humidity. During the study period, the number of hospitalizations for preterm birth was 4623. Taking the median temperature (16.8 °C) as a reference, the highest risk estimate at extreme cold temperature (- 2.8 °C, 1st percentile) was found at lag 0-1 days. Exposure to extreme cold (- 2.8 °C, 1st percentile), or moderate cold (6.8 °C, 25th percentile) were associated with 1.659 (95% confidence interval [CI] 1.177-2.338) and 1.456 (95% CI 1.183-1.790) increased risks of preterm birth, respectively. In the further stratified analysis of the age of pregnant women, we found that there were significant associations between cold temperatures and preterm birth in both groups (older group ? 35; younger group < 35). In a subtropical humid monsoon climate, low ambient temperatures may lead to preterm birth, suggesting that women should stay away from low temperatures during pregnancy.
Temperature change is an important meteorological indicator reflecting weather stability. This study aimed to examine the effects of ambient temperature change on non-accidental mortality using diurnal temperature change (DTR) and temperature change between neighboring days (TCN) from two perspectives, intra-day and inter-day temperature change, and further, to explore seasonal variations of mortality, identify the susceptible population and investigate the interaction between temperature change and apparent temperature (AT). We collected daily data on cause-specific mortality, air pollutants and meteorological indicators in Shenzhen, China, from 1 January 2013 to 29 December 2017. A Quasi-Poisson generalized linear regression combined with distributed lag non-linear models (DLNMs) were conducted to estimate the effects of season on temperature change-related mortality. In addition, a non-parametric bivariate response surface model was used to explore the interaction between temperature change and AT. The cumulative effect of DTR was a U-shaped curve for non-accidental mortality, whereas the curve for TCN was nearly monotonic. The overall relative risks (RRs) of non-accidental, cardiovascular and respiratory mortality were 1.407 (95% CI: 1.233-1.606), 1.470 (95% CI: 1.220-1.771) and 1.741 (95% CI: 1.157-2.620) from exposure to extreme large DTR (99th) in cold seasons. However, no statistically significant effects were observed in warm seasons. As for TCN, the effects were higher in cold seasons than warm seasons, with the largest RR of 1.611 (95% CI: 1.384-1.876). The elderly and females were more sensitive, and low apparent temperature had a higher effect on temperature change-related non-accidental mortality. Temperature change was positively correlated with an increased risk of non-accidental mortality in Shenzhen. Both female and elderly people are more vulnerable to the potential adverse effects, especially in cold seasons. Low AT may enhance the effects of temperature change.
Considering the increasing rate of hospitalization due to the symptoms intensification, and the increasing trend of air pollution, this study aimed to determine the relationship between the amount of air pollutants and the incidence of cardiovascular disease leading to hospitalization. This case-crossover study was carried out on the data of admitted patients with cardiovascular disease such as hypertension, ischemic heart disease, and cerebrovascular disease in Urmia during 2011-2016. Weather data about air pollutants (NO2, PM10, SO2, and CO) were obtained from the meteorological department of Urmia. The data were coded for each patient and matched with the meteorological data for statistical modeling. The data were analyzed through STATA version 14. Conditional logistic regression was used to estimate the effects of air pollutants on cardiovascular disease adjusted to air temperature, relative humidity, and air pollutants. The final analysis was performed on 43,424 patients with cardiovascular disease using code I10-I99 including ischemic heart disease, hypertension, and cerebrovascular disease adjusted to air temperature and relative humidity. Of all pollutants, CO with each increase 10 ?g/m(3) had a meaningful relationship with the incidence of cardiovascular hospitalization. By selecting the window of exposure, 1, 2, and 6 days before admission, lag 6 (6 days) was the best estimation for exposure time in the patients with cardiovascular patients (OR 1.0056, CI 1.0041-1.007), and in the patients with ischemic heart disease (OR 1.000055, CI 1.000036-1.000075) and in the patients with hypertension (OR 1.000076, CI 1.00002-1.000132). Regarding cerebrovascular disease, no statistically significant association was observed. The results showed that only CO was associated with an increased risk of admission in patients with cardiovascular disease, ischemic heart disease, and hypertension, and there was no clear evidence for pollution effects on cerebrovascular diseases.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors, and the daily reported infected cases caused by novel coronavirus in India. The daily positive infected cases, concentrations of air pollutants, and meteorological factors in 288 districts were collected from January 30, 2020, to April 23, 2020, in India. Spearman’s correlation and generalized additive model (GAM) were applied to investigate the correlations of four air pollutants (PM(2.5), PM(10), NO(2), and SO(2)) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS, and WD) with COVID-19-infected cases. The study indicated that a 10 ?g/m(3) increase during (Lag0-14) in PM(2.5), PM(10), and NO(2) resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01), and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of Coronavirus Disease 2019 (COVID 19)-infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19-infected cases respectively. In addition, SO(2) and relative humidity were negatively associated with COVID-19-infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO(2) and for relative humidity respectively. The study recommended that there are significant correlations between air pollutants and meteorological factors with COVID-19-infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.
PURPOSE: The aim of the present study was to investigate the effect of short-term exposure to ambient black carbon (BC) on daily cause-specific mortality, including mortality due to respiratory, cardiovascular, ischemic heart and cerebrovascular diseases in Tehran, Iran. MATERIALS AND METHODS: Daily non-accidental death counts, meteorological data and hourly concentrations of air pollutants from 2014 to 2017 were collected in Tehran. A distributed lag non-linear model was used to assess the association between exposure to BC and daily mortality. RESULTS: The mean daily BC concentration during the study period was 3.96?±?1.19 µg/m(3). The results indicated that BC was significantly associated with cardiovascular, ischemic heart disease, and cerebrovascular mortality, but not with respiratory mortality. In first model, each 10 µg/m(3) increase in at lag 3, lag 4 and lag 5 were associated with cardiovascular mortality in 16-65 year age group with the relative risks (RRs) of 1.17 (95?% CI: 1.02-1.33), 1.17 (95?% CI: 1.04-1.31) and 1.12 (95?% CI: 1.02-1.24), respectively. The highest mortality rate per 10 µg/m(3) increase in exposure was found for ischemic heart diseases with RR of 3.98 (95?% CI: 1.04-1.81, lag 01) for 16-65 age group. Cerebrovascular mortality was associated with 10 µg/m(3) increases in non-cumulative exposure with RR of 1.17 (95?% 1.009-1.35, lag 5) in the age group ? 65 years. In the second model for a 10 µg/m(3) increase in BC, cardiovascular mortality at specific lag days (5 and 6 days) in the age group ? 16 years were associated with RR of 1.34 (95?% CI 1.08-1.66) and 1.35(95?% CI 1.02-1.77), respectively. CONCLUSIONS: This study in Tehran found significant effects of BC exposure on daily mortality for cardiovascular, ischemic heart disease, cerebrovascular disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40201-021-00659-0.
Ischemic stroke is one of the most common causes of death worldwide, and uncomfortable meteorological and built environments may increase its risk. Residents in different built environments are exposed to different risks of ischemic stroke in cold and hot weather. By using the data from 3547 patients hospitalized, a distributed lag non-linear model was established to compare the differences in the risk of ischemic stroke in urban areas with respect to different Building Height, Building Density, Normalized Differential Vegetation Index, and Distance to Water under the meteorological condition. The results showed that lower Building Height is related to the negative cold effects in winter, and higher Building Height is related to increased risks at high temperatures. Built environments with Building Heights of 10-15 m in hot weather and above 15 m in cold weather have low risks. Higher Building Density was found to be associated with reduced negative cold effects; however, the negative hot effects increased in summer. Built environments with a Building Density of more than 0.3 showed low risks, regardless of the weather conditions. Increasing NDVI seemed to mitigate negative effects in uncomfortable weather, and built environments with higher NDVI were found to be associated with lower risks of ischemic stroke. Built environments with shorter Distance to Water seemed to pose higher risks in summer, and longer Distance to Water was correlated with higher risks in winter. Built environments with Distance to Water in the range of 0.65-2.30 km showed low risks. The research results could have some implications for urban planners to form reasonable built environments under certain meteorological factors which can be beneficial for the mitigation of incidence of ischemic stroke. (C) 2020 Elsevier B.V. All rights reserved.
During the summer of 2018 Sweden experienced a high occurrence of wildfires, most intense in the low-densely populated Jämtland Härjedalen region. The aim of this study was to investigate any short-term respiratory health effects due to deteriorated air quality generated by the smoke from wildfires. For each municipality in the region Jämtland Härjedalen, daily population-weighted concentrations of fine particulate matter (PM(2.5)) were calculated through the application of the MATCH chemistry transport model. Modelled levels of PM(2.5) were obtained for two summer periods (2017, 2018). Potential health effects of wildfire related levels of PM(2.5) were examined by studying daily health care contacts concerning respiratory problems in each municipality in a quasi-Poisson regression model, adjusting for long-term trends, weekday patterns and weather conditions. In the municipality most exposed to wildfire smoke, having 9 days with daily maximum 1-h mean of PM(2.5) > 20 ?g/m(3), smoke days resulted in a significant increase in daily asthma visits the same and two following days (relative risk (RR) = 2.64, 95% confidence interval (CI): 1.28-5.47). Meta-estimates for all eight municipalities revealed statistically significant increase in asthma visits (RR = 1.68, 95% CI: 1.09-2.57) and also when grouping all disorders of the lower airways (RR = 1.40, 95% CI: 1.01-1.92).
Desert dust transported from the Saharan-Sahel region to the Caribbean Sea is responsible for peak exposures of particulate matter (PM). This study explored the potential added value of satellite aerosol optical thickness (AOT) measurements, compared to the PM concentration at ground level, to retrospectively assess exposure during pregnancy. MAIAC MODIS AOT retrievals in blue band (AOT(470)) were extracted for the French Guadeloupe archipelago. AOT(470) values and PM(10) concentrations were averaged over pregnancy for 906 women (2005-2008). Regression modeling was used to examine the AOT(470)-PM(10) relationship during pregnancy and test the association between dust exposure estimates and preterm birth. Moderate agreement was shown between mean AOT(470) retrievals and PM(10) ground-based measurements during pregnancy (R(2)?=?0.289). The magnitude of the association between desert dust exposure and preterm birth tended to be lower using the satellite method compared to the monitor method. The latter remains an acceptable trade-off between epidemiological relevance and exposure misclassification, in areas with few monitoring stations and complex topographical/meteorological conditions, such as tropical islands.
Previous studies demonstrated that global warming can lead to deteriorated air quality even when anthropogenic emissions were kept constant, which has been called a climate change penalty on air quality. It is expected that anthropogenic emissions will decrease significantly in the future considering the aggressive emission control actions in China. However, the dependence of climate change penalty on the choice of emission scenario is still uncertain. To fill this gap, we conducted multiple independent model simulations to investigate the response of PM(2.5) to future (2050) climate warming (RCP8.5) in China but with different emission scenarios, including the constant 2015 emissions, the 2050 CLE emissions (based on Current Legislation), and the 2050 MTFR emissions (based on Maximum Technically Feasible Reduction). For each set of emissions, we estimate climate change penalty as the difference in PM(2.5) between a pair of simulations with either 2015 or 2050 meteorology. Under 2015 emissions, we find a PM(2.5) climate change penalty of 1.43 ?g m(-3) in Eastern China, leading to an additional 35,000 PM(2.5)-related premature deaths [95% confidence interval (CI), 21,000-40,000] by 2050. However, the PM(2.5) climate change penalty weakens to 0.24 ?g m(-3) with strict anthropogenic emission controls under the 2050 MTFR emissions, which decreases the associated PM(2.5)-related deaths to 17,000. The smaller MTFR climate change penalty contributes 14% of the total PM(2.5) decrease when both emissions and meteorology are changed from 2015 to 2050, and 24% of total health benefits associated with this PM(2.5) decrease in Eastern China. This finding suggests that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM(2.5) and its associated premature deaths, even though a climate change penalty still occurs even under MTFR. Strengthened controls on anthropogenic emissions are key to attaining air quality targets and protecting human health in the context of future global climate change.
OBJECTIVES: The primary objective was to evaluate the association between weather variables and joint pain in patients with chronic rheumatic diseases (CRD: rheumatoid arthritis (RA), osteoarthritis (OA), and spondyloarthritis (SpA)). A secondary objective was to study the impact of air pollution indicators on CRD pain. METHOD: The study is prospective, correlational, with time-series analysis. Patients with CRD, living in a predefined catchment area, filled their level of pain daily using a 0-10 numerical scale (NS), for 1 year. Weather (temperature, relative humidity (H), atmospheric pressure (P)) and air pollution indicators (particulate matters (PM(10), PM(2.5)), nitrogen dioxide (NO(2)), and ozone (O(3))) were recorded daily using monitoring systems positioned in the same area. Association between pain and weather and air pollution indicators was studied using Pearson’s correlation. Time-series analysis methodology was applied to determine the temporal relationship between pain and indicators. RESULTS: The study included 94 patients, 82% reported they were weather-sensitive. Pain variation was similar across diseases over a year. Pain was associated negatively with temperature, H, and O(3,) and positively with P and NO(2). However, the strength of correlation was moderate; temperature explained 22% of pain variance. A drop of 10°C in temperature corresponded to an increase of 0.5 points in pain NS. Also, there was a significant interaction among environmental factors. In time-series analysis, temperature and NO(2) remained independently associated with pain. CONCLUSIONS: The perception of joint pain in patients with CRD was correlated with weather and air pollution. The strength of association was moderate and independent of underlying disease. Key Points •Weather variation was moderately correlated with joint pain in chronic rheumatic diseases, with an inverse association with temperature, humidity, and O(3). • Air pollution indicators, mainly nitrogen dioxide and ozone, were correlated with joint pain; particulate matters were also correlated but to a lesser extent. • The influence of these environmental factors was independent of the type of rheumatic disease, thus raising the hypothesis of their impact on pain perception mechanisms.
Exposure to air pollution has been suggested to be associated with an increased risk of women’s health disorders. However, it remains unknown to what extent changes in ambient air pollution affect gynecological cancer. In our case-control study, the logistic regression model was combined with the restricted cubic spline to examine the association of short-term exposure to air pollution with gynecological cancer events using the clinical data of 35,989 women in Beijing from December 2008 to December 2017. We assessed the women’s exposure to air pollutants using the monitor located nearest to each woman’s residence and working places, adjusting for age, occupation, ambient temperature, and ambient humidity. The adjusted odds ratios (ORs) were examined to evaluate gynecologic cancer risk in six time windows (Phase 1-Phase 6) of women’s exposure to air pollutants (PM(2.5), CO, O(3), and SO(2)) and the highest ORs were found in Phase 4 (240 days). Then, the higher adjusted ORs were found associated with the increased concentrations of each pollutant (PM(2.5), CO, O(3), and SO(2)) in Phase 4. For instance, the adjusted OR of gynecological cancer risk for a 1.0-mg m(-3) increase in CO exposures was 1.010 (95% CI: 0.881-1.139) below 0.8 mg m(-3), 1.032 (95% CI: 0.871-1.194) at 0.8-1.0 mg m(-3), 1.059 (95% CI: 0.973-1.145) at 1.0-1.4 mg m(-3), and 1.120 (95% CI: 0.993-1.246) above 1.4 mg m(-3). The ORs calculated in different air pollution levels accessed us to identify the nonlinear association between women’s exposure to air pollutants (PM(2.5), CO, O(3), and SO(2)) and the gynecological cancer risk. This study supports that the gynecologic risks associated with air pollution should be considered in improved public health preventive measures and policymaking to minimize the dangerous effects of air pollution.
Exposure to air pollution is of great concern for public health although studies on the associations between exposure estimates and personal exposure are limited and somewhat inconsistent. The aim of this study was to quantify the associations between personal nitrogen oxides (NO(x)), ozone (O(3)) and particulate matter (PM(10)) exposure levels and ambient levels, and the impact of climate and time spent outdoors in two cities in Sweden. Subjects (n?=?65) from two Swedish cities participated in the study. The study protocol included personal exposure measurements at three occasions, or waves. Personal exposure measurements were performed for NO(x) and O(3) for 24 h and PM(10) for 24 h, and the participants kept an activity diary. Stationary monitoring stations provided hourly data of NO(x), O(3) and PM, as well as data on air temperature and relative humidity. Data were analysed using mixed linear models with the subject-id as a random effect and stationary exposure and covariates as fixed effects. Personal exposure levels of NO(x), O(3) and PM(10) were significantly associated with levels measured at air pollution monitoring stations. The associations persisted after adjusting for temperature, relative humidity, city and wave, but the modelled estimates were slightly attenuated from 2.4% (95% CI 1.8-2.9) to 2.0% (0.97-2.94%) for NO(x), from 3.7% (95% CI 3.1-4.4) to 2.1% (95% CI 1.1-2.9%) for O(3) and from 2.6% (95% 0.9-4.2%) to 1.3% (95% CI?-?1.5-4.0) for PM(10). After adding covariates, the degree of explanation offered by the model (coefficient of determination, or R(2)) did not change for NO(x) (0.64 to 0.63) but increased from 0.46 to 0.63 for O(3), and from 0.38 to 0.43 for PM(10). Personal exposure to NO(x), O(3) and PM has moderate to good association with levels measured at urban background sites. The results indicate that stationary measurements are valid as measure of exposure in environmental health risk assessments, especially if they can be refined using activity diaries and meteorological data. Approximately 50-70% of the variation of the personal exposure was explained by the stationary measurement, implying occurrence of misclassification in studies using more crude exposure metrics, potentially leading to underestimates of the effects of exposure to ambient air pollution.
Although Ahvaz is considered as one of the warmest cities around the world, few epidemiological studies have been conducted on the adverse effects of temperature on human health using thermal indices in this city. This study investigates the relation between physiologically equivalent temperature (PET) and respiratory hospital admissions in Ahvaz. Distributed lag non-linear models (DLNMs) combined with quasi-Poisson regression models were used to investigate the relation between PET and respiratory disease hospital admissions, adjusted for the effect of time trend, air pollutants (NO(2), SO(2), and PM(10)), and weekdays. The analysis was performed by utilizing R software. Low PET values significantly decreased the risk of hospital admissions for total respiratory diseases, respiratory diseases in men and women, chronic obstructive pulmonary diseases (COPD), and bronchiectasis. However, low PET (16.9°C) in all lags except lag 0-30 significantly increased the risk of hospital admissions for asthma. The results indicate that in Ahvaz, which has a warm climate, cold weather decreased overall respiratory hospital admissions, except for asthma.
Air pollution in large cities produces numerous diseases and even millions of deaths annually according to the World Health Organization. Pollen exposure is related to allergic diseases, which makes its prediction a valuable tool to assess the risk level to aeroallergens. However, airborne pollen concentrations are difficult to predict due to the inherent complexity of the relationships among both biotic and environmental variables. In this work, a stochastic approach based on supervised machine learning algorithms was performed to forecast the daily Olea pollen concentrations in the Community of Madrid, central Spain, from 1993 to 2018. Firstly, individual Light Gradient Boosting Machine (LightGBM) and artificial neural network (ANN) models were applied to predict the day of the year (DOY) when the peak of the pollen season occurs, resulting the estimated average peak date 149.1?±?9.3 and 150.1?±?10.8 DOY for LightGBM and ANN, respectively, close to the observed value (148.8?±?9.8). Secondly, the daily pollen concentrations during the entire pollen season have been calculated using an ensemble of two-step GAM followed by LightGBM and ANN. The results of the prediction of daily pollen concentrations showed a coefficient of determination (r(2)) above 0.75 (goodness of the model following cross-validation). The predictors included in the ensemble models were meteorological variables, phenological metrics, specific site-characteristics, and preceding pollen concentrations. The models are state-of-the-art in machine learning and their potential has been shown to be used and deployed to understand and to predict the pollen risk levels during the main olive pollen season.
According to the European Environment Agency, the year 2015 was the warmest on record to that point, with a series of heat waves from May to September resulted in high levels of tropospheric ozone. The implications of such a year on the human well-being and health are therefore of multiple nature and can be quantified referring to the exceedances of the corresponding thresholds. This work focused on the analysis of the May-September period of 2015 in the city of Milan (Italy) in terms of Mediterranean Outdoor Comfort Index (MOCI) and ozone concentrations, recorded by monitoring stations and modeled through the Weather Research and Forecasting model. Main findings show that thermo-hygrometric stress events (periods of at least six consecutive days characterized by daily maximum values of the MOCI higher than 0.5) are characterized by daily ozone higher than the guideline level of the World Health Organization (equal to 100 ?gm(-3)). This means that thermo-hygrometric stress conditions are added up to poor air quality conditions, with severe risks for human health. Moreover, a daily MOCI-daily ozone correlation coefficient equal to 0.6 was found for the whole period. The degree of correspondence between ozone events (defined according to the European Air Quality Directive) and MOCI events was also investigated pointing out that 86% and 95% of days during ozone events are correctly predicted by events of recorded and modeled MOCI respectively, with a corresponding false alarm rate of 3% and 9%.
Schizophrenia (SCZ) hospital re-admissions constitute a serious disease burden worldwide. Some studies have reported an association between air pollutants and hospital admissions for SCZ. However, evidence is scarce regarding the effects of ambient particulate matter (PM) on SCZ hospital re-admissions, especially in coastal cities in China. The purpose of this study was to examine whether PM affects the risk of SCZ hospital re-admission in the coastal Chinese city of Qingdao. Daily SCZ hospital re-admissions, daily air pollutants, and meteorological factors from 2015 to 2019 were collected. A quasi-Poisson generalized linear regression model combined with distributed lag non-linear model (DLNM) was applied to model the exposure-lag-response relationship between PM and SCZ hospital re-admissions. The relative risks (RRs) were estimated for an inter-quartile range (IQR) increase in PM concentrations. Subgroup analyses by age and gender were conducted to identify the vulnerable subgroups. There were 6220 SCZ hospital re-admissions during 2015-2019. The results revealed that PM, including PM(10) (particles with an aerodynamic diameter ?10 ?m), PM(c) (particles >2.5 ?m but <10 ?m), and PM(2.5) (particles ?2.5 ?m), was positively correlated with SCZ hospital re-admissions. The strongest single-day effects all occurred on lag3 day, and the corresponding RRs were 1.07 (95% CI: 1.02-1.11) for PM(10), 1.03 (95% CI: 1.00-1.07) for PM(c), and 1.05 (95% CI: 1.01-1.09) for PM(2.5) per IQR increase. Stronger associations were observed in males and younger individuals (<45 years). Our findings suggest that PM exposure is associated with increased risk of SCZ hospital re-admission. Active intervention measures against PM exposure should be taken to reduce the risk of SCZ hospital re-admission, especially for males and younger individuals.
The short-term effects of ambient temperature on mortality have been widely investigated. However, the epidemiological evidence on the long-term effects of temperature on mortality is rare. In present study, we conducted a nationwide quasi-experimental design, which based on a variant of difference-in-differences (DID) approach, to examine the association between long-term exposure to ambient temperature and mortality risk in China, and to analyze the effect modification of population characteristics and socioeconomic status. Data on mortality were collected from 364 communities across China during 2006-2017, and environmental data were obtained for the same period. We estimated a 2.93 % (95 % CI: 2.68 %, 3.18 %) increase in mortality risk per 1 °C decreases in annual temperature, the greater effects were observed on respiratory diseases (5.16 %, 95 % CI: 4.53 %, 5.79 %) than cardiovascular diseases (3.43 %, 95 % CI: 3.06 %, 3.80 %), and on younger people (4.21 %, 95 % CI: 3.73 %, 4.68 %) than the elderly (2.36 %, 95 % CI: 2.06 %, 2.65 %). In seasonal analysis, per 1 °C decreases in average temperature was associated with 1.55 % (95 % CI: 1.23 %, 1.87 %), -0.53 % (95 % CI: -0.89 %, -0.16 %), 2.88 % (95 % CI: 2.45 %, 3.31 %) and 4.21 % (95 % CI: 3.98 %, 4.43 %) mortality change in spring, summer, autumn and winter, respectively. The effects of long-term temperature on total mortality were more pronounced among the communities with low urbanization, low education attainment, and low GDP per capita. In total, the decrease of average temperature in summer decreased mortality risk, while increased mortality risk in other seasons, and the associations were modified by demographic characteristics and socioeconomic status. Our findings suggest that populations with disadvantaged characteristics and socioeconomic status are vulnerable to long-term exposure of temperature, and targeted policies should be formulated to strengthen the response to the health threats of temperature exposure.
Livability, resilience, and justice in cities are challenged by climate change and the historical legacies that together create disproportionate impacts on human communities. Urban green infrastructure has emerged as an important tool for climate change adaptation and resilience given their capacity to provide ecosystem services such as local temperature regulation, stormwater mitigation, and air purification. However, realizing the benefits of ecosystem services for climate adaptation depend on where they are locally supplied. Few studies have examined the potential spatial mismatches in supply and demand of urban ecosystem services, and even fewer have examined supply-demand mismatches as a potential environmental justice issue, such as when supply-demand mismatches disproportionately overlap with certain socio-demographic groups. We spatially analyzed demand for ecosystem services relevant for climate change adaptation and combined results with recent analysis of the supply of ecosystem services in New York City (NYC). By quantifying the relative mismatch between supply and demand of ecosystem services across the city we were able to identify spatial hot- and coldspots of supply-demand mismatch. Hotspots are spatial clusters of census blocks with a higher mismatch and coldspots are clusters with lower mismatch values than their surrounding blocks. The distribution of mismatch hot- and coldspots was then compared to the spatial distribution of socio-demographic groups. Results reveal distributional environmental injustice of access to the climate-regulating benefits of ecosystem services provided by urban green infrastructure in NYC. Analyses show that areas with lower supply-demand mismatch tend to be populated by a larger proportion of white residents with higher median incomes, and areas with high mismatch values have lower incomes and a higher proportion of people of color. We suggest that urban policy and planning should ensure that investments in “nature-based” solutions such as through urban green infrastructure for climate change adaptation do not reinforce or exacerbate potentially existing environmental injustices.
Statistical models to evaluate the relationships between large-scale meteorological conditions, prevailing air pollution levels and combined ozone and temperature events, were developed during the 1993-2012 period with Central Europe as regional focus. Combined ozone and temperature events were defined based on the high frequency of coinciding, health-relevant elevated levels of daily maximum tropospheric ozone concentrations (based on running 8-h means) and daily maximum temperature values in the peak ozone and temperature season from April to September. By applying two different modeling approaches based on lasso, logistic regression, and multiple linear regression mean air temperatures at 850 hPa, ozone persistence, surface thermal radiation, geopotential heights at 850 hPa, meridional winds at 500 hPa, and relative humidity at 500 hPa were identified as main drivers of combined ozone and temperature events. Statistical downscaling projections until the end of the twenty-first century were assessed by using the output of seven models of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Potential frequency shifts were evaluated by comparing the mid- (2031-2050) and late-century (2081-2100) time windows to the base period (1993-2012). A sharp increase of ozone-temperature events was projected under RCP4.5 and RCP8.5 scenario assumptions with respective multi-model mean changes of 8.94% and 16.84% as well as 13.33% and 37.52% for mid- and late-century European climate.
BACKGROUND: Short-term exposure to PM(2.5) has been widely associated with human morbidity and mortality. However, most up-to-date research was conducted at a daily timescale, neglecting the intra-day variations in both exposure and outcome. As an important fraction in PM(2.5), PM(1) has not been investigated about the very acute effects within a few hours. METHODS: Hourly data for size-specific PMs (i.e., PM(1), PM(2.5), and PM(10)), all-cause emergency department (ED) visits and meteorological factors were collected from Guangzhou, China, 2015-2016. A time-stratified case-crossover design with conditional logistic regression analysis was performed to evaluate the hourly association between size-specific PMs and ED visits, adjusting for hourly mean temperature and relative humidity. Subgroup analyses stratified by age, sex and season were conducted to identify potential effect modifiers. RESULTS: A total of 292,743 cases of ED visits were included. The effects of size-specific PMs exhibited highly similar lag patterns, wherein estimated odds ratio (OR) experienced a slight rise from lag 0-3 to 4-6 h and subsequently attenuated to null along with the extension of lag periods. In comparison with PM(2.5) and PM(10), PM(1) induced slightly larger effects on ED visits. At lag 0-3 h, for instance, ED visits increased by 1.49% (95% confidence interval: 1.18-1.79%), 1.39% (1.12-1.66%) and 1.18% (0.97-1.40%) associated with a 10-?g/m(3) rise, respectively, in PM(1), PM(2.5) and PM(10). We have detected a significant effect modification by season, with larger PM(1)-associated OR during the cold months (1.017, 1.013 to 1.021) compared with the warm months (1.010, 1.005 to 1.015). CONCLUSIONS: Our study provided brand-new evidence regarding the adverse impact of PM(1) exposure on human health within several hours. PM-associated effects were significantly more potent during the cold months. These findings may aid health policy-makers in establishing hourly air quality standards and optimizing the allocation of emergency medical resources.
PM(2.5) pollution has adverse health effects on humans. Urbanization and long-term meteorological variations play important roles in influencing the PM(2.5) concentration and its associated health effects. Our results indicate that the urbanization process can enhance the PM(2.5) concentration globally. The PM(2.5)-caused mortality density (deaths/100 km(2)) is also positively correlated with the urbanization degree in both developed and developing countries. The results from machine learning technique revealed that the meteorology-driven variation in PM(2.5)-caused health burden has increased with the increase in the urbanization degree from 1980 to 2018, suggesting that residents living in urban areas are more vulnerable to experiencing unfavorable meteorological conditions (e.g. low wind speed and planetary boundary layer height). The maximum difference in PM(2.5)-caused mortality due to the variation in annual meteorological conditions (between 2013 and 1986) was 270 600 (196 800-317 900). Our findings indicate an urgent need to understand the driving force behind the appearance of unfavorable meteorological situations and propose suitable climate mitigation measures.
The aim of this study was to compare airborne levels of Phl p 1 and Phl p 5, with Poaceae pollen concentrations inside and outside of the pollen season, and to evaluate their association with symptoms in grass allergic patients and the influence of climate and pollution. The Hirst and the Burkard Cyclone samplers were used for pollen and allergen quantification, respectively. The sampling period ran from 23 March 2009 to 27 July 2010. Twenty-three patients with seasonal allergic asthma and rhinitis used an electronic symptom card. The aerosol was extracted and quantified for Phl p 1 and Phl p 5 content. Descriptive statistics, non-parametric paired contrast of Wilcoxon, Spearman’s correlations, and a categorical principal component analysis (CatPCA) were carried out. Significant variations in pollen, aeroallergen levels, pollen allergen potency, and symptoms score were observed in this study. Phl p 5 pollen allergen potency was higher at the beginning of the 2010 grass pollen season. Presence of Phl p 1 outside the pollen season with positive O(3) correlation was clinically relevant. 45.5% of the variance was explained by two dimensions in the CatPCA analysis, showing the symptom relationships dissociated in two dimensions. In the first one, the more important relationship was with grass pollen grains concentration and Phl p 5 and to a lesser extent with Phl p 1 and levels of NO(2) and O(3), and in the second dimension, symptoms were associated with humidity and SO(2). Clinically relevant out-season Phl p 1 was found with a positive O(3) correlation. The effect of climate and pollution may have contributed to the higher seasonal allergic rhinitis symptom score recorded in 2009.
Particulate matter (PM) has been occurring regularly during the dry season in the upper north of Thailand including Lamphun Province that might be influenced by various factors including climatologic and other pollutants. This paper aims to investigate the climatologic and gaseous factors influencing the occurrence of PM(10) concentration using Pollution Control Department (PCD) data. The secondary data of 2009 to 2017 obtained from the PCD was used for analysis. We used descriptive statistics, Pearson’s correlation coefficient, multiple regression and graphic presentation using R program (R packages of ‘open air’ and ‘ncdf4’) and Microsoft Excel Spreadsheet®. In addition, the periodic measurement of PM(2.5) and PM(10) were investigated to determine the ratio of PM(2.5)/PM(10). The results indicated that haze episodes (daily PM(10) concentration always over the PCD standard) normally occur during the dry season from February to April. The maximum concentration was always found in March. The PM(10) concentration was negatively associated with relative humidity and temperature while the PM(10) concentration showed a strongly positive association with CO and NO(2) concentration with correlation values of 0.70 and 0.57, respectively. Furthermore, we found CO and PM(10) concentration was associated with ozone concentration. This finding will benefit local communities and the public health sector to provide a warning system for preparation and response plans to react to PM(10) episodes in their responsible areas.
The International Agency for Research on Cancer (IARC) classifies benzene in group 1 (carcinogenic to humans). Particulate matter (PM) has recently also been classified in this category. This was an advance toward prioritizing the monitoring of particles in urban areas. The aim of the present study was to assess levels of PM(2.5) and BTEX (benzene, toluene, ethylbenzene, and xylene), the influence of meteorological variables, the planetary boundary layer (PBL), and urban variables as well as risks to human health in the city of Fortaleza, Brazil, in the wet and dry periods. BTEX compounds were sampled using the 1501 method of NIOSH and determined by GC-HS-PID/FID. PM(2.5) was monitored using an air sampling pump with a filter holder and determined by the gravimetric method. Average concentrations of BTEX ranged from 1.6 to 45.5 ?g m(-3), with higher values in the wet period, which may be explained by the fact that annual distribution is influenced by meteorological variables and the PBL. PM(2.5) levels ranged from 4.12 to 33.0 ?g m(-3) and 4.18 to 86.58 ?g m(-3) in the dry and wet periods, respectively. No seasonal pattern was found for PM(2.5), probably due to the influence of meteorological variables, the PBL, and urban variables. Cancer risk ranged from 2.46E(-04) to 4.71E(-03) and 1.72E(-04) to 2.01E(-03) for benzene and from 3.07E(-06) to 7.04E(-05) and 3.08E(-06) to 2.85E(-05) for PM(2.5) in the wet and dry periods, respectively. Cancer risk values for benzene were above the acceptable limit established by the international regulatory agency in both the dry and wet periods. The results obtained of the noncarcinogenic risks for the compounds toluene, ethylbenzene, and xylene were within the limits of acceptability. The findings also showed that the risk related to PM is always greater among smokers than nonsmokers.
In order to assess the influence of atmospheric conditions and particulate matter (PM) on the seasonally varying incidence of influenza-like illnesses (ILI) in the capital of Poland-Warsaw, we analysed time series of ILI reported for the about 1.75 million residents in total and for different age groups in 288 approximately weekly periods, covering 6 years 2013-2018. Using Poisson regression, we predicted ILI by the Universal Thermal Climate Index (UTCI) as biometeorological indicator, and by PM2.5 and PM10, respectively, as air quality measures accounting for lagged effects spanning up to 3 weeks. Excess ILI incidence after adjusting for seasonal and annual trends was calculated by fitting generalized additive models. ILI morbidity increased with rising PM concentrations, for both PM2.5 and PM10, and with cooler atmospheric conditions as indicated by decreasing UTCI. While the PM effect focused on the actual reporting period, the atmospheric influence exhibited a more evenly distributed lagged effect pattern over the considered 3-week period. Though ILI incidence adjusted for population size significantly declined with age, age did not significantly modify the effect sizes of both PM and UTCI. These findings contribute to better understanding environmental conditionings of influenza seasonality in a temperate climate. This will be beneficial to forecasting future dynamics of ILI and to planning clinical and public health resources under climate change scenarios.
Tropospheric ozone is known to have adverse effects on human health. Ozone pollution events are often associated with specific atmospheric circulation conditions. Therefore, studying the relationship between atmospheric circulation and ozone is particularly important for early warning and forecasting of ozone pollution events. Focusing on the Yangtze River Delta region, particularly in four important large industrial cities (Xuzhou, Nanjing, Shanghai, and Hangzhou) in the Yangtze River Delta, the T-mode objective classification method was applied to classify the weather circulation that mainly affects the Yangtze River Delta region into nine types. Local wind fields for the four industrial cities were classified according to their propensity for ventilation, stagnation, and recirculation based on the Allwine and Whiteman method. Based on the analysis of large-scale atmospheric circulation, we concluded that certain circulation patterns correspond to excessive ozone concentrations, while other circulation patterns correspond to good air quality. Moreover, ozone pollution was not closely related to local regional transmission. The importance of high temperatures in potentiating ozone pollution was also identified in the study area, whereas the effect of relative humidity was negligible. Finally, the importance of the different scale atmospheric motions was analyzed by studying two specific ozone pollution events in Xuzhou area (March, 2019) and Nanjing area (July-August, 2017). This analysis was complemented by HYSPLIT model’s outputs to simulate the pollutant diffusion path. Regarding the first episode, ozone concentration is often closely related to the slowly approaching thermal high-pressure system. In the second episode, local transmission had little effect on the generation and spread of ozone pollution. Furthermore, and comparing the circulation conditions with local meteorological factors, it was found that the increase in ozone concentration was often accompanied by higher temperature, and the response to humidity was not clear.
This study aimed to estimate morbidity risk/number attributed to air extreme temperatures using time-stratified case crossover study and distributed lag non-linear model in a region of Iran during 2015-2019. A time-stratified case crossover design based on aggregated exposure data was used in this study. In order to have no overlap bias in the estimations, a fixed and disjointed window by using 1-month strata was used in the design. A conditional Poisson regression model allowing for over dispersion (Quasi-Poisson) was applied into Distributed Lag Non-linear Model (DLNM). Different approaches were applied to estimate Optimum Temperature (OT). In the model, the interaction effect between temperature and humidity was assessed to see if the impact of heat or cold on Hospital Admissions (HAs) are different between different levels of humidity. The cumulative effect of heat during 21 days was not significant and it was the cold that had significant cumulative adverse effect on all groups. While the number of HAs attributed to any ranges of heat, including medium, high, extreme, and even all values were negligible, but a large number was attributable to cold values; about 10000 HAs were attributable to all values of cold temperature, of which about 9000 were attributed to medium range and about 1000 and less than 500 were attributed to high and extreme values of cold, respectively. This study highlights the need for interventions in cold seasons by policymakers. The results inform researchers as well as policy makers to address both men and women and elderly when any plan or preventive program is developed in the area under study.
The occurrence of long-lasting severe heat stress, such as in July-August 2003, July 2010, or in April-May 2018 has been one of the biggest meteorological threats in Europe in recent years. The paper focuses on the biometeorological and mortality effects of the hot June that was observed in Central Europe in 2019. The basis of the study was hourly and daily Universal Thermal Climate Index (UTCI) values at meteorological stations in Poland for June 2019. The average monthly air temperature and UTCI values from 1951 to 2018 were analysed as background. Grosswetterlagen calendar of atmospheric circulation was used to assess synoptic conditions of heat wave. Several heat strain measures were applied : net heat storage (S), modelled heart rate (HR), sultriness (HSI), and UTCI index. Actual total mortality (TM) and modelled strong heat-related mortality (SHRM) were taken as indicators of biometeorological consequences of the hot June in 2019. The results indicate that prolonged persistence of unusually warm weather in June 2019 was determined by the synoptic conditions occurring over the European region and causing advection of tropical air. They led to the emergence of heat waves causing 10% increase in TM and 5 times bigger SHRM then in preceding 10 years. Such increase in SHRM was an effect of overheating and overload of circulatory system of human organism.
In this study, 30 subjects were exposed to different combinations of air temperature (T(a) : 24, 27, and 30°C) and CO(2) level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T(a) = 24°C, exposure to 30°C at all CO(2) levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T(a) on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO(2) from 8000 to 12 000 ppm at all T(a) caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T(a) and CO(2) concentration on human responses was identified.
Extreme fine particulate matter (PM2.5) events heavily impact residents, incurring high social and medical costs. As such, it is important to understand the characteristics of extreme PM2.5 events. This study used hourly PM2.5 and meteorological data to elucidate the effects, and predict the occurrence of these extreme weather events in Taiwan. The results show that synoptic conditions are unique for extreme PM2.5 events. During the maximum mean PM2.5 concentrations, weather conditions in Taiwan were dominated by synoptic weather patterns and the north-easterly monsoon. The maximum mean surface air pressure indicator had also occurred at this time. The azimuth of the resultant surface air pressure was 36.8 degrees + 7.6 degrees, while 96.2% of winds were in the north-north-easterly and north-easterly direction. The back trajectories suggest that the cold continental high air pressure system introduced dry and cold air masses with PM2.5. The SImax (mu g/m(3)/h)(,) relative humidity (%), global solar radiation (MJ/m(2)), visibility (km), weather type I, and weather type II predictor variables of the multi-regression model accounted for 80.6% of the variance in the magnitude of maximum hourly PM2.5 events. Extreme PM2.5 events were related to synoptic weather characteristics including type, strength, and position. The new quantitative variables aid the development of an efficient alarm system for extreme PM2.5 events that will help protect public health.
BACKGROUND: Climate change and increasing risks of extreme weather events affect human health and lead to changes in the emergency department (ED) admissions and the emergency medical services (EMS) operations. For a better allocation of resources in the healthcare system, it is essential to predict ED numbers based on environmental variables. This publication aims to quantify weather, air pollution and calendar-related effects on daily ED admissions. METHODS: Analyses were based on 575,725 admissions from the web-based IVENA system recording all patients in the greater Munich area with pre-hospital emergency care in ambulance operations during 2014-2018. Linear models were used to identify statistically significant associations between daily ED admissions and calendar, meteorological and pollution factors, allowing for lag effects of one to three days. Separate analyses were performed for seasons, with additional subset analyses by sex, age and surgical versus internal department. RESULTS: ED admissions were exceptionally high during the three-week Oktoberfest, particularly for males and on the weekends, as well as during the New Year holiday. Admissions significantly increased during the years of study, decreased in spring and summer holidays, and were lower on Sundays while higher on Mondays. In the warmer seasons, admissions were significantly associated with higher temperature, adjusting for the effects of sunshine and humidity in all age groups except for the elderly. Adverse weather conditions in non-summer seasons were either linked to increasing ED admissions (from storms, gust) or decreasing them from rain. Mostly, but not exclusively, in winter, increasing ED admissions were associated with colder minimum temperatures as well as with higher NO and PM(10) concentrations. CONCLUSIONS: In addition to standard calendar-related factors, incorporating seasonal weather, air pollutant and interactions with patient demographics into resource planning models can improve the daily allocation of resources and staff of EMS operations at hospital and city levels.
BACKGROUND: Tuberculosis (TB) is a serious public health problem in China. There is evidence to prove that meteorological factors and exposure to air pollutants have a certain impact on TB. But the evidence of this relationship is insufficient, and the conclusions are inconsistent. METHODS: Descriptive epidemiological methods were used to describe the distribution characteristics of TB in Shijiazhuang in the past five years. Through the generalized linear regression model (GLM) and the generalized additive model (GAM), the risk factors that affect the incidence of TB are screened. A combination of GLM and distribution lag nonlinear model (DLNM) was used to evaluate the lag effect of environmental factors on the TB. Results were tested for robustness by sensitivity analysis. RESULTS: The incidence of TB in Shijiazhuang showed a downward trend year by year, with seasonality and periodicity. Every 10 ?g/m(3) of PM(10) changes, the RR distribution is bimodal. The first peak of RR occurs on the second day of lag (RR = 1.00166, 95% CI: 1.00023, 1.00390); the second risk period starts from 13th day of lag and peaks on15th day (RR = 1.00209, 95% CI: 1.00076, 1.00341), both of which are statistically significant. The cumulative effect of increasing 10 ?g/m(3) showed a similar bimodal distribution. Time zones where the RR makes sense are days 4-6 and 13-20. RR peaked on the 18th day (RR = 1.02239, 95% CI: 1.00623, 1.03882). The RR has a linear relationship with the concentration. Under the same concentration, the RR peaks within 15-20 days. CONCLUSION: TB in Shijiazhuang City showed a downward trend year by year, with obvious seasonal fluctuations. The air pollutant PM(10) increases the risk of TB. The development of TB has a short-term lag and cumulative lag effects. We should focus on protecting susceptible people from TB in spring and autumn, and strengthen the monitoring and emission management of PM(10) in the atmosphere.
The present study was planned to explore the pollution characteristics, health risks, and influence of atmospheric fine particulate matter (PM(2.5)) and its components on blood routine parameters in a typical industrial city (Xinxiang City) in China. In this study, 102 effective samples 28 (April-May), 19 (July-August), 27 (September-October), 28 (December-January) of PM(2.5) were collected during different seasons from 2017 to 2018. The water-soluble ions and metal elements in PM(2.5) were analyzed via ion chromatography and inductively coupled plasma-mass spectrometry. The blood routine physical examination parameters under different polluted weather conditions from January to December 2017 and 2018, the corresponding PM(2.5) concentration, temperature, and relative humidity during the same period were collected from Second People’s Hospital of Xinxiang during 2017-2018. Risk assessment was carried out using the generalized additive time series model (GAM). It was used to analyze the influence of PM(2.5) concentration and its components on blood routine indicators of the physical examination population. The “mgcv” package in R.3.5.3 statistical software was used for modeling and analysis and used to perform nonparametric smoothing on meteorological indicators such as temperature and humidity. When Akaike’s information criterion (AIC) value is the smallest, the goodness of fit of the model is the highest. Additionally, the US EPA exposure model was used to evaluate the health risks caused by different heavy metals in PM(2.5) to the human body through the respiratory pathway, including carcinogenic risk and non-carcinogenic risk. The result showed that the air particulate matter and its chemical components in Xinxiang City were higher in winter as compared to other seasons with an overall trend of winter > spring > autumn > summer. The content of nitrate (NO(3)(-)) and sulfate (SO(4)(2)(-)) ions in the atmosphere were higher in winter, which, together with ammonium, constitute the main components of water-soluble ions in PM(2.5) in Xinxiang City. Source analysis reported that mobile pollution sources (coal combustion emissions, automobile exhaust emissions, and industrial emissions) in Xinxiang City during the winter season contributed more to atmospheric pollution as compared to fixed sources. The results of the risk assessment showed that the non-carcinogenic health risk of heavy metals in fine particulate matter is acceptable to the human body, while among the carcinogenic elements, the order of lifetime carcinogenic risk is arsenic (As) > chromium(Cr) > cadmium (Cd) > cobalt(Co) > nickel (Ni). During periods of haze pollution, the exposure concentration of PM(2.5) has a certain lag effect on blood routine parameters. On the day when haze pollution occurs, when the daily average concentration of PM(2.5) rises by 10 ?g·m(-3), hemoglobin (HGB) and platelet count (PLT) increase, respectively, by 9.923% (95% CI, 8.741-11.264) and 0.068% (95% CI, 0.067-0.069). GAM model analysis predicted the maximum effect of PM(2.5) exposure concentration on red blood cell count (RBC) and PLT was reached when the hysteresis accumulates for 1d (Lag0). The maximum effect of exposure concentration ofPM(2.5) on MONO is reached when the lag accumulation is 3d (Lag2). When the hysteresis accumulates for 6d (Lag5), the exposure concentration of PM(2.5) has the greatest effect on HGB. The maximum cumulative effect of PM(2.5) on neutrophil count (NEUT) and lymphocyte (LMY) was strongest when the lag was 2d (Lag1). During periods of moderate to severe pollution, the concentration of water-soluble ions and heavy metal elements in PM(2.5) increases significantly and has a significant correlation with some blood routine indicators.
BACKGROUND: Previous studies have reported that fine particulate matter (PM(2.5)) affects the incidence of premature births. In addition, recent studies have suggested that heat waves have a negative impact on birth outcomes. However, the combined effect of PM(2.5) and heat waves on the incidence of premature birth is controversial. This study investigated the independent and combined effects of PM(2.5) and heat wave exposures during the 1st and 2nd trimesters on premature birth. METHODS: The National Statistical Office of Korea provided birth data from 2010 to 2016. Preterm birth was defined as birth between 22 and 36 weeks. To assess the exposure to PM(2.5) and heat waves, we used PM(2.5) data estimated by the Community Multiscale Air Quality Modeling System (CMAQ) and heat wave warning data provided by the Korea Meteorological Administration. A multivariate logistic regression was used to investigate the risk of preterm birth according to the exposure to PM(2.5) and heat waves during the 1st and 2nd trimesters, and it was adjusted for residential area, year of birth, season of birth, parity, education level of the mother, age of the mother, and sex of the baby. RESULTS: In the 2nd trimester, compared with the 0 h of heat wave exposure (?67 percentile), 62.50-314.00 h (79-88 percentile) and>315.00 h of heat wave exposure (>88 percentile) were both significantly associated with preterm birth (OR for 79-88 percentile, 1.037, 95% CI, 1.003-1.073; OR for > 88 percentile, 1.174, 95% CI, 1.134-1.215). However, PM(2.5) exposure was not significantly associated with preterm birth. On the other hand, in the analysis to evaluate the combined effect of PM(2.5) and heat wave exposures of the 2nd trimester, compared with 0 h of heat wave exposure (?67 percentile) and<11.64 ?g/m(3) (?25 percentile) of PM(2.5), 11.64-22.74 ?g/m(3) (?25 percentile), 22.74-27.58 ?g/m(3) (26-50 percentile), and 27.57-32.39 ?g/m(3) (51-75 percentile) of PM(2.5) exposure combined with>315.00 h of heat wave exposure (>88 percentile) were all significantly associated with preterm birth. In addition, the effect size was increased with an increase of PM(2.5) exposure (OR for ? 25 percentile, 1.148, 95% CI, 1.095-1.203; OR for 26-50 percentile, 1.248, 95% CI, 1.178-1.323; OR for 51-75 percentile, 1.370, 95% CI, 1.245-1.507). CONCLUSION: Our findings suggest that the combined effect of heat wave and PM(2.5) exposure during the 2nd trimester on the risk of preterm birth was greater than that of each exposure alone. In other words, exposure to PM(2.5) increases the impact of heat waves on the risk of preterm birth. These results indicate that control of prenatal exposure to fine particular matter and extreme temperatures is important for the prevention of preterm birth.
Heatwaves and greenness have been shown to affect health, but the evidence on their joint effects is limited. We aim to assess the associations of the combined exposure to greenness and heatwaves. We utilized five waves (February 2000-October 2014) of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), a prospective cohort of older adults aged 65. We defined heatwaves as the daily maximum temperature ?92.5th percentile with duration ?3 days. We calculated the number of heatwave days in one year before death to and cumulative Normalized Difference Vegetation Index (NDVI) during follow-up to assess individual long-term exposure to heatwaves and greenness. Cox proportional hazards models were used to assess the effects of greenness, heatwaves, and their interaction on mortality, adjusted for covariates. We conducted subgroup analyses by residence, gender, and age. There were 20,758 participants in our study, totaling 67,312 person-years of follow-up. The mean NDVI was 0·41 (SD 0.13), and the mean number of heatwave days was 8.92 (2.04). In the adjusted model, the mortality hazard ratio (HR) for each 3-day increase in heatwave days was 1.04 (95% CI 1.04, 1.05), each 0.1-unit decrease in cumulative NDVI was 1.06 (1.05, 1.07). In the adjusted model with an interaction term, the HR for the interaction term was 1.01 (1.01, 1.02) with a p-value less than 0.001. In our subgroup analyses, the HR for each 3-day increase in heatwave days was higher in urban areas than in rural areas (1.06 vs. 1.03), and the HR for 0.1-unit decrease in NDVI was higher in urban areas than in rural areas (1.08 vs. 1.04). Greenness can protect against the effect of heatwaves on mortality, and heatwaves affect the health effects of greenness. Urban dwellers have a higher response to the detrimental effect of heatwaves and a higher marginal benefit from greenness exposure.
BACKGROUND/AIM: Previous studies have suggested that the short-term ambient air pollution and temperature are associated with myocardial infarction. In this study, we aimed to conduct a time-series analysis to assess the impact of fine particulate matter (PM2.5) and temperature on acute myocardial infarction (AMI) among adults over 20 years of age in Korea by using the data from the Korean National Health Information Database (KNHID). METHODS: The daily data of 192,567 AMI cases in Seoul were collected from the nationwide, population-based KNHID from 2005 to 2014. The monitoring data of ambient PM2.5 from the Seoul Research Institute of Public Health and Environment were also collected. A generalized additive model (GAM) that allowed for a quasi-Poisson distribution was used to analyze the effects of PM2.5 and temperature on the incidence of AMI. RESULTS: The models with PM2.5 lag structures of lag 0 and 2-day averages of lag 0 and 1 (lag 01) showed significant associations with AMI (Relative risk [RR]: 1.011, CI: 1.003-1.020 for lag 0, RR: 1.010, CI: 1.000-1.020 for lag 01) after adjusting the covariates. Stratification analysis conducted in the cold season (October-April) and the warm season (May-September) showed a significant lag 0 effect for AMI cases in the cold season only. CONCLUSIONS: In conclusion, acute exposure to PM2.5 was significantly associated with AMI morbidity at lag 0 in Seoul, Korea. This increased risk was also observed at low temperatures.
The health, economic, and social impact of COVID-19 has been significant across the world. Our objective was to evaluate the association between air pollution (through NO(2) and PM(2.5) levels) and COVID-19 mortality in Spanish provinces from February 3, 2020, to July 14, 2020, adjusting for climatic parameters. An observational and ecological study was conducted with information extracted from Datadista repository (Datadista, 2020). Air pollutants (NO(2) and PM(2.5) levels) were analyzed as potential determinants of COVID-19 mortality. Multilevel Poisson regression models were used to analyze the risk of mortality after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Models were adjusted by four climatic variables (hours of solar radiation, precipitation, daily temperature and wind speed) and population size. The mean levels of PM(2.5) and NO(2) across all provinces and time in Spain were 8.7 ?g/m(3) (SD 9.7) and 8.7 ?g/m(3) (SD 6.2), respectively. High levels of PM(2.5) (IRR?=?1.016, 95% CI: 1.007-1.026), NO(2) (IRR?=?1.066, 95% CI: 1.058-1.075) and precipitation (IRR(NO2)?=?0.989, 95% CI: 0.981-0.997) were positively associated with COVID-19 mortality, whereas temperature (IRR(PM2.5)?=?0.988, 95% CI: 0.976-1.000; and IRR(NO2)?=?0.771, 95% CI: 0.761-0.782, respectively) and wind speed (IRR(NO2)?=?1.095, 95% CI: 1.061-1.131) were negatively associated with COVID-19 mortality. Air pollution can be a key factor to understand the mortality rate for COVID-19 in Spain. Furthermore, climatic variables could be influencing COVID-19 progression. Thus, air pollution and climatology ought to be taken into consideration in order to control the pandemic. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11869-021-01062-2.
The present study explored the association between daily ambient air pollution and daily emergency room (ER) visits due to acute respiratory symptoms in children of Delhi. The daily counts of ER visits (ERV) of children (?15 years) having acute respiratory symptoms were obtained from two hospitals of Delhi for 21 months. Simultaneously, data on daily concentrations of particulate matter (PM(10) and PM(2.5)), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), carbon monoxide (CO), and ozone (O(3)) and weather variables were provided by the Delhi Pollution Control Committee. K-means clustering with time-series approach and multi-pollutant generalized additive models with Poisson link function was used to estimate the 0-6-day lagged change in daily ER visits with the change in multiple pollutants levels. Out of 1,32,029 children screened, 19,120 eligible children having acute respiratory symptoms for ?2 weeks and residing in Delhi for the past 4 weeks were enrolled. There was a 29% and 21% increase in ERVs among children on high and moderate level pollution cluster days, respectively, compared to low pollution cluster days on the same day and previous 1-6 days of exposure to air pollutants. There was percentage increase (95% CI) 1.50% (0.76, 2.25) in ERVs for acute respiratory symptoms for 10 ?g/m(3) increase of NO(2) on previous day 1, 46.78% (21.01, 78.05) for 10 ?g/m(3) of CO on previous day 3, and 13.15% (9.95, 16.45) for 10 ?g/m(3) of SO(2) on same day of exposure. An increase in the daily ER visits of children for acute respiratory symptoms was observed after increase in daily ambient air pollution levels in Delhi.
Eczema resulting from external and internal factors accounts for the biggest global burden of disability owing to skin disease. This study aimed to determine an association between environmental factors and outpatient clinic visits for eczema. We collected data on dermatology clinic outpatient visits for eczema between January 2013 and July 2019. Data concerning environmental factors during this period were collated using national air quality network and air monitoring measurement parameters, namely barometric pressure, relative humidity, air temperature, and air pollutant concentrations, such as sulfur dioxide (SO(2)) and particulate matter (PM(10)). A distributed lag nonlinear model was used to investigate the relationship among eczema, environmental factors, and lagged effects. In total, 27,549 outpatient visits for eczema were recorded. In both single-factor and multiple-factor lag models, the effects of a 10-µg/m(3) increase in PM(10) and SO(2) values had significantly positive effects on the number of daily outpatient visits over a total 5 days of lag after adjusting for temperature, the number of daily outpatient visits increased with 0.87%, 7.65% and 0.69%, 5.34%, respectively. Relative humidity (RR?=?1.3870, 95% CI 1.3117-1.4665) and pressure (RR?=?1.0394, 95% CI 1.0071-1.0727) had significantly positive effects on the number of daily outpatients in single-factor lag models. However temperature had a significantly negative effect on them in the number of daily outpatients (RR?=?0.9686, 95% CI 0.9556-0.9819). Exposure to air pollution exacerbated eczema. Outpatient visits for eczema were found to have strong positive associations with changes in PM(10) levels.
Rotavirus A is the most common cause of infectious diarrhea worldwide. This study aimed to retrospectively study and analyze 4009 stool samples that were tested for viruses causing diarrhea, using multiplex reverse transcription PCR at Dankook University Hospital between 2010 and 2019. Furthermore, we determined the correlation between these factors and various climatic factors, including wind-chill temperature, relative humidity, rate of sunshine, and particulate matter. Rotavirus A infections occurred frequently in February, March, and April on an annual basis. Furthermore, during the study, the detection rate was highest at 17.0% (n=61/359) in 2011. Based on an analysis of weather big data, patient age, and period-specific infection during the summer, when the wind-chill temperature and relative humidity were high, the Rotavirus A infection rate was very low. Relative humidity (p=0.020) and particulate matter (p=0.049) were associated with the average number of monthly cases of Rotavirus A infection. However, wind chill temperature (p=0.074) and rate of sunshine (p=0.993) were not associated with the average monthly distribution of Rotavirus A cases. These results indicate that Rotavirus A infection was correlated with relative humidity and particulate matter during the study period and further the current understanding of the distribution of Rotavirus A infections resulting from climatic factors and particulate matter. This could help establish climate-related health policies to reduce the incidence of diarrhea and guide the development of vaccines against Rotavirus A.
Growing studies have shown that high temperature is a potential risk factor of schizophrenia occurrence. Therefore, elaborate analysis of different temperature exposure patterns, such as cumulative heat exposure within a time period and transient exposure at a particular time point, is of important public health significance. This study aims to utilize hourly temperature data to better capture the effects of cumulative and transient heat exposures on schizophrenia during the warm season in Hefei, China. We included the daily mean temperature and daily schizophrenia hospitalizations into the distributed lag non-linear model (DLNM) to simulate the exposure-response curve and determine the heat threshold (19.4 °C). We calculated and applied a novel indicator-daily excess hourly heat (DEHH)-to examine the effects of cumulative heat exposure over a day on schizophrenia hospitalizations. Temperature measurements at each time point were also incorporated in the DLNM as independent exposure indicators to analyze the impact of transient heat exposure on schizophrenia. Each increment of interquartile range (IQR) in DEHH was associated with elevated risk of schizophrenia hospitalizations from lag 1 (RR = 1.036, 95% confidence interval (CI): 1.016, 1.057) to lag 4 (RR = 1.025, 95% CI: 1.005, 1.046). Men and people over 40 years old were more susceptible to DEHH. Besides, we found a greater risk of heat-related schizophrenia hospitalizations between 0 a.m. and 6 a.m. This study revealed the adverse effects of accumulated and transient heat exposures on schizophrenia hospitalizations. Our findings need to be further tested in other regions with distinct regional features.
Industrialization and urbanization have aggravated the contradiction between environmental protection and economic growth, leading to health issues. While there are considerable interests in understanding the health effects of carbon emissions in the context of climate change, little is observed at regional scale and by econometric methods. Applying regression analysis on 2002-2017 Chinese provincial-level panel data, this study explores the intermediary mechanisms and regional differences of carbon emissions on residents’ health. The results indicate that: (1) Carbon emissions have a long-term adverse impact on residents’ health-a 1% rise in carbon emission adds 0.298% more outpatients and 0.162% more inpatients; (2) The rise in carbon emissions impairs residents’ health mainly by raising the temperature; (3) In areas with high levels of industrialization and urbanization, increased carbon emissions bring greater health risks; and (4) In terms of China’s unique “leading industrialization and lagging urbanization” situation, only by upgrading industrial structure, improving urbanization quality, and promoting coordinated industrialization and urbanization can the harm of carbon emissions to residents’ health be reduced. Therefore, the “one-size-fits-all” policy model is not suitable for China’s current situation. To address global “climate change” issues, China must act according to local conditions by applying mitigating (adaptive) measures in economically developed (less developed) regions. Simultaneously, the authorities must focus on the interaction and synergy between industrialization and urbanization.
Many methods have been developed to verify the correlation between meteorological conditions and air pollutants; however, all have limitations that lead to biased or incomplete conclusions. Hence, improved methods are urgently required to describe this correlation comprehensively and accurately. In this study, we demonstrated the ability of the Copula function to apply time-varying correlations between meteorological factors and atmospheric pollutants. A mixed Copula model was constructed using meteorological monitoring data for Beijing and Guangzhou from 2014 to 2019 to dynamically analyse the correlation characteristics and tail dependence between these factors. We then performed a correlation analysis for the data from the average, lower, and upper tails to obtain a more accurate and comprehensive correlation description. Dynamic analysis results demonstrated significant seasonal fluctuations between meteorological conditions and pollutants relationships. Moreover, the correlation coefficient variations differ according to their average and tail values. High humidity is more likely to be accompanied by increased NO2 compared with average summer humidity. Our proposed model represents a novel application of the Copula function for determining the factors influencing air pollution. This model emphasizes the tail dependence between meteorological conditions and air pollutant concentrations and can be used to guide more targeted prevention and control strategies.
Air pollution has been a rising concern of the 21st due to its effects to public health. Air Monitoring Stations are state-of-the-art equipment used to measure airborne pollutants concentration i.e. carbon monoxide, nitrogen oxide, sulphur dioxide, particulate matter (PM10) and ozone (O-3), as well as the meteorological parameters (i.e. ambient air temperature, relative humidity, wind speed and wind direction). Effects of climate change will affect the ambient temperature and humidity, which may induce a direct effect on air quality. In light of this, feed forward artificial neural network was employed to simulate the dynamic variations of PM10 and O-3 with relative humidity, temperature, and windspeed data being the inputs under 12 different training algorithms. Based on the results obtained, Bayesian regularization with 12 hidden neurons is the optimized network structure, with mean absolute percentage error in testing dataset of O-3 and PM10 at 51.31% and 36.49%, respectively. The models performed better in O-3 prediction as it is a photochemical reaction where ozone concentration varies according to temperature, the effect of meteorological parameters is significant. On the other hand, PM10 is not heavily dependent on meteorological parameters as the diversity of particulate matter components where most of its sources are dormant to changes in climate.
The impacts of wildfires in the western United States have been increasing for decades. Combining physical, epidemiological and economic models, this study finds that the economic damage of California wildfires in 2018 was roughly 1.5% of California’s annual gross domestic product. Recent increases in the frequency and scale of wildfires worldwide have raised concerns about the influence of climate change and associated socioeconomic costs. In the western United States, the hazard of wildfire has been increasing for decades. Here, we use a combination of physical, epidemiological and economic models to estimate the economic impacts of California wildfires in 2018, including the value of destroyed and damaged capital, the health costs related to air pollution exposure and indirect losses due to broader economic disruption cascading along with regional and national supply chains. Our estimation shows that wildfire damages in 2018 totalled $148.5 (126.1-192.9) billion (roughly 1.5% of California’s annual gross domestic product), with $27.7 billion (19%) in capital losses, $32.2 billion (22%) in health costs and $88.6 billion (59%) in indirect losses (all values in US$). Our results reveal that the majority of economic impacts related to California wildfires may be indirect and often affect industry sectors and locations distant from the fires (for example, 52% of the indirect losses-31% of total losses-in 2018 were outside of California). Our findings and methods provide new information for decision makers tasked with protecting lives and key production sectors and reducing the economic damages of future wildfires.
Climate change affects the reproductive life cycles of plants, including pollen production, which has consequences for allergic respiratory diseases. We examined climatic trends at eight locations in Bavaria, Southern Germany, with pollen time series of at least 10 years (up to 30 years in Munich). Climate change in Bavaria was characterized by a rise in temperature, but not during the winter. There is also a trend towards a more continental climate in Bavaria, which is significant in the Alps in the south of the territory. The influence of climate change depended on pollen type. Wind-pollinated arboreal species (e.g. Alnus, Betula and Cupressaceae/Taxaceae) showed advances in the start and end dates of pollen seasons and an increase in pollen load. These changes correlated negatively with late-winter (February) and spring temperatures (April). For herbaceous species, like Poaceae and Urticaceae, an earlier season was observed. Although precipitation is not a limiting factor in Southern Germany, water availability in the spring did influence the magnitude of grass pollen seasons. The effect of climatic change on the characteristics of pollen seasons was also more pronounced at higher altitudes, significant at > 800 m above sea level. Our results show that trends for start, end dates and intensity were similar at all locations, but only statistically significant at some. If we assume that earlier and more intense pollen seasons result in increases in prevalence and severity of allergic diseases, then the effect of climate change on public health in Bavaria may be significant.
Air Quality assessment and forecasting are the essentials today and they attracted many researchers. Environmental organizations regularly monitor and predict the air contaminants to make the public awareness, provide a better environment, and suitable for human health. Physical factors like climate changes, Industrialization, Fires and Urbanization are some of the factors which directly affect and reduce the air quality. All these data are time-series and real-time data. The primary pollutant is PMx that affect the respiratory systems and cardiac activity of humans. The secondary pollutants are SO2, CO, NOx, and O-3. Each has allowable range of concentration levels. In this work, meteorological elements are collected in different locations in last 5 years, with time window of 24 h and mapped to the concentration level of pollutants. The Machine Learning(ML) Methods such as Non-Linear Artificial Neural Network(ANN), Statistical Multilevel Regression, Neuro- Fuzzy and Deep Learning Long-Short-Term Memory (DL-LSTM) are used; to find the current concentration level of pollutants and will be useful for Real Time Correction (RTC) to give a feedback that can be used to reduce the contaminants in air for further days. The results are compared with the parameters such as R-2, RMSE and MAPE. Using these methods, the concentration level of contaminants is predicted with the deviation of R-2 in the range of 0.71-0.89. The results proved that DL-LSTM suits well when comparing to the ANN, Neuro-fuzzy and regression algorithms.
BACKGROUND: The impact of simultaneous adverse climate conditions in the risk of myocardial infarction (MI) was not tested before. The aim of the present study was to investigate the impact of the combination of climate and air pollution features in the number of admissions and mortality due to acute myocardial infarction in 39 municipalities of São Paulo from 2012 to 2015. METHODS: Data about MI admissions were obtained from the Brazilian public health system (DataSUS). Daily information on weather were accessed from the Meteorological Database for Teaching and Research. Additionally, daily information on air pollution were obtained from the Environmental Company of the State of São Paulo. A hierarchical cluster analysis was applied for temperature, rainfall patterns, relative air humidity, nitrogen dioxide, particulate matter 2.5 and particulate matter 10. MI admissions and in-hospital mortality were compared among the clusters. RESULTS: Data analysis produced 3 clusters: High temperature variation-Low humidity-high pollution (n=218 days); Intermediate temperature variation/high humidity/intermediate pollution (n=751 days) and low temperature variation/intermediate humidity-low pollution (n=123 days). All environmental variables were significantly different among clusters. The combination of high temperature variation, dry weather and high pollution resulted in a significant 9% increase in hospital admissions for MI [30.5 (IQR 25.0-36.0)]; patients/day; P<0.01). The differences in weather and pollution did not have impact on in-hospital mortality (P=0.88). CONCLUSION: The combination of atmospheric conditions with high temperature variation, lower temperature, dryer weather and increased inhalable particles was associated with a marked increase of hospital admissions due to MI.
Epidemiological studies have reported significant associations between weather situations and health. Cardiovascular disease is a serious chronic non-communicable disease which causes mortality and morbidity, bringing large economic burden to patients’ families. This study explored the relationship between cardiovascular disease (CVD) and weather conditions in Changchun, northeast China. The frequency distributions of 13 main circulation weather types (CWTs) were analyzed, and a comparison between air mass classification and hospital admissions was performed for various groups using an admission index (AI). The results indicated that women had a lower risk of CVD than men did. The risk of CVD for older people (aged???65 years) was lower than that for young people (aged?
IMPORTANCE: Future changes in climate are likely to adversely affect human health by affecting concentrations of particulate matter sized less than 2.5 ?m (PM2.5) and ozone (O3) in many areas. However, the degree to which these outcomes may be mitigated by reducing air pollutant emissions is not well understood. OBJECTIVE: To model the associations between future changes in climate, air quality, and human health for 2 climate models and under 2 air pollutant emission scenarios. DESIGN, SETTING, AND PARTICIPANTS: This modeling study simulated meteorological conditions over the coterminous continental US during a 1995 to 2005 baseline and over the 21st century (2025-2100) by dynamically downscaling representations of a high warming scenario from the Community Earth System Model (CESM) and the Coupled Model version 3 (CM3) global climate models. Using a chemical transport model, PM2.5 and O3 concentrations were simulated under a 2011 air pollutant emission data set and a 2040 projection. The changes in PM2.5 and O3-attributable deaths associated with climate change among the US census-projected population were estimated for 2030, 2050, 2075, and 2095 for each of 2 emission inventories and climate models. Data were analyzed from June 2018 to June 2020. MAIN OUTCOMES AND MEASURES: The main outcomes were simulated change in summer season means of the maximum daily 8-hour mean O3, annual mean PM2.5, population-weighted exposure, and the number of avoided or incurred deaths associated with these pollutants. Results are reported for 2030, 2050, 2075, and 2095, compared with 2000, for 2 climate models and 2 air pollutant emissions data sets. RESULTS: The projected increased maximum daily temperatures through 2095 were up to 7.6 °C for the CESM model and 11.8 °C for the CM3 model. Under each climate model scenario by 2095, compared with 2000, an estimated additional 21?000 (95% CI, 14?000-28?000) PM2.5-attributable deaths and 4100 (95% CI, 2200-6000) O3-attributable deaths were projected to occur. These projections decreased to an estimated 15?000 (95% CI, 10?000-20?000) PM2.5-attributable deaths and 640 (95% CI, 340-940) O3-attributable deaths when simulated using a future emission inventory that accounted for reduced anthropogenic emissions. CONCLUSIONS AND RELEVANCE: These findings suggest that reducing future air pollutant emissions could also reduce the climate-driven increase in deaths associated with air pollution by hundreds to thousands.
Since 2001, a synthesizing element in Intergovernmental Panel on Climate Change assessment reports has been a summary of how risks in a particular system could change with additional warming above pre-industrial levels, generally accompanied by a figure called the burning embers. We present a first effort to develop burning embers for climate change risks for heat-related morbidity and mortality, ozone-related mortality, malaria, diseases carried by Aedes sp., Lyme disease, and West Nile fever. We used an evidence-based approach to construct the embers based on a comprehensive global literature review. Projected risks for these health outcomes under 1.5 degrees C, 2 degrees C, and >2 degrees C of warming were used to estimate at what temperatures risk levels increased from undetectable to medium, high, and very high, from the pre-industrial baseline, under three adaptation scenarios. Recent climate change has likely increased risks from undetectable to moderate for heat-related morbidity and mortality, ozone-related mortality, dengue, and Lyme disease. Recent climate change also was assessed as likely beginning to affect the burden of West Nile fever. A detectable impact of climate change on malaria is not yet apparent but is expected to occur with additional warming. The risk for each climate-sensitive health outcome is projected to increase as global mean surface temperature increases above pre-industrial levels, with the extent and pace of adaptation expected to affect the timing and magnitude of risks. The embers may be an effective tool for informing efforts to build climate-resilient health systems including through vulnerability, capacity, and adaptation assessments and the development of national adaptation plans. The embers also can be used to raise awareness of future threats from climate change and advocate for mitigation actions to reduce the overall magnitude of health risks later this century and to expand current adaptation efforts to protect populations now.
Current models for flu-like epidemics insufficiently explain multi-cycle seasonality. Meteorological factors alone, including the associated behavior, do not predict seasonality, given substantial climate differences between countries that are subject to flu-like epidemics or COVID-19. Pollen is documented to be allergenic, it plays a role in immuno-activation and defense against respiratory viruses, and seems to create a bio-aerosol that lowers the reproduction number of flu-like viruses. Therefore, we hypothesize that pollen may explain the seasonality of flu-like epidemics, including COVID-19, in combination with meteorological variables. We have tested the Pollen-Flu Seasonality Theory for 2016-2020 flu-like seasons, including COVID-19, in the Netherlands, with its 17.4 million inhabitants. We combined changes in flu-like incidence per 100 K/Dutch residents (code: ILI) with pollen concentrations and meteorological data. Finally, a predictive model was tested using pollen and meteorological threshold values, inversely correlated to flu-like incidence. We found a highly significant inverse correlation of r(224) = -0.41 (p < 0.001) between pollen and changes in flu-like incidence, corrected for the incubation period. The correlation was stronger after taking into account the incubation time. We found that our predictive model has the highest inverse correlation with changes in flu-like incidence of r(222) = -0.48 (p < 0.001) when average thresholds of 610 total pollen grains/m(3), 120 allergenic pollen grains/m(3), and a solar radiation of 510 J/cm(2) are passed. The passing of at least the pollen thresholds, preludes the beginning and end of flu-like seasons. Solar radiation is a co-inhibitor of flu-like incidence, while temperature makes no difference. However, higher relative humidity increases with flu-like incidence. We conclude that pollen is a predictor of the inverse seasonality of flu-like epidemics, including COVID-19, and that solar radiation is a co-inhibitor, in the Netherlands.
What is already known on this topic? The health risk caused by high-temperatures depends on the interaction between high temperature exposure and the sensitivity and adaptability of the affected populations. What is added by this report? A comprehensive assessment model was established by principal component analysis using the data of 19 cities, 15 provincial-level administrative divisions and used to identify regional characteristics and major influencing factors of health vulnerability to extreme heat in China. What are the implications for public health practice? The results of the health vulnerability assessment could effectively identify the regions highly vulnerable to extreme heat in China and provide scientific evidence for the development of adaptive measures and resource allocation plans.
People with chronic obstructive pulmonary disease, cardiovascular disease, or hypertension have a high risk of developing severe coronavirus disease 2019 (COVID-19) and of COVID-19 mortality. However, the association between long-term exposure to air pollutants, which increases cardiopulmonary damage, and vulnerability to COVID-19 has not yet been fully established. We collected data of confirmed COVID-19 cases during the first wave of the epidemic in mainland China. We fitted a generalized linear model using city-level COVID-19 cases and severe cases as the outcome, and long-term average air pollutant levels as the exposure. Our analysis was adjusted using several variables, including a mobile phone dataset, covering human movement from Wuhan before the travel ban and movements within each city during the period of the emergency response. Other variables included smoking prevalence, climate data, socioeconomic data, education level, and number of hospital beds for 324 cities in China. After adjusting for human mobility and socioeconomic factors, we found an increase of 37.8% (95% confidence interval [CI]: 23.8%-52.0%), 32.3% (95% CI: 22.5%-42.4%), and 14.2% (7.9%-20.5%) in the number of COVID-19 cases for every 10-?g/m(3) increase in long-term exposure to NO(2), PM(2.5), and PM(10), respectively. However, when stratifying the data according to population size, the association became non-significant. The present results are derived from a large, newly compiled and geocoded repository of population and epidemiological data relevant to COVID-19. The findings suggested that air pollution may be related to population vulnerability to COVID-19 infection, although the extent to which this relationship is confounded by city population density needs further exploration.
In the present study, we aim to evaluate the delayed and cumulative effect of ozone (O(3)) exposure on mumps in a megacity with high population density and high humidity. We took Chongqing, a megacity in Southwest China, as the research area and 2013-2017 as the research period. A total of 49,258 confirmed mumps cases were collected from 122 hospitals of Chongqing. We employed the distributed lag nonlinear models with quasi-Poisson link to investigate the relationship between prevalence of mumps and O(3) exposure after adjusting for the effects of meteorological conditions. The results show that the effect of O(3) exposure on mumps was mainly manifested in the lag of 0-7 days. The ?single-day ;lag effect was the most obvious on the 4th day, with the relative risk (RR) of mumps occurs of 1.006 (95% CI: 1.003-1.007) per 10 ?g/m(3) in the O(3) exposure. The cumulative RR within 7 days was 1.025 (95% CI: 1.013-1.038). Our results suggest that O(3) exposure can increase the risk of mumps infection, which fills the gap of relevant research in mountainous areas with high population density and high humidity.
Evidence of the impact of ambient temperatures on emergency ambulance calls (EACs) in developing countries contributes to the improvement and complete understanding of the acute health effects of temperatures. This study aimed to examine the impacts and burden of heat on EACs in China, quantify the contributions of regional modifiers, and identify the vulnerable populations. A semi-parametric generalized additive model with a Poisson distribution was used to analyze the city-specific impacts of the daily maximum temperature (T-ma(x)) on EACs in June-August in 2014-2017. Stratified analyses by sex and age were performed to identify the vulnerable sub-populations. Meta-analysis was undertaken to illustrate the pooled associations. Further subgroup analysis, stratified by climate, latitude, and per capita disposable income (PCDI), and meta-regression analysis were conducted to explore the regional heterogeneity and quantify the contributions of possible modifiers. The city- and region-specific attributable fractions of EACs attributable to heat were calculated. Strong associations were observed between the daily T-max and total EACs in all cities. A total of 11.7% (95% confidence interval (CI): 11.2%-12.3%) of EACs were attributed to high temperatures in ten Chinese cities, and the central region with a low level of PCDI had the highest attributable fraction of 17.8% (95% CI: 17.2%-18.4%). People living in the central region with lower PCDI, and those aged 18-44 and 0-6 years were more vulnerable to heat than the others. The combined effects of PCDI, temperature, and latitude contributed 88.6% of the regional heterogeneity. The results complemented the understanding of the burden of EACs attributable to heat in developing countries and the quantitative contribution of regional modifiers.
BACKGROUND: Ozone pollution keeps deteriorating in the context of climate change. Maternal ozone exposure may be associated with low birth weight (LBW), but the results are still inconsistent. The identification of the critical exposure windows, a specific period of particular susceptibility during pregnancy, remains unresolved. We aimed to evaluate whether ozone exposure was associated with term LBW and further identify the susceptible exposure windows. METHODS: A retrospective cohort study was conducted in Guangzhou, a megacity in the most populous and economically developed city clusters in China. We included 444,096 singleton live births between January 2015 and July 2017. From 11 fixed stations, we collected daily 1-h maximum and 8-h maximum moving average ozone level (O(3)-1 h and O(3)-8 h) and calculated exposures for each participant based on their district of residence during pregnancy. We used traditional Logistic regression to estimate the trimester-specific association between ozone exposure and term LBW, and further estimated monthly- and weekly association by distributed lag models (DLMs) with Logistic regression. Odds ratios (ORs) and 95% confidence intervals (CIs) of term LBW were calculated for an interquartile range (IQR) increase in ozone exposure. Stratified analyses and heterogeneity tests were conducted by maternal age and infant sex. RESULTS: The incidence of term LBW was 1.9%. During the study period, the mean O(3)-1 h and O(3)-8 h levels were 112.6 µg/m(3) and 84.5 µg/m(3), respectively. Increased O(3)-1 h (IQR: 90 µg/m(3)) and O(3)-8 h (73 µg/m(3)) exposure during the second trimester were associated with increased risk of term LBW. At a monthly level, the term LBW risk was associated with O(3)-1 h exposure during the 4th-6th month and O(3)-8 h exposure during the 6th month. By estimating the weekly-specific association, we observed that critical exposure windows were the 15th- 26th gestational weeks for O(3)-1 h, and the 20th-26th weeks for O(3)-8 h, respectively. Estimated ORs and 95% CIs ranged from 1.012 (1.000, 1.024) to 1.023 (1.007, 1.039). When examined by subgroups, the effects were present among women ? 35 years or < 25 years old and those with female babies. CONCLUSIONS: This study provides compelling evidence that exposure to O(3) was associated with increased risk of term LBW, and gestational weeks 15th- 26th was found to be particularly susceptible. These findings provide a research basis for further mechanism examination, public health interventions, and targeted environmental policy-making.
IMPORTANCE Air pollution is a worldwide public health issue that has been exacerbated by recent wildfires, but the relationship between wildfire-associated air pollution and inflammatory skin diseases is unknown. OBJECTIVE To assess the associations between wildfire-associated air pollution and clinic visits for atopic dermatitis (AD) or itch and prescribed medications for AD management. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional time-series study assessed the associations of air pollution resulting from the California Camp Fire in November 2018 and 8049 dermatology clinic visits (4147 patients) at an academic tertiary care hospital system in San Francisco, 175 miles from the wildfire source. Participants included pediatric and adult patients with AD or itch from before, during, and after the time of the fire (October 2018 through February 2019), compared with those with visits in the same time frame of 2015 and 2016, when no large wildfires were near San Francisco. Data analysis was conducted from November 1, 2019, to May 30, 2020. EXPOSURES Wildfire-associated air pollution was characterized using 3 metrics: fire status, concentration of particulate matter less than 2.5 mu m in diameter (PM2.5), and satellite-based smoke plume density scores. MAIN OUTCOMES AND MEASURES Weekly clinic visit counts for AD or itch were the primary outcomes. Secondary outcomes were weekly numbers of topical and systemic medications prescribed for AD in adults. RESULTS Visits corresponding to a total of 4147 patients (mean [SD] age, 44.6 [21.1] years; 2322 [56%] female) were analyzed. The rates of visits for AD during the Camp Fire for pediatric patients were 1.49 (95% CI, 1.07-2.07) and for adult patients were 1.15 (95% CI, 1.02-1.30) times the rate for nonfire weeks at lag 0, adjusted for temperature, relative humidity, patient age, and total patient volume at the clinics for pediatric patients. The adjusted rate ratios for itch clinic visits during the wildfire weeks were 1.82 (95% CI, 1.20-2.78) for the pediatric patients and 1.29 (95% CI, 0.96-1.75) for adult patients. A 10-mu g/m(3) increase in weekly mean PM2.5 concentration was associated with a 7.7% (95% CI, 1.9%-13.7%) increase in weekly pediatric itch clinic visits. The adjusted rate ratio for prescribed systemic medications in adults during the Camp Fire at lag 0 was 1.45 (95% CI, 1.03-2.05). CONCLUSIONS AND RELEVANCE This cross-sectional study found that short-term exposure to air pollution due to the wildfire was associated with increased health care use for patients with AD and itch. These results may provide a better understanding of the association between poor air quality and skin health and guide health care professionals’ counseling of patients with skin disease and public health practice.
Prevalence of allergic diseases has been increasing due to multiple factors, among which climate change has had the most impact. Climate factors increase production of pollen, which also exhibits increased allergenicity. Also, as a result of climate change, there has been a shift in flowering phenology and pollen initiation causing prolonged pollen exposure. Various numerical models have been developed to understand the effect of climate change on pollen emission and transport and the impact on allergic airway diseases.
Previous studies have demonstrated that plants are a very good indicator of global environmental variations. The responses of many plant species to climate change are confirmed by aerobiological research. This paper presents an analysis of many parameters of pollen seasons in the Amaranthaceae family based on measurements of pollen concentrations in atmospheric air. Pollen samples were collected with the volumetric method at a sampling site in Lublin (Poland) in 2001-2019. The obtained data were verified using statistical analyses. Moreover, the presence of pollenkitt on the pollen grain surface was examined in fresh anthers using scanning electron and light microscopes, since there are some difficulties in identification of Amaranthaceae pollen grains deposited on microscopic slides in aerobiological analysis. The pollen season in Amaranthaceae began on average on June 23 and ended on October 5, i.e. it lasted 105 days. The peak value and annual pollen sum were characterized by the highest variability in the study years in comparison with other season characteristics. The annual pollen sum was in the range from 183 to 725. Maximum concentrations were most often recorded in the second half of August, which is associated with the greatest risk of development of pollen allergy symptoms in sensitive subjects during this period. The results obtained in the 19-year study revealed that the pollen seasons began 14 days earlier. Similarly, the end of the season was accelerated by 24 days. The response of these plants to climate change also include the reduced pollen production by representatives of this family, which was manifested by a decrease in the annual sum of daily airborne pollen concentrations, on average by 35%, and a reduction in the maximum pollen concentration, on average by more than 60%. We found that temperature in May and June had an effect on pollen release, and relative air humidity in May influenced pollen concentrations. We noted significant similarities in the pollen release rate during the last 8 years of the study. The scanning electron microscopy examinations showed that the pollen grain surface in the representative of this family was covered completely or partially with pollenkitt. Hence, the apertures characteristic for pollen in this family were poorly visible. The presence of pollenkitt on the surface of these polyaperturate pollen grains may play an important role in preventing water loss during pollen migration in the air. Our research has demonstrated the response of plants flowering in summer to climate change. The results not only have practical importance for public health in the aspect of allergy risk but can also help to assess environmental changes.
Most studies of short-term exposure to ambient air pollution and cerebrovascular diseases focused on specific stroke-related outcomes, and results were inconsistent due to data unavailability and limited sample size. It is unclear yet how ambient air pollution contributes to the total cardiovascular mortality in central China. Daily deaths from cerebrovascular diseases were obtained from the Disease Surveillance Point System (DSPs) of Wuhan Center for Disease Control and Prevention during the period from 2013 to 2019. Air pollution data were obtained from Wuhan Ecology and Environment Institute from 10 national air quality monitoring stations, including average daily PM(2.5), PM(10), SO(2), NO(2), and O(3). Average daily temperature and relative humidity were obtained from Wuhan Meteorological Bureau. We performed a Poisson regression in generalized additive models (GAM) to examine the association between ambient air pollution and cerebrovascular disease mortality. We observed a total of 84,811 deaths from cerebrovascular diseases from 1 January 2013 to 31 December 2019 in Wuhan. Short-term exposure to PM(2.5), PM(10), SO(2), and NO(2) was positively associated with daily deaths from cerebrovascular diseases, and no significant association was found for O(3). The largest effect on cerebrovascular disease mortality was found at lag0 for PM(2.5) (ERR: 0.927, 95% CI: 0.749-1.105 per 10 ?g/m3) and lag1 for PM(10) (ERR: 0.627, 95% CI: 0.493-0.761 per 10 ?g/m(3)), SO(2) (ERR: 2.518, 95% CI: 1.914, 3.122 per 10 ?g/m(3)), and NO(2) (ERR: 1.090, 95% CI: 0.822-1.358 per 10 ?g/m(3)). The trends across lags were statistically significant. The stratified analysis demonstrated that females were more susceptible to SO(2) and NO(2), while elder individuals aged above 65 years old, compared with younger people, suffered more from air pollution, especially from SO(2). Short-term exposure to PM(2.5), PM(10), SO(2), and NO(2) were significantly associated with a higher risk of cerebrovascular disease mortality, and elder females seemed to suffer more from air pollution. Further research is required to reveal the underlying mechanisms.
Air pollution is considered as an important concern all over the world. It disturbs the whole environment and produces more harmful effects to human’s healthy life. Relevant statistical reports from World Health Organization notify that air pollution play a major role in cause of diseases like asthma, lung cancer, stroke, early death and premature birth. Apart from diseases pollution also influence dangerous climate, weather conditions and may cause acid rain, global warming, ozone layer depletion, rainfall declines, etc. Therefore, it is essential to take necessary and preventive measures against air pollution. A comprehensive study is required to assess quality of ambient (outdoor) air, based on the observations of the major pollutants concentration drawn from different monitoring stations. Aiming at this problem, we proposed an ensemble based model to assess the air quality of United States from the period 2000 to 2016. In this article, we resolved the issues related to preprocessing of imbalanced dataset and improved the performance of the entire system through ensemble methods. We compared the recommended model with the existing ones. The experimental results show that the suggested model is superior to other systems and yield high accuracy, low error rate.
Admissions of newborn infants into Neonatal Intensive Care Units (NICU) has increased in the US over the last decade yet the role of environmental exposures as a risk factor for NICU admissions is under studied. Our study aims to determine the ecologic association between acute and intermediate ambient PM2.5 exposure durations and rates of NICU admissions, and to explore whether this association differs by area-level social stressors and meteorological factors. We conducted an ecologic time-series analysis of singleton neonates (N = 1,027,797) born in Florida hospitals between December 26, 2011 to April 30, 2019. We used electronic medical records (EMRs) in the OneFlorida Data Trust and included infants with a ZIP code in a Metropolitan Statistical Areas (MSA) and excluded extreme preterm births (<24wks gestation). The study outcome is the number of daily NICU admission at 28 days old or younger for each ZIP code in the study area. The exposures of interest are average same day, 1- and 2-day lags, and 1-3 weeks ambient PM2.5 concentration at the ZIP code-level estimated using inverse distance weighting (IDW) for each day of the study period. We used a zero-inflated Poisson regression mixed effects models to estimate adjusted associations between acute and intermediate PM2.5 exposure durations and NICU admissions rates. NICU admissions rates increased over time during the study period. Ambient 7-day average PM2.5 concentrations was significantly associated with incidence of NICU admissions, with an interquartile range (IQR = 2.37 ?g/m(3)) increase associated with a 1.4% (95% CI: 0.4%, 2.4%) higher adjusted incidence of daily NICU admissions. No other exposure duration metrics showed a significant association with daily NICU admission rates. The magnitude of the association between PM2.5 7-day average concentrations with NICU admissions was significantly (p < 0.05) higher among ZIP codes with higher proportions of non-Hispanic Blacks, ZIP codes with household incomes in the lowest quartile, and on days with higher relative humidity. Our data shows a positive relationship between acute (7-day average) PM2.5 concentrations and daily NICU admissions in Metropolitan Statistical Areas of Florida. The observed associations were stronger in socioeconomically disadvantaged areas, areas with higher proportions with non-Hispanic Blacks, and on days with higher relative humidity. Further research is warranted to study other air pollutants and multipollutant effects and identify health conditions that are driving these associations with NICU admissions.
Ambient air pollutants have been linked to adverse health outcomes, but evidence is still relatively rare in college students. Upper respiratory tract infection (URTI) is a common disease of respiratory system among college students. In this study, we assess the acute effect of air pollution on clinic visits of college students for URTI in Wuhan, China. Data on clinic visits due to URTI were collected from Wuhan University Hospital, meteorological factors (including daily temperature and relative humidity) provided by Wuhan Meteorological Bureau, and air pollutants by Wuhan Environmental Protection Bureau. In the present study, generalized additive model with a quasi-Poisson distribution link function was used to examine the association between ambient air pollutants (fine particulate matter (PM(2.5)), particulate matter (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), and ozone (O(3))) and the daily number of clinic visits of college students for URTI at Wuhan University Hospital in Wuhan, China. In the meantime, the model was adjusted for the confounding effects of long-term trends, seasonality, day of the week, public holidays, vacation, and meteorological factors. The best degrees of free in model were selected based on AIC (Akaike Information Criteria). The effect modification by gender was also examined. A total of 44,499 cases with principal diagnosis of URTI were included from January 1, 2016, to December 31, 2018. In single-pollutant models, the largest increment of URTI visits were found at lag 0 day in single-day lags, and the effect values in cumulative lags were greater than those in single-day lags. PM(2.5) (0.74% (95%CI: 0.05, 1.44)) at lag 0 day, PM(10) (0.61% (95%CI: 0.12, 1.11)) and O(3) (1.01% (95%CI: 0.24, 1.79)) at lag 0-1 days, and SO(2) (9.18% (95%CI: 3.27, 15.42)) and NO(2) (3.40% (95% CI:1.64, 5.19)) at lag 0-3 days were observed to be strongly and significantly associated with clinic visits for URTI. PM(10) and NO(2) were almost still significantly associated with URTI after controlling for the other pollutants in our two-pollutant models, where the effect value of SO(2) after inclusion of O(3) appeared to be the largest and the effects of NO(2) were also obvious compared with the other pollutants. Subgroups analysis demonstrated that males were more vulnerable to PM(10) and O(3), while females seemed more vulnerable to exposure to SO(2) and NO(2). This study implied that short-term exposure to ambient air pollution was associated with increased risk of URTI among college students at Wuhan University Hospital in Wuhan, China. And gaseous pollutants had more negative health impact than solid pollutants. SO(2) and NO(2) were the major air pollutants affecting the daily number of clinic visits on URTI, to which females seemed more vulnerable than males.
Conjunctivitis is one of the most common eye-related health problems and significantly influences patients’ quality of life. Whether air pollution increased the risks of conjunctivitis is still unclear. Daily counts of outpatient visits for conjunctivitis, air pollution, and meteorological data during January 1, 2015-December 31, 2019 were collected from Tai’an, China. Generalized additive model with Poisson distribution was used to estimate the relationship between air pollution and visits for conjunctivitis, after controlling for the long-term and seasonal trends, weather variables, and day of the week. The effect of air pollution on visits for conjunctivitis was generally acute and significant at the current day and disappeared after 2 days. The relative risk of conjunctivitis visits associated with per 10 ?g/m(3) increases in PM(2.5), PM(10), SO(2), and NO(2) at lag 0-2 days was 1.006 (95% CI: 1.001-1.011), 1.003 (95% CI: 1.000-1.0107), 1.023 (95% CI: 1.009-1.037), and 1.025 (95% CI: 1.010-1.040), respectively. The impact of air pollution on visits for conjunctivitis varied greatly by individual characteristics. The impact of NO(2) was higher in males than in females, with the opposite trend for SO(2) and PM(2.5). Effect estimates of air pollutants were higher among return visits for conjunctivitis, the elderly, and white-collar workers. Our study highlights that the vulnerable subpopulations should pay more attention to protect themselves from air pollution.
Air pollution has become a threat to human health in urban settlements, ultimately leading to negative impacts on overall economic system as well. Already developed nations and still developing countries both are at the risk of air pollution globally. In this scenario, this work aims to investigate the associations of asthma (AS) and acute upper respiratory infection (ARI) patients with satellite-based aerosol optical depth (AOD) and meteorological factors, i.e., relative humidity (RH), temperature (TEMP), and wind speed (WS). We applied second-generation unit root tests to provide empirical evidence. Two sets of unit root tests confirmed mix order of integration, and the other Westerlund co-integration test further showed strong linkages between estimated variables. Fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) tests were applied, only to explore that TEMP and WS lower the number of AS and ARI patients, but RH and AOD increase the number of patients. Therefore, in accordance with these findings, our study provides some important policy instruments to improve the health status in megacities of Pakistan.
Heatwaves-excessively hot ambient conditions that are considered a serious threat to human health-are often associated with poor air quality. The aim of this study was to examine the impact of an early heatwave episode in an industrialized plain in the eastern Mediterranean region (Thriasio, Greece) on human thermal discomfort and urban air quality. The heatwave occurred in mid (15-20) May 2020, shortly after some of the restrictions that were improsed to halt the spread of coronavirus disease 2019 (COVID-19) in Greece were lifted (on 4 May). The discomfort index (DI) and the daily air quality index (DAQI) were calculated on an hourly basis throughout spring 2020 (March, April, May) using data from two stations that measure meteorological parameters and air pollutant concentrations in the Thriasio Plain. The analysis showed that the air temperature increased during 7-17 May to levels that were more than 10 °C above the monthly average value (25.8 °C). The maximum measured air temperature was 38 °C (on 17 May). The results showed a high level of thermal discomfort. The DI exceeded the threshold of 24 °C for several hours during 13-20 May. Increased air pollution levels were also identified. The average DAQI was estimated as 0.83?±?0.1 and 1.14?±?0.2 at two monitoring stations in the region of interest during the heatwave. Particulate matter (diameter < 10 ?m) appeared to contribute significantly to the poor air quality. Significant correlations between the air temperature, DI, and AQSI were also identified.
OBJECTIVE: The wildfire allied environmental pollution is highly toxic and can cause significant wide-ranging damage to the regional environment, weather conditions, and it can facilitate the transmission of microorganisms and diseases. The present study aims to investigate the effect of wildfire allied pollutants, particulate matter (PM-2.5 ?m), and carbon monoxide (CO) on the dynamics of daily cases and deaths due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in San Francisco, USA. MATERIALS AND METHODS: For this study, we selected San Francisco, one of the regions affected by the wildfires allied pollution in California, USA. The data on the COVID-19 pandemic in San Francisco, including daily new cases and new deaths were recorded from Worldometer Web. The daily environmental pollutants particulate matter (PM-2.5 ?m) and carbon monoxide (CO) were recorded from the metrological web “BAAQMD”. The daily cases, deaths, particulate matter (PM-2.5 ?m) and carbon monoxide were documented from the date of the occurrence of the first case of (SARS-CoV-2) in San Francisco, CA, USA, from March 20, 2020 to Sept 16, 2020. RESULTS: The results revealed a significant positive correlation between the environmental pollutants particulate matter (PM2.5 ?m) and the number of daily cases (r=0.203, p=0.007), cumulative cases (r=0.567, p<0.001) and cumulative deaths (r=0.562, p<0.001); whereas the PM2.5 ?m and daily deaths had no relationship (r=-0.015, p=0.842). In addition, CO was also positively correlated with cumulative cases (r=0.423, p<0.001) and cumulative deaths (r=0.315, p<0.001), however, CO had no correlation with the number of daily cases (r=0.134, p=0.075) and daily deaths (r=0.030, p=0.693). In San Francisco, one micrometer (?g/m3) increase in PM2.5 caused an increase in the daily cases, cumulative cases and cumulative deaths of SARS-COV-2 by 0.5%, 0.9% and 0.6%, respectively. Moreover, with a 1 part per million (ppm) increase in carbon monoxide level, the daily number of cases, cumulative cases and cumulative deaths increased by 5%, 9.3% and 5.3%, respectively. On the other hand, CO and daily deaths had no significant relationship. CONCLUSIONS: The wildfire allied pollutants, particulate matter PM-2.5?m and CO have a positive association with an increased number of SARS-COV-2 daily cases, cumulative cases and cumulative deaths in San Francisco. The metrological, disaster management and health officials must implement the necessary policies and assist in planning to minimize the wildfire incidences, environmental pollution and COVID-19 pandemic both at regional and international levels.
We estimate the effects of wildfire smoke exposure on infant health. Exposure to wildfire smoke is determined using the latitude and longitude coordinates corresponding to each infant’s home address and a fine-scaled spatial dataset of wildfire smoke plumes constructed in GIS from satellite images of the landscape. Using a difference-in-differences estimation strategy, model estimates show that exposure to wildfire smoke leads to a .034 increase in the probability of low birthweight.
Objective: The study examines how wildfire smoke exposure may impact health and safety in the agricultural workplace. Methods: Semi-structured interviews were conducted with agricultural employers and focus group discussions were held with farmworkers in three regions of California. Results: Agricultural employers had varying knowledge about and experience responding to poor air quality due to wildfire smoke. Respirators or masks were not mentioned as a potential protective measure when describing their safety practices. Farmworkers reported experiencing poor air quality due to wildfire smoke, although knowledge of safety precautions varied. Farmworkers reported employer and supervisors’ attitudes toward safety as having the greatest impact on the implementation of workplace safety measures. Conclusion: Adapting health promotion and workplace safety strategies to meet the multiple vulnerabilities and diverse needs of farmworkers is critical to successful implementation of workplace protection and safety measures. Given limited familiarity with the topic, wildfire smoke exposure resources are needed to assist employers and supervisors in their compliance with a new wildfire smoke safety regulation in California. To the best of our knowledge, this is the first study to explore agricultural employer and farmworker perceptions of the health and safety impacts of wildfire smoke and workplace exposure.
The air quality and human health impacts of wildfires depend on fire, meteorology, and demography. These properties vary substantially from one region to another in China. This study compared smoke from more than a dozen wildfires in Northeast, North, and Southwest China to understand the regional differences in smoke transport and the air quality and human health impacts. Smoke was simulated using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) with fire emissions obtained from the Global Fire Emission Database (GFED). Although the simulated PM2.5 concentrations reached unhealthy or more severe levels at regional scale for some largest fires in Northeast China, smoke from only one fire was transported to densely populated areas (population density greater than 100 people/km(2)). In comparison, the PM2.5 concentrations reached unhealthy level in local densely populated areas for a few fires in North and Southwest China, though they were very low at regional scale. Thus, individual fires with very large sizes in Northeast China had a large amount of emissions but with a small chance to affect air quality in densely populated areas, while those in North and Southwest China had a small amount of emissions but with a certain chance to affect local densely populated areas. The results suggest that the fire and air quality management should focus on the regional air quality and human health impacts of very large fires under southward/southeastward winds toward densely populated areas in Northeast China and local air pollution near fire sites in North and Southwest China.
Future climate change may worsen air quality in many regions. However, evaluations of this ‘climate penalty’ on air quality have typically not assessed the radiative effects of changes in short-lived aerosols. Additionally, China’s clean air goals will decrease pollutant emissions and aerosol loadings, with concomitant weakening of aerosol feedbacks. Here we assess how such weakened aerosol direct effects alter the estimates of air pollution and premature mortality in China attributable to mid-century climate change under Representative Concentration Pathway 4.5. We found that weakening aerosol direct effects cause boundary layer changes that facilitate diffusion. This reduces air-pollution exposure (similar to 4% in fine particulate matter) and deaths (13,800 people per year), which largely offset the additional deaths caused by greenhouse gas-dominated warming. These results highlight the benefits of reduced pollutant emissions through weakening aerosol direct effects and underline the potential of pollution control measures to mitigate climate penalties locked in by greenhouse gas emissions.
Environmental factors have been suspected to have effects on the development of Kawasaki disease. However, the associations have been conflicting. The aim of this study was to investigate the effects of air pollution, weather conditions, and epidemic infections on the risks for Kawasaki disease in Japan. The concentrations of air pollutants (nitric oxide, nitrogen dioxide, and sulfur dioxide); ambient weather conditions (temperature, atmospheric pressure, relative air humidity, precipitation, sunshine duration, and wind velocity); and the epidemic conditions of 14 infectious diseases in hospitalized patients with Kawasaki disease were monitored from 2011 to 2018 in Beppu, Japan. The overdispersed generalized additive model was used to evaluate the effects, and a combination model with a distributed lag nonlinear model was used to estimate the cumulative effects. The incidence of Kawasaki disease had positive associations with preceding hot temperature and increased concentrations of nitric oxide and sulfur dioxide and a negative association with epidemic herpangina. The cumulative relative risk of Kawasaki disease at 5 lagged days of increased temperature was 1.76 (95% confidence interval: 1.01-3.07). This city-level observational study suggested that the incidence of Kawasaki disease was associated with air pollution and increased temperature and may be indirectly influenced by epidemic herpangina.
Nitrogen dioxide (NO(2)) is an air pollutant discharged from combustion of human activities. Nitrous acid (HONO), measured as NO(2), is thought to impact respiratory function more than NO(2). HONO and NO(2) have an equilibrium relationship, and their reaction is affected by climate conditions. This study was conducted to discuss the extent of HONO contained in NO(2), depending on the level of urbanization. Whether climate conditions that promote HONO production enhanced the level of NO(2) measured was investigated using time series analysis. Climate and outdoor air pollution data measured in April 2009-March 2017 in urban (Tokyo, Osaka, and Aichi) and rural (Yamanashi) areas in Japan were used for the analysis. Air temperature had a trend of negative associations with NO(2), which might indicate the decomposition of HONO in the equilibrium between HONO and NO(2). The associations of relative humidity with NO(2) did not have consistent trends by prefecture: humidity only in Yamanashi was positively associated with NO(2). In high relative humidity conditions, the equilibrium goes towards HONO production, which was observed in Yamanashi, suggesting the proportion of HONO in NO(2) might be low/high in urban/rural areas.
BACKGROUND: We assessed the association between multiple meteorological factors and air pollutants and the number of acute myocardial infarction (AMI) cases using a multi-step process. METHODS: Daily AMI hospitalizations matched with 16 meteorological factors and air pollutants in 7 metropolitan provinces of the Republic of Korea from 2002 to 2017 were analyzed. We chose the best fit model after conducting the Granger causality (GC) test and examined the daily lag time effect on the orthogonalized impulse response functions. To define dose-response relationships, we performed a time series analysis using multiple generalized additive lag models based on seasons. RESULTS: A total of 196,762 cases of AMI in patients older than 20 years admitted for hospitalization were identified. The distribution of meteorological factors and air pollutants showed characteristics of a temperate climate. The GC test revealed a complex interaction between meteorological factors, including air pollutants, and AMI. The final selected factors were NO(2) and temperature; these increased the incidence of AMI on lag day 4 during summer (NO(2): population-attributable fraction [PAF], 3.9%; 95% confidence interval [CI], 3.6-4.0; mean temperature: PAF, 3.3%; 95% CI, 2.7-3.9). CONCLUSIONS: This multi-step time series analysis found that average temperature and NO(2) are the most important factors impacting AMI hospitalizations, specifically during summer. Based on the model, we were able to visualize the effect-time association of meteorological factors and air pollutants and AMI.
To curb the staggering health burden attributed to air pollution, the sustainable solution for India would be to reduce emissions in future. Here we project ambient fine particulate matter (PM2.5) exposure in India for the year 2030 under two contrasting air pollution emission pathways for two different climate scenarios based on Representative Concentration Pathways (RCP4.5 and RCP8.5). All-India average PM2.5 is expected to increase from 41.4 +/- 26.5 mu g m(-3) in 2010 to 61.1 +/- 40.8 and 58.2 +/- 37.5 mu g m(-3) in 2030 under RCP8.5 and RCP4.5 scenarios, respectively if India follows the current legislation (baseline) emission pathway. In contrast, ambient PM2.5 in 2030 would be 40.2 +/- 27.5 (for RCP8.5) and 39.2 +/- 25.4 (for RCP4.5) mu g m(-3) following the short-lived climate pollutant (SLCP) mitigation emission pathway. We find that the lower PM2.5 in the mitigation pathway (34.2% and 32.6%, respectively for RCP8.5 and RCP4.5 relative to the baseline emission pathway) would come at a cost of 0.3-0.5 degrees C additional warming due to the direct impact of aerosols. The premature mortality burden attributable to ambient PM2.5 exposure is expected to rise from 2010 to 2030, but 381,790 (5-95% confidence interval, CI 275,620-514,600) deaths can be averted following the mitigation emission pathway relative to the baseline emission pathway. Therefore, we conclude that given the expected large health benefit, the mitigation emission pathway is a reasonable tradeoff for India despite the meteorological response. However, India needs to act more aggressively as the World Health Organization (WHO) annual air quality guideline (10 mu g m(-3)) would remain far off.
The aim of the paper is to describe the spread forest fire event occurred in the Italian Alps in 2017 under extremely drought conditions. In the study the root causes of wildfires and their direct relapses to the air quality of the Western Po valley and the urban centre of Torino have been assessed by means of air pollution measurements (focused to particulate matter with reference samplers and optical particle counters OPCs), meteorological indicators and additional public data. Results show a good correlation among different urban sites and instrument technologies. Concentration data, compared with environmental conditions and historical values describe the clear impact of fires on both local and regional air quality. Indeed, the deferred impact of wildfires on the local wood biomass energy supply chain is briefly outlined. (C) 2019 Published by Elsevier Ltd.
PURPOSE: Global warming and air pollution are among the most important problems all over the world. Considering the key role of traffic officers who saliently deal with traffic management and are in full, constant and direct exposure to thermal stress and air pollution index, this study aims to investigate the simultaneous effects of these factors on the body temperature of traffic officers in the main squares of Tehran. METHODS: This study was conducted among 119 traffic officers who were working in 29 squares of Tehran, located near the active pollutant’s stations during 2017. Samples were selected by the census method. Environmental parameters such as air temperature (dry and wet), radiation temperature, the level of air pollution in the main squares and characteristics of officers such as body temperature and the Wet-Bulb-Globe-Temperature (WBGT) index were evaluated. Data were analyzed through independent samples t-test and factorial ANOVA with a p value of p???0.05 in SPSS software. RESULTS: There was no significant relationship between air pollution and ear temperature, but there was a statistically significant difference between the wet-bulb temperature and the ear temperature (t?=?26.4, P?
The interactive effects between particulate matter (PM) and heat waves on circulatory mortality are under-researched in the context of global climate change. We aimed to investigate the interaction between heat waves and PM on circulatory mortality in Fuzhou, a city characterized by a humid subtropical climate and low level of air pollution in China. We collected data on deaths, pollutants, and meteorology in Fuzhou between January 2016 and December 2019. Generalized additive models were used to examine the effect of PM on circulatory mortality during the heat waves, and to explore the interaction between different PM levels and heat waves on the circulatory mortality. During heat waves, circulatory mortality was estimated to increase by 8.21% (95% confidence intervals (CI): 0.32-16.72) and 3.84% (95% CI: 0.28-7.54) per 10 ?g/m(3) increase of PM(2.5) and PM(10), respectively, compared to non-heat waves. Compared with low-level PM(2.5) concentration on non-heat waves layer, the high level of PM(2.5) concentration on heat waves layer has a significant effect on the cardiovascular mortality, and the effect value was 48.35% (95% CI: 6.37-106.89). Overall, we found some evidence to suggest that heat waves can significantly enhance the impact of PM on circulatory mortality.
Climate change is a global threat that poses significant risks to pregnant women and to their developing fetus and newborn. Educating pregnant women about the risks to their pregnancy may improve maternal and child health outcomes. Prior research suggests that presenting health information in narrative format can be more effective than a didactic format. Hence, the purpose of this study was to test the effectiveness of two brief educational interventions in a diverse group of pregnant women (n = 151). Specifically, using a post-test only randomized experiment, we compared the effectiveness of brief information presented in a narrative format versus a didactic format; both information formats were also compared to a no information control group. Outcome measures included pregnant women’s actual and perceived knowledge, risk perception, affective assessment, self-efficacy, intention to take protective behaviors, and subsequent information seeking behavior. As hypothesized, for all outcome measures, the narrative format was more effective than the didactic format. These results suggest the benefits of a narrative approach (versus a didactic approach) to educating pregnant women about the maternal and child health threats posed by climate change. This study adds to a growing literature on the effectiveness of narrative-based approaches to health communication.
The coal-dominated electricity system poses major challenges for India to tackle air pollution and climate change. Although the government has issued a series of clean air policies and low-carbon energy targets, a key barrier remains enforcement. Here, we quantify the importance of policy implementation in India’s electricity sector using an integrated assessment method based on emissions scenarios, air quality simulations, and health impact assessments. We find that limited enforcement of air pollution control policies leads to worse future air quality and health damages (e.g., 14?200 to 59?000 more PM(2.5)-related deaths in 2040) than when energy policies are not fully enforced (5900 to 8700 more PM(2.5)-related deaths in 2040), since coal power plants with end-of-pipe controls already emit little air pollution. However, substantially more carbon dioxide will be emitted if low-carbon and clean coal policies are not successfully implemented (e.g., 400 to 800 million tons more CO(2) in 2040). Thus, our results underscore the important role of effectively implementing existing air pollution and energy policy to simultaneously achieve air pollution, health, and carbon mitigation goals in India.
Particularly in rural settings, there has been little research regarding the health impacts of fine particulate matter (PM2.5) during the wildfire season smoke exposure period on respiratory diseases, such as influenza, and their associated outbreaks months later. We examined the delayed effects of PM2.5 concentrations for the short-lag (1-4 weeks prior) and the long-lag (during the prior wildfire season months) on the following winter influenza season in Montana, a mountainous state in the western United States. We created gridded maps of surface PM2.5 for the state of Montana from 2009 to 2018 using spatial regression models fit with station observations and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness data. We used a seasonal quasi-Poisson model with generalized estimating equations to estimate weekly, county-specific, influenza counts for Montana, associated with delayed PM2.5 concentration periods (short-lag and long-lag effects), adjusted for temperature and seasonal trend. We did not detect an acute, short-lag PM2.5 effect nor short-lag temperature effect on influenza in Montana. Higher daily average PM2.5 concentrations during the wildfire season was po- sitively associated with increased influenza in the following winter influenza season (expected 16% or 22% increase in influenza rate per 1 mu g/m(3) increase in average daily summer PM2.5 based on two analyses, p = 0.04 or 0.008). This is one of the first observations of a relationship between PM2.5 during wildfire season and influenza months later.
BACKGROUND: Suicidal ideation is subject to serious underestimation among existing public health studies. While numerous factors have been recognized in affecting suicidal thoughts and behaviors (STB), the associated environmental risks have been poorly understood. Foremost among the various environment risks were air pollution, in particular, the PM2.5. The present study attempted to examine the relationship between PM(2.5) level and local weekly index of suicidal ideation (ISI). METHODS: Using Internet search query volumes in Baidu (2017), the largest internet search engine in China, we constructed a prefectural panel data (278 prefectures, 52?weeks) and employed dynamic panel GMM system estimation to analyze the relationship between weekly concentration of PM2.5 (Mean?=?87??g·m(-?3)) and the index of suicidal ideation (Mean?=?49.9). RESULTS: The results indicate that in the spring and winter, a 10??g·m(-?3) increase in the prior week’s PM(2.5) in a Chinese city is significantly associated with 0.020 increase in ISI in spring and a 0.007 increase in ISI in winter, after taking account other co-pollutants and meteorological conditions. CONCLUSION: We innovatively proposed the measure of suicidal ideation and provided suggestive evidence of a positive association between suicidal ideation and PM(2.5) level.
BACKGROUND: Few epidemiological investigations have focused on the influence of environmental temperature on human sperm quality. Here, we evaluated the potential association between ambient temperature and human sperm quality in Wuhan, China, and examined the interactive effect of particulate matter (PM(2.5)) and temperature. METHODS: 1780 males who had been living in Wuhan for no less than three months and received semen analysis at the Department of Reproductive Medicine in Renmin Hospital of Wuhan University between April 8, 2013 and June 30, 2015 were recruited. Daily mean meteorological data and air pollution data (PM(2.5), O(3) and NO(2)) in Wuhan between 2013 and 2015 were collected. A generalized linear model was used to explore the associations between ambient temperature and sperm quality (including sperm concentration, percentage of normal sperm morphology, and progressive motility) at 0-9, 10-14, 15-69, 70-90, and 0-90?days before semen examination, and the interaction between temperature and PM(2.5). RESULTS: The associations between ambient temperature and sperm quality were an inverted U-shape at five exposure windows, except for a lag of 0-9?days for sperm concentration. A 1?°C increase in ambient temperature above the thresholds was associated with a 2.038 (1.292?~?2.783), 1.814 (1.217?~?2.411), 1.458 (1.138?~?1.777), 0.934(0.617?~?1.251) and 1.604 (1.258?~?1.951) decrease in the percentage of normal sperm morphology at lag 0-9, lag 10-14, lag 15-69, lag 70-90, and lag 0-90?days, respectively. The interaction p-values of PM(2.5) and temperature were mostly less than 0.05 at five exposure windows. When ambient temperature exposure levels were above the thresholds, a 0.979 (0.659-1.299) and 3.559 (0.251?~?6.867) decrease in percentage of normal sperm morphology per 1?°C increase in temperature at lag 0-90?days was observed in the PM(2.5)???P(50) group and PM(2.5)?>?P(50) group, respectively. CONCLUSIONS: Our results indicate that exposure to ambient temperature has a threshold effect on sperm quality, and PM(2.5) enhances the effect of temperature on sperm quality when temperatures are above the threshold.
BACKGROUND AND OBJECTIVES: The number of pediatric patients diagnosed with influenza types A and B is increasing annually, especially in temperate regions such as Shanghai (China). The onset of pandemic influenza viruses might be attributed to various ambient meteorological factors including temperature, relative humidity (Rh), and PM(1) concentrations, etc. The study aims to explore the correlation between the seasonality of pandemic influenza and these factors. METHODS: We recruited pediatric patients aged from 0 to 18?years who were diagnosed with influenza A or B from July 1st, 2017 to June 30th, 2019 in Shanghai Children’s Medical Centre (SCMC). Ambient meteorological data were collected from the Shanghai Meteorological Service (SMS) over the same period. The correlation of influenza outbreak and meteorological factors were analyzed through preliminary Pearson’s r correlation test and subsequent time-series Poisson regression analysis using the distributed lag non-linear model (DLNM). RESULTS: Pearson’s r test showed a statistically significant correlation between the weekly number of influenza A outpatients and ambient meteorological factors including weekly mean, maximum, minimum temperature and barometric pressure (P?
Wildfire smoke (WFS) increases the risk of respiratory hospitalizations. We evaluated the association between WFS and asthma healthcare utilization (AHCU) during the 2013 wildfire season in Oregon. WFS particulate matter <= 2.5 mu m in diameter (PM2.5) was estimated using a blended model of in situ monitoring, chemical transport models, and satellite-based data. Asthma claims and place of service were identified from Oregon All Payer All Claims data from 1 May 2013 to 30 September 2013. The association with WFS PM2.5 was evaluated using time-stratified case-crossover designs. The maximum WFS PM2.5 concentration during the study period was 172 mu g/m(3). A 10 mu g/m(3) increase in WFS increased risk in asthma diagnosis at emergency departments (odds ratio [OR]: 1.089, 95% confidence interval [CI]: 1.043-1.136), office visit (OR: 1.050, 95% CI: 1.038-1.063), and outpatient visits (OR: 1.065, 95% CI: 1.029-1.103); an association was observed with asthma rescue inhaler medication fills (OR: 1.077, 95% CI: 1.065-1.088). WFS increased the risk for asthma morbidity during the 2013 wildfire season in Oregon. Communities impacted by WFS could see increases in AHCU for tertiary, secondary, and primary care.
OBJECTIVES: to evaluate the effect of air pollution (ozone – O3 and particulate matter <=10 ?m and <=2.5 ?m - PM10 and PM2.5) on the severity of Raynaud's phenomenon (RP) secondary to systemic sclerosis (SSc). DESIGN: cross-sectional, observational, and single centre study. SETTING AND PARTICIPANTS: all consecutive SSc patients residing in Lombardy (Northern Italy) were enrolled. PM10, PM2.5, and O3 concentrations were calculated for each patient at municipality resolution in the week before the evaluation. Similar considerations were made for meteorological variables (temperature and humidity). MAIN OUTCOME MEASURES: patients were asked to assess RP severity during the week before the evaluation according to a visual analogue scale (VAS). Ordinal logistic regression models were fitted to evaluate the short-term effect of temperature and air pollution with respect to RP. A univariate linear regression model was created to consider the association between temperature and pollutants. RESULTS: in this study, 87 SSc patients were enrolled. Temperature was confirmed to strongly influence RP severity. PM10 and PM.5 were found to significantly worsen RP severity for the first four days before the evaluation, including the day of the visit, and as mean up to six days before the evaluation. O3 seemed to exert a protective effect on RP severity that was significant for the first four days before the evaluation, including the day of the visit, and as mean up to seven days before the evaluation. CONCLUSIONS: since the overwhelming effect of temperature on RP, final conclusions about the exact contribution of pollutants on RP severity cannot be drawn because of the strong inter-correlation between air pollution and temperature.
In this study, the spatial pattern and temporal evolution of PM(2.5) over North China Plain (NCP) and Northeast China (NEC) during 2014-2018 was investigated. The annual mean PM(2.5) shows clear decreasing trends over time, but the seasonal mean PM(2.5) as well as the seasonal total duration and frequency of haze days shows large inter-annual fluctuation. Based on the atmospheric stagnation index (ASI), this study examined the correlation between ASI and haze events over NCP and NEC. Detailed analysis indicates that location dependency exists of ASI in the capability of capturing the haze events, and the ability is limited in NCP. Therefore, we first propose two alternative methods in defining the ASI to either account for the lag effect or enlarge the threshold value of wind speed at 500 hPa. The new methods can improve the ability of ASI to explain the haze events over NEC, though marginal improvement was achieved in NCP. Furthermore, this study constructed the equation based on the boundary layer height and wind speed at 10-meter, apparently improving the ability in haze capture rate (HCR), a ratio of haze days during the stagnation to the total haze days. Based on a multi-model ensemble analyses under Representative Concentration Pathway (RCP) 8.5, we found that by the end of this century, climate change may lead to increases in both the duration and frequency of wintertime stagnation events over NCP. In contrast, the models predict a decrease in stagnant events and the total duration of stagnation in winter over NEC.
Hot weather episodes are globally associated with excess mortality rates. Elevated ozone concentrations occurring simultaneously also contribute to excess mortality rates during these episodes. However, the relative importance of both stressors for excess mortality rates is not yet known and assumed to vary from region to region. This study analyzes time series of daily observational data of air temperature and ozone concentrations for eight of the largest German cities during the years 2000 and 2017 with respect to the relative importance of both stressors for excess mortality rates in each city. By using an event-based risk approach, various thresholds for air temperature were explored for each city to detect hot weather episodes that are statistically associated with excess mortality rates. Multiple linear regressions were then calculated to investigate the relative contribution of variations in air temperature and ozone concentrations to the explained variance in mortality rates during these episodes, including the interaction of both predictors. In all cities hot weather episodes were detected that are related to excess mortality rates. Across the cities, a strong increase of this relation was observed around the 95th percentile of each city-specific air temperature distribution. Elevated ozone concentrations during hot weather episodes are also related to excess mortality rates in all cities. In general, the relative contribution of elevated ozone concentrations on mortality rates declines with increasing air temperature thresholds and occurs mainly as a statistically inseparable part of the air temperature impact. The specific strength of the impact of both stressors varies across the investigated cities. City-specific drivers such as background climate and vulnerability of the city population might lead to these differences and could be the subject of further research. These results underline strong regional differences in the importance of both stressors during hot weather episodes and could thus help in the development of city-specific heat- ozone-health warning systems to account for city-specific features.
Previous studies have revealed associations of meteorological factors with tuberculosis (TB) cases. However, few studies have examined their lag effects on TB cases. This study was aimed to analyse nonlinear lag effects of meteorological factors on the number of TB notifications in Hong Kong. Using a 22-year consecutive surveillance data in Hong Kong, we examined the association of monthly average temperature and relative humidity with temporal dynamics of the monthly number of TB notifications using a distributed lag nonlinear models combined with a Poisson regression. The relative risks (RRs) of TB notifications were >1.15 as monthly average temperatures were between 16.3 and 17.3 °C at lagged 13-15 months, reaching the peak risk of 1.18 (95% confidence interval (CI) 1.02-1.35) when it was 16.8 °C at lagged 14 months. The RRs of TB notifications were >1.05 as relative humidities of 60.0-63.6% at lagged 9-11 months expanded to 68.0-71.0% at lagged 12-17 months, reaching the highest risk of 1.06 (95% CI 1.01-1.11) when it was 69.0% at lagged 13 months. The nonlinear and delayed effects of average temperature and relative humidity on TB epidemic were identified, which may provide a practical reference for improving the TB warning system.
Climate change and air pollution are two independent risk factors to cardiovascular diseases (CVD). Few studies investigated their interaction and potential effect modification of one another in developing countries. Individual level CVD hospital admission (ICD10: I00-I99) data for 1 January 2011 to 31 October 2016 were obtained from seven private hospitals in Cape Town. NO(2), SO(2), PM(10), temperature and relative humidity data were obtained from the South African Weather Services and the City of Cape Town. A case-crossover epidemiological study design and conditional logistic regression model were applied. Various cut-off values were applied to classify cold and warm days. In total, 54,818 CVD hospital admissions were included in the study. In general, on warm and cold days the 15-64 years old group was more at risk for CVD hospitalization with increasing air pollution levels compared to all ages combined or the ??65 years old group. Females appeared to be more at risk than males with increasing PM(10) levels. In contrast, males were more vulnerable to the effects of NO(2) and SO(2) than females. The study showed the modification effect of temperature on air pollution associated with CVD hospital admissions. The consideration of such interaction will help in policy making and public health interventions dealing with climate change-related health risks.
Exposure to particulate matter of smaller than 2.5 ?m in diameter (PM(2.5)) is linked to increased human mortality, and could be further complicated by concurrent ambient air temperatures. Published reports indicate that the association between ambient temperatures and mortality due to PM(2.5) exposure is dissimilar across different geographic areas. Thus, it is unclear how ambient temperatures at different geographic locations can together modulate the influence of PM(2.5) on mortality. In this paper, we examined how temperature modulated the association between mortality and PM(2.5) exposure in 15 Chinese cities during 2014-2016. For analysis, First, Poisson generalized additive models under different temperature stratifications (<10th, 10-90th, and >90th temperature percentiles) was used to estimate PM(2.5) associations to mortality, which were specific to different cities. Second, we used a meta-analysis to combine the effects at each temperature stratum and region (southern and northern China). Results revealed that high temperatures (daily mean temperature >90th percentile) robustly amplified observed associations of mortality and PM(2.5) exposure, and the modifications were heterogeneous geographically. In the northern regions, a 10 ?g/m(3) increment in PM(2.5) was associated with 0.18%, 0.28%, and 1.54% increase in non-accidental mortalities and 0.33%, 0.39%, and 1.32% increase in cardiovascular mortalities at low, moderate, and high temperature levels, respectively. In the southern regions, a 10 ?g/m(3) increment in PM(2.5) was associated with 0.52%, 0.62%, and 1.90% increase in non-accidental mortalities and 0.55%, 0.98%, and 2.25% increase in cardiovascular mortalities at low, moderate, and high temperature levels, respectively. It is concluded that temperature altered PM(2.5)-mortality associations in southern and northern China synergistically, but the effect was more pronounced in the south. Therefore, geography and temperature need to be considered when studying how PM(2.5) affects health.
To investigate the correlation between environmental-meteorological factors and daily visits for acute otitis media (AOM) in Lanzhou, China. METHODS: Data were collected in 2014-2016 by the Departments of Otolaryngology-Head and Neck Surgery at two hospitals in Lanzhou. Relevant information, including age, sex and visiting time, was collected. Environmental data included air quality index, PM10, PM2.5, O(3), CO, NO(2) and SO(2), and meteorological data included daily average temperature (T, °C), daily mean atmospheric pressure (AP, hPa), daily average relative humidity (RH, %) and daily mean wind speed (W, m/s). The SPSS22.0 software was used to generate Spearman correlation coefficients in descriptive statistical analysis, and the R3.5.0 software was used to calculate relative risk (RR) and to obtain exposure-response curves. The relationship between meteorological-environmental parameters and daily AOM visits was summarized. RESULTS: Correlations were identified between daily AOM visits and CO, O(3), SO(2), CO, NO(2), PM2.5 and PM10 levels. NO(2), SO(2), CO, AP, RH and T levels significantly correlated with daily AOM visits with a lag exposure-response pattern. The effects of CO, NO(2), SO(2) and AP on daily AOM visits were significantly stronger compared to other factors (P < 0.01). O(3), W, T and RH were negatively correlated with daily AOM visits. The highest RR lagged by 3-4 days. CONCLUSIONS: The number of daily AOM visits appeared to be correlated with short-term exposure to mixed air pollutants and meteorological factors from 2014 through 2016 in Lanzhou.
A thunderstorm is a risk factor for severe respiratory allergy or asthma attacks in patients suffering from pollen/spore allergy. This study aimed to investigate the changes in the spectrum and quantity of pollen and fungal spores in the air of Bratislava during summer storms as well as the impact of selected environmental parameters on these changes. Pollen/spore samples were collected using a Burkard volumetric aerospore trap during summer 2016. To identify those types of pollen/spores that may harm human health during the storm episodes, we analysed how the concentration of individual bioparticles in the air changed during pre-storm/storm/post-storm periods. The effect of environmental variables on the concentration of selected pollen/spore types was evaluated through Spearman’s correlation analysis. The results of our study suggest that thunderstorm-related respiratory allergy symptoms in the study area may be caused by (1) spores of Myxomycetes, the airborne concentration of which increases due to an increase in wind speed during the pre-storm period; (2) ruptured pollen and Diatripaceae spores, the concentration of which increases due to increase in precipitation and relative air humidity, respectively, during the storm period; and (3) spores of Fusarium and Leptosphaeria, the concentration of which increases due to increase in precipitation and air temperature, respectively, during the post-storm period.
Extreme wildfire events are becoming more common and while the immediate risks of particulate exposures to susceptible populations (i.e., elderly, asthmatics) are appreciated, the long-term health effects are not known. In 2017, the Seeley Lake (SL), MT area experienced unprecedented levels of wildfire smoke from July 31 to September 18, with a daily average of 220.9 mu g/m(3). The aim of this study was to conduct health assessments in the community and evaluate potential adverse health effects. The study resulted in the recruitment of a cohort (n= 95, average age: 63 years), for a rapid response screening activity following the wildland fire event, and two follow-up visits in 2018 and 2019. Analysis of spirometry data found a significant decrease in lung function (FEV1/FVC ratio: forced expiratory volume in first second/forced vital capacity) and a more than doubling of participants that fell below the lower limit of normal (10.2% in 2017 to 45.9% in 2018) one year following the wildfire event, and remained decreased two years (33.9%) post exposure. In addition, observed FEV(1)was significantly lower than predicted values. These findings suggest that wildfire smoke can have long-lasting effects on human health. As wildfires continue to increase both here and globally, understanding the health implications is vital to understanding the respiratory impacts of these events as well as developing public health strategies to mitigate the effects.
OBJECTIVE: The study aimed to determine if and how environmental factors correlated with asthma admission rates in geographically different parts of Guangxi province in China. SETTING: Guangxi, China. PARTICIPANTS: This study was done among 7804 asthma patients. PRIMARY AND SECONDARY OUTCOME MEASURES: Spearman correlation coefficient was used to estimate correlation between environmental factors and asthma hospitalisation rates in multiple regions. Generalised additive model (GAM) with Poisson regression was used to estimate effects of environmental factors on asthma hospitalisation rates in 14 regions of Guangxi. RESULTS: The strongest effect of carbon monoxide (CO) was found on lag1 in Hechi, and every 10?µg/m(3) increase of CO caused an increase of 25.6% in asthma hospitalisation rate (RR 1.26, 95%?CI 1.02 to 1.55). According to the correlation analysis, asthma hospitalisations were related to the daily temperature, daily range of temperature, CO, nitrogen dioxide (NO(2)) and particulate matter (PM(2.5)) in multiple regions. According to the result of GAM, the adjusted R(2) was high in Beihai and Nanning, with values of 0.29 and 0.21, which means that environmental factors are powerful in explaining changes of asthma hospitalisation rates in Beihai and Nanning. CONCLUSION: Asthma hospitalisation rate was significantly and more strongly associated with CO than with NO(2), SO(2) or PM(2.5) in Guangxi. The risk factors of asthma exacerbations were not consistent in different regions, indicating that targeted measures should differ between regions.
OBJECTIVE: To assess short term mortality risks and excess mortality associated with exposure to ozone in several cities worldwide. DESIGN: Two stage time series analysis. SETTING: 406 cities in 20 countries, with overlapping periods between 1985 and 2015, collected from the database of Multi-City Multi-Country Collaborative Research Network. POPULATION: Deaths for all causes or for external causes only registered in each city within the study period. MAIN OUTCOME MEASURES: Daily total mortality (all or non-external causes only). RESULTS: A total of 45?165?171 deaths were analysed in the 406 cities. On average, a 10 µg/m(3) increase in ozone during the current and previous day was associated with an overall relative risk of mortality of 1.0018 (95% confidence interval 1.0012 to 1.0024). Some heterogeneity was found across countries, with estimates ranging from greater than 1.0020 in the United Kingdom, South Africa, Estonia, and Canada to less than 1.0008 in Mexico and Spain. Short term excess mortality in association with exposure to ozone higher than maximum background levels (70 µg/m(3)) was 0.26% (95% confidence interval 0.24% to 0.28%), corresponding to 8203 annual excess deaths (95% confidence interval 3525 to 12?840) across the 406 cities studied. The excess remained at 0.20% (0.18% to 0.22%) when restricting to days above the WHO guideline (100 µg/m(3)), corresponding to 6262 annual excess deaths (1413 to 11?065). Above more lenient thresholds for air quality standards in Europe, America, and China, excess mortality was 0.14%, 0.09%, and 0.05%, respectively. CONCLUSIONS: Results suggest that ozone related mortality could be potentially reduced under stricter air quality standards. These findings have relevance for the implementation of efficient clean air interventions and mitigation strategies designed within national and international climate policies.
The objective of this study is to analyze the short-term effects of atmospheric pollutant concentrations (PM(10), NO(2) and O(3)) and heat and cold waves on the number of pre-term births and cases of low birth weight related to Saharan dust advection and biomass combustion. The dependent variables used in this analysis were the total number of births, births with low weight (>2.500?g) and pre-term births (<37?weeks), that occurred at the province level. Data provided by the NSI included: days with Saharan dust intrusion or biomass advection classified in terms of information provided by MITECO for each of the nine regions in Spain. A representative city was selected for reach region in which the registered average daily concentrations of PM(10), NO(2) and O(3) (?g/m(3)) were used. These were also provided by MITECO. The daily maximum and daily minimum temperature (°C) used was those registered by the meteorological observatory station located in each province capital, provided by AEMET. Using Poisson log linear regression models, the associated relative risks (RR) were measured as well as the population attributable risk (PAR) corresponding to the variables that resulted statistically significant at p?
BACKGROUND: Evidence on the acute effect of short-term exposure to nitrogen dioxide (NO(2)) on years of life lost (YLL) is rare, especially in multicity setting. METHODS: We conducted a time series study among 48 major Chinese cities covering more than 403 million people from 2013 to 2017. The relative percentage changes of NO(2)-YLL were estimated by generalized additive models in each city, then were pooled to generate average effects using random-effect models. In addition, stratified analyses by individual demographic factors and temperature as well as meta-regression analyses incorporating city-specific air pollutant concentrations, meteorological conditions, and socioeconomic indicators were performed to explore potential effect modification. RESULTS: A 10 ?g/m(3) increase in two-day moving average (lag01) NO(2) concentration was associated with 0.64% (95% CI: 0.47%, 0.81%), 0.47% (95% CI: 0.27%, 0.68%), and 0.68% (95% CI: 0.34%, 1.02%) relative increments in YLL due to nonaccidental causes, cardiovascular diseases (CVD), and respiratory diseases (RD), respectively. These associations were generally robust to the adjustment of co-pollutants, except for NO(2)-CVD that might be confounded by fine particulate matter. The increased YLL induced by NO(2) were more pronounced in elderly people, hotter days, and cities characterized by less severe air pollution or higher temperature. CONCLUSIONS: Our results demonstrated robust evidence on the associations between NO(2) exposure and YLL due to nonaccidental causes, CVD, and RD, which provided novel evidence to better understand the disease burden related to NO(2) pollution and to facilitate allocation of health resources targeting high-risk subpopulation.
Short-term effects of air pollution on the health of residents in the Metropolitan Area of Monterrey, Mexico were assessed from 2012-2015 using a time-series approach. Guadalupe had the highest mean concentrations for SO(2), CO and O(3); whereas Santa Catarina showed the highest NO(2) concentrations. Escobedo and Garcia registered the highest levels for PM(10). Only PM(10) and O(3) exceeded the maximum permissible values established in the Mexican official standards. Most of pollutants and municipalities showed a great number of associations between an increase of 10% in their current concentrations and mortality, especially for people >60 years. Different scenarios resulting from climatic change were built (increases of 5-25% in daily mean temperature), but only the increase of 25% (5 °C) showed a significant association with air pollutant concentrations and mortality. All pollutants and municipalities showed significant increases in relative risk indexes (RRI) resulting from an increase of 5 °C when people >60 years was considered. Results were comparable to those reported by other authors around the world. The RRI were low but significant, and thus are of public concern. This study demonstrated that the elderly is strongly threatened not only by atmospheric pollution but also by climatic change scenarios in warm and semiarid places.
Particulate matter from natural sources such as desert dust causes harmful effects for health. Asian dust (AD) increases the risk of acute myocardial infarction (AMI). However, little is known about the risk of myocardial infarction with nonobstructive coronary arteries (MINOCA), compared to myocardial infarction with coronary artery disease (MI-CAD). Using a time-stratified case-crossover design and conditional logistic regression models, the association between short-term exposure to AD whereby decreased visibility (
BACKGROUND: PM(2·5) is an important but modifiable environmental risk factor, not only for pulmonary diseases and cancers, but for cardiovascular health. However, the evidence regarding the association between air pollution and acute cardiac events, such as out-of-hospital cardiac arrest (OHCA), is inconsistent, especially at concentrations lower than the WHO daily guideline (25 ?g/m(3)). This study aimed to determine the associations between exposure to ambient air pollution and the incidence of OHCA. METHODS: In this nationwide case-crossover study, we linked prospectively collected population-based registry data for OHCA in Japan from Jan 1, 2014, to Dec 31, 2015, with daily PM(2·5), carbon monoxide (CO), nitrogen dioxide (NO(2)), photochemical oxidants (O(x)), and sulphur dioxide (SO(2)) exposure on the day of the arrest (lag 0) or 1-3 days before the arrest (lags 1-3), as well as the moving average across days 0-1 and days 0-3. Daily exposure was calculated by averaging the measurements from all PM(2·5) monitoring stations in the same prefecture. The effect of PM(2·5) on risk of all-cause or cardiac OHCA was estimated using a time-stratified case-crossover design coupled with conditional logistic regression analysis, adjusted for daily temperature and relative humidity. Single-pollutant models were also investigated for the individual gaseous pollutants (CO, NO(2), O(x), and SO(2)), as well as two-pollutant models for PM(2·5) with these gaseous pollutants. Subgroup analyses were done by sex and age. FINDINGS: Over the 2 years, 249?372 OHCAs were identified, with 149?838 (60·1%) presumed of cardiac origin. The median daily PM(2·5) was 11·98 ?g/m(3) (IQR 8·13-17·44). Each 10 ?g/m(3) increase in PM(2·5) was associated with increased risk of all-cause OHCA on the same day (odds ratio [OR] 1·016, 95% CI 1·009-1·023) and at lags of up to 3 days, ranging from OR 1·015 (1·008-1·022) at lag 1 to 1·033 (1·023-1·043) at lag 0-3. Results for cardiac OHCA were similar (ORs ranging from 1·016 [1·007-1·025] at lags 1 and 2 to 1·034 [1·021-1·047] at lag 0-3). Patients older than 65 years were more susceptible to PM(2·5) exposure than younger age groups but no sex differences were identified. CO, O(x), and SO(2) were also positively associated with OHCA while NO(2) was not. However, in two-pollutant models of PM(2·5) and gaseous pollutants, only PM(2·5) (positive association) and NO(2) (negative association) were independently associated with increased risk of OHCA. INTERPRETATION: Short-term exposure to PM(2·5) was associated with an increased risk of OHCA even at relatively low concentrations. Regulatory standards and targets need to incorporate the potential health gains from continual air quality improvement even in locations already meeting WHO standards. FUNDING: None.
BACKGROUND: Research investigating the effect of air pollution on diabetes incidence is mostly conducted in Europe and the United States and often produces conflicting results. The link between meteorological factors and diabetes incidence remains to be explored. We aimed to explore associations between air pollution and diabetes incidence and to estimate the nonlinear and lag effects of meteorological factors on diabetes incidence. METHODS: Our study included 19,000 people aged ?60 years from the Binhai New District without diabetes at baseline. The generalized additive model (GAM) and the distributed lag nonlinear model (DLNM) were used to explore the effect of air pollutants and meteorological factors on the incidence of diabetes. In the model combining the GAM and DLNM, the impact of each factor (delayed by 30 days) was first observed separately to select statistically significant factors, which were then incorporated into the final multivariate model. The association between air pollution and the incidence of diabetes was assessed in subgroups based on age, sex, and body mass index (BMI). RESULTS: We found that cumulative RRs for diabetes incidence were 1.026 (1.011-1.040), 1.019 (1.012-1.026), and 1.051 (1.019-1.083) per 10??g/m(3) increase in PM(2.5), PM(10), and NO(2), respectively, as well as 1.156 (1.058-1.264) per 1?mg/m(3) increase in CO in a single-pollutant model. Increased temperature, excessive humidity or dryness, and shortened sunshine duration were positively correlated with the incidence of diabetes in single-factor models. After adjusting for temperature, humidity, and sunshine, the risk of diabetes increased by 9.2% (95% confidence interval (CI):2.1%-16.8%) per 10??g/m(3) increase in PM(2.5). We also found that women, the elderly (?75 years), and obese subjects were more susceptible to the effect of PM(2.5). CONCLUSION: Our data suggest that PM(2.5) is positively correlated with the incidence of diabetes in the elderly, and the relationship between various meteorological factors and diabetes in the elderly is nonlinear.
BACKGROUND: Extreme ambient temperatures and air quality have been directly associated with various human diseases from several studies around the world. However, few analyses involving the association of these environmental circumstances with mental and behavioral disorders (MBD) have been carried out, especially in developing countries such as Brazil. METHODS: A time series study was carried out to explore the associations between daily air pollutants (SO(2), NO(2), O(3), and PM(10)) concentrations and meteorological variables (temperature and relative humidity) on hospital admissions for mental and behavioral disorders for Curitiba, Brazil. Daily hospital admissions from 2010 to 2016 were analyzed by a semi-parametric generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM). RESULTS: Significant associations between environmental conditions (10??g/m(3) increase in air pollutants and temperature °C) and hospitalizations by MBD were found. Air temperature was the environmental variable with the highest relative risk (RR) at 0-day lag for all ages and sexes analyzed, with RR values of 1.0182 (95% CI: 1.0009-1.0357) for men, and 1.0407 (95% CI: 1.0230-1.0587) for women. Ozone exposure was a risk for all women groups, being higher for the young group, with a RR of 1.0319 (95% CI: 1.0165-1.0483). Elderly from both sexes were more susceptible to temperature variability, with a RR of 1.0651 (95% CI: 1.0213-1.1117) for women, and 1.0215 (95% CI: 1.0195-1.0716) for men. CONCLUSIONS: This study suggests that temperatures above and below the thermal comfort threshold, in addition to high concentrations of air pollutants, present significant risks on hospitalizations by MBD; besides, there are physiological and age differences resulting from the effect of this exposure.
OBJECTIVE: The objective of this study was to identify frequency, severity, and risk factors associated with bronchiolitis in Puerto Rican children. METHODS: A cross-sectional was study performed at 4 emergency departments of Puerto Rico’s metropolitan area, between June 2014 and May 2015. We included children younger than 24 months, with a clinical diagnosis of bronchiolitis, who were born and living in Puerto Rico at the time of recruitment. A physician-administered questionnaire inquiring about the patient’s medical, family, and social history and a bronchiolitis severity assessment were performed. Daily weather conditions were monitored, and aeroallergens were collected with an air sample and precision weather station within the metropolitan area to evaluate environmental factors. RESULTS: We included 600 patients for 12 months. More than 50% of the recruited patients had a previous episode of bronchiolitis, of which 40% had been hospitalized. Older age (odds ratio [OR], 18.3; 95% confidence interval [CI], 9.2-36.5), male sex (OR, 1.6; 95% CI, 1.1-2.4), history of asthma (OR, 8.9; 95% CI, 3.6-22), allergic rhinitis (OR, 3.6; 95% CI, 1.8-7.4), and smoke exposure by a caretaker (OR, 2.3; 95% CI, 1.2-4.4) were predictors of bronchiolitis episodes. Bronchiolitis episodes were associated with higher severity score (P = 0.040), increased number of atopic factors (P < 0.001), and higher number of hospitalizations (P < 0.001). CONCLUSIONS: This study identifies Puerto Rican children who may present a severe clinical course of disease without traditional risk factors. Atopy-related factors are associated with frequency and severity of bronchiolitis. Puerto Rican children present risk factors related to atopy earlier in life, some of which may be modified to prevent the subsequent development of asthma.
Fine particulate matter (PM2.5) raises human health concerns since it can deeply penetrate the respiratory system and enter the bloodstream, thus potentially impacting vital organs. Strong winds transport and disperse PM2.5, which can travel over long distances. Smoke from wildfires is a major episodic and seasonal hazard in Southern California (SoCal), where the onset of Santa Ana winds (SAWs) in early fall before the first rains of winter is associated with the region’s most damaging wildfires. However, SAWs also tend to improve visibility as they sweep haze particles from highly polluted areas far out to sea. Previous studies characterizing PM2.5 in the region are limited in time span and spatial extent, and have either addressed only a single event in time or short time series at a limited set of sites. Here we study the space-time relationship between daily levels of PM2.5 in SoCal and SAWs spanning 1999-2012 and also further identify the impact of wildfire smoke on this relationship. We used a rolling correlation approach to characterize the spatial-temporal variability of daily SAW and PM2.5. SAWs tend to lower PM2.5 levels, particularly along the coast and in urban areas, in the absence of wildfires upwind. On the other hand, SAWs markedly increase PM2.5 in zip codes downwind of wildfires. These empirical relationships can be used to identify windows of vulnerability for public health and orient preventive measures.
Over the last decades, energy and pollution control policies combined with structural changes in the economy decoupled emission trends from economic growth, increasingly also in the developing world. It is found that effective implementation of the presently decided national pollution control regulations should allow further economic growth without major deterioration of ambient air quality, but will not be enough to reduce pollution levels in many world regions. A combination of ambitious policies focusing on pollution controls, energy and climate, agricultural production systems and addressing human consumption habits could drastically improve air quality throughout the world. By 2040, mean population exposure to PM2.5 from anthropogenic sources could be reduced by about 75% relative to 2015 and brought well below the WHO guideline in large areas of the world. While the implementation of the proposed technical measures is likely to be technically feasible in the future, the transformative changes of current practices will require strong political will, supported by a full appreciation of the multiple benefits. Improved air quality would avoid a large share of the current 3-9 million cases of premature deaths annually. At the same time, the measures that deliver clean air would also significantly reduce emissions of greenhouse gases and contribute to multiple UN sustainable development goals. This article is part of a discussion meeting issue ‘Air quality, past present and future’.
Pollen is an important component of bioaerosol and the distribution of pollen and its relationship with meteorological parameters can be analyzed to better prevent hay fever. Pollen assemblages can also provide basic data for analyzing the relationship between bioaerosol and PM. We collected 82 samples of airborne pollen using a TSP large flow pollen collector from June 1, 2015 to June 1, 2016, from central Zhanjiang city in South China. We also conducted a survey of the nearby vegetation at the same time, in order to characterize the major plant types and their flowering times. We then used data on daily temperature, relative humidity, precipitation, vapor pressure and wind speed from a meteorological station in the center of Zhanjiang City to assess the relationship between the distribution of airborne pollen and meteorological parameters. Our main findings and conclusions are as follows: (1) We identified 15 major pollen types, including Pinus, Castanopsis, Myrica, Euphorbiaceae, Compositae, Gramineae, Microlepia and Polypodiaceae. From the vegetation survey, we found that the pollen from these taxa represented more than 75% of local pollen, while the pollen of Podocarpus, Dacrydium and other regional pollen types represented less than 25%. (2) The pollen concentrations varied significantly in different seasons. The pollen concentrations were at a maximum in spring, consisting mainly of tree pollen; the pollen concentrations were at an intermediate level in autumn and winter, consisting mainly of herb pollen and fern spores; and the pollen concentrations in summer were the lowest, consisting mainly of fern spores. (3) Analysis of the relationship between airborne pollen concentrations and meteorological parameters showed that variations in the pollen concentrations were mainly affected by temperature and relative humidity. In addition, there were substantial differences in these relationships in different seasons. In spring, pollen concentrations were mainly affected by temperature; in summer, they were mainly affected by the direction of the maximum wind speed; in autumn, they were mainly affected by relative humidity and temperature; and in winter, they were mainly affected by relative humidity and wind speed. Temperature and relative humidity promote plant growth and flowering. Notably, the variable wind direction in summer and the increased wind speed in winter and spring are conductive to pollen transmission. (4) Of the 15 major pollen types, Moraceae, Artemisia and Gramineae are the main allergenic pollen types, with peaks in concentration during April-May, August-September, and October-December, respectively. (5) Atypical weather conditions have substantial effects on pollen dispersal. In South China, the pollen concentrations in the sunny day were usually significantly higher than that of the rainy day. The pollen concentrations increased in short rainy days, which usually came from the Herb and Fern pollen. The pollen concentrations decreased in continuous rainy days especially for the Tree and Shrub pollen. the pollen concentrations in the sunny days were usually significantly higher than that in the rainy days. The pollen concentrations increased in short and strong rainfall.
The incidence of asthma exacerbation depends on atmospheric conditions, including such meteorological factors as the ambient temperature, relative air humidity or concentration of atmospheric aerosols. An assessment of relations between the frequency of asthma exacerbation and environmental conditions was made according to the meteorological components, the biometeorological index UTCI (Universal Thermal Climate Index), as well as selected air quality parameters, including concentrations of PM(10) and PM(2.5). The study was conducted on the basis of a retrospective analysis of medical data collected at the Independent Public Hospital of Tuberculosis and Pulmonary Diseases in Olsztyn (Poland). Our analysis of patient data (from 1 January 2013 until 31 December 2017) showed a significant correlation between the number of asthma exacerbation and the UTCI value. More frequent asthma exacerbations are observed in patients aged over 65 years when air humidity increases. The UTCI values contained within class 5, describing thermoneutral conditions, correspond to an average frequency of asthma exacerbation. A decline in the UTCI value leads to a reduced number of asthma exacerbation, while a rise makes the cases of asthma exacerbations increase.
BACKGROUND: Gastroesophageal reflux disease (GERD) is a highly prevalent disease of the upper gastrointestinal tract, and it is associated with environmental and lifestyle habits. Due to an increasing interest in the environment, several groups are studying the effects of meteorological factors and air pollutants (MFAPs) on disease development. AIM: To identify MFAPs effect on GERD-related medical utilization. METHODS: Data on GERD-related medical utilization from 2002 to 2017 were obtained from the National Health Insurance Service of Korea, while those on MFAPs were obtained from eight metropolitan areas and merged. In total, 20071900 instances of GERD-related medical utilizations were identified, and 200000 MFAPs were randomly selected from the eight metropolitan areas. Data were analyzed using a multivariable generalized additive Poisson regression model to control for time trends, seasonality, and day of the week. RESULTS: Five MFAPs were selected for the prediction model. GERD-related medical utilization increased with the levels of particulate matter with a diameter ? 2.5 ?m (PM(2.5)) and carbon monoxide (CO). S-shaped and inverted U-shaped changes were observed in average temperature and air pollutants, respectively. The time lag of each variable was significant around nine days after exposure. CONCLUSION: Using five MFAPs, the final model significantly predicted GERD-related medical utilization. In particular, PM(2.5) and CO were identified as risk or aggravating factors for GERD.
The relationship between the fires occurrences and diseases is an essential issue for making public health policy and environment protecting strategy. Thanks to the Internet, today, we have a huge amount of health data and fire occurrence reports at our disposal. The challenge, therefore, is how to deal with 4 Vs (volume, variety, velocity and veracity) associated with these data. To overcome this problem, in this paper, we propose a method that combines techniques based on Data Mining and Knowledge Discovery from Databases (KDD) to discover spatial and temporal association between diseases and the fire occurrences. Here, the case study was addressed to Malaria, Leishmaniasis and respiratory diseases in Brazil. Instead of losing a lot of time verifying the consistency of the database, the proposed method uses Decision Tree, a machine learning-based supervised classification, to perform a fast management and extract only relevant and strategic information, with the knowledge of how reliable the database is. Namely, States, Biomes and period of the year (months) with the highest rate of fires could be identified with great success rates and in few seconds. Then, the K-means, an unsupervised learning algorithms that solves the well-known clustering problem, is employed to identify the groups of cities where the fire occurrences is more expressive. Finally, the steps associated with KDD is perfomed to extract useful information from mined data. In that case, Spearman’s rank correlation coefficient, a nonparametric measure of rank correlation, is computed to infer the statistical dependence between fire occurrences and those diseases. Moreover, maps are also generated to represent the distribution of the mined data. From the results, it was possible to identify that each region showed a susceptible behaviour to some disease as well as some degree of correlation with fire outbreak, mainly in the drought period.
This time-series study collects data on stroke-related mortality, years of life lost (YLL), air pollution, and meteorological conditions in 96 Chinese cities from 2013 to 2016 and proposes a three-stage strategy to generate the national and regional estimations of avoidable YLL, gains in life expectancy and stroke-related population attributable fraction by postulating that the daily fine particulate matter (PM(2.5)) has been kept under certain standards. A total of 1 318 911 stroke deaths are analyzed. Each 10 µg m(-3) increment in PM(2.5) at lag(03) is associated with a city-mean increase of 0.31 (95% CI: 0.19, 0.44) years of life lost from stroke. A number of 914.11 (95% CI: 538.28, 1288.94) years of city-mean life lost from stoke could be avoided by attaining the WHO’s Air Quality Guidelines (AQG) (25 µg m(-3)). Moreover, by applying the AQG standard, 0.11 (0.08, 0.15) years of life lost might be prevented for each death, and about 0.91% (95% CI: 0.62%, 1.19%) of the total years of life lost from stroke might be explained by the daily excess PM(2.5) exposure. This study indicates that stroke patients can have a longer life expectancy if stricter PM(2.5) standards are put in place, especially ischemic stroke patients.
Here, we develop a dry eye syndrome (DES) incidence rate prediction model using air pollutants (PM10, NO2, SO2, O-3, and CO), meteorological factors (temperature, humidity, and wind speed), population rate, and clinical data for South Korea. The prediction model is well fitted to the incidence rate (R-2= 0.9443 and 0.9388,p< 2.2 x 10(-16)). To analyze regional deviations, we classify outpatient data, air pollutant, and meteorological factors in 16 administrative districts (seven metropolitan areas and nine states). Our results confirm NO(2)and relative humidity are the factors impacting regional deviations in the prediction model.
There is a lack of evidence on causal effects of air pollution on gestational age (GA) at delivery. METHODS: Inverse probability weighting (IPW) quantile regression was applied to derive causal marginal population-level GA reduction for GA percentiles associated with increased ambient particulate matter with diameter <2.5 ?m (PM(2.5)) levels at maternal residential address for each trimester and the month preceding delivery using Massachusetts birth registry 2001 to 2015. Stratified analyses were conducted for neonatal sex, maternal age/race/education, and extreme ambient temperature conditions. RESULTS: For neonates at 2.5th, 10th, 25th, 50th, 75th, and 97.5th percentiles of GA at delivery, we estimated an adjusted GA reduction of 4.2 days (95% confidence interval [CI] = 3.4, 5.0), 1.9 days (1.6, 2.1), 1.2 days (1.0, 1.4), 0.82 days (0.72, 0.92), 0.74 days (0.54, 0.94), and 0.54 days (0.15, 0.93) for each 5 ?g/m3 increment in third trimester average PM(2.5) levels. Final gestational month average exposure yielded a similar effect with greater magnitude. Male neonates and neonates of younger (younger than 35 years) and African American mothers as well as with high/low extreme temperature exposure in third trimester were more affected. Estimates were consistently higher at lower GA percentiles, indicating preterm/early-term births being more affected. Low-exposure analyses yielded similar results, restricting to areas with PM(2.5) levels under US ambient annual standard of 12 ?g/m(3). CONCLUSIONS: Prenatal exposure to PM(2.5) in late pregnancy reduced GA at delivery among Massachusetts neonates, especially among preterm/early-term births, male neonates, and neonates of younger and African American mothers. Exposure to extremely high/low temperature amplifies the effect of PM(2.5) on GA.
This is the first study to look at future temporal urban heath island (UHI) trends of Athens (Greece) under different UHI intensity regimes. Historical changes in the Athens UHI, spanning 1971-2016, were assessed by contrasting two air temperature records from stable meteorological stations in contrasting urban and rural settings. Subsequently, we used a five-member regional climate model (RCM) sub-ensemble from EURO-CORDEX with a horizontal resolution of 0.11 degrees (similar to 12 x 12 km) to simulate air temperature data, spanning the period 1976-2100, for the two station sites. Three future emissions scenarios (RCP2.6, RCP4.5, and RCP8.5) were implanted in the simulations after 2005 covering the period 2006-2100. Two 20-year historical reference periods (1976-1995 and 1996-2015) were selected with contrasting UHI regimes; the second period had a stronger intensity. The daily maximum and minimum air temperature data (T(max)and T-min) for the two reference periods were perturbed to two future periods, 2046-2065 and 2076-2095, under the three RCPs, by applying the empirical quantile mapping (eqm) bias-adjusting method. This novel approach allows us to assess future temperature developments in Athens under two UHI intensity regimes that are mainly forced by differences in air pollution and heat input. We found that the future frequency of days with T-max> 37 degrees C in Athens was only different from rural background values under the intense UHI regime. Thus, the impact of heatwaves on the urban environment of Athens is dependent on UHI intensity. There is a large increase in the future frequency of nights with T-min> 26 degrees C in Athens under all UHI regimes and climate scenarios; these events remain comparatively rare at the rural site. This large urban amplification of the frequency of extremely hot nights is likely caused by air pollution. Consequently, local mitigation policies aimed at decreasing urban atmospheric pollution are expected to be highly effective in reducing urban temperatures and extreme heat events in Athens under future climate change scenarios. Such policies directly have multiple benefits, including reduced electricity (energy) needs, improved living quality and strong health advantages (heat- and pollution-related illness/deaths).
In October 2017, hundreds of wildfires ravaged the forests of the north and centre of Portugal. The fires were fanned by strong winds as tropical storm Ophelia swept the Iberian coast, dragging up smoke (together with Saharan dust from north-western Africa) into higher western European latitudes. Here we analyse the long-range transport of particulate matter (PM(10)) and study associations between PM(10) and short-term mortality in the Portuguese population exposed to PM(10) due to the October 2017 wildfires, the worst fire sequence in the country over the last decades. We analysed space- and ground-level observations to track the smoke plume and dust trajectory over Portugal and Europe, and to access PM(10) concentrations during the wildfires. The effects of PM(10) on mortality were evaluated using satellite data for exposure and Poisson regression models. The smoke plume covered most western European countries (including Spain, France, Belgium and the Netherlands), and reached the United Kingdom, where the population was exposed in average to an additional PM(10) level of 11.7 µg/m(3) during seven smoky days (three with dust) in relation to the reference days (days without smoke or dust), revealing the impact of the wildfires on distant populations. In Portugal, the population was exposed in average to additional PM(10) levels that varied from 16.2 to 120.6 µg/m(3) in smoky days with dust and from 6.1 to 20.9 µg/m(3) in dust-free smoky days. Results suggest that PM(10) had a significant effect on the same day natural and cardiorespiratory mortalities during the month of October 2017. For every additional 10 µg/m(3) of PM(10), there was a 0.89% (95% confidence interval, CI, 0-1.77%) increase in the number of natural deaths and a 2.34% (95% CI, 0.99-3.66%) increase in the number of cardiorespiratory-related deaths. With rising temperatures and a higher frequency of storms due to climate change, PM from Iberian wildfires together with NW African dust will tend to be more often transported into Northern European countries, which may carry health threats to areas far from the ignition sites.
Mycotoxin-producing Aspergilli (Circumdati, Flavi, and Nigri), usually associated with contaminated food, may also cause respiratory disorders and are insufficiently studied in water-damaged indoor environments. Airborne (N = 71) and dust borne (N = 76) Aspergilli collected at post-flood and control locations in Croatia resulted in eleven different species based on their calmodulin marker: A. ochraceus, A. ostianus, A. pallidofulvus, A. sclerotiorum, and A. westerdijkiae (Circumdati); A. flavus (Flavi); and A. tubingensis, A. welwitschiae, A. niger, A. piperis, and A. uvarum (Nigri). Most of the airborne (73%) and dust borne (54%) isolates were found at post-flood locations, and the highest concentrations measured in indoor air (5720 colony-forming units (CFU)/m(3)) and dust (2.5 × 10(5) CFU/g) were up to twenty times higher than in the control locations. A. flavus dominated among airborne isolates (25%) at the unrepaired locations, while 56% of the dust borne Aspergilli were identified as A. tubingensis and A. welwitschiae. The ability of identified isolates to produce mycotoxins aflatoxin B(1) (AFB(1)), fumonisin B(2) (FB(2)), and ochratoxin A were assessed by LC-MS analysis. All ochratoxin A (OTA)-producing Circumdati belonged to A. westerdijkiae (13.7 ± 15.81 µg/mL); in the section, FlaviA. flavus produced AFB(1) (2.51 ± 5.31 µg/mL), while A. welwitschiae and A. niger (section Nigri) produced FB(2) (6.76 ± 13.51 µg/mL and 11.24 ± 18.30 µg/mL, respectively). Water damage dominantly supported the occurrence of aflatoxigenic A. flavus in indoor environments. Yet unresolved, the causal relationship of exposure to indoor Aspergilli and adverse health effects may support the significance of this research.
As climate change progresses, understanding the impact on human health associated with the temperature and air pollutants has been paramount. However, the predicted effect on temperature associated with particulate matter (PM(10)) is not well understood due to the difficulty in predicting the local and regional PM(10). We compared temperature-attributable mortality for the baseline (2003-2012), 2030s (2026-2035), 2050s (2046-2055), and 2080s (2076-2085) based on a distributed lag non-linear model by simultaneously considering assumed levels of PM(10) on historical and projected temperatures under representative concentration pathway (RCP) scenarios. The considered projected PM(10) concentrations of 35, 50, 65, 80, and 95 ?g/m(3) were based on historical concentration quantiles. Our findings confirmed greater temperature-attributable risks at PM(10) concentrations above 65 ?g/m(3) due to the modification effect of the pollutants on temperature. In addition, this association between temperature and PM(10) was higher under RCP8.5 than RCP4.5. We also confirmed regional heterogeneity in temperature-attributable deaths by considering PM(10) concentrations in South Korea with higher risks in heavily populated areas. These results demonstrated that the modification association of air pollutants on health burdens attributable to increasing temperatures should be considered by researchers and policy makers.
Particulate matter (PM), a major component of air pollution, is an important carrier medium of various chemical and microbial compounds. Air pollution due to PM could increase the level of bacteria and associated adverse health effects. Staphylococci as important opportunistic pathogens that cause hospital- and community-acquired infections may transmit through air. This study aimed to obtain knowledge about the concentration of airborne bacteria as well as staphylococci associated with particulate matter with a diameter of less than 2.5 micrometers (PM(2.5)) in ambient air. The impact of meteorological factors including ultraviolet (UV) index, wind speed, temperature, and moisture on microbial concentrations was also investigated. Quartz filters were used to collect PM(2.5) and associated bacteria in ambient air of a semiarid area. Airborne bacteria were quantified by culture method and Staphylococcus species identified by molecular methods. The mean (SD) concentration of PM(2.5) and airborne bacteria was 64.83 (24.87) µg/m(3) and 38 (36) colony forming unit (CFU)/m(3), respectively. The results showed no significant correlation between the levels of PM(2.5) and concentrations of bacteria (p?<?0.05). Staphylococcus species were detected in 8 of 37 (22%) samples in a concentration from 3 to 213 CFU/m(3). S. epidermidis was detected with the highest frequency followed by S. gallinarum and S. hominis, but S. aureus and methicillin-resistant Staphylococcus aureus (MRSA) were not detected. No significant correlation between the concentrations of bacteria with meteorological parameters was observed (p?<?0.05). Our finding showed that, although the study area is sometimes subject to air pollution from PM(2.5), the concentration of PM(2.5)- associated bacteria is relatively low. According to the results, PM(2.5) may not be a source of community-associated staphylococcal infections.
OBJECTIVE: To test the hypothesis that particulate matter with an aerodynamic diameter of less than 10 ?m (PM(10)) and temperature are associated with an increased risk of adverse clinical outcomes in patients with atrial fibrillation (AF) taking vitamin K antagonists (VKAs). PATIENTS AND METHODS: We included patients with AF whose condition was stable while taking VKAs (international normalized ratio, 2.0 to 3.0) for 6 months seen in a tertiary hospital (recruitment from May 1, 2007, to December 1, 2007). During a median follow-up of 6.5 years (interquartile range, 4.3 to 7.9 years), ischemic strokes, major bleeding, adverse cardiovascular events, and mortality were recorded. From 2007 to 2016, data on average temperature and PM(10) were compared with clinical outcomes. RESULTS: The study group included 1361 patients (663 [48.7%] male; median age, 76 years [interquartile range, 71 to 81 years]). High PM(10) and low temperatures were associated with higher risk of major bleeding (adjusted hazard ratio [aHR], 1.44; 95% CI, 1.22 to 1.70 and aHR, 1.03; 95% CI, 1.01 to 1.05, respectively) and mortality (aHR, 1.50; 95% CI, 1.34 to 1.69 and aHR, 1.04; 95% CI, 1.02 to 1.06, respectively); PM(10) was also associated with ischemic stroke and temperature with cardiovascular events. The relative risk (RR) for cardiovascular events and mortality increased in months in the lower quartile of temperature (RR, 1.12; 95% CI, 1.04 to 1.21 and RR, 1.41; 95% CI, 1.15 to 1.74, respectively). Comparing seasons, there were higher risks of cardiovascular events in spring, autumn, and winter than in summer, whereas the risk of mortality increased only in winter. CONCLUSION: In patients with AF taking VKAs, high PM(10) and low temperature were associated with increased risk of ischemic stroke and cardiovascular events, respectively. Both factors increased major bleeding and mortality risks, which were higher during colder months and seasons.
A probe of a patient, seeking help in an emergency ward of a French hospital in late December 2019 because of Influenza like symptoms, was retrospectively tested positive to COVID-19. Despite the early appearance of the virus in Europe, the prevalence and virulence appeared to be low for several weeks, before the spread and severity of symptoms increased exponentially, yet with marked spatial and temporal differences. Here, we compare the possible linkages between peaks of fine particulate matter (PM2.5) and the sudden, explosive increase of hospitalizations and mortality rates in the Swiss Canton of Ticino, and the Greater Paris and London regions. We argue that these peaks of fine particulate matter are primarily occurring during thermal inversion of the boundary layer of the atmosphere. We also discuss the influence of Saharan dust intrusions on the COVID-19 outbreak observed in early 2020 on the Canary Islands. We deem it both reasonable and plausible that high PM2.5 concentrations-favored by air temperature inversions or Saharan dust intrusions-are not only modulating but even more so boosting severe outbreaks of COVID-19. Moreover, desert dust events-besides enhancing PM2.5 concentrations-can be a vector for fungal diseases, thereby exacerbating COVID-19 morbidity and mortality. We conclude that the overburdening of the health services and hospitals as well as the high over-mortality observed in various regions of Europe in spring 2020 may be linked to peaks of PM2.5 and likely particular weather situations that have favored the spread and enhanced the virulence of the virus. In the future, we recommended to monitor not only the prevalence of the virus, but also to consider the occurrence of weather situations that can lead to sudden, very explosive COVID-19 outbreaks.
Organophosphate esters (OPEs) in atmospheric fine particles (PM(2.5)) were comprehensively investigated in the Beijing-Tianjin-Hebei (BTH) region from April 2016 to March 2017. The concentrations of ?(8)OPEs in all the five sampling sites ranged from 90 to 8291 pg/m(3) (mean 1148 ± 1239 pg/m(3); median 756 pg/m(3)). The highest level (median 1067 pg/m(3)) was found at one of the urban sites in Beijing, followed by Tianjin (746 pg/m(3)) and Shijiazhuang (724 pg/m(3)). Tris(2-chloroethyl) phosphate (TCEP) and tri[(2R)-1-chloro-2-propyl] phosphate (TCPP) were the dominant compounds across the five sampling locations. Generally, the concentrations of chlorinated OPEs were relatively higher in summer than in winter (p < 0.05), but no significant seasonal difference was discovered for non-chlorinated individual OPEs. The concentrations of tri-n-butyl phosphate (TBP), TCEP, TCPP and triphenyl phosphate (TPP) were positively correlated with the meteorological parameters (i.e. temperature and relative humidity) (p < 0.05), indicating an evident influence of meteorological condition on OPE distribution. We observed a negative correlation (p < 0.05) between octanol-air partition coefficients (logK(oa)) and the ratio of PM(2.5)-bound OPE concentrations to total suspended particulates-bound OPE concentrations, suggesting that physicochemical properties affect the particle-size distribution of OPEs. Furthermore, the median value of cancer hazard quotients (HQs) of TCEP was higher than TBP and tris(2-ethylhexyl) phosphate (TEHP). The health risk assessment showed that HQ values for children were ~1.6 times higher than those for adults. Relatively higher health risk induced by PM(2.5)-bound OPEs via inhalation was found during severe hazy days than in clear days.
Fine particulate matter (PM(2.5), aerodynamic diameter ?2.5?µm) impacts the climate, reduces visibility and severely influences human health. The Indo-Gangetic Plain (IGP), home to about one-seventh of the world’s total population and a hotspot of aerosol loading, observes strong enhancements in the PM(2.5) concentrations towards winter. We performed high-resolution (12?km × 12?km) atmospheric chemical transport modeling (WRF-Chem) for the post-monsoon to winter transition to unravel the underlying dynamics and influences of regional emissions over the region. Model, capturing the observed variations to an extent, reveals that the spatial distribution of PM(2.5) having patches of enhanced concentrations (?100 µgm(-3)) during post-monsoon, evolves dramatically into a widespread enhancement across the IGP region during winter. A sensitivity simulation, supported by satellite observations of fires, shows that biomass-burning emissions over the northwest IGP play a crucial role during post-monsoon. Whereas, in contrast, towards winter, a large-scale decline in the air temperature, significantly shallower atmospheric boundary layer, and weaker winds lead to stagnant conditions (ventilation coefficient lower by a factor of ~4) thereby confining the anthropogenic influences closer to the surface. Such changes in the controlling processes from post-monsoon to winter transition profoundly affect the composition of the fine aerosols over the IGP region. The study highlights the need to critically consider the distinct meteorological processes of west-to-east IGP and changes in dominant sources from post-monsoon to winter in the formulation of future pollution mitigation policies.
Background The natural cycle of large-scale wildfires is accelerating, increasingly exposing both rural and populous urban areas to wildfire emissions. While respiratory health effects associated with wildfire smoke are well established, cardiovascular effects have been less clear. Methods and Results We examined the association between out-of-hospital cardiac arrest and wildfire smoke density (light, medium, heavy smoke) from the National Oceanic Atmospheric Association’s Hazard Mapping System. Out-of-hospital cardiac arrest data were provided by the Cardiac Arrest Registry to Enhance Survival for 14 California counties, 2015-2017 (N=5336). We applied conditional logistic regression in a case-crossover design using control days from 1, 2, 3, and 4 weeks before case date, at lag days 0 to 3. We stratified by pathogenesis, sex, age (19-34, 35-64, and >= 65 years), and socioeconomic status (census tract percent below poverty). Out-of-hospital cardiac arrest risk increased in association with heavy smoke across multiple lag days, strongest on lag day 2 (odds ratio, 1.70; 95% CI, 1.18-2.13). Risk in the lower socioeconomic status strata was elevated on medium and heavy days, although not statistically significant. Higher socioeconomic status strata had elevated odds ratios with heavy smoke but null results with light and medium smoke. Both sexes and age groups 35 years and older were impacted on days with heavy smoke. Conclusions Out-of-hospital cardiac arrests increased with wildfire smoke exposure, and lower socioeconomic status appeared to increase the risk. The future trajectory of wildfire, along with increasing vulnerability of the aging population, underscores the importance of formulating public health and clinical strategies to protect those most vulnerable.
Ozone exposure is associated with higher risk of asthma-related emergency department visits. The meteorological conditions that govern ozone concentration are projected to be more favorable to ozone formation over much of the United States due to continued climate change, even as emissions of anthropogenic ozone precursors are expected to decrease by 2050. Our goal is to quantify the health benefits of a climate change mitigation scenario versus a “business-as-usual” scenario, defined by the United Nations Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) 4.5 and 8.5, respectively, using the health impact analytical program Benefits Mapping and Analysis Program – Community Edition (BenMAP – CE) to project the number of asthma ED visits in 2045-2055. We project an annual average of 3100 averted ozone-related asthma ED visits during the 2045-2055 period under RCP4.5 versus RCP8.5, with all other factors held constant, which translates to USD $1.7 million in averted costs annually. We identify counties with tens to hundreds of avoided ozone-related asthma ED visits under RCP4.5 versus RCP8.5. Overall, we project a heterogeneous distribution of ozone-related asthma ED visits at different spatial resolutions, specifically national, regional, and county levels, and a substantial net health and economic benefit of climate change mitigation.
Background Wildfire events are increasing in prevalence in the western United States. Research has found mixed results on the degree to which exposure to wildfire smoke is associated with an increased risk of mortality. Methods We tested for an association between exposure to wildfire smoke and non-traumatic mortality in Washington State, USA. We characterized wildfire smoke days as binary for grid cells based on daily average PM2.5 concentrations, from June 1 through September 30, 2006-2017. Wildfire smoke days were defined as all days with assigned monitor concentration above a PM2.5 value of 20.4 mu g/m(3), with an additional set of criteria applied to days between 9 and 20.4 mu g/m(3). We employed a case-crossover study design using conditional logistic regression and time-stratified referent sampling, controlling for humidex. Results The odds of all-ages non-traumatic mortality with same-day exposure was 1.0% (95% CI: – 1.0 – 4.0%) greater on wildfire smoke days compared to non-wildfire smoke days, and the previous day’s exposure was associated with a 2.0% (95% CI: 0.0-5.0%) increase. When stratified by cause of mortality, odds of same-day respiratory mortality increased by 9.0% (95% CI: 0.0-18.0%), while the odds of same-day COPD mortality increased by 14.0% (95% CI: 2.0-26.0%). In subgroup analyses, we observed a 35.0% (95% CI: 9.0-67.0%) increase in the odds of same-day respiratory mortality for adults ages 45-64. Conclusions This study suggests increased odds of mortality in the first few days following wildfire smoke exposure. It is the first to examine this relationship in Washington State and will help inform local and state risk communication efforts and decision-making during future wildfire smoke events.
Background Wildfires are increasingly a significant source of fine particulate matter (PM2.5), which has been linked to adverse health effects and increased mortality. ESKD patients are potentially susceptible to this environmental stressor. Methods We conducted a retrospective time-series analysis of the association between daily exposure to wildfire PM2.5 and mortality in 253 counties near a major wildfire between 2008 and 2012. Using quasi-Poisson regression models, we estimated rate ratios (RRs) for all-cause mortality on the day of exposure and up to 30 days following exposure, adjusted for background PM2.5, day of week, seasonality, and heat. We stratified the analysis by causes of death (cardiac, vascular, infectious, or other) and place of death (clinical or nonclinical setting) for differential PM2.5 exposure and outcome classification. Results We found 48,454 deaths matched to the 253 counties. A 10-mu g/m(3) increase in wildfire PM2.5 associated with a 4% increase in all-cause mortality on the same day (RR, 1.04; 95% confidence interval [95% CI], 1.01 to 1.07) and 7% increase cumulatively over 30 days following exposure (RR, 1.07; 95% CI, 1.01 to 1.12). Risk was elevated following exposure for deaths occurring in nonclinical settings (RR, 1.07; 95% CI, 1.02 to 1.12), suggesting modification of exposure by place of death. “Other” deaths (those not attributed to cardiac, vascular, or infectious causes) accounted for the largest portion of deaths and had a strong same-day effect (RR, 1.08; 95% CI, 1.03 to 1.12) and cumulative effect over the 30-day period. On days with a wildfire PM2.5 contribution >10 mu g/m(3), exposure accounted for 8.4% of mortality. Conclusions Wildfire smoke exposure was positively associated with all-cause mortality among patients receiving in-center hemodialysis.
Air pollution and heat are significant threats to public health, especially in urban areas with intensive human activities under the trend of climate change. However, the mediation effects of urban form on health via air pollution and heat have been overlooked in previous investigations. This study explored the potential impacts and pathways of urban form on cardiovascular mortality through air pollutants and heat by using partial least squares model with data from Taiwan. The measurable characteristics of urban form include city size, urban sprawl, and mixed land use. Other factors that influence cardiovascular mortality, such as urban industrial level, economic status, aging population, and medical resource, were also considered in the model. Results revealed that maximizing mixed land use and minimizing city size and urban sprawl can help reduce cardiovascular mortality, and the minimizing city size was the most important one. Urban industrial level, economic status, aging population, and medical resource were also influential factors. This is the first study to consider the pathways and impacts of urban form on cardiovascular mortality, and our results indicate that proper urban planning and policy could reduce cardiovascular mortality.
Both ozone exposure and extreme temperatures are found to be significantly associated with mortality; however, inconsistent results have been obtained on the modification effects of temperature on the ozone-mortality association. In the present study, we conducted a nationwide time-series analysis in 128 counties from 2013-2018 to examine whether temperature modifies the association between short-term ozone exposure with nonaccidental and cause-specific mortality in China. First, we analyzed the effects of ozone exposure on mortality at different temperature levels. Then, we calculated the pooled effects through a meta-analysis across China. We found that high-temperature conditions (>75th percentile in each county) significantly enhanced the effects of ozone on nonaccidental, cardiovascular, and respiratory mortality, with increases of 0.44% (95% confidence interval (CI): 0.36 and 0.51%), 0.42% (95% CI: 0.32 and 0.51%) and 0.50% (95% CI: 0.31 and 0.68%), respectively, for a 10 ?g/m(3) increase in ozone at high temperatures. Stronger effects on nonaccidental and cardiovascular mortality were observed at high temperatures among elderly individuals aged 65 years and older compared with the younger people. Our findings provide evidence that health damage because of ozone may be influenced by the impacts of increasing temperatures, which point to the importance of mitigating ozone exposure in China under the context of climate change to further reduce the public health burden.
OBJECTIVES: This study investigated the modification of temperature effects on cardiovascular and respiratory mortality by air pollutants (particulate matter less than 2.5 and 10 µm in diameter [respectively], ozone, nitrogen dioxide, carbon monoxide, and sulfur dioxide). METHODS: Poisson additive models with a penalized distributed lag non-linear model were used to assess the association of air temperature with the daily number of deaths from cardiovascular and respiratory diseases in Ahvaz, Iran from March 21, 2014 to March 20, 2018, controlling for day of the week, holidays, relative humidity, wind speed, air pollutants, and seasonal and long-term trends. Subgroup analyses were conducted to evaluate the effect modification for sex and age group. To assess the modification of air pollutants on temperature effects, the level of each pollutant was categorized as either greater than the median value or less than/equal to the median value. RESULTS: We found no significant associations between temperature and cardiovascular and respiratory mortality. In the subgroup analyses, however, high temperatures were significantly associated with an increased risk of cardiovascular mortality among those 75 years old and older, with the strongest effect observed on day 0 relative to exposure. The results revealed a lack of interactive effects between temperature and air pollutants on cardiovascular and respiratory mortality. CONCLUSIONS: A weak but significant association was found between high temperature and cardiovascular mortality, but only in elderly people. Air pollution did not significantly modify the effect of ambient temperature on cardiovascular and respiratory mortality.
Exposure to air pollution is one of the primary global health risk factors, yet individuals lack the knowledge to engage in individual risk mitigation and the skills to mobilize for the change necessary to reduce such risks. News media is an important tool for influencing individual actions and support for public policies to reduce environmental threats; thus, a lack of news coverage of such issues may exacerbate knowledge deficits. This study examines the reporting of health risks and precautionary measures regarding air pollution in national and regional print news. We conducted a content analysis of two national and two local newspapers covering the USA’s most polluted region during a 5-year period. Coders identified information on threat, self-efficacy, protective measures and information sources. Nearly 40% of air pollution news articles mentioned human health risks. Fewer than 10% of news stories about air pollution provided information on the precautionary measures necessary for individuals to take action to mitigate their risk. Local newspapers did not report more threat (X-2= 1.931,p= 0.165) and efficacy (X-2= 1.118,p= 0.209) information. Although air pollution levels are high and continue to rise at alarming rates, our findings suggest that news media reporting is not conducive to raising environmental health literacy.
OBJECTIVE: The aim of this study was to investigate the status of Vitamin D deficiency and the effect of environmental factors on Vitamin D levels so as to provide theoretical support for public health promotion in this region. METHODS: A total of 22,387 subjects who underwent a physical examination at the center in the West China Hospital, Sichuan University, between April, 2018 and May, 2020 were enrolled in this study. Their data on gender, age, inspection date, serum 25 hydroxyvitamin D (25-(OH) D), parathyroid hormone (PTH), and total calcium were retrospectively reviewed. Next, the percentage of Vitamin D status was compared in different sex and age groups, and the fluctuation of Vitamin D level was described in relation to the change of environment. Finally, the univariable and multivariable linear regression analyses were performed to explore the risk and protective factors of Vitamin D deficiency. RESULTS: The proportion of Vitamin D deficiency in this area was 42.17%, and it was significantly higher among women and young people. The fluctuation trend of 25-(OH) D levels are consistent with temperature and solar radiation, and opposite to air quality, in the whole year. There was a positive relationship between 25-(OH) D levels with temperature and solar radiation; however, parathyroid hormone, female and AQI were negatively correlated with Vitamin D levels. CONCLUSION: Vitamin D deficiency is common in subtropic areas, such as Sichuan Basin, which is related to solar radiation and air pollution.
Short-lived climate pollutants (SLCPs) including black carbon (BC), methane (CH4), and tropospheric ozone (O-3) are major climate forcers after carbon dioxide (CO2). These SLCPs also have detrimental impacts on human health and agriculture. Studies show that the Hindu Kush Himalayan (HKH) region, which includes Nepal, has been experiencing the impacts of these pollutants in addition to greenhouse gases. In this study, we derive a national-level emission inventory for SLCPs, CO2, and air pollutants for Nepal and project their impacts under reference (REF) and mitigation policy (POL) scenarios. The impacts on human health, agriculture, and climate were then estimated by applying the following: (1) adjoint coefficients from the Goddard Earth Observing System (GEOS)-chemical transport model that quantify the sensitivity of fine particulate matter (PM2.5) and surface O-3 concentrations in Nepal, and radiative forcing in four latitudinal bands, to emissions in 2 x 2.5 degrees grids, and (2) concentration-response functions to estimate health and crop loss impacts in Nepal. With the mitigating measures undertaken, emission reductions of about 78% each of BC and CH4 and 87% of PM2.5 could be achieved in 2050 compared with the REF scenario. This would lead to an estimated avoidance of 29,000 lives lost and 1.7 million tonnes of crop loss while bringing an economic benefit in present value of 2.7 times more than the total cost incurred in its implementation during the whole period 2010-2050. The results provide useful policy insights and pathways for evidence-based decision-making in the design and effective implementation of SLCP mitigation measures in Nepal.
It is often difficult to define the relationship and the influence of climate on the occurrence and distribution of disease. To examine this issue, the effects of climate indices on the distributions of malaria and meningitis in Nigeria were assessed over space and time. The main purpose of the study was to evaluate the relationships between climatic variables and the prevalence of malaria and meningitis, and develop an early warning system for predicting the prevalence of malaria and meningitis as the climate varies. An early warning system was developed to predetermine the months in a year that people are vulnerable to malaria and meningitis. The results revealed a significant positive relationship between rainfall and malaria, especially during the wet season with correlation coefficient R-2 >= 60.0 in almost all the ecological zones. In the Sahel, Sudan and Guinea, there appears to be a strong relationship between temperature and meningitis with R-2 > 60.0. In all, the results further reveal that temperatures and aerosols have a strong relationship with meningitis. The assessment of these initial data seems to support the finding that the occurrence of meningitis is higher in the northern region, especially the Sahel and Sudan. In contrast, malaria occurrence is higher in the southern part of the study area. We suggest that a thorough investigation of climate parameters is critical for the reallocation of clinical resources and infrastructures in economically underprivileged regions.
The effects of atmospheric black carbon (BC) on climate and public health have been well established, but large uncertainties remain regarding the extent of the impacts of BC at different temporal and spatial scales. These uncertainties are largely due to the heterogeneous nature of BC in terms of its spatiotemporal distribution, mixing state, and coating composition. Here, we seek to further understand the size and mixing state of BC emitted from various sources and aged over different timescales using field measurements in the Los Angeles region. We measured refractory black carbon (rBC) with a single-particle soot photometer (SP2) on Catalina Island, California (similar to 70 km southwest of downtown Los Angeles) during three different time periods. During the first campaign (September 2017), westerly winds were dominant and measured air masses were representative of wellaged background over the Pacific Ocean. In the second and third campaigns (December 2017 and November 2018, respectively), atypical Santa Ana wind conditions allowed us to measure biomass burning rBC (BCbb) from air masses dominated by large biomass burning events in California and fossil fuel rBC (BCff) from the Los Angeles Basin. We observed that the emissions source type heavily influenced both the size distribution of the rBC cores and the rBC mixing state. BCbb had thicker coatings and larger core diameters than BBff. We observed a mean coating thickness (CTBc) of similar to 40-70 nm and a count mean diameter (CMD) of similar to 120 nm for BCbb. For BCff, we observed a CTBc of similar to 5-15 nm and a CMD of similar to 100 nm. Our observations also provided evidence that aging led to an increased CTBc for both BCbb and BCff . Aging timescales < similar to 1 d were insufficient to thickly coat freshly emitted BCff. However, CTBc for aged B-ff within aged background plumes was similar to 35 nm thicker than CTBc for fresh BCff. Likewise, we found that CTBc for aged BCbb was similar to 18 nm thicker than CTBc for fresh BCbb. The results presented in this study highlight the wide variability in the BC mixing state and provide additional evidence that the emissions source type and aging influence rBC microphysical properties.
Central to public health risk communication is understanding the perspectives and shared values among individuals who need the information. Using the responses from a Smoke Sense citizen science project, we examined perspectives on the issue of wildfire smoke as a health risk in relation to an individual’s preparedness to adopt recommended health behaviors. The Smoke Sense smartphone application provides wildfire-related health risk resources and invites participants to record their perspectives on the issue of wildfire smoke. Within the app, participants can explore current and forecasted daily air quality, maps of fire locations, satellite images of smoke plumes, and learn about health consequences of wildfire smoke. We used cluster analysis to identify perspective trait-clusters based on health status, experience with fire smoke, risk perception, self-efficacy, access to exposure-reducing resources, health information needs, and openness to health risk messaging. Differences between traits were examined based on demographics, health status, activity level and engagement with the app. We mapped these traits to the Precaution Adoption Process Model (PAPM) to indicate where each trait lies in adopting recommended health behaviors. Finally, we suggest messaging strategies that may be suitable for each trait. We determined five distinct perspective traits which included individuals who were Protectors and have decided to engage on the issue by adopting new behaviors to protect their health; Cautious, Proactive, and Susceptible individuals who were at a Deciding stage but differed based on risk perceptions and information needs; and the Unengaged who did not perceive smoke as a health issue and were unlikely to change behavior in response to messaging. Across all five traits, the level of engagement and information needs differed substantially, but were not defined by demographics. Individuals in the Susceptible trait had the highest level of engagement and the highest information needs. Messaging that emphasizes self-efficacy and benefits of reducing exposure may be effective in motivating individuals from the deciding stage to taking health protective action. Shared perspectives define an individual’s propensity for acting on recommended health behaviors, therefore, health risk message content should be tailored based on these perspectives.
Environmental hazards increase the health morbidity and mortality burden. This study compared the knowledge and perceptions about the health effects of environmental hazards among medical and engineering students of Hamdard University Karachi. A total of 263 (44.1%) engineering students, and 333 (55.9%) medical students participated in the study. Cumulatively, the three most commonly identified environmental hazards included tobacco smoking 561 (94.1%), global climate change 518 (86.9%), and solar ultraviolet radiation 511 (85.7%). The study results suggest the need for better quantifying the magnitude of understanding environmental hazards, and for health education and promotion programmes at the graduate level for medical and engineering students in Karachi.
Several studies have reported that air pollution and climatic factors are major contributors to human morbidity and mortality globally. However, the combined interactive effects of air pollution and climatic factors on human health remain largely unexplored. This study aims to investigate the interactive effects of air pollution and climatic factors on circulatory and respiratory mortality in Xi’an, China. Time-series analysis and the distributed lag non-linear model (DLNM) were employed as the study design and core statistical method. The interaction relative risk (IRR) and relative excess risk due to interaction (RERI) for temperature and Air Quality Index (AQI) interaction on circulatory mortality were 0.973(0.969, 0.977) and -0.055(-0.059, -0.048), respectively; while for relative humidity and AQI interaction, 1.098(1.011, 1.072) and 0.088(0.081, 0.107) respectively, were estimated. Additionally, the IRR and RERI for temperature and AQI interaction on respiratory mortality were 0.805(0.722, 0.896) and -0.235(-0.269, -0.163) respectively, while 1.008(0.965, 1.051) and -0.031(-0.088, 0.025) respectively were estimated for relative humidity and AQI interaction. The interaction effects of climatic factors and AQI were synergistic and antagonistic in relation to circulatory and respiratory mortality, respectively. Interaction between climatic factors and air pollution contributes significantly to circulatory and respiratory mortality.
BACKGROUND: Daily air quality index (AQI) forecast can provide early warning information, and it is not clear whether it is appropriate for childhood asthma hospitalizations (CAHs). Furthermore, little is known about the effects of AQI on CAHs, as well as the interactions between temperature, humidity and AQI. METHODS: We collected 32,238 cases in Hefei from 2013 to 2016 and estimated the association between daily CAHs and AQI by combining the Poisson Generalized Linear Models (PGLMs) with the Distributed Lag Nonlinear Models (DLNMs). The interaction between AQI and temperature was tested by stratifying AQI and temperature, as well as humidity. RESULTS: AQI was associated with an increased risk of hospitalizations for childhood asthma. The adverse effect first appeared on the 3rd day, with the RR of 1.011 (95%CI: 1.000-1.023) and continued until the 19th day of lag (RR = 1.010, 95%CI: 1.001-1.020). In the subgroup analysis, the male and pre-school children were more sensitive to AQI, and there are seasonal differences in the effects of AQI on CAHs. Besides, in a stratified analysis with an AQI of 150, we found synergies between temperature, humidity and AQI. The interaction relative risk (IRR) and relative excess risk due to interaction (RERI) for the interaction between temperature and AQI were 1.157 (95%CI: 1.029-1.306) and 0.122 (95%CI: 0.022-0.223) respectively. For the humidity, the IRR and RERI were 1.090 (95%CI: 1.056-1.206) and 0.083 (95%CI: 0.083-0.143) respectively. Exploring different subgroups in the interaction analyses, it was worth noting that female and pre-school children were more sensitive to the interaction between AQI and temperature, while school-age children were more sensitive to the interaction between AQI and humidity. CONCLUSIONS: The study found that not only AQI can significantly increase the risk of CAHs, but also that under the context of climate change, temperature and humidity have a synergistic effect on AQI, suggesting that considering only the warning information of air pollution is not enough to strengthen the prevention of childhood asthma hospitalization.
BACKGROUND: Both extreme heat and air pollution exposure during pregnancy have been associated with preterm birth; however, their combined effects are unclear. OBJECTIVES: Our goal was to estimate the independent and joint effects of heatwaves and fine particulate matter [PM < 2.5 ?m in aerodynamic diameter (PM2.5)], exposure during the final gestational week on preterm birth. METHODS: Using birth registry data from Guangzhou, China, we included 215,059 singleton live births in the warm season (1 May-31 October) between January 2015 and July 2017. Daily meteorological variables from 5 monitoring stations and PM2.5 concentrations from 11 sites were used to estimate district-specific exposures. A series of cut off temperature thresholds and durations (2, 3, and 4 consecutive d) were used to define 15 different heatwaves. Cox proportional hazard models were used to estimate the effects of heatwaves and PM2.5 exposures during the final week on preterm birth, and departures from additive joint effects were assessed using the relative excess risk due to interaction (RERI). RESULTS: Numbers of preterm births increased in association with heatwave exposures during the final gestational week. Depending on the heatwave definition used, hazard ratios (HRs) ranged from 1.10 (95% CI: 1.01, 1.20) to 1.92 (1.39, 2.64). Associations were stronger for more intense heatwaves. Combined effects of PM2.5 exposures and heatwaves appeared to be synergistic (RERIs > 0) for less extreme heatwaves (i.e., shorter or with relatively low temperature thresholds) but were less than additive (RERIs < 0) for more intense heatwaves. CONCLUSIONS: Our research strengthens the evidence that exposure to heatwaves during the final gestational week can independently trigger preterm birth. Moderate heatwaves may also act synergistically with PM2.5 exposure to increase risk of preterm birth, which adds new evidence to the current understanding of combined effects of air pollution and meteorological variables on adverse birth outcomes. https://doi.org/10.1289/EHP5117.
BACKGROUND: Due to variations in climatic conditions, the effects of meteorological factors and PM(2.5) on influenza activity, particularly in subtropical regions, vary in existing literature. In this study, we examined the relationship between influenza activity, meteorological parameters, and PM(2.5) . METHODS: A total of 20 165 laboratory-confirmed influenza cases in Hangzhou, Zhejiang province, were documented in our dataset and aggregated into weekly counts for downstream analysis. We employed a combination of the quasi-Poisson-generalized additive model and the distributed lag non-linear model to examine the relationship of interest, controlling for long-term trends, seasonal trends, and holidays. RESULTS: A hockey-stick association was found between absolute humidity and the risk of influenza infections. The overall cumulative adjusted relative risk (ARR) was statistically significant when weekly mean absolute humidity was low (<10 µg/m(3) ) and high (>17.5 µg/m(3) ). A slightly higher ARR was observed when weekly mean temperature reached over 30.5°C. A statistically significantly higher ARR was observed when weekly mean relative humidity dropped below 67%. ARR increased statistically significantly with increasing rainfall. For PM(2.5) , the ARR was marginally statistically insignificant. In brief, high temperature, wet and dry conditions, and heavy rainfall were the major risk factors associated with a higher risk of influenza infections. CONCLUSIONS: The present study contributes additional knowledge to the understanding of the effects of various environmental factors on influenza activities. Our findings shall be useful and important for the development of influenza surveillance and early warning systems.
The sensitivities of meteorological and chemical predictions to urban effects over four major North American cities are investigated using the high-resolution (2.5-km) Environment and Climate Change Canada’s air quality model with the Town Energy Balance (TEB) scheme. Comparisons between the model simulation results with and without the TEB effect show that urbanization has great impacts on surface heat fluxes, vertical diffusivity, air temperature, humidity, atmospheric boundary layer height, land-lake circulation, air pollutants concentrations and Air Quality Health Index. The impacts have strong diurnal variabilities, and are very different in summer and winter. While the diurnal variations of the impacts share some similarities over each city, the magnitudes can be very different. The underlying mechanisms of the impacts are investigated. The TEB impacts on the predictions of meteorological and air pollutants over Toronto are evaluated against ground-based observations. The results show that the TEB scheme leads to a great improvement in biases and root-mean-square deviations in temperature and humidity predictions in downtown, uptown and suburban areas in the early morning and nighttime. The scheme also leads to a big improvement of predictions of NOx, PM2.5 and ground-level ozone in the downtown, uptown and industrial areas in the early morning and nighttime.
Urbanization and climate change have been rapidly occurring globally. Evidence-based healthy city development is required to improve living quality and mitigate the adverse impact of the outdoor neighborhood environment on public health. Taking Guangzhou as an example to explore the association of neighborhood environment and public health and preferably to offer some implications for better future city development, we measured ten environmental factors (temperature (T), wind-chill index (WCI), thermal stress index (HSI), relative humidity (RH), average wind speed (AWS), negative oxygen ions (NOI), PM2.5, luminous flux (LF), and illuminance (I)) in four seasons in four typical neighborhoods, and the SF-36 health scale was employed to assess the physical and mental health of neighborhood residents in nine subscales (health transition(HT), physiological functions (PF), general health status (GH), physical pain (BP), physiological functions (RP), energy vitality (VT), mental health (MH), social function (SF), and emotional functions (RE)). The linear mixed model was used in an analysis of variance. We ranked the different environmental factors in relation to aspects of health and weighted them accordingly. Generally, the thermal environment had the greatest impact on both physical and mental health and the atmospheric environment and wind environment had the least impact on physical health and mental health, respectively. In addition, the physical health of the resident was more greatly affected by the environment than mental health. According to the results, we make a number of strategic suggestions for the renewal of the outdoor neighborhood environment in subtropical monsoon climate high-density cities and provide a theoretical basis for improving public health through landscape architecture at the neighborhood scale.
Rationale: There is significant evidence of increased healthcare utilization from cardiopulmonary causes in adults from exposure to wildfire smoke, but evidence in pediatric age groups is limited.Objectives: To quantify and examine the healthcare utilization effects of the December 2017 Lilac Fire in San Diego County among pediatric patients at the Rady Children’s Hospital (RCH) emergency department and urgent care (UC) clinics.Methods: Using data from 2011 to 2017, including data on daily particulate matter <2.5 ?m (PM(2.5)) in an inverse-distance interpolation model and RCH electronic medical records, we retrospectively analyzed pediatric respiratory visits at the RCH emergency department and UC clinics during the Santa Ana wind (SAW)-driven Lilac Fire from December 7 to 16, 2017. An interrupted time series study design was applied as our primary analysis to compare the observed pediatric respiratory visits from December 7 to 16, 2017 to what would have occurred in a counterfactual situation, namely, if the Lilac Fire had not occurred. A complementary descriptive spatial analysis was also used to evaluate the geographic distribution of respiratory visits in relationship to satellite imaging of the Lilac Fire and the associated wind pattern.Results: The Lilac Fire was associated with 16.0 (95% confidence interval [CI], 11.2-20.9) excess respiratory visits per day at the RCH emergency department across all pediatric age groups. Children aged 0 to 5 years had the highest absolute excess respiratory visits per day with 7.3 (95% CI, 3.0-11.7), whereas those aged 6 to 12 years had the highest relative increase in visits, with 3.4 (95% CI, 2.3-4.6). RCH UC clinics had similar results. The top five ZIP codes in San Diego County with the highest standard deviations of age-adjusted respiratory visits were all located generally downwind of the fire perimeter, as expected for the SAW pattern.Conclusions: We have demonstrated an increase in pediatric respiratory visits during the SAW-driven Lilac Fire in San Diego County in a patterned geographic distribution that is attributable to an increase in PM(2.5) exposure. Younger children were particularly affected. Climate change is expected to result in more frequent and extensive wildfires in the region and will require greater preparedness and adaptation efforts to protect vulnerable populations, such as young children.
Background: Air pollution is a global problem and also linked to respiratory diseases. Wildfire smog is a major cause of air pollution in the upper northern area of Thailand. Thus, in the current study, we examined whether long-term exposure to wildfire smog induces lung function changes in a population from the upper northern area of Thailand. Methods: The lung function of 115 participants with long-term exposure smog was determined using peak flow meter. Results: Long-term smoke exposure participants decreased FEV1 (forced expiratory volume in 1 second)/FVC (forced vital capacity) ratio (56.49 +/- 23.88 in males and 56.29 +/- 28.23 in females) compared with general Thai population. Moreover, the reduction of FVC, FEV1, and peak expiratory flow rate (PEFR) values also showed in both male and female subjects. These results suggest that long-term smoke exposure induces obstructive lung abnormality. Moreover, itchy/watery nose, cough, phlegm, and chest pain also reported in these subjects. Conclusion: Wildfire smog could be induced respiratory pathway inflammation and easily collapsible respiratory airways.
Sand and dust storms in arid and semiarid regions deteriorate regional air quality and threaten public health security. To quantify the negative effects of river dust on regional air quality, this study selected the estuary areas located in central Taiwan as a case study and proposed an integrated framework to measure the fugitive emission of dust from riverbeds with the aid of satellite remote sensing and wind tunnel test, together with the concentrations of particulate matter with a diameter of <10 ?m (PM(10)) around the river system by using The Air Pollution Model. Additionally, the effects of 25 types of meteorological conditions on the health risk due to exposure to dust were evaluated near the estuary areas. The results reveal landscape changes in the downstream areas of Da'an and Dajia rivers, with an increase of 370,820 m(2) and 1,554,850 m(2) of bare land areas in the dry season compared with the wet season in Da'an and Dajia rivers, respectively. On the basis of the maximum emission of river dust, PM(10) concentration increases considerably during both wet and dry seasons near the two rivers. Among 25 different types of weather conditions, frontal surface transit, outer-region circulation from tropical depression system, weak northeast monsoons, and anticyclonic outflow have considerable influence on PM(10) diffusion. In particular, weak northeast monsoons cause the highest health risk in the areas between Da'an and Dajia rivers, which is the densely populated Taichung City. Future studies should attempt to elucidate the environmental impact of dust in different weather conditions and understand the spatial risks to human health due to PM(10) concentration. Facing the increasing threat of climate and landscape changes, governments are strongly encouraged to begin multimedia assessments in environmental management and propose a long-term and systematic framework in resources planning.
Relationships of larger scale meteorological predictors with ground-level daily maximum ozone (O-3max) and daily maximum air temperature (T-max) for stations in Bavaria were analysed. O-3max and T-max as well as threshold exceedances of these variables were assessed under the constraints of ongoing climate change until the end of the twenty-first century. Under RCP8.5 scenario conditions, a substantial increase of T-max in the months from April to September arose, with a mean value of 5 K in the period 2081-2100 compared with the historical period 1986-2005. Statistical downscaling projections pointed to a mean O-3max rise of 17 mu g/m(3). The frequency of threshold exceedances showed also large changes. Hot days may occur in the future at about 30% of all days. Exceedances of O-3max > 100 mu g/m(3) were projected to increase to about 40% of all days at urban traffic sites and up to about 70% in the rural regional background. Days with O-3max > 120 mu g/m(3) occurred still at about 20% of all days at urban traffic sites and at about 45% in rural regional background locations. With respect to combined T-max > 30 degrees C and O-3max > 100 mu g/m(3) events in the future, an occurrence of such events at about 27-29% of all days in the summer months from April to September was assessed. The increases were mainly associated with the strong temperature rise until the end of the century. In summary, the projected T-max and O-3max changes point to a considerable increased health burden in Bavaria until the end of the century, resulting from strong changes of both variables and their associated individual and combined impact on human health.
Air pollution and hot temperatures present two major health risks, especially for vulnerable groups such as children, the elderly, and people with pre-existing conditions. Episodes of high ozone concentrations and heat waves have been registered throughout Europe and are expected to continue to grow due to climate change. Here, several different heat and ozone wave definitions were applied to characterize the wave-type extremes for two climatically different regions, i.e., Portugal (South Europe) and Bavaria (Central Europe), and their impacts were evaluated considering each type of hazard independently but also when they occur simultaneously. Heat and ozone waves were analyzed with respect to the underlying atmospheric circulation patterns and in terms of their association with human mortality. Heat waves were identified as the most frequent wave type and, despite different climate settings, a comparable exposure to heat and ozone waves was found in Central and South Europe. Waves were associated with in-situ built-up as well as with advection of air masses. However, in Bavaria waves showed the strongest connection with autochthonous weather conditions, while for Portugal, the strongest relationship appeared for eastern and north-eastern inflow. The most severe events, as measured by excess mortality, were always associated to compound heat-ozone waves.
BACKGROUND: Summer temperatures are expected to increase and heat waves will occur more frequently, be longer, and be more intense as a result of global warming. A growing body of evidence indicates that increasing temperature and heatwaves are associated with excess mortality and therefore global heating may become a major public health threat. However, the heat-mortality relationship has been shown to be location-specific and differences could largely be explained by the most frequent temperature. So far, in Belgium there is little known regarding the heat-mortality relationship in the different urban areas. OBJECTIVES: The objective of this study is to assess the heat-mortality relationship in the two largest urban areas in Belgium, i.e. Antwerp and Brussels for the warm seasons from 2002 until 2011 taking into account the effect of air pollution. METHODS: The threshold in temperature above which mortality increases was determined using segmented regressions for both urban areas. The relationship between daily temperature and mortality above the threshold was investigated using a generalized estimated equation with Poisson distribution to finally determine the percentage of deaths attributable to the effect of heat. RESULTS: Although only 50 km apart, the heat-mortality curves for the two urban areas are different. More specifically, an increase in mortality occurs above a maximum temperature of 25.2 °C in Antwerp and 22.8 °C in Brussels. We estimated that above these thresholds, there is an increase in mortality of 4.9% per 1 °C in Antwerp and of 3.1% in Brussels. During the study period, 1.5% of the deaths in Antwerp and 3.5% of the deaths in Brussels can be attributed to the effect of heat. The thresholds differed considerably from the most frequent temperature, particularly in Antwerp. Adjustment for air pollution attenuated the effect of temperature on mortality and this attenuation was more pronounced when adjusting for ambient ozone. CONCLUSION: Our results show a significant effect of temperature on mortality above a city-specific threshold, both in Antwerp and in Brussels. These findings are important given the ongoing global warming. Recurrent, intense and longer episodes of high temperature and expected changes in air pollutant levels will have an important impact on health in urban areas.
Wildfires have a significant adverse impact on air quality in the United States (US). To understand the potential health impacts of wildfire smoke, many epidemiology studies rely on concentrations of fine particulate matter (PM) as a smoke tracer. However, there are many gas-phase hazardous air pollutants (HAPs) identified by the Environmental Protection Agency (EPA) that are also present in wildfire smoke plumes. Using observations from the Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE-CAN), a 2018 aircraft-based field campaign that measured HAPs and PM in western US wildfire smoke plumes, we identify the relationships between HAPs and associated health risks, PM, and smoke age. We find the ratios between acute, chronic noncancer, and chronic cancer HAPs health risk and PM in smoke decrease as a function of smoke age by up to 72% from fresh (<1 day of aging) to old (>3 days of aging) smoke. We show that acrolein, formaldehyde, benzene, and hydrogen cyanide are the dominant contributors to gas-phase HAPs risk in smoke plumes. Finally, we use ratios of HAPs to PM along with annual average smoke-specific PM to estimate current and potential future smoke HAPs risks.
Smoke from wildfires contains many air pollutants of concern and epidemiological studies have identified associations between exposure to wildfire smoke PM(2.5) and mortality and respiratory morbidity, and a possible association with cardiovascular morbidity. For this study, a retrospective analysis of air quality modelling was performed to quantify the exposure to wildfire-PM(2.5) across the Canadian population. The model included wildfire emissions from across North America for a 5-month period from May to September (i.e. wildfire season), between 2013 and 2015 and 2017-2018. Large variations in wildfire-PM(2.5) were noted year-to-year, geospatially, and within fire season. The model results were then used to estimate the national population health impacts attributable to wildfire-PM(2.5) and the associated economic valuation. The analysis estimated annual premature mortalities ranging from 54-240 premature mortalities attributable to short-term exposure and 570-2500 premature mortalities attributable to long-term exposure, as well as many non-fatal cardiorespiratory health outcomes. The economic valuation of the population health impacts was estimated per year at $410M-$1.8B for acute health impacts and $4.3B-$19B for chronic health impacts for the study period. The health impacts were greatest in the provinces with populations in close proximity to wildfire activity, though health impacts were also noted across many provinces indicating the long-range transport of wildfire-PM(2.5). Understanding the population health impacts of wildfire smoke is important as climate change is anticipated to increase wildfire activity in Canada and abroad.
OBJECTIVES: To identify key predictors of general practitioner (GP) consultations for allergic rhinitis (AR) using meteorological and environmental data. DESIGN: A retrospective, time series analysis of GP consultations for AR. SETTING: A large GP surveillance network of GP practices in the London area. PARTICIPANTS: The study population was all persons who presented to general practices in London that report to the Public Health England GP in-hours syndromic surveillance system during the study period (3 April 2012 to 11 August 2014). PRIMARY MEASURE: Consultations for AR (numbers of consultations). RESULTS: During the study period there were 186?401 GP consultations for AR. High grass and nettle pollen counts (combined) were associated with the highest increases in consultations (for the category 216-270 grains/m(3), relative risk (RR) 3.33, 95%?CI 2.69 to 4.12) followed by high tree (oak, birch and plane combined) pollen counts (for the category 260-325 grains/m(3), RR 1.69, 95%?CI 1.32 to 2.15) and average daily temperatures between 15°C and 20°C (RR 1.47, 95%?CI 1.20 to 1.81). Higher levels of nitrogen dioxide (NO(2)) appeared to be associated with increased consultations (for the category 70-85?µg/m(3), RR 1.33, 95%?CI 1.03 to 1.71), but a significant effect was not found with ozone. Higher daily rainfall was associated with fewer consultations (15-20?mm/day; RR 0.812, 95% CI 0.674 to 0.980). CONCLUSIONS: Changes in grass, nettle or tree pollen counts, temperatures between 15°C and 20°C, and (to a lesser extent) NO(2) concentrations were found to be associated with increased consultations for AR. Rainfall has a negative effect. In the context of climate change and continued exposures to environmental air pollution, intelligent use of these data will aid targeting public health messages and plan healthcare demand.
Climate policies can bring local air quality and health co-benefits, which may partially or entirely offset the costs of implementing these policies. In this study, we introduce an integrated health co-benefits assessment model, the Regional Emissions-Air quality-Climate-Health (REACH) Modeling Framework, which is capable of evaluating the impact of policies on air pollution-related mortality and morbidity in the whole economic system overtime at the provincial level for China. We first provide a detailed description of the modeling framework and conduct a case study to estimate the health benefits of different climate policy scenarios. We show that a scenario consistent with the 2 degrees C target that peaks China’s emissions before 2025 could avoid around 190 thousand premature deaths in 2030. The health benefits could partially or fully cover the policy costs under different assumptions of the value of a statistical life (VSL). Our framework also illustrates that estimated costs and health benefits distribute unevenly across regions in China.
The flow of the Earth’s atmosphere not only largely determines its temperature status, but also profoundly affects aerosol concentrations. Therefore, exploring how to evaluate the synthetical effects of temperature and aerosol pollution on human health is an important topic. Regarding the atmosphere as a whole, we quantified the mortality burden attributable to short-term exposure to abnormal temperatures and PM2.5 in Beijing from the perspective of atmospheric flow. We first divided the atmospheric stability into three levels (including disturbed, normal, and stable conditions) according to the variations in meteorological conditions and PM2.5 concentrations across the stable weather index levels. We then applied a generalized additive model to separately evaluate the short-term effects of temperature and PM2.5 on mortality under each level of atmospheric stability. We further estimate the associated mortality burden using two indicators, namely attributable fraction and attributable number of deaths. Abnormal temperatures were responsible for most of the mortality burden. Cold temperatures accounted for a substantially higher mortality burden than hot temperatures. The synthetical mortality effects of temperature and PM2.5 varied for different atmospheric stabilities. A stable atmosphere poses the strongest synthetical effects of temperature and PM2.5, while a normal atmosphere provides comparatively beneficial conditions for human health. Our results indicated that the synthetical health impacts of temperature and PM2.5 driven by atmospheric flow need to be considered in the further promulgation of public health policies and air pollution abatement strategies, particularly in the context of climate change.
Background.Exposure to high air temperature in late pregnancy is increasingly recognized as a risk factor for preterm birth (PTB). However, the combined effects of heatwaves with air pollution and green space are still unexplored. In the context of climate change, investigating the interaction between environmental factors and identifying communities at higher risk is important to better understand the etiological mechanisms and design targeted interventions towards certain women during pregnancy.Objectives.To examine the combined effects of heatwaves, air pollution and green space exposure on the risk of PTB.Methods.California birth certificate records for singleton births (2005-2013) were obtained. Residential zip code-specific daily temperature during the last week of gestation was used to create 12 definitions of heatwave with varying temperature thresholds and durations. We fit multi-level Cox proportional hazard models with time to PTB as the outcome and gestational week as the temporal unit. Relative risk due to interaction (RERI) was applied to estimate the additive interactive effect of air pollution and green space on the effect of heatwaves on PTB.Results.In total, 1 967 300 births were included in this study. For PM2.5, PM(10)and O-3, we found positive additive interactions (RERIs >0) between heatwaves and higher air pollution levels. Combined effects of heatwaves and green space indicated negative interactions (RERIs <0) for less intense heatwaves (i.e. shorter duration or relatively low temperature), whereas there were potential positive interactions (RERIs >0) for more intense heatwaves.Conclusion.This study found synergistic harmful effects for heatwaves with air pollution, and potential positive interactions with lack of green space on PTB. Implementing interventions, such as heat warning systems and behavioral changes, targeted toward pregnant women at risk for high air pollution and low green space exposures may optimize the benefits of reducing acute exposure to extreme heat before delivery.
An energy supply dominated by the use of fossil fuels causes both climate change and air pollution, which have negative impacts on human capital via both health and productivity. In addition, different people are affected differently because of factors such as age, gender and education level. To enhance the understanding of the benefits of low carbon transition from the labor supply perspective and help to identify strategies of collaborative control for CO2 and local air pollutants in China, an integrated assessment model linking the air quality module and the health impact module with a disaggregated labor sector computable general equilibrium (CGE) economic system is developed and applied in this study. Results show some key findings. First, renewable energy development and carbon capture and storage (CCS) technologies will contribute significantly to GDP in terms of their impact on air quality improvement by 0.99% and 0.54%, respectively, in 2050. Second, due to differences in labor composition, air pollution has, and will continue to have, the greatest impact on sectors with a higher proportion of male and lower-educated workers – such as the coal sector, and it will have the least impact on sectors with a higher proportion of female and higher-educated workers – such as the public administration sector. Third, the different impacts of sector output will increase economic inequality.
Air pollution regulation requires knowing major sources on any given zone, setting specific controls, and assessing how health risks evolve in response to those controls. Receptor models (RM) can identify major sources: transport, industry, residential, etc. However, RM results are typically available for short term periods, and there is a paucity of RM results for developing countries. We propose to combine a cluster analysis (CA) of air pollution and meteorological measurements with a short-term RM analysis to estimate a long-term, hourly source apportionment of ambient PM(2.5) and PM(10). We have developed a proof of the concept for this proposed methodology in three case studies: a large metropolitan zone, a city with dominant residential wood burning (RWB) emissions, and a city in the middle of a desert region. We have found it feasible to identify the major sources in the CA results and obtain hourly time series of their contributions, effectively extending short-term RM results to the whole ambient monitoring period. This methodology adds value to existing ambient data. The hourly time series results would allow researchers to apportion health benefits associated with specific air pollution regulations, estimate source-specific trends, improve emission inventories, and conduct environmental justice studies, among several potential applications.
Because of fast-paced industrialization, urbanization, and population growth in Indonesia, there are serious health issues in the country resulting from air pollution. This study uses geospatial modelling technologies, namely land-use regression (LUR), geographically weighted regression (GWR), and geographic and temporal weighted regression (GTWR) models, to assess variations in particulate matter (PM(10)) and nitrogen dioxide (NO(2)) concentrations in Surabaya City, Indonesia. This is the first study to implement spatiotemporal variability of air pollution concentrations in Surabaya City, Indonesia. To develop the prediction models, air pollution data collected from seven monitoring stations from 2010 to 2018 were used as dependent variables, while land-use/land cover allocations within a 250 m to 5000 m circular buffer range surrounding the monitoring stations were collected as independent variables. A supervised stepwise variable selection procedure was applied to identify the important predictor variables for developing the LUR, GWR, and GTWR models. The developed models of LUR, GWR, and GTWR accounted for 49%, 50%, and 51% of PM(10) variations and 46%, 47%, and 48% of NO(2) variations, respectively. The GTWR model performed better (R(2) = 0.51 for PM(10) and 0.48 for NO(2)) than the other two models (R(2) = 0.49-0.50 for PM(10) and 0.46-0.47 for NO(2)), LUR and GWR. In the PM(10) model four predictor variables, public facility, industry and warehousing, paddy field, and normalized difference vegetation index (NDVI), were selected during the variable selection procedure. Meanwhile, paddy field, residential area, rainfall, and temperature played important roles in explaining NO(2) variations. Because of biomass burning issues in South Asia, the paddy field, which has a positive correlation with PM(10) and NO(2), was selected as a predictor. By using long-term monitoring data to establish prediction models, this model may better depict PM(10) and NO(2) concentration variations within areas across Asia.
We investigated the geographical character of the COVID-19 infection in China and correlated it with satellite- and ground-based measurements of air quality. Controlling for population density, we found more viral infections in those prefectures (U.S. county equivalent) afflicted by high Carbon Monoxide, Formaldehyde, PM 2.5, and Nitrogen Dioxide values. Higher mortality was also correlated with relatively poor air quality. When summarizing the results at a greater administrative level, we found that the 10 provinces (U.S. state equivalent) with the highest rate of mortality by COVID-19, were often the most polluted but not the most densely populated. Air pollution appears to be a risk factor for the incidence of this disease, despite the conventionally apprehended influence of human mobility on disease dynamics from the site of first appearance, Wuhan. The raw correlations reported here should be interpreted in a broader context, accounting for the growing evidence reported by several other studies. These findings warn communities and policymakers on the implications of long-term air pollution exposure as an ecological, multi-scale public health issue.
OBJECTIVES: There are still controversies about the impact of climatic and environmental factors on thyroid function parameters in healthy populations. We investigated the relationships between climate, air pollution exposure, and thyroid function fluctuations. METHODS: We retrospectively reviewed 327,913 individuals attending routine health checks from December 2013 to December 2018. We analyzed the associations between thyroid function and climatic factors using Spearman’s correlation analysis. We explored the relationships between thyroid function and air pollution exposure using multiple linear regression analysis, after adjusting for age, sex, season, and outdoor temperature. We also performed subgroup analyses by age and sex and sensitivity analyses of different anti-thyroid peroxidase antibody status. RESULTS: Thyroid-stimulating hormone (TSH) and free triiodothyronine (FT3) were negatively associated with outdoor temperature (r?=?-?0.66, P?<?0.001; r?=?-?0.55, P?<?0.001), while free thyroxine (FT4) and FT4/FT3 were positively associated with temperature (r?=?0.35, P?<?0.001; r?=?0.79, P?<?0.001). An increase of 10 ?g/m(3) in fine particulate matter???2.5 ?m (PM2.5) was associated with a decrease of 0.12 pmol/L in FT4 and an increase of 0.07 pmol/L in FT3 (both P?<?0.01). FT4/FT3 was significantly negatively associated with PM2.5 (coefficient: -?0.06, P?<?0.01). These results remained robust in hierarchical analyses and sensitivity analyses. CONCLUSIONS: Thyroid function parameters are associated with climate and air pollution exposure. These factors may influence variations in thyroid function. Our results also highlight the importance of public health interventions to reduce air pollution.
The shift towards the new paradigm, that is, the “ecological and humanistic” paradigm, introduced by the United Nations in the Agenda 2030, and the current period of health emergency due to COVID-19 place the human dimension at the centre of the development strategies for our cities. The humanistic dimension, in particular, is related to human wellbeing, health and living conditions. The health and wellbeing of citizens depend on factors and actions that go beyond the health sector. In particular, here, the attention is focused on the negative impacts produced by pollution and climate change, issues that concern (and that are closely related to) most urban agglomerations in the world. The pandemic due to COVID-19 has highlighted the close relationship existing among social, natural and economic systems. Each system is interdependent on the other. Thus, the pandemic has boosted the necessity to accelerate efforts to address climate change. Therefore, in this framework, new urban development models are required. The circular economy model is proposed as a model able to reduce the negative impacts of urban transformations. The attention is then focused on implementation tools for improving decision-making processes and, in particular, on the evaluation tools for assessing the multidimensional impacts of urbanisation on human health.
Human actions intensify the greenhouse effect, aggravating climate changes in the Amazon and elsewhere in the world. The Intergovernmental Panel on Climate Change (IPCC) foresees a global increase of up to 4.5 °C and 850 ppm CO(2) (above current levels) by 2100. This will impact the biology of the Aedes aegypti mosquito, vector of Dengue, Zika, urban Yellow Fever and Chikungunya. Heat shock proteins are associated with adaptations to anthropic environments and the interaction of some viruses with the vector. The transcription of the hsp26, hsp83 and hsc70 genes of an A. aegypti population, maintained for more than forty-eight generations, in the Current, Intermediate and Extreme climatic scenario predicted by the IPCC was evaluated with qPCR. In females, highest levels of hsp26, hsp83 and hsc70 expression occurred in the Intermediate scenario, while in males, levels were high only for hsp26 gene in Current and Extreme scenarios. Expression of hsp83 and hsc70 genes in males was low under all climatic scenarios, while in the Extreme scenario females had lower expression than in the Current scenario. The data suggest compensatory or adaptive processes acting on heat shock proteins, which can lead to changes in the mosquito’s biology, altering vectorial competence.
Air pollution and the urban heat island effect are consistently linked to numerous respiratory and heat-related illnesses. Additionally, these stressors disproportionately impact low-income and historically marginalized communities due to their proximity to emissions sources, lack of access to green space, and exposure to other adverse environmental conditions. Here, we use relatively low-cost stationary sensors to analyze PM2.5 and temperature data throughout the city of Richmond, Virginia, on the ten hottest days of 2019. For both hourly means within the ten hottest days of 2019 and daily means for the entire record for the year, the temperature was found to exhibit a positive correlation with PM2.5. Analysis of hourly means on the ten hottest days yielded a diurnal pattern in which PM2.5 levels peaked in the early morning and reached their minima in the mid-afternoon. Spatially, sites exhibiting higher temperatures consistently had higher PM2.5 readings, with vulnerable communities in the east end and more intensely developed parts of the city experiencing significantly higher temperatures and PM2.5 concentrations than the suburban neighborhoods in the west end. These findings suggest an uneven distribution of air pollution in Richmond during extreme heat events that are similar in pattern but less pronounced than the temperature differences during these events, although further investigation is required to verify the extent of this relationship. As other studies have found both of these environmental stressors to correlate with the distribution of green space and other land-use factors in cities, innovative and sustainable planning decisions are crucial to the mitigation of these issues of inequity going forward.
Objectives: Inconsistent results have been found between pneumonia and meteorological factors. We aimed to identify principal meteorological factors associated with pneumonia, and to estimate the effect size and lag time. Methods: This was nationwide population-based study used a healthcare claims database merged with a weather database in eight metropolitan cities in Korea. We applied a stepwise approach using the Granger causality test and generalized additive model to elucidate the association between weekly pneumonia incidence (WPI) and meteorological factors/air pollutants (MFAP). Impulse response function was used to examine the time lag. Results: In total, 2 011 424 cases of pneumonia were identified from 2007 to 2017. Among MFAP, diurnal temperature range (DTR), humidity and particulate matter <= 2.5 mm in diameter (PM2.5) showed statistically significant associations with WPI (p < 0.001 for all 3 MFAPs). The association of DTR and WPI showed an inverted U pattern for bacterial and unspecified pneumonia, whereas for viral pneumonia, WPI increased gradually in a more linear manner with DTR and no substantial decline. Humidity showed a consistent pattern in all three pneumonia categories. WPI steeply increased up to 10 to 20 mu g/m(3) of PM2.5 but did not show a further increase in higher concentrations. On the basis of the result, we examined the effect of MFAP in different lag times up to 3 weeks. Conclusions: DTR, humidity and PM2.5 were identified as MFAP most closely associated with WPI. With the model, we were able to visualize the effectetime association of MFAP and WPI. (C) 2020 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.
Objective: Given the lack of studies examining the associations between daily weather and air pollution with nightly objective sleep over multiple weeks, we quantified these associations in a prospective cohort of healthy participants with episodic migraine. Methods: Ninety-eight participants completed daily electronic diaries and wore an actigraph for an average of 45 ds, and a total 4406 nights of data were collected. Nightly sleep characteristics including duration, wake after sleep onset (WASO), and efficiency were assessed using wrist actigraphy. Daily weather parameters and air pollution levels were collected from local weather station and ground-level air quality monitors. We used linear fixed effects models adjusting for participant, day of the week, and day of the year (for weather analysis), and additionally adjusted for temperature and relative humidity (for air pollution analysis). Results: The participants were 35 +/- 12 yrs old and 86 were women. A 10 degrees F higher daily average temper-ature was associated with 0.88 (95% CI: 0.06, 1.70) minutes longer WASO and 0.14% (95% CI:-0.01%, 0.30%) lower sleep efficiency on that night. A 14 parts per billion (ppb) (interquartile range) higher daily maximum eight-h ozone was associated with 7.51 (95% CI: 3.23, 11.79) minutes longer sleep duration on that night. Associations did not differ between cold (October-March) and warm (April-September) seasons. Conclusions: Higher daily ozone was associated with longer sleep duration and modest associations were observed between higher temperature and lower WASO and lower efficiency. (c) 2020 Elsevier B.V. All rights reserved.
BACKGROUND: Despite the substantial role indoor exposure has played in heat wave-related mortality, few epidemiological studies have examined the health effects of exposure to indoor heat. As a result, knowledge gaps regarding indoor heat-health thresholds, vulnerability, and adaptive capacity persist. OBJECTIVE: We evaluated the role of indoor heat exposure on mortality and morbidity among the elderly ( ? 65?years of age) in Houston, Texas. METHODS: Mortality and emergency hospital admission data were obtained through the Texas Department of State Health Services. Summer indoor heat exposure was modeled at the U.S. Census block group (CBG) level using building energy models, outdoor weather data, and building characteristic data. Indoor heat-health associations were examined using time-stratified case-crossover models, controlling for temporal trends and meteorology, and matching on CBG of residence, year, month, and weekday of the adverse health event. Separate models were fitted for three indoor exposure metrics, for individual lag days 0-6, and for 3-d moving averages (lag 0-2). Effect measure modification was explored via stratification on individual- and area-level vulnerability factors. RESULTS: We estimated positive associations between short-term changes in indoor heat exposure and cause-specific mortality and morbidity [e.g., circulatory deaths, odds ratio per?5°C?increase = 1.16 (95% CI: 1.03, 1.30)]. Associations were generally positive for earlier lag periods and weaker across later lag periods. Stratified analyses suggest stronger associations between indoor heat and emergency hospital admissions among African Americans compared with Whites. DISCUSSION: Findings suggest excess mortality among certain elderly populations in Houston who are likely exposed to high indoor heat. We developed a novel methodology to estimate indoor heat exposure that can be adapted to other U.S. LOCATIONS: In locations with high air conditioning prevalence, simplified modeling approaches may adequately account for indoor heat exposure in vulnerable neighborhoods. Accounting for indoor heat exposure may improve the estimation of the total impact of heat on health. https://doi.org/10.1289/EHP6340.
Background: A growing number of cities, including Greater London, have set ambitious targets, including detailed policies and implementation plans, to reach global goals on sustainability, health, and climate change. Here we present a tool for a rapid assessment of the magnitude of impact of specific policy initiatives to reach these targets. The decision-support tool simultaneously quantifies the environmental and health impacts of specified selected policies. Methods: The ‘Cities Rapid Assessment Framework for Transformation (CRAFT)’ tool was applied to Greater London. CRAFT quantifies the effects of ten environmental policies on changes in (1) greenhouse gas (GHG) emissions, (2) exposures to environmental hazards, (3) travel-related physical activity, and (4) mortality (the number of attributable deaths avoided in one typical year). Publicly available data and epidemiological evidence were used to make rapid quantitative estimates of these effects based on proportional reductions in GHG emissions and environmental exposures from current baseline levels and to compute the mortality impacts. Results: The CRAFT tool estimates that, of roughly 50,000 annual deaths in Greater London, the modelled hazards (PM (2.5) (from indoor and outdoor sources), outdoor NO (2), indoor radon, cold, overheating) and low travel-related physical activity are responsible for approximately 10,000 premature environment-related deaths. Implementing the selected polices could reduce the annual mortality number by about 20% (~1,900 deaths) by 2050. The majority of these deaths (1,700) may be avoided through increased uptake in active travel. Thus, out of ten environmental policies, the ‘active travel’ policy provides the greatest health benefit. Also, implementing the ten policies results in a GHG reduction of around 90%. Conclusions: The CRAFT tool quantifies the effects of city policies on reducing GHG emissions, decreasing environmental health hazards, and improving public health. The tool has potential value for policy makers through providing quantitative estimates of health impacts to support and prioritise policy options.
China’s gains in food production over the past four decades have been associated with substantial agricultural nitrogen losses, which contribute to air and water pollution, greenhouse gas emissions and damage to human health. Here, we explore the potential to improve agricultural production practices that simultaneously increase yields while addressing these environmental challenges. We link agronomic research with air quality modelling for an integrated assessment of four improved nitrogen management strategies: improved farm management practices with nitrogen use reductions; machine deep placement of fertilizer; enhanced-efficiency fertilizer use; and improved manure management. We find that simultaneous implementation of the four strategies provides the largest benefits, which include: reductions in PM2.5 concentrations and associated premature deaths; increases in grain yields and grain nitrogen use efficiency; reductions in NO3- leaching and runoff and greenhouse gas emissions. Total benefits of US$30 billion per year exceed the US$18 billion per year in costs. Our findings indicate that policies that improve farmers’ agricultural nitrogen management in China will improve both food security and public health while addressing multiple environmental challenges. Similar increases in attention on agricultural policy around the world are likely to provide large benefits in food security, environmental integrity and public health.
