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.
