More recurrent heat waves and extreme ozone (O(3)) episodes are likely to occur during the next decades and a key question is about the concurrence of those hazards, the atmospheric patterns behind their appearance, and their joint effect on human health. In this work, we use surface maximum temperature and O(3) observations during extended summers in two cities from Morocco: Casablanca and Marrakech, between 2010 and 2019. We assess the connection between these data and climate indices (North Atlantic Oscillation (NAO), Mediterranean Oscillation (MO), and Saharan Oscillation (SaO)). We then identify concurrent heat waves and O(3) episodes, the weather type behind this concurrence, and the combined health risks. Our findings show that the concurrence of heat waves and O(3) episodes depends both on the specific city and the large-scale atmospheric circulation. The likely identified synoptic pattern is when the country is under the combined influence of an anticyclonic area in the north and the Saharan trough extending the depression centered in the south. This pattern generates a warm flow and may foster photochemical pollution. Our study is the first step toward the establishment of an alert system. It will help to provide recommendations for coping with concurrent heat waves and air pollution episodes.
Exposure of humans to high concentrations of PM2.5 has adverse effects on their health. Researchers estimate that exposure to particulate matter from fossil fuel emissions accounted for 18% of deaths in 2018-a challenge policymakers argue is being exacerbated by the increase in the number of extreme weather events and rapid urbanization as they tinker with strategies for reducing air pollutants. Drawing on a number of ensemble machine learning methods that have emerged as a result of advancements in data science, this study examines the effectiveness of using ensemble models for forecasting the concentrations of air pollutants, using PM2.5 as a representative case. A comprehensive evaluation of the ensemble methods was carried out by comparing their predictive performance with that of other standalone algorithms. The findings suggest that hybrid models provide useful tools for PM2.5 concentration forecasting. The developed models show that machine learning models are efficient in predicting air particulate concentrations, and can be used for air pollution forecasting. This study also provides insights into how climatic factors influence the concentrations of pollutants found in the air.
This review highlights the importance of air quality in the African urban development process. We address connections between air pollution and (a) rapid urbanization, (b) social problems, (c) health impacts, (d) climate change, (e) policies, and (f) new innovations. We acknowledge that air pollution levels in Africa can be extremely high and a serious health threat. The toxic content of the pollution could relate to region-specific sources such as low standards for vehicles and fuels, cooking with solid fuels, and burning household waste. We implore the pursuit of interdisciplinary research to create new approaches with relevant stakeholders. Moreover, successful air pollution research must regard conflicts, tensions, and synergies inherent to development processes in African municipalities, regions, and countries. This includes global relationships regarding climate change, trade, urban planning, and transportation. Incorporating aspects of local political situations (e.g., democracy) can also enhance greater political accountability and awareness about air pollution.
Using new satellite data from the European Space Agency’s Sentinel-5P system, this article investigates the spatial and temporal dynamics of vehicular traffic congestion, air pollution, and the distributional impacts on vulnerable populations in Dar es Salaam, Tanzania. The metro region’s rapid growth in vehicle traffic exceeds road network capacity, generating congestion, transport delays, and air pollution from excess fuel use. Dangerously high pollution levels from tailpipe emissions put the health of vulnerable residents at risk, calling for the need to adopt continuous air-quality monitoring and effective pollution control. Our results highlight significant impacts of seasonal weather and wind-speed factors on the spatial distribution and intensity of air pollution from vehicle emissions, which vary widely by area. In seasons when weather factors maximize pollution, the worst exposure occurs along the wind path of high-traffic roadways. The study identifies priority areas for reducing congestion to yield the greatest exposure reduction for young children and the elderly in poor households. This new research direction, based only on the use of free global information sources with the same coverage for all cities, offers metropolitan areas in developing regions the opportunity to benefit from the rigorous analyses traditionally limited to well-endowed cites in developing countries.
Externalities, such as air pollution and increased occupational hazards, resulting from global trends in climate change, rapid industrialization, and rapidly increasing populations are raising global concerns about the associated health risks. The Global Environmental and Occupational Health Hub for Eastern Africa was established to address some of these problems at national and regional levels through focused training and applied research that would yield evidence supporting policies and investments to mitigate risks of increasing environmental threats throughout the Eastern African region. Emphasis has been placed on air pollution, a leading risk factor for global mortality, accounting for over 7 million premature deaths or 8.7% of the 2017 global mortality burden. Despite the enormous disease burden that air pollution causes, global investment in air pollution monitoring and research capacity building in low-middle and middle-income countries have been inadequate. This study outlines the activities the Hub has undertaken in planning for and carrying out its initial capacity building and building its primary research programs and identifies central lessons that can inform other large global research partnerships.
RATIONALE: To date, there is no published local epidemiological evidence documenting the respiratory health effects of source specific air pollution in South Asia, where PM2.5 composition is different from past studies. Differences include more biomass and residue crop-burning emissions, which may have differing health implications. OBJECTIVES: We assessed PM2.5 associations with respiratory emergency department (ED) visits in a biomass-burning dominated high pollution region, and evaluated their variability by pollution source and composition. METHODS: Time-series regression modeling was applied to daily ED visits from January 2014 through December 2017. Air pollutant effect sizes were estimated after addressing long-term trends and seasonality, day-of-week, holidays, relative humidity, ambient temperature, and the effect modification by season, age, and sex. RESULTS: PM2.5 yielded a significant association with increased respiratory ED visits [0.84% (95% CI: 0.33%, 1.35%)] per 10 μg/m3 increase. The PM2.5 health effect size varied with season, the highest being during monsoon season, when fossil-fuel combustion sources dominated exposures. Results from a source-specific health effect analysis was also consistent with fossil-fuel PM2.5 having a larger effect size per 10 μg/m3 than PM2.5 from other sources [fossil-fuel PM2.5: 2.79% (0.33% to 5.31%), biomass-burning PM2.5: 1.27% (0% to 2.54%), and other-PM2.5: 0.95% (0.06% to 1.85%)]. Age-specific associations varied, with children and older adults being disproportionately affected by the air pollution, especially by the combustion-related particles. CONCLUSIONS: This study provided novel and important evidence that respiratory health in Dhaka is significantly affected by particle air pollution, with a greater health impact by fossil-fuel combustion derived PM2.5.
A large concern with estimates of climate and health co-benefits of “clean” cookstoves from controlled emissions testing is whether results represent what actually happens in real homes during normal use. A growing body of evidence indicates that in-field emissions during daily cooking activities differ substantially from values obtained in laboratories, with correspondingly different estimates of co-benefits. We report PM(2.5) emission factors from uncontrolled cooking (n = 7) and minimally controlled cooking tests (n = 51) using traditional chulha and angithi stoves in village kitchens in Haryana, India. Minimally controlled cooking tests (n = 13) in a village kitchen with mixed dung and brushwood fuels were representative of uncontrolled field tests for fine particulate matter (PM(2.5)), organic and elemental carbon (p > 0.5), but were substantially higher than previously published water boiling tests using dung or wood. When the fraction of nonrenewable biomass harvesting, elemental, and organic particulate emissions and modeled estimates of secondary organic aerosol (SOA) are included in 100 year global warming commitments (GWC(100)), the chulha had a net cooling impact using mixed fuels typical of the region. Correlation between PM(2.5) emission factors and GWC (R(2) = 0.99) implies these stoves are climate neutral for primary PM(2.5) emissions of 8.8 ± 0.7 and 9.8 ± 0.9 g PM(2.5)/kg dry fuel for GWC(20) and GWC(100), respectively, which is close to the mean for biomass stoves in global emission inventories.
Despite low per capita emissions, with over a billion population, India is pivotal for climate change mitigation globally, ranking as the third largest emitter of greenhouse gases. We linked a previously published multidimensional population projection with emission projections from an integrated assessment model to quantify the localised (i.e. state-level) health benefits from reduced ambient fine particulate matter in India under global climate change mitigation scenarios in line with the Paris Agreement targets and national scenarios for maximum feasible air quality control. We incorporated assumptions about future demographic, urbanisation and epidemiological trends and accounted for model feedbacks. Our results indicate that compared to a business-as-usual scenario, pursuit of aspirational climate change mitigation targets can avert up to 8.0 million premature deaths and add up to 0.7 years to life expectancy (LE) at birth due to cleaner air by 2050. Combining aggressive climate change mitigation efforts with maximum feasible air quality control can add 1.6 years to LE. Holding demographic change constant, we find that climate change mitigation and air quality control will contribute slightly more to increases in LE in urban areas than in rural areas and in states with lower socio-economic development.
This research was carried out to analyze variations in indoor and outdoor ozone concentrations and their health impact on local communities of megacities in Pakistan. For indoor ozone measurements, industrial units of an economic zone, Hattar Industrial Estate, Haripur, KPK, Pakistan, were selected. For outdoor ozone measurements, maximum and minimum peaks from different selected stations of three megacities (Islamabad, Abbottabad, and Haripur Hattar) in Pakistan were analyzed for paired comparisons. The tropospheric ozone levels were measured with the help of a portable SKY 2000-WH-O-3 meter from December 2018 to November 2019. According to the findings of this investigation, the indoor ozone concentrations at Hattar Industrial Estate exceeded the permissible limit devised by the WHO. The highest concentration (0.37 ppm) was recorded in the month of May in the food industry, while the lowest concentration (0.00 ppm) was recorded in the cooling area of the steel industry in the month of December. For outdoor ozone concentrations, the maximum concentration (0.23 ppm) was detected in Islamabad in the month of March 2019, whereas the rest of year showed comparatively lower concentrations. In Haripur, the maximum concentration (0.22 ppm) was detected in the month of February 2019 and a minimum concentration (0.11 ppm) was found in the month of November 2019. In Abbottabad, the maximum concentration (0.21 ppm) was detected in the month of March 2019 and the minimum concentration was 0.082 ppm. Increasing tropospheric ozone levels might be harmful for local communities and industrial laborers in the winter season because of the foggy weather. In the Abbottabad and Hattar regions, since COVID infection is indirectly related to low temperature and high emission of gases may compromise the respiratory systems of humans. The results of the present study were shared with industrialists to set precautions for ambient air quality and support the adoption of low emission techniques in industries for the safety of labour and nearby residents.
This paper examines the effect of biomass burning on adolescent health in India. The biomass burning problem is quite acute especially in North India, with some states experiencing forest fires and few states actively engaging in crop burning practice. We combine remote sensing data on biomass burning events with a pan-India survey on teenage girls (TAG survey). We exploit regional and temporal variation in our data to establish the link between occurrence of extremely high levels of biomass burning during early life and adolescent height for girls in India. Our results indicate that exposure to extremely high level of biomass burning during prenatal and postnatal period is associated with lower height (by 0.7 percent or 1.07 cm) later in life. Girls from North India are found to be especially vulnerable to the harmful effects of exposure to biomass burning. (c) 2021 Elsevier B.V. All rights reserved.
Smoke from wildfires is a growing health risk across the US. Understanding the spatial and temporal patterns of such exposure and its population health impacts requires separating smoke-driven pollutants from non-smoke pollutants and a long time series to quantify patterns and measure health impacts. We develop a parsimonious and accurate machine learning model of daily wildfire-driven PM(2.5) concentrations using a combination of ground, satellite, and reanalysis data sources that are easy to update. We apply our model across the contiguous US from 2006 to 2020, generating daily estimates of smoke PM(2.5) over a 10 km-by-10 km grid and use these data to characterize levels and trends in smoke PM(2.5). Smoke contributions to daily PM(2.5) concentrations have increased by up to 5 μg/m(3) in the Western US over the last decade, reversing decades of policy-driven improvements in overall air quality, with concentrations growing fastest for higher income populations and predominantly Hispanic populations. The number of people in locations with at least 1 day of smoke PM(2.5) above 100 μg/m(3) per year has increased 27-fold over the last decade, including nearly 25 million people in 2020 alone. Our data set can bolster efforts to comprehensively understand the drivers and societal impacts of trends and extremes in wildfire smoke.
Pakistan ranks third in the world in terms of mortality attributable to air pollution, with aerosol mass concentrations (PM2.5) consistently well above WHO (World Health Organization) air quality guidelines (AQG). However, regulation is dependent on a sparse network of air quality monitoring stations and insufficient ground data. This study utilizes long-term observations of aerosols and trace gases to characterize and rank the air pollution scenarios and pollution characteristics of 80 selected cities in Pakistan. Datasets used include (1) the Aqua and Terra (AquaTerra) MODIS (Moderate Resolution Imaging Spectmradiometer) Level 2 Collection 6.1 merged Dark Target and Deep Blue (DTB) aerosol optical depth (AOD) retrieval products; (2) the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis PM1, PM2.5, and PM10 data; (3) the MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) reanalysis PM2.5 data, (4) the OMI (Ozone Monitoring Instrument) tropospheric vertical column density (TVCD) of nitrogen dioxide (NO2), and VCD of sulfur dioxide (SO2) in the Planetary Boundary Layer (PBL), (5) the VIIRS (Visible Infrared Imaging Radiometer Suite) Nighttime Lights data, (6) MODIS Collection 6 Version 2 global monthly fire location data (MCD14ML), (7) population density, (8) MODIS Level 3 Collection 6 land cover types, (9) AERONET (AErosol RObotic NETwork) Version 3 Level 2.0 data, and (10) ground-based PM2.5 concentrations from air quality monitoring stations. Potential Source Contribution Function (PSCF) analyses were performed by integrating with ground-based PM2.5 concentrations and the NOAA (National Oceanic and Atmospheric Administration) HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) air parcel back trajectories to identify potential pollution source areas which are responsible for extreme air pollution in Pakistan. Results show that the ranking of the top polluted cities depends on the type of pollutant considered and the metric used.For example, Jhang, Multan, and Vehari were characterized as the top three polluted cities in Pakistan when considering AquaTerra DTB AOD products; for PM1, PM2.5, and PM10 Lahore, Gujranwala, and Okara were the top three; for tropospheric NO2 VCD Lahore, Rawalpindi, and Islamabad and for PBL SO2 VCD Lahore, Mirpur, and Gujranwala. The results demonstrate that Pakistan’s entire population has been exposed to high PM2.5 concentrations for many years, with a mean annual value of 54.7 mu g/m(3), over all Pakistan from 2003 to 2020.This value exceeds Pakistan’s National Environmental Quality Standards (Pak-NEQS, i.e., <15 mu g/m(3) annual mean) for ambient air defined by the Pakistan Environmental Protection Agency (Pak-EPA) as well as the WHO Interim Target-1 (i.e., mean annual PM2.5 < 35 mu g/m(3)).The spatial analyses of the concentrations of aerosols and trace gases in terms of population density, nighttime lights, land cover types, and fire location data, and the PSCF analysis indicate that Pakistan's air quality is strongly affected by anthropogenic sources inside of Pakistan, with contributions from surrounding countries.Statistically significant positive (increasing) trends in PM1, PM2. 5, PM10, tropospheric NO2 VCD, and SO2 VCD were observed in similar to 89%, similar to 67%, similar to 48%, 91%, and similar to 88% of the Pakistani cities (80 cities), respectively. This comprehensive analysis of aerosol and trace gas levels, their characteristics in spatio-temporal domains, and their trends over Pakistan, is the first of its kind. Results will be helpful to the Ministry of Climate Change (Government of Pakistan), Pak-EPA, SUPARCO (Pakistan Space and Upper Atmosphere Research Commission), policymakers, and the local research community to mitigate air pollution and its effects on human health.
The troubling trend of rising heat-associated mortalities in an urban desert region (Maricopa County, AZ, USA) has motivated us to explore the extent to which environmental factors may contribute to increased heat-health risks. Summertime data from 2010 to 2019 were used to construct a suite of models for daily heat-associated mortalities. The best-performing full model included the following predictors, ordered from strongest to weakest influence: daily average air temperature, average of previous 5 days daily average air temperature, year, day of year, average of previous 5 days daily average dew point temperature, average of previous 5 days daily average PM(2.5), and daily average PM(10). This full model exhibited a 5.39% reduction in mean absolute error in daily heat-associated mortalities as compared to the best-performing model that included only air temperature as an environmental predictor. The extent to which issued and modeled excessive heat warnings (from both the temperature only and full models) corresponded with heat-associated mortalities was also examined. Model hindcasts for 2020 and 2021 showed that the models were able to capture the high number of heat-associated mortalities in 2020, but greatly undercounted the highest yet observed number of heat-associated mortalities in 2021. Results from this study lend insights into environmental factors corresponding to an increased number of heat-associated mortalities and can be used for informing strategies towards reducing heat-health risks. However, as the best-performing model was unable to fully capture the observed number of heat-associated mortalities, continued scrutiny of both environmental and non-environmental factors affecting these observations is needed.
Concerns over regional climate change include its impact on air quality. A major contributor to unhealthy air quality is surface-based temperature inversions. Poor air quality is a serious public health concern that is often addressed by public health agencies. To assist with understanding the climatology and trend of temperature inversions for a large public health department, innovative pragmatic criteria were developed and used to determine morning and evening surface-based temperature inversions from datasets derived from Pittsburgh National Weather Service (NWS) radiosonde measurements made from 1 January 1991 through 31 December 2020. During this 30-year period, the strength of the morning (7 a.m. EST; 12 UTC) inversions was 3.9 °C on average. The depth of the inversion layer measured an average height of 246 m above the ground. The inversions tended to dissipate by 10 a.m. EST. The frequency of occurrence of morning inversions averaged 47%. The mean strength of the evening (7 p.m. EST; 00 UTC) inversions was 1.1 °C with a mean depth of 101 m above the ground. The frequency of evening inversion occurrence averaged 20% during this period. The 30-year climatology revealed generally declining frequency of inversions in the Pittsburgh area. Morning surface-based inversion strengths usually declined while morning depths and break times were steady. Evening inversion strengths and depths increased overall during the 30-year period. Monthly means showed a morning-evening overlap of some months that record the most frequent substantial inversions during the fall time of the year, coinciding with the time when the worst air pollution events occur.
The smart helmet is designed for a wildland firefighter to send vital data to their supervisor while they are working to extinguish an active fire. The smart helmet collects temperature, heart rate, and acceleration data from each firefighter via sensors inside and around the helmet. The data is used to alert the supervisor of potential health or emergency issues, such as heat-related illness, dehydration, potential falls or abnormal heart rates. A mobile app that the supervisor connects to their smart helmet device collects data in real time from the firefighters, without the need of any cellular coverage or WiFi.
The impacts of wildfires on the health of children are becoming a more urgent matter as wildfires become more frequent, intense and affecting, not only forested areas, but also urban locations. It is important that medical professionals be prepared to provide information to patients and families on how to minimize the adverse health effects on children of wildfire smoke and ash from wildfires. (C) 2021 Elsevier Inc. All rights reserved.
Bacteria in the air present patterns in space and time produced by different sources and environmental factors. Few studies have focused on the link between airborne pathogenic bacteria in densely populated cities, and the risk to the population’s health. Bacteria associated with particulate matter (PM) were monitored from the air of Mexico City (Mexico). We employed a metagenomic approach to characterise bacteria using the 16S rRNA gene. Airborne bacteria sampling was carried out in the north, centre, and south of Mexico City, with different urbanisation rates, during 2017. Bacteria added to the particles were sampled using high-volume PM10 samplers. To ascertain significant differences in bacterial diversity between zones and seasons, the Kruskal-Wallis, Wilcoxon tests were done on alpha diversity parameters. Sixty-three air samples were collected, and DNA was sequenced using next-generation sequencing. The results indicated that the bacterial phyla in the north and south of the city were Firmicutes, Cyanobacteria, Proteobacteria, and Actinobacteria, while in the central zone there were more Actinobacteria. There were no differences in the alpha diversity indices between the sampled areas. According to the OTUs, the richness of bacteria was higher in the central zone. Alpha diversity was higher in the rainy season than in the dry season; the Shannon index and the OTUs observed were higher in the central zone in the dry season. Pathogenic bacteria such as Kocuria, Paracoccus, and Micrococcus predominated in both seasonal times, while Staphylococcus, Corynebacterium, and Nocardioides were found during the rainy season, with a presence in the central zone. (C) Higher Education Press 2022
Understanding whether and how wildfires exacerbate COVID-19 outcomes is important for assessing the efficacy and design of public sector responses in an age of more frequent and simultaneous natural disasters and extreme events. Drawing on environmental and emergency management literatures, we investigate how wildfire smoke (PM(2.5)) impacted COVID-19 infections and deaths during California’s 2020 wildfire season and how public housing resources and hospital capacity moderated wildfires’ effects on COVID-19 outcomes. We also hypothesize and empirically assess the differential impact of wildfire smoke on COVID-19 infections and deaths in counties exhibiting high and low social vulnerability. To test our hypotheses concerning wildfire severity and its disproportionate impact on COVID-19 outcomes in socially vulnerable communities, we construct a county-by-day panel dataset for the period April 1 to November 30, 2020, in California, drawing on publicly available state and federal data sources. This study’s empirical results, based on panel fixed effects models, show that wildfire smoke is significantly associated with increases in COVID-19 infections and deaths. Moreover, wildfires exacerbated COVID-19 outcomes by depleting the already scarce hospital and public housing resources in local communities. Conversely, when wildfire smoke doubled, a one percent increase in the availability of hospital and public housing resources was associated with a 2 to 7 percent decline in COVID-19 infections and deaths. For California communities exhibiting high social vulnerability, the occurrence of wildfires worsened COVID-19 outcomes. Sensitivity analyses based on an alternative sample size and different measures of social vulnerability validate this study’s main findings. An implication of this study for policymakers is that communities exhibiting high social vulnerability will greatly benefit from local government policies that promote social equity in housing and healthcare before, during, and after disasters.
BACKGROUND: Increasing number of studies have linked air pollution exposure with renal function decline and disease. However, there is a lack of data on its impact among end-stage kidney disease (ESKD) patients and its potential modifying effect from extreme heat events (EHE). METHODS: Fresenius Kidney Care records from 28 selected northeastern US counties were used to pool daily all-cause mortality (ACM) and all-cause hospital admissions (ACHA) counts. County-level daily ambient PM(2.5) and ozone (O(3)) were estimated using a high-resolution spatiotemporal coupled climate-air quality model and matched to ESKD patients based on ZIP codes of treatment sites. We used time-stratified case-crossover analyses to characterize acute exposures using individual and cumulative lag exposures for up to 3 days (Lag 0-3) by using a distributed lag nonlinear model framework. We used a nested model comparison hypothesis test to evaluate for interaction effects between air pollutants and EHE and stratification analyses to estimate effect measures modified by EHE days. RESULTS: From 2001 to 2016, the sample population consisted of 43,338 ESKD patients. We recorded 5217 deaths and 78,433 hospital admissions. A 10-unit increase in PM(2.5) concentration was associated with a 5% increase in ACM (rate ratio [RR(Lag0)(-)(3)]: 1.05, 95% CI: 1.00-1.10) and same-day O(3) (RR(Lag0): 1.02, 95% CI: 1.01-1.03) after adjusting for extreme heat exposures. Mortality models suggest evidence of interaction and effect measure modification, though not always simultaneously. ACM risk increased up to 8% when daily ozone concentrations exceeded National Ambient Air Quality Standards established by the United States, but the increases in risk were considerably higher during EHE days across lag periods. CONCLUSION: Our findings suggest interdependent effects of EHE and air pollution among ESKD patients for all-cause mortality risks. National level assessments are needed to consider the ESKD population as a sensitive population and inform treatment protocols during extreme heat and degraded pollution episodes.
BACKGROUND/OBJECTIVE: Research suggests gestational exposure to particulate matter ≤2.5 μm (PM(2.5)) and extreme heat may independently increase risk of birth defects. We investigated whether duration of gestational extreme heat exposure modifies associations between PM(2.5) exposure and specific congenital heart defects (CHDs). We also explored nonlinear exposure-outcome relationships. METHODS: We identified CHD case children (n = 2824) and non-malformed live-birth control children (n = 4033) from pregnancies ending between 1999 and 2007 in the National Birth Defects Prevention Study, a U.S. population-based multicenter case-control study. We assigned mothers 6-week averages of PM(2.5) exposure during the cardiac critical period (postconceptional weeks 3-8) using the closest monitor within 50 km of maternal residence. We assigned a count of extreme heat days (EHDs, days above the 90th percentile of daily maximum temperature for year, season, and weather station) during this period using the closest weather station. Using generalized additive models, we explored logit-nonlinear exposure-outcome relationships, concluding logistic models were reasonable. We estimated joint effects of PM(2.5) and EHDs on six CHDs using logistic regression models adjusted for mean dewpoint and maternal age, education, and race/ethnicity. We assessed multiplicative and additive effect modification. RESULTS: Conditional on the highest observed EHD count (15) and at least one critical period day during spring/summer, each 5 μg/m(3) increase in average PM(2.5) exposure was significantly associated with perimembranous ventricular septal defects (VSDpm; OR: 1.54 [95% CI: 1.01, 2.41]). High EHD counts (8+) in the same population were positively, but non-significantly, associated with both overall septal defects and VSDpm. Null or inverse associations were observed for lower EHD counts. Multiplicative and additive effect modification estimates were consistently positive in all septal models. CONCLUSIONS: Results provide limited evidence that duration of extreme heat exposure modifies the PM(2.5)-septal defects relationship. Future research with enhanced exposure assessment and modeling techniques could clarify these relationships.
BACKGROUND: Individuals with respiratory conditions, such as asthma, are particularly susceptible to adverse health effects associated with higher levels of ambient air pollution and temperature. This study evaluates whether hourly levels of fine particulate matter (PM2.5) and dry bulb globe temperature (DBGT) are associated with the lung function of adult participants with asthma. METHODS AND FINDINGS: Global positioning system (GPS) location, respiratory function (measured as forced expiratory volume at 1 second (FEV1)), and self-reports of asthma medication usage and symptoms were collected as part of the Exposure, Location, and Lung Function (ELF) study. Hourly ambient PM2.5 and DBGT exposures were estimated by integrating air quality and temperature public records with time-activity patterns using GPS coordinates for each participant (n = 35). The relationships between acute PM2.5, DBGT, rescue bronchodilator use, and lung function collected in one week periods and over two seasons (summer/winter) were analyzed by multivariate regression, using different exposure time frames. In separate models, increasing levels in PM2.5, but not DBGT, were associated with rescue bronchodilator use. Conversely DBGT, but not PM2.5, had a significant association with FEV1. When DBGT and PM2.5 exposures were placed in the same model, the strongest association between cumulative PM2.5 exposures and the use of rescue bronchodilator was identified at the 0-24 hours (OR = 1.030; 95% CI = 1.012-1.049; p-value = 0.001) and 0-48 hours (OR = 1.030; 95% CI = 1.013-1.057; p-value = 0.001) prior to lung function measure. Conversely, DBGT exposure at 0 hours (β = 3.257; SE = 0.879; p-value>0.001) and 0-6 hours (β = 2.885; SE = 0.903; p-value = 0.001) hours before a reading were associated with FEV1. No significant interactions between DBGT and PM2.5 were observed for rescue bronchodilator use or FEV1. CONCLUSIONS: Short-term increases in PM2.5 were associated with increased rescue bronchodilator use, while DBGT was associated with higher lung function (i.e. FEV1). Further studies are needed to continue to elucidate the mechanisms of acute exposure to PM2.5 and DBGT on lung function in asthmatics.
Air pollution risk assessments typically estimate ozone-attributable mortality counts using concentration-response (C-R) parameters from epidemiologic studies that treat temperature as a potential confounder. However, some recent epidemiologic studies have indicated that temperature can modify the relationship between short-term ozone exposure and mortality, which has potentially important implications when considering the impacts of climate change on public health. This proof-of-concept analysis quantifies counts of temperature-modified ozone-attributable mortality using temperature-stratified C-R parameters from a multicity study in which the pooled ozone-mortality effect coefficients change in concert with daily temperature. Meteorology downscaled from two global climate models is used with a photochemical transport model to simulate ozone concentrations over the 21st century using two emission inventories: one holding air pollutant emissions constant at 2011 levels and another accounting for reduced emissions through the year 2040. The late century climate models project increased summer season temperatures, which in turn yields larger total counts of ozone-attributable deaths in analyses using temperature-stratified C-R parameters compared to the traditional temperature confounder approach. This analysis reveals substantial heterogeneity in the magnitude and distribution of the temperature-stratified ozone-attributable mortality results, which is a function of regional variability in both the C-R relationship and the model-predicted temperature and ozone.
The combined effects of heat events and poor air quality conditions can severely affect population health. A novel correlational method was developed to assess the impact of the short-term variations of environmental variables (air pollutants and ambient conditions) on community health responses (mortalities and emergency department visits). A multi-dimensional clustering approach was proposed by combining hierarchical and k-means clustering to promote flexibility and robustness to improve the correlation procedure. The study focused on the health records of the elderly population and people diagnosed with cardiorespiratory causes. The study investigated multiple health records on different levels of investigation: total, elderly, cause-based, and elderly cause-based records. The developed method was validated by investigating the short-term impact of ambient air temperature, relative humidity, ground-level ozone, and fine particulate matter on the health records during hot and warm seasons in the municipalities of Mississauga and Brampton, Peel Region, Ontario, Canada for 15 years. The analysis confirmed the association between moderate levels of environmental variables and increased short-term daily total deaths and emergency department visits, while the elderly sector showed higher vulnerability to environmental changes. Furthermore, the association with extreme heat conditions and poor air quality levels was affirmed with cause-based mortalities and emergency visits; the correlation was strongest with elderly cause-based health records. Findings confirm that cardiorespiratory patients, especially elderly people, were at the greatest risk of poor environmental conditions.
OBJECTIVES: We aimed to characterize polycyclic aromatic hydrocarbons (PAHs) in the breathing zone and on the skin of wildland firefighters and to assess their contribution to urinary 1-hydroxypyrene (1-HP) over repeated firefighting rotations. We asked if improved skin hygiene or discretionary use of an N95 mask would reduce absorption. METHODS: In collaboration with wildfire services of two Canadian provinces, Alberta and British Columbia (BC), we recruited wildland firefighters from crews willing to be followed up over successive rotations and to be randomly assigned to normal practice, enhanced skin hygiene (ESH), or ESH plus discretionary use of an N95 mask. We collected spot urine samples at the beginning and end of up to four rotations/firefighter. On designated fire days, as close as possible to the end of rotation, we collected skin wipes from the hands, throat, and chest at the beginning and end of the fire day and, in BC, start of fire-day urine samples. Volunteers carried air monitoring pumps. Participants completed questionnaires at the beginning and end of rotations. Exposure since the start of the fire season was estimated from fire service records. Urinary 1-HP was analyzed by LC-MS-MS. Analysis of 21 PAHs on skin wipes and 27 PAHs from air sampling was done by GC-MS-MS. Statistical analysis used a linear mixed effects model. RESULTS: Firefighters in Alberta were recruited from five helitack crews and two unit crews, and in BC from two unit crews with 80 firefighters providing data overall. The fire season in BC was very active with five monitored fire days. In Alberta, with more crews, there were only seven fire days. Overall, log 1-HP/creatinine (ng/g) increased significantly from the start (N = 145) to end of rotation (N = 136). Only three PAHs (naphthalene, phenanthrene, and pyrene) were found on >20% of skin wipes. PAHs from 40 air monitoring pumps included 10 PAHs detected on cassette filters (particles) and 5 on sorbent tubes (vapor phase). A principal component extracted from air monitoring data represented respiratory exposure and total PAH from skin wipes summarized skin exposure. Both routes contributed to the end of rotation urinary 1-HP. The ESH intervention was not demonstrated to effect absorption. Allocation of an N95 mask was associated with lower 1-HP when modeling respiratory exposure (β = -0.62, 95% CI -1.15 to -0.10: P = 0.021). End of rotation 1-HP was related to 1-HP at the start of the next rotation (β = 0.25, 95% CI 0.12 to 0.39: P < 0.001). CONCLUSIONS: Exposures to PAHs during firefighting were significant, with samples exceeding the American Conference of Governmental Industrial Hygienists Biological Exposure Index for 1-HP suggesting a need for control of exposure. PAH exposure accumulated during the rotation and was not fully eliminated during the break between rotations. Both respiratory and skin exposures contributed to 1-HP. While improved skin hygiene may potentially reduce dermal absorption, that was not demonstrated here. In contrast, those allocated to discretionary use of an N95 mask had reduced 1-HP excretion. Wildland firefighters in North America do not use respiratory protection, but the results of this study support more effective interventions to reduce respiratory exposure.
Wildfires can significantly impact air quality and human health. However, little is known about how different fuel bed components contribute to these impacts. This study investigates the air quality impacts of duff and peat consumption during wildfires in the southeastern United States, with a focus on the differing contributions of fine particulate matter less than 2.5 mu m in size (PM2.5) and ozone (O-3) to air quality episodes associated with the four largest wildfire events in the region during this century. The emissions of duff burning were estimated based on a field measurement of a 2016 southern Appalachian fire. The emissions from the burning of other fuels were obtained from the Fire INventory from NCAR (FINN). The air quality impacts were simulated using a three-dimensional regional air quality model. The results show the duff burning emitted PM2.5 comparable to the burning of the above-ground fuels. The simulated surface PM2.5 concentrations due to duff burning increased by 61.3% locally over a region approximately 300 km within the fire site and by 21.3% and 29.7% in remote metro Atlanta and Charlotte during the 2016 southern Appalachian fires and by 131.9% locally and by 17.7% and 24.8% in remote metro Orlando and Miami during the 2007 Okefenokee Fire. However, the simulated ozone impacts from the duff burning were negligible due to the small duff emission factors of ozone precursors such as NOx. This study suggests the need to improve the modeling of PM2.5 and the air quality, human health, and climate impacts of wildfires in moist ecosystems by including duff burning in global fire emission inventories.
Climate change-related disasters have drawn increased attention to the impact of air pollution on health. 122 children ages 9-11 years old, M(SD) = 9.91(.56), participated. Levels of particulate matter (PM2.5) near participants’ homes were obtained from the Environmental Protection Agency. Cytokines were assayed from 100 child serum samples: IL-6, IL-8, IL-10, and TNFα. Autonomic physiology was indexed by pre-ejection period (PEP), respiratory sinus arrhythmia (RSA), cardiac autonomic regulation (CAR), and cardiac autonomic balance (CAB). IL-6 was positively related to daily PM2.5 (r = .26, p = .009). IL-8 was negatively associated with monthly PM2.5 (r = -.23, p = .02). PEP was positively related to daily (r = .29, p = .001) and monthly PM2.5 (r = .18, p = .044). CAR was negatively associated with daily PM2.5 (r = -.29, p = .001). IL-10, TNFα, RSA, and CAB were not associated with PM2.5. Air pollution may increase risk of inflammation in children.
Major wildfires and heatwaves have begun to increase in frequency throughout much of the United States, particularly in western states such as California, causing increased risk to public health. Air pollution is exacerbated by both wildfires and warmer temperatures, thus adding to such risk. With climate change and the continued increase in global average temperatures, the frequency of major wildfires, heat days, and unhealthy air pollution episodes is projected to increase, resulting in the potential for compounding risks. Risks will likely vary by region and may disproportionately impact low-income communities and communities of color. In this study, we processed daily particulate matter (PM) data from over 18,000 low-cost PurpleAir sensors, along with gridMET daily maximum temperature data and government-compiled wildfire perimeter data from 2018-2020 in order to examine the occurrence of compound risk (CR) days (characterized by high temperature and high PM2.5) at the census tract level in California, and to understand how such days have been impacted by the occurrence of wildfires. Using American Community Survey data, we also examined the extent to which CR days were correlated with household income, race/ethnicity, education, and other socioeconomic factors at the census tract level. Results showed census tracts with a higher frequency of CR days to have statistically higher rates of poverty and unemployment, along with high proportions of child residents and households without computers. The frequency of CR days and elevated daily PM2.5 concentrations appeared to be strongly related to the occurrence of nearby wildfires, with over 20% of days with sensor-measured average PM2.5 > 35 mu g/m(3) showing a wildfire within a 100 km radius and over two-thirds of estimated CR days falling on such days with a nearby wildfire. Findings from this study are important to policymakers and government agencies who preside over the allocation of state resources as well as organizations seeking to empower residents and establish climate resilient communities.
Indoor flooding is a leading contributor to indoor dampness and the associated mold infestations in the coastal United States. Whether the prevalent mold genera that infest the coastal flood-prone buildings are different from those not flood-prone is unknown. In the current case study of 28 mold-infested buildings across the U.S. east coast, we surprisingly noted a trend of higher prevalence of indoor Aspergillus and Penicillium genera (denoted here as Asp-Pen) in buildings with previous flooding history. Hence, we sought to determine the possibility of a potential statistically significant association between indoor Asp-Pen prevalence and three building-related variables: (i) indoor flooding history, (ii) geographical location, and (iii) the building’s use (residential versus non-residential). Culturable spores and hyphal fragments in indoor air were collected using the settle-plate method, and corresponding genera were confirmed using phylogenetic analysis of their ITS sequence (the fungal barcode). Analysis of variance (ANOVA) using Generalized linear model procedure (GLM) showed that Asp-Pen prevalence is significantly associated with indoor flooding as well as coastal proximity. To address the small sample size, a multivariate decision tree analysis was conducted, which ranked indoor flooding history as the strongest determinant of Asp-Pen prevalence, followed by geographical location and the building’s use.
Fire Influence on Regional to Global Environments and Air Quality was a NOAA/NASA collaborative campaign conducted during the summer of 2019. The objectives included identifying and quantifying wildfire composition, smoke evolution, and climate and health impacts of wildfires and agricultural fires in the United States. Ground based mobile sampling via sorbent tubes occurred at the Nethker and Williams Flats fires (2019) and Chief Timothy and Whitetail Loop fires (2020) in Idaho and Washington. Air samples were analyzed through thermal desorption-gas chromatography-mass spectrometry for a variety of volatile organic compounds to elucidate both composition and health impacts. Benzene, toluene, ethylbenzene, xylenes, butenes, phenol, isoprene and pinenes were observed in the wildfire smoke, with benzene ranging from 0.04 to 25 ppbv. Health risk was assessed for each fire by determining sub-chronic (wildfire event) and projected chronic inhalation risk exposure from benzene, a carcinogen, as well as other non-carcinogenic compounds including toluene, ethylbenzene, xylenes, and hexane. The cancer risk of benzene from sub-chronic exposure was 1 extra cancer per million people and ranged from 1 to 19 extra cancers per million people for the projected chronic scenarios, compared to a background level of 1 extra cancer per million people. The hazard index of non-carcinogenic compounds was less than one for all scenarios and wildfires sampled, which was considered low risk for non-cancer health events.
Exposure to wildfire smoke increases the risk of respiratory and cardiovascular hospital admissions. Health impact assessments, used to inform decision-making processes, characterize the health impacts of environmental exposures by combining preexisting epidemiological concentration-response functions (CRFs) with estimates of exposure. These two key inputs influence the magnitude and uncertainty of the health impacts estimated, but for wildfire-related impact assessments the extent of their impact is largely unknown. We first estimated the number of respiratory, cardiovascular, and asthma hospital admissions attributable to fire-originated PM2.5 exposure in central California during the October 2017 wildfires, using Monte Carlo simulations to quantify uncertainty with respect to the exposure and epidemiological inputs. We next conducted sensitivity analyses, comparing four estimates of fire-originated PM2.5 and two CRFs, wildfire and nonwildfire specific, to understand their impact on the estimation of excess admissions and sources of uncertainty. We estimate the fires accounted for an excess 240 (95% CI: 114, 404) respiratory, 68 (95% CI: -10, 159) cardiovascular, and 45 (95% CI: 18, 81) asthma hospital admissions, with 56% of admissions occurring in the Bay Area. Although differences between impact assessment methods are not statistically significant, the admissions estimates’ magnitude is particularly sensitive to the CRF specified while the uncertainty is most sensitive to estimates of fire-originated PM2.5. Not accounting for the exposure surface’s uncertainty leads to an underestimation of the uncertainty of the health impacts estimated. Employing context-specific CRFs and using accurate exposure estimates that combine multiple data sets generates more certain estimates of the acute health impacts of wildfires.
Wildfire smoke is one of the most significant concerns of human and environmental health, associated with its substantial impacts on air quality, weather, and climate. However, biomass burning emissions and smoke remain among the largest sources of uncertainties in air quality forecasts. In this study, we evaluate the smoke emissions and plume forecasts from 12 state-of-the-art air quality forecasting systems during the Williams Flats fire in Washington State, US, August 2019, which was intensively observed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Model forecasts with lead times within 1 d are intercompared under the same framework based on observations from multiple platforms to reveal their performance regarding fire emissions, aerosol optical depth (AOD), surface PM2.5, plume injection, and surface PM2.5 to AOD ratio. The comparison of smoke organic carbon (OC) emissions suggests a large range of daily totals among the models, with a factor of 20 to 50. Limited representations of the diurnal patterns and day-to-day variations of emissions highlight the need to incorporate new methodologies to predict the temporal evolution and reduce uncertainty of smoke emission estimates. The evaluation of smoke AOD (sAOD) forecasts suggests overall underpredictions in both the magnitude and smoke plume area for nearly all models, although the high-resolution models have a better representation of the fine-scale structures of smoke plumes. The models driven by fire radiative power (FRP)-based fire emissions or assimilating satellite AOD data generally outperform the others. Additionally, limitations of the persistence assumption used when predicting smoke emissions are revealed by substantial underpredictions of sAOD on 8 August 2019, mainly over the transported smoke plumes, owing to the underestimated emissions on 7 August. In contrast, the surface smoke PM2.5 (sPM(2.5)) forecasts show both positive and negative overall biases for these models, with most members presenting more considerable diurnal variations of sPM(2.5). Overpredictions of sPM(2.5) are found for the models driven by FRP-based emissions during nighttime, suggesting the necessity to improve vertical emission allocation within and above the planetary boundary layer (PBL). Smoke injection heights are further evaluated using the NASA Langley Research Center’s Differential Absorption High Spectral Resolution Lidar (DIAL-HSRL) data collected during the flight observations. As the fire became stronger over 38 August, the plume height became deeper, with a day-today range of about 2-9 km a.g.l. However, narrower ranges are found for all models, with a tendency of overpredicting the plume heights for the shallower injection transects and underpredicting for the days showing deeper injections. The misrepresented plume injection heights lead to inaccurate vertical plume allocations along the transects corresponding to transported smoke that is 1 d old. Discrepancies in model performance for surface PM2.5 and AOD are further suggested by the evaluation of their ratio, which cannot be compensated for by solely adjusting the smoke emissions but are more attributable to model representations of plume injections, besides other possible factors including the evolution of PBL depths and aerosol optical property assumptions. By consolidating multiple forecast systems, these results provide strategic insight on pathways to improve smoke forecasts.
Background: Recent increases in wildfire frequency and severity necessitate better understanding of health effects of wildfire smoke to protect affected populations. Objectives: We examined relationships between fine particulate matter (PM2.5) and morbidity during wildfires in California, and whether those relationships differed during the fire compared to a similar non-fire period. Methods: For nine San Francisco Bay Area counties, daily county- level diagnosis-specific counts of emergency department visits (EDVs) and hospitalizations were linked with county-level estimates of daily mean PM2.5 during the October 2017 Northern California wildfires and similar October days in 2015, 2016, and 2017. Associations were estimated using Poisson regression. Results: The median difference between county PM2.5 during the fire versus the non-fire period was 23.4 mu g/ m3, with days exceeding 80 mu g/m3 in some counties. Over the entire study period, PM2.5 was most consistently linked to EDVs for respiratory disease ( RREDV(lag0) per 23.4 mu g/ m3 increase: 1.25, 95% CI: 1.21, 1.30), asthma, chronic lower respiratory disease (CLRD; RREDV(lag0): 1.18, 95% CI: 1.10, 1.27), and acute myocardial infarction (RREDV(lag0): 1.14, 95% CI: 1.03, 1.25). Increases in acute upper respiratory infections and decreases in mental/behavioral EDVs were observed but were sensitive to model specification, specifically the inclusion of time-related covariates. Comparing fire and non-fire period EDV associations, we observed indications that PM2.5 during the fire was more strongly associated with asthma (RRlag0: 1.46, 95% CI: 1.38, 1.55) compared to non-fire period PM2.5 (RRlag0: 0.77, 95% CI: 0.55, 1.08), and the opposite observed for dysrhythmia, with the asthma difference being particularly robust to model choice. For hospitalizations, the most robust PM2.5 relationships were positive associations with respiratory, CLRD, and diabetes, and inverse associations with pneumonia. Respiratory and CLRD effect estimates were generally similar or smaller than for EDVs. Conclusions: Elevated short-term PM2.5 levels from wildfire smoke appears to impact respiratory and other health domains. (c) 2021 Elsevier B.V. All rights reserved.
BACKGROUND AND OBJECTIVES: Exposure to airborne fine particles with diameters <= 2.5 mu m (PM2.5) pollution is a well-established cause of respiratory diseases in children; whether wildfire-specific PM2.5 causes more damage, however, remains uncertain. We examine the associations between wildfire-specific PM2.5 and pediatric respiratory health during the period 2011-2017 in San Diego County, California, and compare these results with other sources of PM2.5. METHODS: Visits to emergency and urgent care facilities of Rady's Children Hospital network in San Diego County, California, by individuals (aged <= 19 years) with >= 1 of the following respiratory conditions: difficulty breathing, respiratory distress, wheezing, asthma, or cough were regressed on daily, community-level exposure to wildfire-specific PM2.5 and PM2.5 from ambient sources (eg, traffic emissions). RESULTS: A 10-unit increase in PM2.5 (from nonsmoke sources) was estimated to increase the number of admissions by 3.7% (95% confidence interval: 1.2% to 6.1%). In contrast, the effect of PM2.5 attributable to wildfire was estimated to be a 30.0% (95% confidence interval: 26.6% to 33.4%) increase in visits. CONCLUSIONS: Wildfire-specific PM2.5 was found to be similar to 10 times more harmful on children’s respiratory health than PM2.5 from other sources, particularly for children aged 0 to 5 years. Even relatively modest wildfires and associated PM2.5 resolved on our record produced major health impacts, particularly for younger children, in comparison with ambient PM2.5.
Major wildfires starting in the summer of 2020 along the west coast of the United States made PM2.5 concentrations in this region rank among the highest in the world. Washington was impacted both by active wildfires in the state and aged wood smoke transported from fires in Oregon and California. This study aims to estimate the magnitude and disproportionate spatial impacts of increased PM2.5 concentrations attributable to these wildfires on population health. Daily PM2.5 concentrations for each county before and during the 2020 Washington wildfire episode (September 7-19) were obtained from regulatory air monitors. Utilizing previously established concentration-response function (CRF) of PM2.5 (CRF of total PM2.5) and odds ratio (OR) of wildfire smoke days (OR of wildfire smoke days) for mortality, we estimated excess mortality attributable to the increased PM2.5 concentrations in Washington. On average, daily PM2.5 concentrations increased 97.1 mu g/m(3) during the wildfire smoke episode. With CRF of total PM2.5, the 13-day exposure to wildfire smoke was estimated to lead to 92.2 (95% CI: 0.0, 178.7) more all-cause mortality cases; with OR of wildfire smoke days, 38.4 (95% CI: 0.0, 93.3) increased all-cause mortality cases and 15.1 (95% CI: 0.0, 27.9) increased respiratory mortality cases were attributable to the wildfire smoke episode. The potential impact of avoiding elevated PM2.5 exposures during wildfire events significantly reduced the mortality burden. Because wildfire smoke episodes are likely to impact the Pacific Northwest in future years, continued preparedness and mitigations to reduce exposures to wildfire smoke are necessary to avoid excess health burden.
Increases in wildfire activity across the Western US pose a significant public health threat. While there is evidence that wildfire smoke is detrimental for respiratory health, the impacts on cardiovascular health remain unclear. This study evaluates the association between fine particulate matter (PM(2.5)) from wildfire smoke and unscheduled cardiorespiratory hospital visits in California during the 2004-2009 wildfire seasons. We estimate daily mean wildfire-specific PM(2.5) with Goddard Earth Observing System-Chem, a global three-dimensional model of atmospheric chemistry, with wildfire emissions estimates from the Global Fire Emissions Database. We defined a “smoke event day” as cumulative 0-1-day lag wildfire-specific PM(2.5) ≥ 98th percentile of cumulative 0-1 lag day wildfire PM(2.5). Associations between exposure and outcomes are estimated using negative binomial regression. Results indicate that smoke event days are associated with a 3.3% (95% CI: [0.4%, 6.3%]) increase in visits for all respiratory diseases and a 10.3% (95% CI: [2.3%, 19.0%]) increase for asthma specifically. Stratifying by age, we found the largest effect for asthma among children ages 0-5 years. We observed no significant association between exposure and overall cardiovascular disease, but stratified analyses revealed increases in visits for all cardiovascular, ischemic heart disease, and heart failure among non-Hispanic white individuals and those older than 65 years. Further, we found a significant interaction between smoke event days and daily average temperature for all cardiovascular disease visits, suggesting that days with high wildfire PM(2.5) concentrations and high temperatures may pose greater risk for cardiovascular disease. These results suggest substantial increases in adverse outcomes from wildfire smoke exposure and indicate the need for improved prevention strategies and adaptations to protect vulnerable populations.
This study proposes an approach to improve the spatial resolution of ground-level concentrations of PM2.5 that is required to assess health risks associated with exposure to pollutants released during wildfires. We use this approach to analyze the impact on air quality of the wildfire complex consisting of the Atlas, Nuns, Tubbs, Pocket, and Redwood Valley fires in northern California that started on October 8, 2017 and the Camp Fire in northern California that was first reported on November 8, 2018. The PM2.5 concentrations measured in populated areas downwind of these fires were well above the 24-h standard of 35 mu g/m3 during several days of both fires. To estimate health risks at locations where ground-based monitors did not provide sufficient spatial coverage we first estimate the emissions from the fires by fitting concentration estimates from two models, a Lagrangian model and a segmented plume dispersion model, to corresponding concentrations from ground monitors. We also use a power law model to fit the measured PM2.5 concentrations to the ratio of aerosol optical depth (AOD) to planetary boundary layer measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried by NASA’s Terra and Aqua satellites. Dispersion model estimates are then combined with estimates from the AOD model to compute ground-level concentrations at a resolution of 1 km. Kriged residuals between estimates from the combined model and measured PM2.5 concentrations are then added to obtain high resolution maps that can be used for exposure studies.
Background: Wildfire smoke is responsible for around 20% of all particulate emissions in the U.S. and affects millions of people worldwide. Children are especially vulnerable, as ambient air pollution exposure during early childhood is associated with reduced lung function. Most studies, however, have focused on the short-term impacts of wildfire smoke exposures. We aimed to identify long-term baseline epigenetic changes associated with early-life exposure to wildfire smoke. We collected nasal epithelium samples for whole genome bisulfite sequencing (WGBS) from two groups of adult female rhesus macaques: one group born just before the 2008 California wildfire season and exposed to wildfire smoke during early-life (n = 8), and the other group born in 2009 with no wildfire smoke exposure during early-life (n = 14). RNA-sequencing was also performed on a subset of these samples. Results: We identified 3370 differentially methylated regions (DMRs) (difference in methylation ≥5%, empirical p < 0.05) and 1 differentially expressed gene (FLOT2) (FDR < 0.05, fold of change ≥ 1.2). The DMRs were annotated to genes significantly enriched for synaptogenesis signaling, protein kinase A signaling, and a variety of immune processes, and some DMRs significantly correlated with gene expression differences. DMRs were also significantly enriched within regions of bivalent chromatin (top odds ratio = 1.46, q-value < 3 x 10^(-6)) that often silence key developmental genes while keeping them poised for activation in pluripotent cells. Conclusions: These data suggest that early-life exposure to wildfire smoke leads to long-term changes in the methylome over genes impacting the nervous and immune systems. Follow-up studies will be required to test whether these changes influence transcription following an immune/respiratory challenge.
Objective: The California Emergency Medical Services Authority manages and deploys California Medical Assistance Teams (CAL-MAT) to disaster medical incidents in the state. This analysis reviews diagnoses for ambulatory medical visits at multiple wildland fire incident base camp field sites in California during the 2020 fire season. Methods: Clinical data without personal health information were extracted retrospectively from patient care records from all patients seen by a provider. Results were entered into Excel spreadsheets with calculation of summary statistics. Results: During the 2020 fire season, CAL-MAT teams deployed 21 times for a total of 327 days to base camps supporting large fire incidents and cared for 1756 patients. Impacts of heat and environmental smoke are a constant factor near wildfires; however, our most common medical problem was rhus dermatitis (54.5%) due to poison oak. All 2020 medical missions were further complicated by prevention and management of coronavirus disease (COVID-19). Conclusions: There is very little literature regarding the acute medical needs facing responders fighting wildland fires. Ninety-five percent of clinical conditions presenting to a field medical team at the wildfire incident base camp during a severe fire season in California can be managed by small teams operating in field tents.
Driven by climate change, wildfires are increasing in frequency, duration, and intensity across the Western United States. Outdoor workers are being exposed to increasing wildfire-related particulate matter and smoke. Recognizing this emerging risk, Washington adopted an emergency rule and is presently engaged in creating a permanent rule to protect outdoor workers from wildfire smoke exposure. While there are growing bodies of literature on the exposure to and health effects of wildfire smoke in the general public and wildland firefighters, there is a gap in knowledge about wildfire smoke exposure among outdoor workers generally and construction workers specifically-a large category of outdoor workers in Washington totaling 200,000 people. Several data sources were linked in this study-including state-collected employment data and national ambient air quality data-to gain insight into the risk of PM2.5 exposure among construction workers and evaluate the impacts of different air quality thresholds that would have triggered a new Washington emergency wildfire smoke rule aimed at protecting workers from high PM2.5 exposure. Results indicate the number of poor air quality days has increased in August and September in recent years. Over the last decade, these months with the greatest potential for particulate matter exposure coincided with an annual peak in construction employment that was typically 9.4-42.7% larger across Washington counties (one county was 75.8%). Lastly, the ‘encouraged’ threshold of the Washington emergency rule (20.5 mu g m(-3)) would have resulted in 5.5 times more days subject to the wildfire rule on average across all Washington counties compared to its ‘required’ threshold (55.5 mu g m(-3)), and in 2020, the rule could have created demand for 1.35 million N-95 filtering facepiece respirators among construction workers. These results have important implications for both employers and policy makers as rules are developed. The potential policy implications of wildfire smoke exposure, exposure control strategies, and data gaps that would improve understanding of construction worker exposure to wildfire smoke are also discussed.
Frequent and widespread wildfires in the northwestern United States and Canada have become the “new normal” during the Northern Hemisphere summer months, which significantly degrades particulate matter air quality in the United States. Using the mid-visible Multi Angle Implementation of Atmospheric Correction (MAIAC) satellitederived aerosol optical depth (AOD) with meteorological information from the European Centre for Medium-Range Weather Forecasts (ECMWF) and other ancillary data, we quantify the impact of these fires on fine particulate matter concentration (PM2.5) air quality in the United States. We use a geographically weighted regression (GWR) method to estimate surface PM2.5 in the United States between low (2011) and high (2018) fire activity years. Our results indicate an overall leave-one-out cross-validation (LOOCV) R-2 value of 0.797 with root mean square error (RMSE) between 3 and 5 mu gm(-3). Our results indicate that smoke aerosols caused significant pollution changes over half of the United States. We estimate that nearly 29 states have increased PM2.5 during the fire-active year and that 15 of these states have PM2.5 concentrations more than 2 times that of the inactive year. Furthermore, these fires increased the daily mean surface PM2.5 concentrations in Washington and Oregon by 38 to 259 mu gm(-3), posing significant health risks especially to vulnerable populations. Our results also show that the GWR model can be successfully applied to PM2.5 estimations from wildfires, thereby providing useful information for various applications such as public health assessment.
Introduction: Wildfire smoke (WFS) exposure is a growing threat to human health, and lower socioeconomic position (SEP) has been shown to increase pollution susceptibility. Studies of SEP-related susceptibility, however, are often compromised due to spatial confounding between lower-SEP and pollution. Here we examine outdoorhoused nonhuman primates, living in natural social hierarchy in a common location, born during years of high vs. low WFS, to examine the separate and combined effects of WFS and social rank, an analog to SEP, on lung and immune function. Methods: Twenty-one females were born during extreme WFS events in summer 2008; 22 were born in summer 2009, during low WFS. Pulmonary function and circulating cytokines were measured three years later, in adolescence. We estimated fine particulate (PM2.5) and ozone exposures during each animal’s first 90 days and three years of age using regulatory data. Early-life social status was estimated using maternal rank at birth, as rank in females is relatively stable throughout life, and closely approximates mother’s rank. We tested associations among WFS exposure, rank, and endpoints using linear regression and ANOVA. Results: Higher WFS exposure in infancy was, on average, associated with lower functional residual capacity (FRC), residual volume (RV), tissue compliance (Ct), and IL-8 secretion in adolescence. Higher social rank conferred significantly higher expiratory reserve volume (ERV) and functional residual capacity (FRC) solely among those born in the high-WFS year (2008). Differences in effects of rank between years were not significant after adjustment for multiple comparisons. Conclusions: Exposure to WFS in infancy generally conferred lower adolescent respiratory volumes and inflammatory cytokines. Higher rank conferred higher respiratory volumes only among females born during WFS, suggesting the possibility that the health benefits of rank may be more apparent under environmental challenge.
BACKGROUND: Global climate change has led to an increase in the prevalence and severity of wildfires. Pollutants released into air, soil and groundwater from wildfires may impact embryo development leading to gastroschisis. OBJECTIVE: The objective of this study was to determine the association between wildfire exposure before and during pregnancy and the risk of foetal gastroschisis development. METHODS: This was a retrospective cohort study using The California Office of Statewide Health Planning and Development Linked Birth File linked to The California Department of Forestry and Fire Protection data between 2007 and 2010. Pregnancies complicated by foetal gastroschisis were identified by neonatal hospital discharge ICD-9 code. Pregnancies were considered exposed to wildfire if the mother’s primary residence zip code was within 15 miles to the closest edge of a wildfire. The exposure was further stratified by trimester or if exposed within 30 days prior to pregnancy. Multivariable log-binomial regression analyses were performed to estimate the association between wildfire exposure in each pregnancy epoch and foetal gastroschisis. RESULTS: Between 2007 and 2010, 844,348 (40%) births were exposed to wildfire in California. Compared with births without wildfire exposure, those with first-trimester exposure were associated with higher rates of gastroschisis, 7.8 vs. 5.7 per 10,000 births (adjusted relative risk [aRR] 1.28, 95% confidence interval [CI] 1.07, 1.54). Furthermore, those with prepregnancy wildfire exposure were also found to have higher rates of gastroschisis, 12.5 vs. 5.7 per 10,000 births, (aRR 2.17, 95% CI 1.42, 3.52). In contrast, second- and third-trimester wildfire exposures were not associated with foetal gastroschisis. CONCLUSIONS: Wildfire exposure within 30 days before pregnancy was associated with more than two times higher risk of foetal gastroschisis, whereas a 28% higher risk was demonstrated if exposure was in the first trimester.
The increased risk of wildfires and associated smoke exposure in the United States is a growing public health problem, particularly along the Wildland-Urban Interface (WUI). Using the measure of fire danger, the Energy Release Component, we define fire danger as the onset and duration of fire season, in the continental US, between 1979 and 2016. We then combine the measure of fire danger with census data to quantify changes in population fire exposure across the WUI. We determined that the largest increases in fire danger were observed in the Southwest, Intermountain, and Pacific Southwest regions. The increased fire danger, specifically during peak fire season, accounted for 6.1 more fires each year and 78,000 more acres burned each year, underscoring the link between fire danger and the risks of large fire occurrence and burn acreage. Finally, we observed significant population growth (121.2% between 1990 and 2010) within high-danger WUI areas, further implying significant increases in potential fire exposure.
Alaskan wildfires have major ecological, social, and economic consequences, but associated health impacts remain unexplored. We estimated cardiorespiratory morbidity associated with wildfire smoke (WFS) fine particulate matter with a diameter less than 2.5 μm (PM(2.5)) in three major population centers (Anchorage, Fairbanks, and the Matanuska-Susitna Valley) during the 2015-2019 wildfire seasons. To estimate WFS PM(2.5), we utilized data from ground-based monitors and satellite-based smoke plume estimates. We implemented time-stratified case-crossover analyses with single and distributed lag models to estimate the effect of WFS PM(2.5) on cardiorespiratory emergency department (ED) visits. On the day of exposure to WFS PM(2.5), there was an increased odds of asthma-related ED visits among 15-65 year olds (OR = 1.12, 95% CI = 1.08, 1.16), people >65 years (OR = 1.15, 95% CI = 1.01, 1.31), among Alaska Native people (OR = 1.16, 95% CI = 1.09, 1.23), and in Anchorage (OR = 1.10, 95% CI = 1.05, 1.15) and Fairbanks (OR = 1.12, 95% CI = 1.07, 1.17). There was an increased risk of heart failure related ED visits for Alaska Native people (Lag Day 5 OR = 1.13, 95% CI = 1.02, 1.25). We found evidence that rural populations may delay seeking care. As the frequency and magnitude of Alaskan wildfires continue to increase due to climate change, understanding the health impacts will be imperative. A nuanced understanding of the effects of WFS on specific demographic and geographic groups facilitates data-driven public health interventions and fire management protocols that address these adverse health effects.
Context: Wildfire events are increasing in prevalence and intensity in the Pacific Northwest. Effective communication of health risks and actions to reduce exposure to wildfire smoke is imperative. Objective: We assessed the content of wildfire smoke risk messages from government organizations and mainstream media during a major wildfire smoke event in August 2018. Design: We conducted a content analysis of wildfire smoke risk information communicated by local and state government organizations and the mainstream media. Setting: Eight Washington State counties during a statewide wildfire smoke event in August 2018. Main Outcome Measure: Leveraging the Extended Parallel Process Model and information in the existing literature on wildfire smoke and health, we assessed messages for the presence of information regarding health risk, personal interventions, administrative interventions, vulnerable populations, and trusted sources of information. Summary statistics were calculated to identify common messages about recommended interventions, vulnerable populations cited, and trusted sources of public health information. Results: Of the 273 identified government and media messages on wildfire smoke, the majority (71% and 66%) contained information about health risks. However, only 46% and 33% of government and media messages contained information about personal interventions to reduce risk, and 37% and 14% of government and media messages contained information about administrative interventions to reduce risk. Less than half of government and media messages (28% and 31%) contained information specific to vulnerable populations, and 58% and 46% of government and media messages contained any reference to a trusted source of information. Conclusions: While information about wildfire smoke and health risks was communicated during Washington’s August 2018 wildfire smoke event, there remains considerable opportunity to include additional information about interventions, vulnerable populations, and trusted sources of information. We recommend several opportunities to improve and evaluate risk communication and risk reduction before, during, and after future wildfire smoke events.
Background: The modular British Columbia Asthma Prediction System (BCAPS) is designed to reduce information burden during wildfire smoke events by automatically gathering, integrating, generating, and visualizing data for public health users. The BCAPS framework comprises five flexible and geographically scalable modules: (1) historic data on fine particulate matter (PM2.5) concentrations; (2) historic data on relevant health indicator counts; (3) PM2.5 forecasts for the upcoming days; (4) a health forecasting model that uses the relationship between (1) and (2) to predict the impacts of (3); and (5) a reporting mechanism. Methods: The 2018 wildfire season was the most extreme in British Columbia history. Every morning BCAPS generated forecasts of salbutamol sulfate (e.g., Ventolin) inhaler dispensations for the upcoming days in 16 Health Service Delivery Areas (HSDAs) using random forest machine learning. These forecasts were compared with observations over a 63-day study period using different methods including the index of agreement (IOA), which ranges from 0 (no agreement) to 1 (perfect agreement). Some observations were compared with the same period in the milder wildfire season of 2016 for context. Results: The mean province-wide population-weighted PM2.5 concentration over the study period was 22.0 mu g/m(3), compared with 4.2 mu g/m(3) during the milder wildfire season of 2016. The PM2.5 forecasts underpredicted the severe smoke impacts, but the IOA was relatively strong with a population-weighted average of 0.85, ranging from 0.65 to 0.95 among the HSDAs. Inhaler dispensations increased by 30% over 2016 values. Forecasted dispensations were within 20% of the observed value in 71% of cases, and the IOA was strong with a population-weighted average of 0.95, ranging from 0.92 to 0.98. All measures of agreement were correlated with HSDA population, where BCAPS performance was better in the larger populations with more moderate smoke impacts. The accuracy of the health forecasts was partially dependent on the accuracy of the PM2.5 forecasts, but they were robust to over- and underpredictions of PM2.5 exposure. Conclusions: Daily reports from the BCAPS framework provided timely and reasonable insight into the population health impacts of predicted smoke exposures, though more work is necessary to improve the PM2.5 and health indicator forecasts.
Wildfire smoke exposure is associated with a range of acute health outcomes, which can be more severe in individuals with underlying health conditions. Currently, there is limited information on the susceptibility of healthcare facilities to smoke infiltration. As part of a larger study to address this gap, a rehabilitation facility in Vancouver, Canada was outfitted with one outdoor and seven indoor low-cost fine particulate matter (PM2.5) sensors in Air Quality Eggs (EGG) during the summer of 2020. Raw measurements were calibrated using temperature, relative humidity, and dew point derived from the EGG data. The infiltration coefficient was quantified using a distributed lag model. Indoor concentrations during the smoke episode were elevated throughout the building, though non-uniformly. After censoring indoor-only peaks, the average infiltration coefficient (range) during typical days was 0.32 (0.22-0.39), compared with 0.37 (0.31-0.47) during the smoke episode, a 19% increase on average. Indoor PM2.5 concentrations quickly reflected outdoor conditions during and after the smoke episode. It is unclear whether these results will be generalizable to other years due to COVID-related changes to building operations, but some of the safety protocols may offer valuable lessons for future wildfire seasons. For example, points of building entry and exit were reduced from eight to two during the pandemic, which likely helped to protect the building from wildfire smoke infiltration. Overall, these results demonstrate the utility of indoor low-cost sensors in understanding the impacts of extreme smoke events on facilities where highly susceptible individuals are present. Furthermore, they highlight the need to employ interventions that enhance indoor air quality in such facilities during smoke events.
The negative synergistic effects of air pollution and sensible heat on public health have been noted in numerous studies. While separate, simplified, and public-facing indices have been developed to communicate the risks of unhealthful levels of air pollution and extreme heat, a combined index containing elements of both has rarely been investigated. Utilizing air quality, meteorology, and mortality data in Monterrey, Mexico, we investigated whether the association between the air quality index (AQI) and mortality was improved by considering elements of the heat index (HI). We created combined indices featuring additive, multiplicative, and either/or formulations and evaluated their relationship to mortality. Results showed increased associations with mortality for models employing indices that combined the AQI and the HI in an additive or multiplicative manner, with increases in the interquartile relative risk of 3-5% over that resulting from models employing the AQI alone.
Extreme heat and ozone are co-occurring exposures that independently and synergistically increase the risk of respiratory disease. To our knowledge, no joint warning systems consider both risks; understanding their interactive effect can warrant use of comprehensive warning systems to reduce their burden. We examined heterogeneity in joint effects (on the additive scale) between heat and ozone at small geographical scales. A within-community matched design with a Bayesian hierarchical model was applied to study this association at the zip code level. Spatially varying relative risks due to interaction (RERI) were quantified to consider joint effects. Determinants of the spatial variability of effects were assessed using a random effects metaregression to consider the role of demographic/neighborhood characteristics that are known effect modifiers. A total of 817,354 unscheduled respiratory hospitalizations occurred in California from 2004 to 2013 in the May to September period. RERIs revealed no additive interaction when considering overall joint effects. However, when considering the zip code level, certain areas observed strong joint effects. A lower median income, higher percentage of unemployed residents, and exposure to other air pollutants within a zip code drove stronger joint effects; a higher percentage of commuters who walk/bicycle, a marker for neighborhood wealth, showed decreased effects. Results indicate the importance of going beyond average measures to consider spatial variation in the health burden of these exposures and predictors of joint effects. This information can be used to inform early warning systems that consider both heat and ozone to protect populations from these deleterious effects in identified areas.
Wildfires can be detrimental to urban and rural communities, causing impacts in the form of psychological stress, direct physical injury, and smoke-related morbidity and mortality. This study examined the area burned by wildfires over the entire state of California from the years 2000 to 2020 in order to quantify and identify whether burned area and fire frequency differed across Census tracts according to socioeconomic indicators over time. Wildfire data were obtained from the California Fire and Resource Assessment Program (FRAP) and National Interagency Fire Center (NIFC), while demographic data were obtained from the American Community Survey. Results showed a doubling in the number of Census tracts that experienced major wildfires and a near doubling in the number of people residing in wildfire-impacted Census tracts, mostly due to an over 23,000 acre/year increase in the area burned by wildfires over the last two decades. Census tracts with a higher fire frequency and burned area had lower proportions of minority groups on average. However, when considering Native American populations, a greater proportion resided in highly impacted Census tracts. Such Census tracts also had higher proportions of older residents. In general, high-impact Census tracts tended to have higher proportions of low-income residents and lower proportions of high-income residents, as well as lower median household incomes and home values. These findings are important to policymakers and state agencies as it relates to environmental justice and the allocation of resources before, during, and after wildfires in the state of California.
The health impacts of wildfire smoke are an important and growing global issue, as extreme wildfire events are expected to increase in frequency and intensity throughout this century due to climate change. Research into individual protective health decision-making can elucidate how wildfire smoke exposure contributes to adverse health outcomes and aid in public health interventions to mitigate risks. In this study we investigate the role of psychological factors (threat and efficacy perceptions) and social processes (social norms and social support) in shaping protective behavior in response to wildfire smoke. Through semi-structured interviews of forty-five individuals in Northern California, we explore perceptions of threat and efficacy, social processes, and protective behaviors in response to wildfire smoke events between 2018 and 2020. We found that for many participants sensory experiences and engagement with wildfire smoke information were instrumental in forming perceptions of threat and efficacy. Three themes related to social processes emerged: interpreting information together, protecting vulnerable others, and questioning protective actions. Through these themes we show how social norms and social support interact in complex, non-linear ways to influence threat and efficacy perceptions, and directly affect protective health behavior. Finally, we propose a conceptual framework of wildfire smoke protective behavior. This study contributes to a growing body of knowledge within the disaster risk and protective health literatures related to wildfire smoke response. Our findings demonstrate how the study of psychological factors and social processes during natural hazards, like wildfire smoke events, is essential to understanding individual protective health decision-making pathways and ultimately, to developing a more comprehensive view of how individual actions affect exposure.
Background We studied the impact of fine particulate matter (PM2.5) exposure due to a remote wildfire event in the Pacific Northwest on daily outpatient respiratory and cardiovascular physician visits during wildfire (24-31 August, 2015) and post-wildfire period (1-30 September, 2015) relative to the pre-wildfire period (1-23 August, 2015) in the city of Calgary, Canada. Methods A quasi-Poisson regression model was used for modelling daily counts of physician visits due to PM2.5 while adjusting for day of the week (weekday versus weekend or public holiday), wildfire exposure period (before, during, after), methane, relative humidity, and wind direction. A subgroup analysis of those with pre-existing diabetes or hypertension was performed. Results An elevated risk of respiratory disease morbidity of 33% (relative risk: RR) [95% confidence interval (CI): 10%-59%] and 55% (95% CI: 42%-69%) was observed per 10 mu g/m(3) increase in PM2.5 level during and after wildfire, respectively, relative to the pre-wildfire time period. Increased risk was observed for children aged 0-9 years during (RR = 1.57, 95% CI: 1.21-2.02) and after the wildfire (RR = 2.11, 95% CI: 1.86-2.40) especially for asthma, acute bronchitis and acute respiratory infection. The risk of physician visits among seniors increased by 11% (95% CI: 3%-21%), and 19% (95% CI: 7%-33%) post-wildfire for congestive heart failure and ischaemic heart disease, respectively. Individuals with pre-existing diabetes had an increased risk of both respiratory and cardiovascular morbidity in the post-wildfire period (RR = 1.35, 95% CI: 1.09-1.67; RR = 1.22, 95% CI: 1.01-1.46, respectively). Conclusions Wildfire-related PM2.5 exposure led to increased respiratory condition-related outpatient physician visits during and after wildfires, particularly for children. An increased risk of physician visits for congestive heart failure and ischaemic heart disease among seniors in the post-wildfire period was also observed.
The increasing incidence of extreme wildfire is becoming a concern for public health. Although long-term exposure to wildfire smoke is associated with respiratory illnesses, reports on the association between short-term occupational exposure to wildfire smoke and lung function remain scarce. In this cross-sectional study, we analyzed data from 218 Royal Canadian Mounted Police officers (mean age: 38 & PLUSMN; 9 years) deployed at the Fort McMurray wildfires in 2016. Individual exposure to air pollutants was calculated by integrating the duration of exposure with the air quality parameters obtained from the nearest air quality monitoring station during the phase of deployment. Lung function was measured using spirometry and body plethysmography. Association between exposure and lung function was examined using principal component linear regression analysis, adjusting for potential confounders. In our findings, the participants were predominantly male (71%). Mean forced expiratory volume in 1 s (FEV1), and residual volume (RV) were 76.5 & PLUSMN; 5.9 and 80.1 & PLUSMN; 19.5 (% predicted). A marginal association was observed between air pollution and higher RV [beta: 1.55; 95% CI: -0.28 to 3.37 per interquartile change of air pollution index], but not with other lung function indices. The association between air pollution index and RV was significantly higher in participants who were screened within the first three months of deployment (2.80; 0.91 to 4.70) than those screened later (-0.28; -2.58 to 2.03), indicating a stronger effect of air pollution on peripheral airways. Acute short-term exposure to wildfire-associated air pollutants may impose subtle but clinically important deleterious respiratory effects, particularly in the peripheral airways.
Western North American fires have been increasing in magnitude and severity over the last few decades. The complex coupling of fires with the atmospheric energy budget and meteorology creates short-term feedbacks on regional weather altering the amount of pollution to which Americans are exposed. Using a combination of model simulations and observations, this study shows that the severe fires in the summer of 2017 increased atmospheric aerosol concentrations leading to a cooling of the air at the surface, reductions in sensible heat fluxes, and a lowering of the planetary boundary layer height over land. This combination of lower-boundary layer height and increased aerosol pollution from the fires reduces air quality. We estimate that from start of August to end of October 2017, ∼400 premature deaths occurred within the western US as a result of short-term exposure to elevated PM2.5 from fire smoke. As North America confronts a warming climate with more fires the short-term climate and pollution impacts of increased fire activity should be assessed within policy aimed to minimize impacts of climate change on society.
Background and purpose: We describe a novel, interprofessional, experiential training involving pharmacy students in response to a health emergency in rural Montana (MT). Educational activity and setting: Fourth-year pharmacy students on clinical rotations were recruited to participate in screening events assessing effects of wildfire smoke in Seeley Lake, MT. Students were required to fulfill at least two hours of supplementary training in addition to education on human research guidelines. Students assisted with patient surveys (demographics, health, and respiratory), physiological testing with biomedical researchers, blood pressure and medication counseling, and spirometry specialists. Findings: At least 20 pharmacy students have participated in this project in addition to nursing (n = 8), public health (n = 1), and social work (n = 1) students. In initial and subsequent screenings, students worked alongside a team of biomedical researchers and faculty from the University of Montana. An initial cohort of 95 patients was recruited. Summary: This unique experiential training opportunity has affordedpharmacy students access to rural community patient interaction and exposure to and performance of a variety of tests in response to an environmental health emergency. Furthermore, it enabled health professionals and researchers to assess individual and overall community health following an extreme wildfire smoke event, providing the groundwork for utilization of pharmacy students in healthcare responses to public health emergencies. (c) 2021 Elsevier Inc. All rights reserved.
The increased frequency of wildfires in the Western United States has raised public awareness of the impact of wildfire smoke on air quality and human health. Exposure to wildfire smoke has been linked to an increased risk of cancer and cardiorespiratory morbidity. Evidence-driven interventions can alleviate the adverse health impact of wildfire smoke. During wildfires, public health guidance is based on regional air quality data with limited spatiotemporal resolution. Recently, low-cost air quality sensors have been used in air quality studies, given their ability to capture high-resolution spatiotemporal data. We demonstrate the use of a network of low-cost particulate matter (PM) sensors to gather indoor and outdoor PM2.5 data from seven locations in the urban Seattle area, along with a personal exposure monitor worn by a resident living in one of these locations during the 2020 Washington wildfire event. The data were used to determine PM concentration indoor/outdoor (I/O) ratios, PM reduction, and personal exposure levels. The result shows that locations equipped with high-efficiency particulate air (HEPA) filters and HVAC filtration systems had significantly lower I/O ratios (median I/O = 0.43) than those without air filtration (median I/O = 0.82). The median PM2.5 reduction for the locations with HEPA is 58% compared to 20% for the locations without HEPA. The outdoor PM sensor showed a high correlation to the nearby regional air quality monitoring stations (pre-calibration R-2 = 0.92). The personal monitor showed higher variance in PM measurements as the user moved through different microenvironments and could not be fully characterized by the network of indoor or outdoor monitors. The findings imply that evidence-based interventions can be developed to reduce pollution exposure when combining data from indoor and outdoor sensors. Personal exposure monitoring captured temporal spikes in PM exposure.
Exceptional events occur when air pollution in a specific location exceeds the National Ambient Air Quality Standards (NAAQS) due to an event that cannot be reasonably attributed to human activities, such as a wildland fire. Ground-level ozone (O-3) and particulate matter (PM) are Environmental Protection Agency (EPA) criteria pollutants regulated under the NAAQS. Smoke from wildland fires can increase PM and O-3 concentrations downwind of fire and impact air quality, visibility, and health. Our analysis shows that the frequency of exceptional event reporting for PM with aerodynamic diameters smaller than 2.5 mu m or 10 mu m (PM2.5 and PM10) had increased since 2007 when the air quality standards became more stringent. We also show that wildland fires and windblown dust drive many exceptional events in several EPA regions. We note the importance of growth in the number of exceptional event days due to wildfire smoke in the future due to climate change and point to possible changes to the NAAQS and implementations.
Increased wildland fire activity is producing extreme fine particulate matter (PM2.5) concentrations impacting millions of people every year, especially in the western United States (US). Recommendations for limiting exposure to PM2.5 and associated adverse health outcomes focus on staying inside, closing windows and doors, and increasing filtration; however, relatively little is known about indoor air quality (IAQ) during major smoke events. Indoor and outdoor hourly PM2.5 (µg m–3) measurements from the publicly available PurpleAir sensor (PAS) network were analyzed for 42 sites (26 residential, 6 school, 10 commercial) across the western US during a September 2020 period of heavy wildfire smoke influence. The fraction of ambient PM2.5 that penetrates indoors and remains airborne (Fin), as well as the ratio (I/O) and correlation coefficient (R2) of indoor to outdoor PM2.5 concentrations, were lower in residential compared to commercial and school buildings. Interventions to improve IAQ were highly influential in PM2.5 infiltration in residential case studies, with multiple, continuously run filter units associated with lower Fin, I/O, and R2. A low-cost PM2.5 filtration method consisting of a Minimum Efficiency Rating Value-13 (MERV-13) filter attached to a box fan is evaluated as an alternative for improving IAQ during wildland fire smoke events. The MERV-13 fan filter unit proved highly effective at reducing indoor PM2.5 and particles 0.3–1.0 µm measured by PAS and a particle counter, respectively, when recirculating air in a single room. Low-cost filtration methods can have significant benefit for filtering submicron smoke particles and may reduce exposure to PM2.5 during wildfire smoke events.
Objective(s): This study explored the feasibility, acceptability, preliminary impact, and functionality of two risk reduction mobile application (app) interventions on asthma outcomes as compared to a control arm during wildfire season. Design: Three-arm, 8-week randomized clinical trial. Sample: Sixty-seven young adults with asthma were enrolled. Measurements: The Asthma Control Test, forced expiratory volume in one second (FEV1) and the System Usability Scale were measured at baseline, 4, and 8 weeks. The Research Attitude Scale was administered at 8 weeks. Twenty participants from the two intervention arms completed an optional survey and six were interviewed after completing the study. Intervention: Both intervention arms could access Smoke Sense Urbanova, an app that supports reducing risks from breathing wildfire smoke. The Smoke Sense Urbanova Plus arm also monitored their daily FEV1, received air quality notifications, and accessed preventive tips and a message board. Results: Most participants agreed the app and spirometer were usable and their privacy and confidentiality were maintained. No adverse events were reported. Conclusions: Participant-identified recommendations will support intervention refinement and testing. This research supports asthma self-management tools that public health nurses and community health workers can recommend for at-risk populations.
Wildland fires are diminishing air quality on a seasonal and regional basis, raising concerns about respiratory health risks to the public and occupational groups. This American Thoracic Society (ATS) workshop was convened in 2019 to meet the growing health threat of wildland fire smoke. The workshop brought together a multidisciplinary group of 19 experts, including wildland fire managers, public health officials, epidemiologists, toxicologists, and pediatric and adult pulmonologists. The workshop examined the following four major topics: 1) the science of wildland fire incidence and fire management, 2) the respiratory and cardiovascular health effects of wildland fire smoke exposure, 3) communication strategies to address these health risks, and 4) actions to address wildland fire health impacts. Through formal presentations followed by group discussion, workshop participants identified top priorities for fire management, research, communication, and public policy to address health risks of wildland fires. The workshop concluded that short-term exposure to wildland smoke causes acute respiratory health effects, especially among those with asthma and chronic obstructive pulmonary disease. Research is needed to understand long-term health effects of repeated smoke exposures across fire seasons for children, adults, and highly exposed occupational groups (especially firefighters). Other research priorities include fire data collection and modeling, toxicology of different fire fuel sources, and the efficacy of health protective measures to prevent respiratory effects of smoke exposure. The workshop committee recommends a unified federal response to the growing problem of wildland fires, including investment in fire behavior and smoke air quality modeling, research on the health impacts of smoke, and development of robust clinical and public health communication tools.
Recent dramatic and deadly increases in global wildfire activity have increased attention on the causes of wildfires, their consequences, and how risk from wildfire might be mitigated. Here we bring together data on the changing risk and societal burden of wildfire in the United States. We estimate that nearly 50 million homes are currently in the wildland-urban interface in the United States, a number increasing by 1 million houses every 3 y. To illustrate how changes in wildfire activity might affect air pollution and related health outcomes, and how these linkages might guide future science and policy, we develop a statistical model that relates satellite-based fire and smoke data to information from pollution monitoring stations. Using the model, we estimate that wildfires have accounted for up to 25% of PM (2.5) (particulate matter with diameter <2.5 μm) in recent years across the United States, and up to half in some Western regions, with spatial patterns in ambient smoke exposure that do not follow traditional socioeconomic pollution exposure gradients. We combine the model with stylized scenarios to show that fuel management interventions could have large health benefits and that future health impacts from climate-change-induced wildfire smoke could approach projected overall increases in temperature-related mortality from climate change-but that both estimates remain uncertain. We use model results to highlight important areas for future research and to draw lessons for policy.
Smoke impacts from large wildfires are mounting, and the projection is for more such events in the future as the one experienced October 2017 in Northern California, and subsequently in 2018 and 2020. Further, the evidence is growing about the health impacts from these events which are also difficult to simulate. Therefore, we simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling with WRF-CMAQ, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses. To demonstrate these analyses, we estimated the health impacts from smoke impacts during wildfires in October 8-20, 2017, in Northern California, when over 7 million people were exposed to Unhealthy to Very Unhealthy air quality conditions. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ system. Interestingly, this approach did not necessarily improve overall results, however it was key to simulating the initial 12-hr explosive fire activity and smoke impacts. To improve these results, we applied one data fusion and three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across all cases, the best Pearson correlation was 0.5. Overall, WRF-CMAQ simulations were biased high and the geostatistical methods were biased low. Finally, we applied the optimized PM2.5 exposure estimate in an exposure-response function. Estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% CI: 0, 196) with 47% attributable to wildland fire smoke.Implications: Large wildfires in the United States and in particular California are becoming increasingly common. Associated with these large wildfires are air quality and health impact to millions of people from the smoke. We simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses from the October 2017 Northern California wildfires. Temporary monitors deployed for the wildfires provided an important model evaluation dataset. Total estimated regional mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to the wildland fire smoke. This illustrates the profound effect that even a 12-day exposure to wildland fire smoke can have on human health.
Wildland fire smoke contains hazardous levels of fine particulate mat-ter (PM2.5), a pollutant shown to adversely effect health. Estimating fire at-tributable PM2.5 concentrations is key to quantifying the impact on air quality and subsequent health burden. This is a challenging problem since only to-tal PM2.5 is measured at monitoring stations and both fire-attributable PM2.5 and PM2.5 from all other sources are correlated in space and time. We propose a framework for estimating fire-contributed PM2.5 and PM2.5 from all other sources using a novel causal inference framework and bias-adjusted chemical model representations of PM2.5 under counterfactual scenarios. The chemical model representation of PM2.5 for this analysis is simulated using Commu-nity Multiscale Air Quality Modeling System (CMAQ), run with and without fire emissions across the contiguous U.S. for the 2008-2012 wildfire seasons. The CMAQ output is calibrated with observations from monitoring sites for the same spatial domain and time period. We use a Bayesian model that ac-counts for spatial variation to estimate the effect of wildland fires on PM2.5 and state assumptions under which the estimate has a valid causal interpreta-tion. Our results include estimates of the contributions of wildfire smoke to PM2.5 for the contiguous U.S. Additionally, we compute the health burden associated with the PM2.5 attributable to wildfire smoke.
Wildfire smoke is a growing public health concern in the United States. Numerous studies have documented associations between ambient smoke exposure and severe patient outcomes for single-fire seasons or limited geographic regions. However, there are few national-scale health studies of wildfire smoke in the United States, few studies investigating Intensive Care Unit (ICU) admissions as an outcome, and few specifically framed around hospital operations. This study retrospectively examined the associations between ambient wildfire-related PM2.5 at a hospital ZIP code with total hospital ICU admissions using a national-scale hospitalization data set. Wildfire smoke was characterized using a combination of kriged PM2.5 monitor observations and satellite-derived plume polygons from National Oceanic and Atmospheric Administration’s Hazard Mapping System. ICU admissions data were acquired from Premier, Inc. and encompass 15%-20% of all U.S. ICU admissions during the study period. Associations were estimated using a distributed-lag conditional Poisson model under a time-stratified case-crossover design. We found that a 10 mu g/m(3) increase in daily wildfire PM2.5 was associated with a 2.7% (95% CI: 1.3, 4.1; p = 0.00018) increase in ICU admissions 5 days later. Under stratification, positive associations were found among patients aged 0-20 and 60+, patients living in the Midwest Census Region, patients admitted in the years 2013-2015, and non-Black patients, though other results were mixed. Following a simulated severe 7-day 120 mu g/m(3) smoke event, our results predict ICU bed utilization peaking at 131% (95% CI: 43, 239; p < 10(-5)) over baseline. Our work suggests that hospitals may need to preposition vital critical care resources when severe smoke events are forecast. Plain Language Summary Wildfire smoke negatively affects people's health. Heavy smoke has been linked to higher rates of hospital admissions, emergency room, admissions, and death. However, we do not know the impact of smoke on Intensive Care Unit (ICU) admissions or on limited hospital resources like ICU beds. To fill this knowledge gap, we linked hospital ICU admissions to smoke levels near those hospitals. We also predicted how many ICU admissions would occur during a simulated severe week-long smoke event and how many ICU beds would be needed to care for the patients. We found that the link between smoke and ICU admissions was relatively modest, but a severe smoke event could more than double the number of ICU beds needed.
Wildfires are natural ecological processes that generate high levels of fine particulate matter (PM2.5) that are dispersed into the atmosphere. PM2.5 could be a potential health problem due to its size. Having adequate numerical models to predict the spatial and temporal distribution of PM2.5 helps to mitigate the impact on human health. The compositional data approach is widely used in the environmental sciences and concentration analyses (parts of a whole). This numerical approach in the modelling process avoids one common statistical problem: the spurious correlation. PM2.5 is a part of the atmospheric composition. In this way, this study developed an hourly spatio-temporal PM2.5 model based on the dynamic linear modelling framework (DLM) with a compositional approach. The results of the model are extended using a Gaussian-Mattern field. The modelling of PM2.5 using a compositional approach presented adequate quality model indices (NSE = 0.82, RMSE = 0.23, and a Pearson correlation coefficient of 0.91); however, the correlation range showed a slightly lower value than the conventional/traditional approach. The proposed method could be used in spatial prediction in places without monitoring stations.
We developed daily maps of surface fine particulate matter (PM(2.5)) for the western United States. We used geographically weighted regression fit to air quality station observations with Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) data, and meteorological data to produce daily 1-kilometer resolution PM(2.5) concentration estimates from 2003-2020. To account for impacts of stagnant air and inversions, we included estimates of inversion strength based on meteorological conditions, and inversion potential based on human activities and local topography. Model accuracy based on cross-validation was R(2) = 0.66. AOD data improve the model in summer and fall during periods of high wildfire activity while the stagnation terms capture the spatial and temporal dynamics of PM(2.5) in mountain valleys, particularly during winter. These data can be used to explore exposure and health outcome impacts of PM(2.5) across spatiotemporal domains particularly in the intermountain western United States where measurements from monitoring station data are sparse. Furthermore, these data may facilitate analyses of inversion impacts and local topography on exposure and health outcome studies.
We estimated cardiopulmonary morbidity and mortality associated with wildfire smoke (WFS) fine particulate matter (PM2.5) in the Front Range of Colorado from 2010 to 2015. To estimate WFS PM2.5, we developed a daily kriged PM2.5 surface at a 15 x 15 km resolution based on the Environmental Protection Agency Air Quality System monitors for the western United States; we subtracted out local seasonal-average PM2.5 of nonsmoky days, identified using satellite-based smoke plume estimates, from the local daily estimated PM2.5 if smoke was identified by National Oceanic and Atmospheric Administration’s Hazard Mapping System. We implemented time-stratified case-crossover analyses to estimate the effect of a 10 mu g/m(3) increase in WFS PM2.5 with cardiopulmonary hospitalizations and deaths using single and distributed lag models for lags 0-5 and distinct annual impacts based on local and long-range smoke during 2012, and long-range transport of smoke in 2015. A 10 mu g/m(3) increase in WFS was associated with all respiratory, asthma, and chronic obstructive pulmonary disease hospitalizations for lag day 3 and hospitalizations for ischemic heart disease at lag days 2 and 3. Cardiac arrest deaths were associated with WFS PM2.5 at lag day 0. For 2012 local wildfires, asthma hospitalizations had an inverse association with WFS PM2.5 (OR: 0.716, 95% CI: 0.517-0.993), but a positive association with WFS PM2.5 during the 2015 long-range transport event (OR: 1.455, 95% CI: 1.093-1.939). Cardiovascular mortality was associated with the 2012 long-range transport event (OR: 1.478, 95% CI: 1.124-1.944).
Wildfire activity in the western United States (US) has been increasing, a trend that has been correlated with changing patterns of temperature and precipitation associated with climate change. Health effects associated with exposure to wildfire smoke and fine particulate matter (PM(2.5)) include short- and long-term premature mortality, hospital admissions, emergency department visits, and other respiratory and cardiovascular incidents. We estimate PM(2.5) exposure and health impacts for the entire continental US from current and future western US wildfire activity projected for a range of future climate scenarios through the 21st century. We use a simulation approach to estimate wildfire activity, area burned, fine particulate emissions, air quality concentrations, health effects, and economic valuation of health effects, using established and novel methodologies. We find that climatic factors increase wildfire pollutant emissions by an average of 0.40% per year over the 2006-2100 period under Representative Concentration Pathway (RCP) 4.5 (lower emissions scenarios) and 0.71% per year for RCP8.5. As a consequence, spatially weighted wildfire PM(2.5) concentrations more than double for some climate model projections by the end of the 21st century. PM(2.5) exposure changes, combined with population projections, result in a wildfire PM2.5-related premature mortality excess burden in the 2090 RCP8.5 scenario that is roughly 3.5 times larger than in the baseline period. The combined effect of increased wildfire activity, population growth, and increase in the valuation of avoided risk of premature mortality over time results in a large increase in total economic impact of wildfire-related PM(2.5) mortality and morbidity in the continental US, from roughly $7 billion per year in the baseline period to roughly $36 billion per year in 2090 for RCP4.5, and $43 billion per year in RCP8.5. The climate effect alone accounts for a roughly 60% increase in wildfire PM2.5-related premature mortality in the RCP8.5 scenario, relative to baseline conditions.
BACKGROUND: Rising temperatures due to climate change are expected to impact human adaptive response, including changes to home cooling and ventilation patterns. These changes may affect air pollution exposures via alteration in residential air exchange rates, affecting indoor infiltration of outdoor particles. We conducted a field study examining associations between particle infiltration and temperature to inform future studies of air pollution health effects. METHODS: We measured indoor fine particulate matter (PM(2.5)) in Atlanta in 60 homes (810 sampling-days). Indoor-outdoor sulfur ratios were used to estimate particle infiltration, using central site outdoor sulfur concentrations. Linear and mixed-effects models were used to examine particle infiltration ratio-temperature relationships, based on which we incorporated projected meteorological values (Representative Concentration Pathways intermediate scenario RCP 4.5) to estimate particle infiltration ratios in 20-year future (2046-2065) and past (1981-2000) scenarios. RESULTS: The mean particle infiltration ratio in Atlanta was 0.70 ± 0.30, with a 0.21 lower ratio in summer compared to transition seasons (spring, fall). Particle infiltration ratios were 0.19 lower in houses using heating, ventilation, and air conditioning (HVAC) systems compared to those not using HVAC. We observed significant associations between particle infiltration ratios and both linear and quadratic models of ambient temperature for homes using natural ventilation and those using HVAC. Future temperature was projected to increase by 2.1 °C in Atlanta, which corresponds to an increase of 0.023 (3.9%) in particle infiltration ratios during cooler months and a decrease of 0.037 (6.2%) during warmer months. DISCUSSION: We estimated notable changes in particle infiltration ratio in Atlanta for different 20-year periods, with differential seasonal patterns. Moreover, when stratified by HVAC usage, increases in future ambient temperature due to climate change were projected to enhance seasonal differences in PM(2.5) infiltration in Atlanta. These analyses can help minimize exposure misclassification in epidemiologic studies of PM(2.5), and provide a better understanding of the potential influence of climate change on PM(2.5) health effects.
Air pollution, climate change, and other environmental factors contribute to increasing asthma in many cities, including Washington, DC. This work provides a case study of how community input, neighborhood-level health surveys, and air quality monitoring can inform the understanding of asthma and air pollution. A partnership between residents, concerned citizens, scientists, and educators has been working for environmental health in a DC neighborhood located on a major roadway, next to concrete batch plants and close to several construction projects. A 2016 Community Health and Safety Study by the DC Department of Health, Office of Health Equity, recognized this particular neighborhood as more vulnerable to health impacts from recent construction in the area, compared with the surrounding areas, due to lower average income and higher percentage of seniors and children. This work presents neighborhood health surveys and air quality monitoring data at a more granular, local level than available from DC government agencies. The health surveys documented residents’ experiences around air pollution, asthma, and other health concerns. A key finding was evidence that asthma might be undercounted in this neighborhood; among residents who did not indicate a diagnosis of asthma, many discussed having symptoms that could reflect asthma. Air quality monitoring (particulate matter [PM]) did not indicate that federal air quality standards have been violated. Real-time PM data, however, illustrated how current PM standards, such as 1- and 24-hour averages, may fail to capture shorter duration high PM events that are consistent with resident concerns.
BACKGROUND: While ozone levels in the USA have decreased since the 1980s, the Denver Metro North Front Range (DMNFR) region remains in nonattainment of the National Ambient Air Quality Standard (NAAQS). OBJECTIVE: To estimate the warm season ozone climate penalty to characterize its impact on Colorado Front Range NAAQS attainment and health equity. METHODS: May to October ozone concentrations were estimated using spatio-temporal land-use regression models accounting for climate and weather patterns. The ozone climate penalty was defined as the difference between the 2010s concentrations and concentrations predicted using daily 2010s weather adjusted to match the 1950s climate, holding constant other factors affecting ozone formation. RESULTS: The ozone climate penalty was 0.5-1.0 ppb for 8-h max ozone concentrations. The highest penalty was around major urban centers and later in the summer. The penalty was positively associated with census tract-level percentage of Hispanic/Latino residents, children living within 100-200% of the federal poverty level, and residents with asthma, diabetes, fair or poor health status, or lacking health insurance. SIGNIFICANCE: The penalty increased the DMNFR ozone NAAQS design values, delaying extrapolated future attainment of the 2008 and 2015 ozone standards by approximately 2 years each, to 2025 and 2035, respectively.
BACKGROUND: Air pollution is linked to preterm birth (PTB), but existing studies are primarily focused on chronic exposures, conducted in areas with moderate pollution, and/or subject to confounding. OBJECTIVES: We investigated short-term associations between two pollutants [particulate matter <2.5 microns (PM(2.5) ) and ozone] and PTB, and estimated excess PTB cases potentially attributed to these pollutants. METHODS: This time-stratified case-crossover study includes 196,970 singleton pregnancies affected by PTB and early term birth from the San Joaquin Valley (SJV), California, USA (2007-2015). Daily ozone and PM(2.5) concentrations were estimated by the SJV Air Pollution Control District and geospatially linked to maternal zip code. We used conditional logistic regression models to estimate the odds ratio (OR) and 95% confidence intervals (CI) for the associations between an interquartile range (IQR) increase in pollutants and very preterm (VPTB, 20-34 weeks), moderate preterm (MPTB, 34-36 weeks) and early term births (ETB, 37-38 weeks). We adjusted all models for co-pollutants and meteorological factors. RESULTS: During warm seasons (May-October), an IQR increase in ozone was associated with 9-11% increased odds of VPTB from lag 0 (OR(lag0) 1.09, 95% CI 1.04,1.16) to lag 7 (OR(lag7) 1.11, 95% CI 1.04,1.16). Findings were consistent for MPTB and ETB. Ozone was potentially responsible for an excess of 3-6 VPTBs, 7-9 PTBs and 24-42 ETBs per 1,000 singleton deliveries. During cold seasons (November-April), increased PM(2.5) exposure was associated with 5-6% increased odds of VPTB beginning at lag 3 (OR(lag3) 1.06, 95% CI 1.02,1.11). PM(2.5) was associated with an excess of 1-3 VPTBs, 0-3 MPTBs and 6-18 ETBs per 1,000 singleton deliveries. CONCLUSIONS: PM(2.5) and ozone are associated with increased risk of VPTB, MPTB and ETB within one week of exposure and are potential contributors to the increasing PTB trend. More research is needed to further understand the role of air pollution on PTB risk.
Wildfires and meteorological conditions influence the co-occurrence of multiple harmful air pollutants including fine particulate matter (PM2.5) and ground-level ozone. We examine the spatiotemporal characteristics of PM2.5/ozone co-occurrences and associated population exposure in the western United States (US). The frequency, spatial extent, and temporal persistence of extreme PM2.5/ozone co-occurrences have increased significantly between 2001 and 2020, increasing annual population exposure to multiple harmful air pollutants by similar to 25 million person-days/year. Using a clustering methodology to characterize daily weather patterns, we identify significant increases in atmospheric ridging patterns conducive to widespread PM2.5/ozone co-occurrences and population exposure. We further link the spatial extent of co-occurrence to the extent of extreme heat and wildfires. Our results suggest an increasing potential for co-occurring air pollution episodes in the western US with continued climate change.
BACKGROUND: Long-term exposures to air pollution has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood. OBJECTIVES: We aimed to determine the changes in the blood metabolome and thus the metabolic pathways associated with long-term exposure to outdoor air pollution and ambient temperature. METHODS: We quantified metabolites using mass-spectrometry based global untargeted metabolomic profiling of plasma samples among men from the Normative Aging Study (NAS). We estimated the association between long-term exposure to PM(2.5), NO(2), O(3), and temperature (annual average of central site monitors) with metabolites and their associated metabolic pathways. We used multivariable linear mixed-effect regression models (LMEM) while simultaneously adjusting for the four exposures and potential confounding and correcting for multiple testing. As a reduction method for the intercorrelated metabolites (outcome), we further used an independent component analysis (ICA) and conducted LMEM with the same exposures. RESULTS: Men (N = 456) provided 648 blood samples between 2000 and 2016 in which 1158 metabolites were quantified. On average, men were 75.0 years and had an average body mass index of 27.7 kg/m(2). Almost all men (97%) were not current smokers. The adjusted analysis showed statistically significant associations with several metabolites (58 metabolites with PM(2.5), 15 metabolites with NO(2), and 6 metabolites with temperature) while no metabolites were associated with O(3). One out of five ICA factors (factor 2) was significantly associated with PM(2.5). We identified eight perturbed metabolic pathways with long-term exposure to PM(2.5) and temperature: glycerophospholipid, sphingolipid, glutathione, beta-alanine, propanoate, and purine metabolism, biosynthesis of unsaturated fatty acids, and taurine and hypotaurine metabolism. These pathways are related to inflammation, oxidative stress, immunity, and nucleic acid damage and repair. CONCLUSIONS: Using a global untargeted metabolomic approach, we identified several significant metabolites and metabolic pathways associated with long-term exposure to PM(2.5), NO(2) and temperature. This study is the largest metabolomics study of long-term air pollution, to date, the first study to report a metabolomic signature of long-term temperature exposure, and the first to use ICA in the analysis of both.
Exposure to fine particulate matter (PM(2.5)) is associated with asthma development as well as asthma exacerbation in children. PM(2.5) can be directly emitted or can form in the atmosphere from pollutant precursors. PM(2.5) emitted and formed in the atmosphere is influenced by meteorology; future changes in climate may alter the concentration and distribution of PM(2.5). Our aim is to estimate the future burden of climate change and PM(2.5) on new and exacerbated cases of childhood asthma. Projected concentrations of PM(2.5) are based on the Geophysical Fluid Dynamics Laboratory Coupled Model version 3 climate model, the Representative Concentration Pathway 8.5 greenhouse gas scenario, and two air pollution emissions datasets: a 2011 emissions dataset and a 2040 emissions dataset that reflects substantial reductions in emissions of PM(2.5) as compared to the 2011 inventory. We estimate additional PM(2.5)-attributable asthma as well as PM(2.5)-attributable albuterol inhaler use for four future years (2030, 2050, 2075, and 2095) relative to the year 2000. Exacerbations, regardless of the trigger, are counted as attributable to PM(2.5) if the incident disease is attributable to PM(2.5). We project 38 thousand (95% CI 36, 39 thousand) additional PM(2.5)-attributable incident childhood asthma cases and 29 million (95% CI 27, 31 million) additional PM(2.5)-attributable albuterol inhaler uses per year in 2030, increasing to 200 thousand (95% CI 190, 210 thousand) additional incident cases and 160 million (95% CI 150, 160 million) inhaler uses per year by 2095 relative to 2000 under the 2011 emissions dataset. These additional PM(2.5)-attributable incident asthma cases and albuterol inhaler use would cost billions of additional U.S. dollars per year by the late century. These outcomes could be mitigated by reducing air pollution emissions.
Particulate matter 2.5 (PM2.5) exposure induces oxidative stress associated with many negative health outcomes such as respiratory disorders, cardiovascular disease and neurodegenerative disease. Research shows that diet and exercise can improve antioxidant defense against oxidative stress. This study is the first to use an Arctic animal model to investigate the cumulative effects of two lifestyle interventions on the antioxidant response before, during, and after ambient PM 2.5 exposure from wildfire: antioxidant supplementation (Arthrospira platensis) and exercise. In a two-factorial, longitudinal design, this study divided sled dogs (n = 48) into four groups (exercise and supplemented, exercise, supplemented, and control) to (1) test the effects of a 30-day exercise and antioxidant supplementation protocol on antioxidant response; and (2) measure the antioxidant response of all groups during and after a natural wildfire event. Commercial assays for total antioxidant power (TAP) and the enzymatic antioxidant superoxide dismutase (SOD) were used as markers for antioxidant status and response. During the forest fire, SOD was increased 5- to 10-fold over pre/post-exposure levels in all groups suggesting an endogenous upregulation of defense systems in response to the acute environmental stress. TAP was lower in all groups at peak PM2.5 exposure compared to 48 h after peak exposure in all groups except the exercise alone group which may indicate that exercise offers improved endogenous defense.
Decarbonizing power systems is a critical component of climate change mitigation, which can have public health cobenefits by reducing air pollution. Many studies have examined strategies to decarbonize power grids and quantified their health cobenefits. However, few of them focus on near-term cobenefits at community levels, while comparing various decarbonization pathways. Here, we use a coupled power system and air quality modeling framework to quantify the costs and benefits of decarbonizing the Texas power grid through a carbon tax; replacing coal with natural gas, solar, or wind; and internalizing human health impacts into operations. Our results show that all decarbonization pathways can result in major reductions in CO(2) emissions and public health impacts from power sector emissions, leading to large net benefits when considering the costs to implement these strategies. Operational changes with existing infrastructure can serve as a transitional strategy during the process of replacing coal with renewable energy, which offers the largest benefits. However, we also find that Black and lower-income populations receive disproportionately higher air pollution damages and that none of the examined decarbonization strategies mitigate this disparity. These findings suggest that additional interventions are necessary to mitigate environmental inequity while decarbonizing power grids.
Local and state policymakers have become increasingly interested in developing policies that both reduce greenhouse gas (GHG) emissions and improve local air quality, along with public health. Interest in developing transportation-related policies has grown as transportation became the largest contributing sector to GHG emissions in the United States in 2017. Information on current emissions and health impacts, along with trends over time, is helpful to policymakers who are developing strategies to reduce emissions and improve public health, especially in areas with high levels of transportation-related emissions. Here, we provide a comprehensive assessment of the public health and climate social costs of on-road emissions by linking emissions data generated by the U.S. Environmental Protection Agency to reduced complexity models that provide impacts per ton emitted for pollutants which contribute to ambient fine particulate matter, and the social costs of GHG emissions from on-road transportation. For 2017, social costs totaled $184 billion (min: $78 billion; max: $280 billion) for all on-road emissions from the eight health and climate pollutants that we assessed in the continental U.S. (in $2017 USD). Within this total social cost estimate, health pollutants constituted $93 billion of the social costs (min: $52 billion; max: $146 billion), and climate pollutants constituted $91 billion (min: $26 billion; max: $134 billion). The majority of these social costs came from CO2 followed by NO (x) emissions from privately owned individual vehicles in urban counties (CO2 contributed $51 billion and NO (x) contributed $16 billion in social costs from individual vehicles in urban counties). However, it is important to note that not all the attention should be placed solely on individual vehicles. Although the climate social costs of individual vehicle emissions are higher than those from commercial vehicles in urban counties (by two to eight times depending on the climate pollutant), the health social costs of individual vehicle emissions are roughly equal to those from commercial vehicles in urban counties. Regardless of each pollutant’s contributions to the social costs, the highest social benefits from reducing 1 ton of CO2 and its co-pollutants would occur in urban counties, given their high population density.
Pollution from wildfires constitutes a growing source of poor air quality globally. To protect health, governments largely rely on citizens to limit their own wildfire smoke exposures, but the effectiveness of this strategy is hard to observe. Using data from private pollution sensors, cell phones, social media posts and internet search activity, we find that during large wildfire smoke events, individuals in wealthy locations increasingly search for information about air quality and health protection, stay at home more and are unhappier. Residents of lower-income neighbourhoods exhibit similar patterns in searches for air quality information but not for health protection, spend less time at home and have more muted sentiment responses. During smoke events, indoor particulate matter (PM(2.5)) concentrations often remain 3-4× above health-based guidelines and vary by 20× between neighbouring households. Our results suggest that policy reliance on self-protection to mitigate smoke health risks will have modest and unequal benefits.
The increasing number and severity of wildfires is negatively impacting air quality for millions of California residents each year. Community exposure to PM(2.5) in two main population centers (San Francisco Bay area and Los Angeles County area) was assessed using the low-cost PurpleAir sensor network for the record-setting 2020 California wildfire season. Estimated PM(2.5) concentrations in each study area were compared to census tract-level environmental justice vulnerability indicators, including environmental, health, and demographic data. Higher PM(2.5) concentrations were positively correlated with poverty, cardiovascular emergency department visits, and housing inequities. Sensors within 30 km of actively burning wildfires showed statistically significant increases in indoor (~800 %) and outdoor (~540 %) PM(2.5) during the fires. Results indicate that wildfire emissions may exacerbate existing health disparities as well as the burden of pollution in disadvantaged communities, suggesting a need to improve monitoring and adaptive capacity among vulnerable populations.
As wildfires increase in prevalence and intensity across California and globally, it is anticipated that more children will be exposed to wildfire smoke, and thus face associated adverse health outcomes. Here, we provide a concise summary of the respiratory effects of California’s wildfires on pediatric healthcare utilization, examine global examples of wildfire smoke exposure within the pediatric population and associated physiological effects, and assess the efficacy of metrics used to measure and communicate air quality during wildfires within the United States and elsewhere.
Climate change and human activities have drastically altered the natural wildfire balance in the Western US and increased population health risks due to exposure to pollutants from fire smoke. Using dynamically downscaled climate model projections, we estimated additional asthma emergency room visits and hospitalizations due to exposure to smoke fine particulate matter (PM2.5) in the Western US in the 2050s. Isolating the amount of PM2.5 from wildfire smoke is both difficult to estimate and, thus, utilized by relatively few studies. In this study, we use a sophisticated modeling approach to estimate future increase in wildfire smoke exposure over the reference period (2003-2010) and subsequent health care burden due to asthma exacerbation. Average increases in smoke PM2.5 during future fire season ranged from 0.05 to 9.5 mu g m(-3) with the highest increases seen in Idaho, Montana, and Oregon. Using the Integrated Climate and Land-Use Scenarios (ICLUS) A2 scenario, we estimated the smoke-related asthma events could increase at a rate of 15.1 visits per 10 000 persons in the Western US, with the highest rates of increased asthma (25.7-41.9 per 10 000) in Idaho, Montana, Oregon, and Washington. Finally, we estimated healthcare costs of smoke-induced asthma exacerbation to be over $1.5 billion during a single future fire season. Here we show the potential future health impact of climate-induced wildfire activity, which may serve as a key tool in future climate change mitigation and adaptation planning.
Biomass burning emits a wide range of carbona-ceous particles into the atmosphere and has negative impacts on human health and the Earth’s radiative balance. Nonvolatile spherical organic aerosol particles, commonly known as tar balls, represent one of the most abundant particles in aged biomass burning smoke. However, the detailed molecular level composition of ambient tar balls is largely unknown but critical to assess their environmental impacts. Ambient aerosol samples collected during a wildfire event, which were similar to 90% tar balls by number fraction, were analyzed using ultrahigh-resolution Orbitrap Elite mass spectrometry with four complementary ionization modes. Our results show the molecular composition of tar balls to be complex, composed of over 10,000 molecular formulas. Model estimated saturation mass concentrations and relative humidity-dependent glass-transition temperatures were consistent with low volatility and solid morphology as expected for tar balls. Room-temperature evaporation kinetics showed that these particles retained similar to 90% of their volume after 24 h of evaporation. The molecular complexity detected here signifies a continuum of carbonaceous species, ranging from C-3 to C-45 with continuous ranges of oxygenation and hydrogen saturation for each Cn. Approximately 24% of molecular formulas were estimated to be highly aromatic, which could indicate chemical compounds with negative health effects and which may contribute to visible light absorption. The carbon continuum observed here has significant implications for the molecular characterization of atmospheric organic matter. The level of complexity detected here should not be ignored in future studies, and we demonstrate that multiple analytical methods may be required to suitably interpret this complexity on a molecular level.
This paper presents findings from an online survey that explored public experiences of wildfire smoke, public health advisory information, risk perceptions, and protective actions in response to wildfire smoke in western Canada. Most respondents had wildfire smoke experiences lasting several days with decreased visibility, and many had difficulty breathing and changes to their health. While a majority of respondents were aware of the Air Quality Health Index and how to respond on a high risk day, some did not. Most respondents perceived the risk from wildfire smoke during their most recent experience to be extreme, severe, or moderate, with only 20% perceiving low risk from wildfire smoke. Wildfire smoke experiences affected risk perceptions, and female respondents perceived the risk from wildfire smoke to be higher in comparison to male respondents. Most respondents took protective actions during their most recent exposure to wildfire smoke, with the most popular measures including keeping windows and doors shut, and limiting time spent outdoors. Perceptions of wildfire smoke risks, experiencing health impacts from wildfire smoke, sex and highest level of education, and firefighting experience influenced protective actions. Recommendations to improve public health during wildfire smoke events and future research are included.
First Nation reserves in Canada are at high risk from wildfires, with many evacuated every year. There is a need to understand how First Nations are affected by wildfire evacuations to identify ways to reduce negative impacts. The First Nations Wildfire Evacuation Partnership has conducted research to explore evacuation experiences of seven First Nations in three Canadian provinces. This paper presents findings from research across the seven First Nations. Results show that few participating First Nations had an up to date emergency plan tailored to their community, which contributed to challenges during the evacuation. Family separation, insufficient information, and worries about losing their house caused considerable distress for evacuees. Wildfire smoke health impacts occurred, particularly for those who had pre-existing health conditions. Social and financial support, if available, helped evacuees during and after their evacuation. Several years after First Nations return home after a wildfire evacuation, lingering distress continues and some First Nations were still experiencing fiscal challenges as a result of the evacuation. Recommendations for reducing negative impacts of wildfire evacuations on First Nations people are discussed.
Mexico is expected to become the 6th largest economy in 2050. According to EDGAR database, in 2019 it was the largest polluting country in Latin America and the 13th in the world, regarding Greenhouse Gas (GHG) emissions. Lately, the new Administration has shifted its energy strategy from a renewable path into the reinforcement of conventional energy sources. In this context, new policies have to be deployed to meet the Paris Agreement goals. In such scenario, carbon capture and storage (CCS) technology may contribute reducing CO2 emissions as a way to transform Mexico into a low-carbon economy in the long term. However, the construction and operation and maintenance phases will embody environmental impacts that should be considered. This paper assesses the carbon capture investments required for the expected increasing capacity of natural gas power plants up to 2050 and their impact on production, value added, employment, climate change, acidification, water consumption and human health effects. An environmentally extended multi-regional the input-output analysis (EMRIO) is used to address Mexican policies for the period 2020-2050. Results show that the investment in capture technologies in Mexico allows a net reduction of the carbon emissions in Mexico that is pursued at a low cost (33 EUR/tCO(2)). This mitigation policy has important additional co-benefits in terms of domestic value added and employment creation of medium and high qualification. As for the environmental impacts, most of them are produced in the power plant due to the burning of the natural gas consumed.
BACKGROUND: Short-term exposure to ambient nitrogen dioxide (NO(2)) is associated with adverse respiratory and cardiovascular outcomes. Supplementation of omega-3 polyunsaturated fatty acids (PUFA) has shown protection against exposure to fine particulate matter. This study aims to investigate whether habitual omega-3 PUFA intake differentially modify the associations between respiratory and cardiovascular responses and short-term exposure to ambient NO(2). METHODS: Sixty-two healthy participants were enrolled into low or high omega-3 groups based on their habitual omega-3 PUFA intake. Each participant was repeatedly assessed for lung function, blood lipids, markers of coagulation and fibrinolysis, vascular function, and heart rate variability (HRV) in up to five sessions, each separated by at least 7 days. This study was carried out in the Research Triangle area of North Carolina, USA between October 2016 and September 2019. Daily ambient NO(2) concentrations were obtained from an area air quality monitoring station on the day of outcome assessment (Lag0), 4 days prior (Lag1-4), as well as 5-day moving average (5dMA). The associations between short-term exposure to NO(2) and the measured indices were evaluated using linear mixed-effects models stratified by omega-3 levels and adjusted by covariates including relative humidity and temperature. RESULTS: The average concentration of ambient NO(2) during the study periods was 5.3??3.8 ppb which was below the National Ambient Air Quality Standards (NAAQS). In the high omega-3 group, an interquartile range (IQR) increase in short-term NO(2) concentrations was significantly associated with increased lung function [e.g. 1.2% (95%CI: 0.2%, 2.2%) in FVC at lag1, 2.6% (95%CI: 0.4%, 4.8%) in FEV1 at 5dMA], decreased blood lipids [e.g. -2.6% (95%CI: -4.4%, -0.9%) in total cholesterol at lag2, -3.1% (95%CI: -6.1%, 0.0%) in HDL at 5dMA, and -3.1% (95%CI: -5.5%, -0.7%) in LDL at lag2], improved vascular function [e.g. 8.9% (95%CI: 0.6%, 17.2%) increase in FMD and 43.1% (95%CI: -79.8%, -6.3%) decrease in endothelin-1 at 5dMA], and changed HRV parameters [e.g. -7.2% (95%CI: -13.6%, -0.8%) in HFn and 13.4% (95%CI: 0.2%, 28.3%) in LF/HF ratio at lag3]. In the low omega-3 group, an IQR increase in ambient NO(2) was associated with elevations in coagulation markers (von Willebrand Factor, D-dimer) and a decrease in HRV (very-low frequency); however, null associations were observed between short-term NO(2) exposure and changes in lung function, blood lipids, and vascular function. CONCLUSIONS: The results in this study imply that dietary omega-3 PUFA consumption may offer respiratory and vascular benefits in response to short-term exposure of healthy adults to NO(2) levels below the NAAQS. TRIAL REGISTRATION: ClinicalTrials.gov ( NCT02921048 ).
Heavy-duty trucks and buses continue to contribute significantly to air pollution at the local, regional, and national level, often disproportionally affecting communities of color and low-income populations.
To ensure the progress needed on cleaning trucks and buses and to harness improvements in vehicle technologies, EPA will issue two major regulations over the next three years—the “Clean Trucks Plan” that will result in decreasing emissions from new heavy-duty vehicles, including long-haul tractors, buses, commercial delivery trucks, and many other types of trucks. These new rules will be major steps towards improving air quality and addressing the climate crisis.
Carbon monoxide (CO) is a colorless, odorless gas that can cause injury or death if inhaled. CO is a frequent secondary hazard induced by the aftereffects of natural hazards as individuals, families, and communities often seek alternative power sources for heating, cooking, lighting, and cleanup during the emergency and recovery phases of a disaster. These alternative power sources-such as portable generators, petroleum-based heaters, and vehicles-exhaust CO that can ultimately build to toxic levels in enclosed areas. Ever-increasing environmental and societal changes combined with an aging infrastructure are growing the odds of power failures during hazardous weather events, which, in turn, are increasing the likelihood of CO exposure, illness, and death. This study analyzed weather-related CO fatalities from 2000 to 2019 in the United States using death-certificate data, providing one of the longest assessments of this mortality. Results reveal that over 8300 CO fatalities occurred in the United States during the 20-yr study period, with 17% of those deaths affiliated with weather perils. Cool-season perils such as ice storms, snowstorms, and extreme cold were the leading hazards that led to situations causing CO fatalities. States in the Southeast and Northeast had the highest CO fatality rates, with winter having the greatest seasonal mortality. In general, these preventable CO poisoning influxes are related to a deficiency of knowledge on generator safety and the absence of working detectors and alarms in the enclosed locations where poisonings occur. Education and prevention programs that target the most vulnerable populations will help prevent future weather-related CO fatalities. Significance StatementCarbon monoxide exposure is common after weather disasters when individuals, families, and communities seek alternative power sources-such as portable generators, petroleum-based heaters, and vehicles-that exhaust this deadly, colorless, and odorless gas. Initially, we catalog carbon monoxide fatalities associated with weather events in the United States over two decades; thereafter, we illustrate the characteristics and patterns affiliated with these deaths. Results will assist public officials, first responders, and individuals in their decision-making and response before, during, and after weather events so that these deaths may be prevented in the future.
Many studies project that climate change can cause a significant number of excess deaths. Yet, in integrated assessment models (IAMs) that determine the social cost of carbon (SCC) and prescribe optimal climate policy, human mortality impacts are limited and not updated to the latest scientific understanding. This study extends the DICE-2016 IAM to explicitly include temperature-related mortality impacts by estimating a climate-mortality damage function. We introduce a metric, the mortality cost of carbon (MCC), that estimates the number of deaths caused by the emissions of one additional metric ton of CO2. In the baseline emissions scenario, the 2020 MCC is 2.26 × 10(‒4) [low to high estimate -1.71× 10(‒4) to 6.78 × 10(‒4)] excess deaths per metric ton of 2020 emissions. This implies that adding 4,434 metric tons of carbon dioxide in 2020-equivalent to the lifetime emissions of 3.5 average Americans-causes one excess death globally in expectation between 2020-2100. Incorporating mortality costs increases the 2020 SCC from $37 to $258 [-$69 to $545] per metric ton in the baseline emissions scenario. Optimal climate policy changes from gradual emissions reductions starting in 2050 to full decarbonization by 2050 when mortality is considered.
Research has shown that the healthcare sector is among the least green sectors and constitutes one of the largest contributors to greenhouse gas (GHG) emissions, posing risks to human health. This review discusses the development of a knowledge translation tool that aims to compare a range of interventions that can be applied in hospital settings to reduce the local GHG emissions and associated financial costs. It discusses several interventions that potentially have the most impact on GHG reduction and compares these to interventions that are commonly used in different hospital departments. The authors propose opportunities to advance the implementation of these interventions within hospital operations across many other geographic locations.
OBJECTIVE: Ongoing environmental changes increasingly require public health nurses to understand how environmental factors impact the health of populations. One approach to researching these impacts is incorporating environmental research methods to determine associations between harmful exposures and health. We use the Salton Sea in Southern California as a demonstration of how environmental exposure can be examined using air parcel trajectory analysis. DESIGN: We demonstrate a methodology for public health nurses to better understand and apply data from the Hybrid Single-Particle Lagrangian Integrated Trajectory meteorological model to estimate the effect of airborne particulate matter from a single source. MEASUREMENTS: We explain a method for tracking air parcel trajectories to populations: selection of meterological data to identify air parcels, geographic identification of population centers, generation of trajectories, classification of trajectory dispersions, adjusting for atmospheric stability, and merging environmental variables with health data. CONCLUSIONS: Climate change-related environmental events are expected to become more commonplace and disproportionately affect those populations impacted by health disparities. Public health nurses can identify communities at risk so that public health nursing researchers can use these techniques in collaboration with environmental science to robustly examine health effects of proximal air pollution sources for communities at risk.
Nitrogen dioxide (NO2) is responsible for aggravating respiratory diseases, particularly asthma. The aim of this study is to investigate the association between NO2 exposure and asthma emergency department (ED) visits during the cold season (November-February) in five populated locations (Sacramento, San Francisco, Fresno, Los Angeles, and San Diego) of California from 2005 to 2015 (1320 Days). Conditional logistic regression models were used to obtain the odds ratio (OR) and 95% confidence interval Cl)( associated with a 5 ppb increase in NO2 concentration for the 19,735 ED visits identified. An increase in NO2 exposure increased the odds of having asthma ED visits for the studied population. The potential effect modification by sex (female and male), race (White, Black, Hispanic, and Asian), and age (2-5, 6-18, 19-40, 41-64, and ?65) was explored. A 5 ppb increase in the concentration of NO2 during lag 0-30 was associated with a 56% increase in the odds of having an asthma ED visit (OR 1.560, Cl: 1.428-1.703). Sex was not found lo be a modifier. Asthma ED visits among all the racesiehnicities (except Asians) were associated with NO2 exposure. Whiles had the highest OR 75% (OR 1.750, CI: 1A17-2.160) at lag 0-30 in response to NO2 exposure. The association between NO2 exposure and asthma ED visits was positive among all age groups except fur 19 to 40 years old; the OR was higher among 2 to 18 year old (al lag 0-30: age group 2-5 (OR – 1.699, CI: 1.399-2.062), and age group 6-18 (OR – 1.568, CII.348-1.825)). For stratification by location, San Diego and Fresno were found to have the highest OR, compared lo the other studied locations. (C) 2020 Elsevier B.V. All rights reserved.
BACKGROUND: Hurricane Harvey made landfall along the Texas Gulf Coast as a Category 4 hurricane on August 25, 2017, producing unprecedented precipitation that devastated coastal areas. Catastrophic flooding in the City of Houston inundated industrial and residential properties resulting in the displacement and transfer of soil, sediment, and debris and heightening existing environmental justice (EJ) concerns. OBJECTIVES: The primary aim of this study was to evaluate the presence, distribution, and potential human health implications of polycyclic aromatic hydrocarbons (PAHs) in a residential neighborhood of Houston, Texas following a major hurricane. METHODS: Concentrations of PAHs in 40 soil samples collected from a residential neighborhood in Houston, Texas were measured. Spatial interpolation was applied to determine the distribution of PAHs. Potential human health risks were evaluated by calculating toxicity equivalency quotients (TEQs) and incremental excess lifetime cancer risk (IELCR). RESULTS: Total priority PAH concentrations varied across samples (range: 9.7 × 10(1) ng/g-1.6 × 10(4) ng/g; mean: 3.0 × 10(3) ng/g ± 3.6 × 10(3) standard deviation). Spatial analysis indicated a variable distribution of PAH constituents and concentrations. The IELCR analysis indicated that nine of the 40 samples were above minimum standards. CONCLUSIONS: Findings from this study highlight the need for fine scale soil testing in residential areas as well as the importance of site-specific risk assessment. COMPETING INTERESTS: The authors declare no competing financial interests.
Unprecedented inland precipitation and catastrophic flooding associated with Hurricane Harvey potentially redistributed contaminants from industrial sites and transportation infrastructure to recreational areas that make up networks of green infrastructure, creeks, and waterways used for flood control throughout the Greater Houston Area. Sediment samples were collected in parks located near the Buffalo Bayou watershed 1 week after Hurricane Harvey made landfall and again 7 weeks later. Total concentrations of the U.S. Environmental Protection Agency’s (EPA’s) 16 priority polycyclic aromatic hydrocarbons (PAHs) were measured in each sample at both time points. Diagnostic ratios were calculated to improve understanding of potential sources of PAHs after flooding. Diagnostic ratios suggest vehicular traffic to be a potential source for PAHs in parks. Although the concentrations of PAHs in all samples were below EPA actionable levels, given that no background values were available for comparison, it is difficult to quantify the impact flooding from Hurricane Harvey had on PAH concentrations in Houston parks. However, given the high frequency of flooding in Houston, and the concentration of industrial facilities and transportation infrastructure adjacent to recreation areas, these data demonstrate that PAHs were still present after unprecedented flooding. This study may also serve as a baseline for future efforts to understand the environmental health impacts of disasters.
Hurricane Harvey was a category four storm that induced catastrophic flooding in the Houston metropolitan area. Following the hurricane there was increased concern regarding chemical exposures due to damage caused by flood waters and emergency excess emissions from industrial facilities. This study utilized personal passive samplers in the form of silicone wristbands in Houston, TX to both assess chemical exposure to endocrine disrupting chemicals (EDCs) immediately after the hurricane and determine participant characteristics associated with higher concentrations of exposure. Participants from the Houston-3H cohort (n = 172) wore a wristband for seven days and completed a questionnaire to determine various flood-related and demographic variables. Bivariate and multivariate analysis indicated that living in an area with a high Area Deprivation Index (ADI) (indicative of low socioeconomic status), identifying as Black/African American or Latino, and living in the Houston neighborhoods of Baytown and East Houston were associated with increased exposure to EDCs. These results provide evidence of racial/ethnic and socioeconomic injustices in exposure to EDCs in the Houston Metropolitan Area. Since the multiple regression models conducted did not fully explain exposure (0.047 < R2 < 0.34), more research is needed on the direct sources of EDCs within this area to create effective exposure mitigation strategies.
Pollen grains may contain allergens that exacerbate allergic respiratory diseases like asthma and rhinitis. In the presence of water, pollen grains (10-100 μm) can rupture to produce sub-pollen particles (SPP) with diameters <2.5 μm, which in comparison to intact pollen grains, have longer atmospheric lifetimes and greater penetration to the lower lung. The current study examines SPP, fungal spores, and bacteria in size-resolved atmospheric particulate matter (PM) using chemical and biological tracers. During springtime tree pollen season in Iowa City, Iowa, fine particle (PM(2.5)) concentrations of fructose (a pollen chemical tracer) increased on rainy sampling periods, especially during severe thunderstorms, and peaked when a tornado struck nearby. Submicron fluorescent particles, measured by single-particle fluorescence spectroscopy, were also enhanced during rain events, particularly thunderstorms in agreement with the chemical tracer measurements. PM(2.5) sucrose (a pollen chemical tracer) concentrations were higher in early spring when nighttime temperatures were closer to freezing, while fructose concentrations were higher in late spring with warmer temperatures, consistent with chemical tracers being sensitive to seasonal temperature influences. The first co-located measurements of fructose and Bet v 1 (birch pollen allergen), indicated that SPP ranged in diameter from <0.25 to 2.5 μm during rainy sampling periods and that allergens and carbohydrates exhibited distinct size distributions. Meanwhile, mannitol (a fungal spore tracer) peaked on warm, dry days following rain and was primarily in supermicron particles (>1.0 μm), which is consistent with intact fungal spore diameters (1-30 μm). Bacterial endotoxins in PM also increased during extreme weather events, primarily in supermicron particles. While the concentrations of fructose, mannitol, and endotoxin all increased in PM(2.5) μm during thunderstorms, the greatest relative increase in concentration was observed for fructose. Together, these observations suggest that SPP containing starch granules and allergens (Bet v 1) were released during rainy sampling periods. This study advances the use of chemical tracers to track SPP and other bioaerosols in the atmosphere, by providing new insight to their size distribution and response to extreme weather conditions.
This study focused on the measurement of BTEX (benzene, toluene, ethylbenzene and xylene) concentrations in the air of various regions and indoor-outdoor environments in Bandar Abbas, Iran. Air samples were taken actively and analyzed by gas chromatography-mass spectrometry (GC-MS) during two one-month periods i.e., Feb 2020 (period I) and Sep/Oct 2020 (period II). The mean air temperature and the levels of all BTEX compounds were higher in period II. The highest total BTEX (t-BTEX) levels (median [min-max]) were found in the urban region (18.00 [5.21-67.24] μg m(-3)), followed by industrial region (7.00 [2.05-14.76] μg m(-3)) and rural region (2.81 [ND-7.38] μg m(-3)). The significant positive correlations between all BTEX compounds and T/B ratio >1 indicated the vehicular traffic as the main source of emission. At 95th percentile probability, the non-cancer risk of t-BTEX in urban region was only less than one order of magnitude below the threshold level of unity (1.91E-01) and the cancer risk of benzene exceeded the recommended level of 1.0E-06 by U.S. EPA in urban (7.69E-06) and industrial (2.97E-06) regions. It was found that the indoor/outdoor ratio of BTEX concentration in beauty salon and hospital was greater than 1. Overall, the current levels of BTEX in the ambient air of study area, especially near urban roadside and in some indoor environments, should not be overlooked and appropriate mitigation actions should be undertaken.
The generation and emission of volatile organic compounds (VOCs) affects the environment and air quality, playing an important role in global warming, depletion of atmospheric ozone and emission of unpleasant odors, but also directly affect human health. This study investigated the health risks of benzene, toluene, ethylbenzene, xylene (BTEX) compounds and biogas released in and around the municipal landfill. Sampling of the VOCs was carried out by the 1501NIOSH method from 8 points over 5 months. The samples were analyzed for BTEX in the ambient air of the landfill, resulting in 0.03-18.09 ppm concentrations, while for biogases a 0.08-25.2 ppm range was found. Assessment of definite health and potential risks showed that the lifetime cancer risk (LCR) for benzene and hazard quotient (HQ) for the BTEX components in all studied sampling sites are higher than the acceptable standard. The high concentration of benzene measured in ambient air indicated that petroleum compounds containing benzene and its derivatives have the highest value in the category of BTEX compounds among all emissions. Therefore, high concentrations of volatile compounds derived from VOCs, especially benzene, should be reduced at the site with control engineering measures.
Polycyclic aromatic hydrocarbons (PAHs) represent one of the major toxic pollutants associated with PM(2.5) with significant human health and climate effects. Because of local and long-range transport of atmospheric PAHs to receptor sites, higher global attentions have been focused to improve PAHs pollution emission management. In this study, PM(2.5) samples were collected at three urban sites located in the capital of Iran, Tehran, during the heating and non-heating periods (H-period and NH-period). The US EPA 16 priority PAHs were analyzed and the data were processed to the following detailed aims: (i) investigate the H-period and NH-period variations of PM(2.5) and PM(2.5)-bound PAHs concentrations; (ii) identify the PAHs sources and the source locations during the two periods; (iii) carry out a source-specific excess cancer risk (ECR) assessment highlighting the potential source locations contributing to the ECR using a hybrid approach. Total PAHs (TPAHs) showed significantly higher concentrations (1.56-1.89 times) during the H-period. Among the identified PAHs compounds, statistically significant periodical differences (p-value < 0.05) were observed only between eight PAHs species (Nap, BaA, Chr, BbF, BkF, BaP, IcdP, and DahA) at all three sampling sites which can be due to the significant differences of PAHs emission sources during H and NH-periods. High molecular weight (HMW) PAHs accounted for 52.7% and 46.8% on average of TPAHs during the H-period and NH-period, respectively. Positive matrix factorization (PMF) led to identifying four main PAHs sources including industrial emissions, petrogenic emissions, biomass burning and natural gas emissions, and vehicle exhaust emissions. Industrial and petrogenic emissions exhibited the highest contribution (19.8%, 27.2%, respectively) during the NH-period, while vehicle exhaust and biomass burning-natural gas emissions showed the largest contribution (40.7%, 29.6%, respectively) during the H-period. Concentration weighted trajectory (CWT) on factor contributions was used for tracking the potential locations of the identified sources. In addition to local sources, long-range transport contributed to a significant fraction of TPHAs in Tehran both during the H- and NH-periods. Source-specific carcinogenic risks assessment apportioned vehicle exhaust (44.2%, 2.52 × 10(-4)) and biomass burning-natural gas emissions (33.9%, 8.31 × 10(-5)) as the main cancer risk contributors during the H-period and NH-period, respectively. CWT maps pointed out the different distribution patterns associated with the cancer risk from the identified sources. This will allow better risk management through the identification of priority PAHs sources.
BACKGROUND: In recent years, the prevalence of dust events has increased in the region and the world. According to the Meteorological Organization, the most frequent days with dust events are on stations located in Khuzestan province. Objective: Assessment of the effects of dust events and meteorological elements on stroke morbidity in health in Iran: a health promotion approach. MATERIALS AND METHODS: The present study was a retrospective cohort study 2020 and 2013 provided between based on ecological data-based on population. Information about patients with stroke was obtained from the hospital. Information on the dust events and meteorological elements was also from the data center of the Meteorological Organization of Iran. Using STATA the correlation between the diseases and the, 14 statistical software version occurrence of dust events and changes in meteorological elements was obtained and the statistical model (Spearman correlation coefficient) individually estigate the equation was used inv modified by Poisson regression simultaneous effect of variables. RESULTS: the results of adjusted statistical models show that increasing the severity of dust event increases the risk of stroke in males (lag 0-21 confidence interval [CI] 95% = 1.496-1.0067 relative risk [RR] = 1.03 P = 0.01). Increasing the average wind speed also increases the risk of stroke in males (lag 0-3 CI 95% = 1.0491-0.9996 RR = 1.02 P = 0.05). Increased rainfall and average relative humidity increase the risk of stroke in people under 60 years (lag 0-7 CI 95% = 1.0012-0.9058 RR = 1.95 P = 0.05). Increasing the average daily temperature reduces the risk of stroke in males (lag 0-3 CI 95% = 0.9874-0.9254 RR = 0.51 P < 0.001). CONCLUSION: Increasing the intensity of dust storms along with meteorological elements has increased the risk of stroke. However, increasing the average temperature has had a protective effect on the risk of stroke.
Recife is recognized as the 16th most vulnerable city to climate change in the world. In addition, the city has levels of air pollutants above the new limits proposed by the World Health Organization (WHO) in 2021. In this sense, the present study had two main objectives: (1) To evaluate the health (and economic) benefits related to the reduction in mean annual concentrations of PM(10) and PM(2.5) considering the new limits recommended by the WHO: 15 µg/m(3) (PM(10)) and 5 µg/m(3) (PM(2.5)) and (2) To simulate the behavior of these pollutants in scenarios with increased temperature (2 and 4 °C) using machine learning. The averages of PM(2.5) and PM(10) were above the limits recommended by the WHO. The scenario simulating the reduction in these pollutants below the new WHO limits would avoid more than 130 deaths and 84 hospital admissions for respiratory or cardiovascular problems. This represents a gain of 15.2 months in life expectancy and a cost of almost 160 million dollars. Regarding the simulated temperature increase, the most conservative (+ 2 °C) and most drastic (+ 4 °C) scenarios predict an increase of approximately 6.5 and 15%, respectively, in the concentrations of PM(2.5) and PM(10), with a progressive increase in deaths attributed to air pollution. The study shows that the increase in temperature will have impacts on air particulate matter and health outcomes. Climate change mitigation and pollution control policies must be implemented for meeting new WHO air quality standards which may have health benefits.
BACKGROUND: There is currently a scarcity of air pollution epidemiologic data from low- and middle-income countries (LMICs) due to the lack of air quality monitoring in these countries. Additionally, there is limited capacity to assess the health effects of wildfire smoke events in wildfire-prone regions like Brazil’s Amazon Basin. Emerging low-cost air quality sensors may have the potential to address these gaps. OBJECTIVES: We investigated the potential of PurpleAir PM2.5 sensors for conducting air pollution epidemiologic research leveraging the United States Environmental Protection Agency’s United States-wide correction formula for ambient PM(2.5). METHODS: We obtained raw (uncorrected) PM(2.5) concentration and humidity data from a PurpleAir sensor in Rio Branco, Brazil, between 2018 and 2019. Humidity measurements from the PurpleAir sensor were used to correct the PM(2.5) concentrations. We established the relationship between ambient PM(2.5) (corrected and uncorrected) and daily all-cause respiratory hospitalization in Rio Branco, Brazil, using generalized additive models (GAM) and distributed lag non-linear models (DLNM). We used linear regression to assess the relationship between daily PM(2.5) concentrations and wildfire reports in Rio Branco during the wildfire seasons of 2018 and 2019. RESULTS: We observed increases in daily respiratory hospitalizations of 5.4% (95%CI: 0.8%, 10.1%) for a 2-day lag and 5.8% (1.5%, 10.2%) for 3-day lag, per 10 μg/m(3) PM(2.5) (corrected values). The effect estimates were attenuated when the uncorrected PM(2.5) data was used. The number of reported wildfires explained 10% of daily PM2.5 concentrations during the wildfire season. DISCUSSION: Exposure-response relationships estimated using corrected low-cost air quality sensor data were comparable with relationships estimated using a validated air quality modeling approach. This suggests that correcting low-cost PM(2.5) sensor data may mitigate bias attenuation in air pollution epidemiologic studies. Low-cost sensor PM(2.5) data could also predict the air quality impacts of wildfires in Brazil’s Amazon Basin.
One of the central problems in large cities is air pollution, mainly caused by vehicular emissions. Tropospheric ozone is an atmospheric oxidizing gas that forms in minimal amounts naturally, affecting peoples’ health. This pollutant is formed by the NO2 photolysis, creating a main peak during the day. Nighttime secondary peaks occur in several parts of the world, but their intensity and frequency depend on the local condition. In this sense, this works aims to study the local characteristics for tropospheric nocturnal ozone levels in the Metropolitan Area of Sao Paulo, in Brazil, using the Simple Photochemical Module coupled to the Brazilian Developments on the Regional Atmospheric Modeling System. For this, three different situations of nocturnal occurrence were studied. The results show that the nocturnal maximum of ozone concentrations is related to the vertical transport of this pollutant from higher levels of the atmosphere to the surface and is not related to the synoptic condition.
BACKGROUND: Long-term exposure to fine particles ≤2.5 μm in diameter (PM2.5) has been linked to cancer mortality. However, the effect of wildfire-related PM2.5 exposure on cancer mortality risk is unknown. This study evaluates the association between wildfire-related PM2.5 and site-specific cancer mortality in Brazil, from 2010 to 2016. METHODS AND FINDINGS: Nationwide cancer death records were collected during 2010-2016 from the Brazilian Mortality Information System. Death records were linked with municipal-level wildfire- and non-wildfire-related PM2.5 concentrations, at a resolution of 2.0° latitude by 2.5° longitude. We applied a variant difference-in-differences approach with quasi-Poisson regression, adjusting for seasonal temperature and gross domestic product (GDP) per capita. Relative risks (RRs) and 95% confidence intervals (CIs) for the exposure for specific cancer sites were estimated. Attributable fractions and cancer deaths were also calculated. In total, 1,332,526 adult cancer deaths (age ≥ 20 years), from 5,565 Brazilian municipalities, covering 136 million adults were included. The mean annual wildfire-related PM2.5 concentration was 2.38 μg/m3, and the annual non-wildfire-related PM2.5 concentration was 8.20 μg/m3. The RR for mortality from all cancers was 1.02 (95% CI 1.01-1.03, p < 0.001) per 1-μg/m3 increase of wildfire-related PM2.5 concentration, which was higher than the RR per 1-μg/m3 increase of non-wildfire-related PM2.5 (1.01 [95% CI 1.00-1.01], p = 0.007, with p for difference = 0.003). Wildfire-related PM2.5 was associated with mortality from cancers of the nasopharynx (1.10 [95% CI 1.04-1.16], p = 0.002), esophagus (1.05 [95% CI 1.01-1.08], p = 0.012), stomach (1.03 [95% CI 1.01-1.06], p = 0.017), colon/rectum (1.08 [95% CI 1.05-1.11], p < 0.001), larynx (1.06 [95% CI 1.02-1.11], p = 0.003), skin (1.06 [95% CI 1.00-1.12], p = 0.003), breast (1.04 [95% CI 1.01-1.06], p = 0.007), prostate (1.03 [95% CI 1.01-1.06], p = 0.019), and testis (1.10 [95% CI 1.03-1.17], p = 0.002). For all cancers combined, the attributable deaths were 37 per 100,000 population and ranged from 18/100,000 in the Northeast Region of Brazil to 71/100,000 in the Central-West Region. Study limitations included a potential lack of assessment of the joint effects of gaseous pollutants, an inability to capture the migration of residents, and an inability to adjust for some potential confounders. CONCLUSIONS: Exposure to wildfire-related PM2.5 can increase the risks of cancer mortality for many cancer sites, and the effect for wildfire-related PM2.5 was higher than for PM2.5 from non-wildfire sources.
We quantified the impacts of wildfire-related PM2.5 on 2 million hospital admissions records due to cardiorespiratory diseases in Brazil between 2008 and 2018. The national analysis shows that wildfire waves are associated with an increase of 23% (95%CI: 12%-33%) in respiratory hospital admissions and an increase of 21% (95%CI: 8%-35%) in circulatory hospital admissions. In the North (where most of the Amazon region is located), we estimate an increase of 38% (95%CI: 30%-47%) in respiratory hospital admissions and 27% (95%CI: 15%-39%) in circulatory hospital admissions. Here we report epidemiological evidence that air pollution emitted by wildfires is significantly associated with a higher risk of cardiorespiratory hospital admissions. Brazil is a wildfire-prone region, and few studies have investigated the health impacts of wildfire exposure. Here, the authors show that wildfire waves are associated with an increase of 23% in respiratory hospital admissions and an increase of 21% in circulatory hospital admissions in Brazil.
Background Birth defects are a major cause of poor health outcomes during both childhood and adulthood. A growing body of evidence demonstrated associations between air pollution exposure during pregnancy and birth defects. To date, there is no study looking at birth defects and exposure to wildfire-related air pollution, which is suggested as a type of air pollution source with high toxicity for reproductive health. Objective Our study addresses this gap by examining the association between birth defects and wildfire smoke exposure in Brazil between 2001 and 2018. Based on known differences of impacts of wildfires across different regions of Brazil, we hypothesized differences in risks of birth defects for different regions. Methods We used a logistic regression model to estimate the odds ratios (ORs) for individual birth defects (12 categories) associated with wildfire exposure during each trimester of pregnancy. Results Among the 16,825,497 birth records in our study population, there were a total of 7595 infants born in Brazil between 2001 and 2018 with birth defects in any of the selected categories. After adjusting for several confounders in the primary analysis, we found statistically significant OR for three birth defects, including cleft lip/cleft palate [OR: 1.007 (95% CI: 1.001; 1.013)] during the second trimester of exposure, congenital anomalies of the respiratory system [OR: 1.013 (95% CI: 1.002; 1.023)] in the second trimester of exposure, and congenital anomalies of the nervous system [OR: 1.002 (95% CI: 1.001; 1.003)] during the first trimester of exposure for the regions South, North, and Midwest, respectively. Significance Our results suggest that maternal exposure to wildfire smoke during pregnancy may increase the risk of an infant being born with some congenital anomaly. Considering that birth defects are associated with long-term disability, impacting families and the healthcare system (e.g., healthcare costs), our findings should be of great concern to the public health community. Impact statement Our study focused on the association between maternal exposure to wildfire smoke in Brazil during pregnancy and the risk of an infant being born with congenital anomalies, which presents serious public health and environmental challenges.
Air pollution from Amazon fires has adverse impacts on human health. The number of fires in the Amazon has increased in recent years, but whether this increase was driven by deforestation or climate has not been assessed. We analyzed relationships between fire, deforestation, and climate for the period 2003 to 2019 among selected states across the Brazilian Legal Amazon (BLA). A statistical model including deforestation, precipitation and temperature explained ∼80% of the variability in dry season fire count across states when totaled across the BLA, with positive relationships between fire count and deforestation. We estimate that the increase in deforestation since 2012 increased the dry season fire count in 2019 by 39%. Using a regional chemistry-climate model combined with exposure-response associations, we estimate this increase in fire resulted in 3,400 (95UI: 3,300-3,550) additional deaths in 2019 due to increased exposure to particulate air pollution. If deforestation in 2019 had increased to the maximum recorded during 2003-2019, the number of active fire counts would have increased by an additional factor of 2 resulting in 7,900 (95UI: 7,600-8,200) additional premature deaths. Our analysis demonstrates the strong benefits of reduced deforestation on air quality and public health across the Amazon.
BACKGROUND: In the context of climate change and deforestation, Brazil is facing more frequent and unprecedented wildfires. Wildfire-related PM(2·5) is associated with multiple adverse health outcomes; however, the magnitude of these associations in the Brazilian context is unclear. We aimed to estimate the association between daily exposure to wildfire-related PM(2·5) and cause-specific hospital admission and attributable health burden in the Brazilian population using a nationwide dataset from 2000 to 2015. METHODS: In this nationwide time-series analysis, data for daily all-cause, cardiovascular, and respiratory hospital admissions were collected through the Brazilian Unified Health System from 1814 municipalities in Brazil between Jan 1, 2000, and Dec 31, 2015. Daily concentrations of wildfire-related PM(2·5) were estimated using the 3D chemical transport model GEOS-Chem at a 2·0° latitude by 2·5° longitude resolution. A time-series analysis was fitted using quasi-Poisson regression to quantify municipality-specific effect estimates, which were then pooled at the regional and national levels using random-effects meta-analyses. Analyses were stratified by sex and ten age groups. The attributable fraction and attributable cases of hospital admissions due to wildfire-related PM(2·5) were also calculated. FINDINGS: At the national level, a 10 μg/m(3) increase in wildfire-related PM(2·5) was associated with a 1·65% (95% CI 1·51-1·80) increase in all-cause hospital admissions, a 5·09% (4·73-5·44) increase in respiratory hospital admissions, and a 1·10% (0·78-1·42) increase in cardiovascular hospital admissions, over 0-1 days after the exposure. The effect estimates for all-cause hospital admission did not vary by sex, but were particularly high in children aged 4 years or younger (4·88% [95% CI 4·47-5·28]), children aged 5-9 years (2·33% [1·77-2·90]), and people aged 80 years and older (3·70% [3·20-4·20]) compared with other age groups. We estimated that 0·53% (95% CI 0·48-0·58) of all-cause hospital admissions were attributable to wildfire-related PM(2·5), corresponding to 35 cases (95% CI 32-38) per 100 000 residents annually. The attributable rate was greatest for municipalities in the north, south, and central-west regions, and lowest in the northeast region. Results were consistent for all-cause and respiratory diseases across regions, but remained inconsistent for cardiovascular diseases. INTERPRETATION: Short-term exposure to wildfire-related PM(2·5) was associated with increased risks of all-cause, respiratory, and cardiovascular hospital admissions, particularly among children (0-9 years) and older people (≥80 years). Greater attention should be paid to reducing exposure to wildfire smoke, particularly for the most susceptible populations. FUNDING: Australian Research Council and Australian National Health and Medical Research Council.
The March 2015 extraordinary hydrometeomlogical event in the Andes cordillera caused severe floods in the southern Atacama Desert. One of the most affected cities was CopiapO (northern Chile) located downstream of the junction between the CopiapO river and its ephemeral tributary Quebrada Paipote. This work analyses the features of this catastrophic flood and relates them with the identified impacts. A large volume of water mixed with fine sediments overflowed the tributary channel generating a flood that affected 72% of the urban area. The rheological (velocity, density and flow regime) and sedimentary features of the flow reveal the occurrence of massive mudflows that infilled the space available inside the buildings, buried the streets with a sandy mud deposit of more than 30 cm medium thickness and collapsed the sewer network. The post-event survey carried out by the Ministry of Housing and Urban Planning (MINVU) was used for the development of fragility curves that allows modelling the probability of damage. Results indicate that the greatest probability of building damage is generated by the accumulation of sediments instead of by the flow depth. On the other hand, once the very fine grain sediments of the top of the deposit dried up, it increased the concentration of post-event suspension particulate matter, causing a health issue. This work highlights the need to understand mudflow processes and their consequences in arid environments to improve urban planning and mitigate future damages since their impacts strongly affect infrastructures and communities.
Health risks associated with heatwaves and ozone pollution are projected to rise significantly under the effects of climate change. Although the literature has considered the future health risks of heatwaves and ozone pollution separately, the compound effects remain unexplored, and this could potentially impair risk-prevention plans. Here, using a model from the Coupled Model Intercomparison Project Phase 6 (CMIP6) and four shared socioeconomic pathway (SSPs) scenarios, we explore the global tempo-spatial trend and country disparity of compound-event days and population-exposure person-days. We find that compared with the baseline of 1995-2014, by 2071-2090 under the high-emission scenario of SSP3-7.0, an increased annual mean of 34.6 compound-event days and mean population-exposure of 93.5 million person-days is expected. Furthermore, lower-income countries are facing dramatically higher exposure compared with higher-income countries. These projections could contribute to developing targeted mitigation and adaptation plans.
INTRODUCTION: There is an increasing interest in understanding whether air pollutants modify the quantitative relationships between temperature and health outcomes. The results of available studies were, however, inconsistent. This study aims to sum up the current evidence and provide a comprehensive understanding of this topic. METHODS: We conducted an electronic search in PubMed (MEDLINE), EMBASE, Web of Science Core Collection, and ProQuest Dissertations and Theses. The modified Navigation Guide was applied to evaluate the quality and strength of evidence. We calculated pooled temperature-related mortality at low and high pollutant levels respectively, using the random-effects model. RESULTS: We identified 22 eligible studies, eleven of which were included in the meta-analysis. Significant effect modification was observed on heat effects for all-cause and non-accidental mortality by particulate matter with an aerodynamic diameter of <10 μm (PM(10)) and ozone (O(3)) (p < 0.05). The excess risks (ERs) for all-cause and non-accidental mortality were 5.4% (4.4%, 6.4%) and 6.3% (4.8%, 7.8%) at the low PM(10) level, 8.8% (7.5%, 10.1%) and 11.4% (8.7%, 14.2%) at the high PM(10) level, respectively. As for O(3), the ERs for all-cause and non-accidental mortality were 5.1% (3.9%, 6.3%) and 3.6% (0.1%, 7.2%) at the low O(3) level, 7.6% (6.3%, 9.0%) and 12.5% (4.7%, 20.9%) at the high O(3) level, respectively. Surprisingly, the heat effects on cardiovascular mortality were found to be lower at high carbon monoxide (CO) levels [ERs = 5.4% (3.9%, 6.9%)] than that at low levels [ERs = 9.4% (7.0%, 11.9%)]. The heterogeneity varied, but the results of sensitivity analyses were generally robust. Significant effect modification by air pollutants was not observed for heatwave or cold effects. CONCLUSIONS: PM(10) and O(3) modify the heat-related all-cause and non-accidental mortality, indicating that policymakers should consider air pollutants when establishing heat-health warning systems. Future studies with comparable designs and settings are needed.
Evidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM(10), PM(2.5)), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m(3) increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM(2.5) and PM(10) respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19.
Air pollution is widely viewed as a serious threat to human health and a contributor to deaths. Air pollution appears to be linked to the progression of emphysema, according to epidemiological data. The objective of this study was to examine associations between air pollution and the progression of emphysema using a meta-analysis. A meta-analysis was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol. A systematic literature search was conducted using the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Medline, Embase, PubMed, and Web of Science bibliographic databases. A random-effects model for the meta-analysis was implemented to summarize effect estimates of sufficiently comparable outcomes and pollutants (e.g.: particulate matter, nitrogen oxides and ozone), and the results were visualized in forest plots. We observed that a 1-ppb rise in O3 was associated with a 0.30 increase in the percent emphysema progression (95% CI: 0.02, 0.57, p < 0.05). In contrast, no significant association was found between PM2.5 or NO2 exposure and the percent change in emphysema. Increasing O-3 concentrations may have an impact on and exacerbate human health conditions such as emphysema and respiratory diseases. Air quality and climate change should be concerns for future environmental policies and protection measures.
Surface ozone (O(3)) is an oxidizing gaseous pollutant; long-term exposure to high O(3) concentrations adversely affects human health. Based on daily surface O(3) concentration data, the spatiotemporal characteristics of O(3) concentration, exposure risks, and driving meteorological factors in 347 cities and 10 major countries (China, Japan, India, South Korea, the United States, Poland, Spain, Germany, France, and the United Kingdom) worldwide were analyzed using the MAKESENS model, Moran’ I analysis, and Generalized additive model (GAM). The results indicated that: in the boreal spring season from 2015 to 2020, the global O(3) concentration exhibited an increasing trend at a rate of 0.6 μg/m(3)/year because of the volatile organic compounds (VOCs) and NOx changes caused by human activities. Due to the lockdown policies after the outbreak of COVID-19, the average O(3) concentration worldwide showed an inverted U-shaped growth during the study period, increasing from 21.9 μg/m(3) in 2015 to 27.3 μg/m(3) in 2019, and finally decreasing to 25.9 μg/m(3) in 2020. According to exposure analytical methods, approximately 6.32% of the population (31.73 million people) in the major countries analyzed reside in rapidly increasing O(3) concentrations. 6.53% of the population (32.75 million people) in the major countries were exposed to a low O(3) concentration growth environment. Thus, the continuous increase of O(3) concentration worldwide is an important factor leading to increasing threats to human health. Further we found that mean wind speed, maximum temperature, and relative humidity are the main factors that determine the change of O(3) concentration. Our research results are of great significance to the continued implementation of strict air quality policies and prevention of population hazards. However, due to data limitations, this research can only provide general trends in O(3) and human health, and more detailed research will be carried out in the follow-up. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12403-022-00463-7.
In this article we review the physical and chemical properties of methane (CH4) relevant to impacts on climate, ecosystems, and air pollution, and examine the extent to which this is reflected in climate and air pollution governance. Although CH4 is governed under the UNFCCC climate regime, its treatment there is limited to the ways in which it acts as a “CO2 equivalent” climate forcer on a 100-year time frame. The UNFCCC framework neglects the impacts that CH4 has on near-term climate, as well its impacts on human health and ecosystems, which are primarily mediated by methane’s role as a precursor to tropospheric ozone. Frameworks for air quality governance generally address tropospheric ozone as a pollutant, but do not regulate CH4 itself. Methane’s climate and air quality impacts, together with its alarming rise in atmospheric concentrations in recent years, make it clear that mitigation of CH4 emissions needs to be accelerated globally. We examine challenges and opportunities for further progress on CH4 mitigation within the international governance landscapes for climate change and air pollution.
PURPOSE OF REVIEW: Fine particulate matter (PM(2.5)) and ground-level ozone (O(3)) pose a significant risk to human health. The World Health Organization (WHO) has recently revised healthy thresholds for both pollutants. The formation and evolution of PM(2.5) and O(3) are however governed by complex physical and multiphase chemical processes, and therefore, it is extremely challenging to mitigate both pollutants simultaneously. Here, we review mechanisms and discuss the science-informed pathways for effective and simultaneous mitigation of PM(2.5) and O(3). RECENT FINDINGS: Global warming has led to a general increase in biogenic emissions, which can enhance the formation of O(3) and secondary organic aerosols. Reductions in anthropogenic emissions during the COVID-19 lockdown reduced PM(2.5); however, O(3) was enhanced in several polluted regions. This was attributed to more intense sunlight due to low aerosol loading and non-linear response of O(3) to NO (x) . Such contrasting physical and chemical interactions hinder the formulation of a clear roadmap for clean air over such regions. SUMMARY: Atmospheric chemistry including the role of biogenic emissions, aerosol-radiation interactions, boundary layer, and regional-scale transport are the key aspects that need to be carefully considered in the formulation of mitigation pathways. Therefore, a thorough understanding of the chemical effects of the emission reductions, changes in photolytic rates and boundary layer due to perturbation of solar radiation, and the effect of meteorological/seasonal changes are needed on a regional basis. Statistical emulators and machine learning approaches can aid the cumbersome process of multi-sector multi-species source attribution.
Global air pollution and climate change are major threats to planetary health. These threats are strongly linked through the short-lived climate forcers (SLCFs); ozone (O(3)), aerosols, and methane (CH(4)). Understanding the impacts of ambitious SLCF mitigation in different source emission sectors on planetary health indicators can help prioritize international air pollution control strategies. A global Earth system model is applied to quantify the impacts of idealized 50% sustained reductions in year 2005 emissions in the eight largest global anthropogenic source sectors on the SLCFs and three indicators of planetary health: global mean surface air temperature change (∆GSAT), avoided PM(2.5)-related premature mortalities and gross primary productivity (GPP). The model represents fully coupled atmospheric chemistry, aerosols, land ecosystems and climate, and includes dynamic CH(4). Avoided global warming is modest, with largest impacts from 50% cuts in domestic (-0.085 K), agriculture (-0.034 K), and waste/landfill (-0.033 K). The 50% cuts in energy, domestic, and agriculture sector emissions offer the largest opportunities to mitigate global PM(2.5)-related health risk at around 5%-7% each. Such small global impacts underline the challenges ahead in achieving the World Health Organization aspirational goal of a 2/3 reduction in the number of deaths from air pollution by 2030. Uncertainty due to natural climate variability in PM(2.5) is an important underplayed dimension in global health risk assessment that can vastly exceed uncertainty due to the concentration-response functions at the large regional scale. Globally, cuts to agriculture and domestic sector emissions are the most attractive targets to achieve climate and health co-benefits through SLCF mitigation.
The global food system is essential for the health and wellbeing of society, but is also a major cause of environmental damage. Some impacts, such as on climate change, have been the subject of intense recent inquiry, but others, such as on air quality, are not as well understood. Here, we systematically synthesize the literature to identify the impacts on ambient PM2.5 (particulate matter with diameter <= 2.5 mu m), which is the strongest contributor to premature mortality from exposure to air pollution. Our analysis indicates that the life-cycle of the global food system (pre-production, production, post-production, consumption and waste management) accounts for 58% of anthropogenic, global emissions of primary PM2.5, 72% of ammonia (NH3), 13% of nitrogen oxides (NO (x) ), 9% of sulfur dioxide (SO2), and 19% of non-methane volatile organic compounds (NMVOC). These emissions result in at least 890 000 ambient PM2.5-related deaths, which is equivalent to 23% of ambient PM2.5-related deaths reported in the Global Burden of Disease Study 2015. Predominant contributors include livestock and crop production, which contribute >50% of food-related NH3 emissions, and land-use change and waste burning, which contribute up to 95% of food-related primary PM2.5 emissions. These findings are largely underestimated given the paucity of data from the post-production and consumption stages, total underestimates in NH3 emissions, lack of sector-scale analysis of PM2.5-related deaths in South America and Africa, and uncertainties in integrated exposure-response functions. In addition, we identify mitigation opportunities-including shifts in food demand, changes in agricultural practices, the adoption of clean and low-energy technologies, and policy actions-that can facilitate meeting food demand with minimal PM2.5 impacts. Further research is required to resolve sectoral-scale, region-specific contributions to PM2.5-related deaths, and assess the efficiency of mitigation strategies. Our review is positioned to inform stakeholders, including scientists, engineers, policymakers, farmers and the public, of the health impacts of reduced air quality resulting from the global food system.
Particulate matter with aerodynamic diameter ≤2.5 μm (PM(2.5)) concentrations vary between countries with similar carbon dioxide (CO(2)) emissions, which can be partially explained by differences in air pollution control efficacy. However, no indicator of air pollution control efficacy has yet been developed. We aimed to develop such an indicator, and to evaluate its global and temporal distribution and its association with country-level health metrics. A novel indicator, ambient population-weighted average PM(2.5) concentration per unit per capita CO(2) emission (PM(2.5)/CO(2)), was developed to assess country-specific air pollution control efficacy (abbreviated as APCI). We estimated and mapped the global average distribution of APCI and its changes during 2000-2016 across 196 countries. Pearson correlation coefficients and Generalized Additive Mixed Model (GAMM) were used to evaluate the relationship between APCI and health metrics. APCI varied by country with an inverse association with economic development. APCI showed an almost stable trend globally from 2000 to 2016, with the low-income groups increased and several countries (China, India, Bangladesh) decreased. The Pearson correlation coefficients between APCI and life expectancy at birth (LE), infant-mortality rate (IMR), under-five year of age mortality rate (U5MR) and logarithm of per capita GDP (LPGDP) were -0.57, 0.65, 0.66, -0.59 respectively (all P values < 0.001). APCI could explain international variation of LE, IMR and U5MR. The associations between APCI and LE, IMR, U5MR were independent of per capita GDP and climatic factors. We consider APCI to be a good indicator for air pollution control efficacy given its relation to important population health indicators. Our findings provide a new metric to interpret health inequity across the globe from the point of climate change and air pollution control efficacy.
Accumulating evidence underscores the large role played by the environment in the health of communities and individuals. We review the currently known contribution of environmental exposures and pollutants on kidney disease and its associated morbidity. We review air pollutants, such as particulate matter; water pollutants, such as trace elements, per- and polyfluoroalkyl substances, and pesticides; and extreme weather events and natural disasters. We also discuss gaps in the evidence that presently relies heavily on observational studies and animal models, and propose using recently developed analytic methods to help bridge the gaps. With the expected increase in the intensity and frequency of many environmental exposures in the decades to come, an improved understanding of their potential effect on kidney disease is crucial to mitigate potential morbidity and mortality.
Previous research demonstrates that low-income countries face higher risks than high-income countries from toxic pollution and climate change. However, the relationship between these two risks is little explored or tested, and efforts to address the risks are often independent and uncoordinated. We argue that the global risks from toxic pollution and climate change are highly correlated and should be jointly analyzed in order to inform and better target efforts to reduce or mitigate both risks. We provide such analysis for 176 countries and found a strong (rs = -0.798;95%CI -0.852, -0.727) and significant (p<0.0001) relationship between the distribution of climate risk and toxic pollution. We also found that inequities in pollution production, economic status, and institutional readiness are interconnected and exacerbate risk for countries already in the highest risk categories for both toxic and non-toxic (greenhouse gas) pollution. The findings have policy implications, including the use of the proposed Target assessment to decide where best to address toxic and non-toxic pollution simultaneously, based on the need to minimize human suffering and maximize return on effort.
The coronavirus disease 2019 (COVID-19) pandemic has significantly disrupted global metal mining and associated supply chains. Here we analyse the cascading effects of the metal mining disruption associated with the COVID-19 pandemic on the economy, climate change, and human health. We find that the pandemic reduced global metal mining by 10-20% in 2020. This reduction subsequently led to losses in global economic output of approximately 117 billion US dollars, reduced CO(2) emissions by approximately 33 million tonnes (exceeding Hungary’s emissions in 2015), and reduced human health damage by 78,192 disability-adjusted life years. In particular, copper and iron mining made the most significant contribution to these effects. China and rest-of-the-world America were the most affected. The cascading effects of the metal mining disruption associated with the pandemic on the economy, climate change, and human health should be simultaneously considered in designing green economic stimulus policies.
During wildfire smoke events public health agencies release advisories to stay indoors, close doors and windows, and operate a portable air cleaner (PAC). The do-it-yourself (DIY) air cleaner consisting of a box fan and a furnace filter is a widely used low-cost alternative to commercial PACs because of its increased accessibility. In this study, we evaluate the clean air delivery rate (CADR) of different DIY air cleaner designs for reducing simulated wildfire smoke and identify operating parameters that may impact their performance and use. The simplest formulation of a DIY air cleaner (box fan with taped on minimum effectiveness reporting value – [MERV] 13 furnace filter) had a CADR of 111.2 ± 1.3 ft(3) /min (CFM). Increasing the fan flow by changing the fan type, increasing the fan setting, or reducing the pressure drop across the filtering surface increased the CADR. Large increases in CADR could be obtained by using a shroud (40%), using a 4″ thick filter (123%) using two filters in a wedge shape (137%), or using four filters in a Corsi-Rosenthal (CR) box design (261%). The CADR was greatly reduced with filters heavily loaded with smoke, pointing to the need for frequent filter changes during smoke events.
In recent years, wildland fires have occurred more frequently and with increased intensity in many fire-prone areas. In addition to the direct life and economic losses attributable to wildfires, the emitted smoke is a major contributor to ambient air pollution, leading to significant public health impacts. Wildfire smoke is a complex mixture of particulate matter (PM), gases such as carbon monoxide, nitrogen oxide, and volatile and semi-volatile organic compounds. PM from wildfire smoke has a high content of elemental carbon and organic carbon, with lesser amounts of metal compounds. Epidemiological studies have consistently found an association between exposure to wildfire smoke (typically monitored as the PM concentration) and increased respiratory morbidity and mortality. However, previous reviews of the health effects of wildfire smoke exposure have not established a conclusive link between wildfire smoke exposure and adverse cardiovascular effects. In this review, we systematically evaluate published epidemiological observations, controlled clinical exposure studies, and toxicological studies focusing on evidence of wildfire smoke exposure and cardiovascular effects, and identify knowledge gaps. Improving exposure assessment and identifying sensitive cardiovascular endpoints will serve to better understand the association between exposure to wildfire smoke and cardiovascular effects and the mechanisms involved. Similarly, filling the knowledge gaps identified in this review will better define adverse cardiovascular health effects of exposure to wildfire smoke, thus informing risk assessments and potentially leading to the development of targeted interventional strategies to mitigate the health impacts of wildfire smoke.
Due to climate change, bushfires are becoming a more frequent and more severe phenomenon which contributes to poor health effects associated with air pollution. In pregnancy, environmental exposures can have lifelong consequences for the fetus, but little is known about these consequences in the context of bushfire smoke exposure. In this review we summarise the current knowledge in this area, and propose a potential mechanism linking bushfire smoke exposure in utero to poor perinatal and respiratory outcomes in the offspring. Bushfire smoke exposure is associated with poor pregnancy outcomes including reduced birth weight and an increased risk of prematurity. Some publications have outlined the adverse health effects on young children, particularly in relation to emergency department presentations and hospital admissions for respiratory problems, but there are no studies in children who were exposed to bushfire smoke in utero. Prenatal stress is likely to occur as a result of catastrophic bushfire events, and stress is known to be associated with poor perinatal and respiratory outcomes. Changes to DNA methylation are potential epigenetic mechanisms linking both smoke particulate exposure and prenatal stress to poor childhood respiratory health outcomes. More research is needed in large pregnancy cohorts exposed to bushfire events to explore this further, and to design appropriate mitigation interventions, in this area of global public health importance.
BACKGROUND: Fine particulate matter (PM(2.5)) produced by landscape fires is thought to be more toxic than that from non-fire sources. However, the effects of “fire-sourced” PM(2.5) on acute respiratory infection (ARI) are unknown. METHODS: We combined Demographic and Health Survey (DHS) data from 48 countries with gridded global estimates of PM(2.5) concentrations from 2003 to 2014. The proportions of fire-sourced PM(2.5) were assessed by a chemical transport model using a variety of PM(2.5) source data. We tested for associations between ARI and short-term exposure to fire- and “non-fire-sourced” PM(2.5) using a bidirectional case-crossover analysis. The robustness and homogeneity of the associations were examined by sensitivity analyses. We also established a nonlinear exposure-response relationship between fire- and non-fire-sourced PM(2.5) and ARI using a two-dimensional spline function. RESULTS: The study included 36,432 children under 5 years who reported ARI symptoms. Each 1 µg/m(3) increment of fire-sourced PM(2.5) was associated with a 3.2 % (95 % confidence interval [CI] 0.2, 6.2) increment in the risk of ARI. This effect was comparable to that of each ∼5 µg/m(3) increment in PM(2.5) from non-fire sources (3.1 %; 95 % CI 2.4, 3.7). The association between ARI and total PM(2.5) concentration was significantly mediated by the proportion of fire-sourced particles. Nonlinear analysis showed that the risk of ARI was increased by both fire- and non-fire-sourced PM(2.5), but especially by the former. CONCLUSIONS: PM(2.5) produced by landscape fire was more strongly associated to ARI among children under 5 years than that from non-fire sources.
Exposures to ambient fine particulate matter (PM(2.5)) and cold ambient temperatures have been identified as important risk factors in contributing towards the global mortality from chronic obstructive pulmonary disease (COPD). Despite China currently being the country with the largest population in the world, previous relative risk (RR) models have considered little or no information from the ambient air pollution related cohort studies in the country. This likely provides a less accurate picture of the trend in air pollution attributable mortality in the country over time. A novel relative risk model called pollutant-temperature exposure (PTE) model is proposed to estimate the RR attributable to the combined effect of air pollution and ambient temperature in a population. In this paper, the pollutant concentration-response curve was extrapolated from the cohort studies in China, whereas the temperature response curve was extracted from a study in Yangtze River Delta (YRD) region. The performance of the PTE model was compared with the integrated exposure-response (IER) model using the data of YRD region, which revealed that the estimated relative risks of the PTE model were noticeably higher than the IER model during the winter season. Furthermore, the predictive ability of the PTE model was validated using actual data of Ningbo city, which showed that the estimated RR using the PTE model with 1-month moving average data showed a good result with the trend of actual COPD mortality, indicated by a lower root mean square error (RMSE = 0.956). By considering the combined effect of ambient air pollutant and ambient temperature, the PTE model is expected to provide more accurate relative risk estimates for the regions with high levels of ambient PM(2.5) and seasonal variation of ambient temperature.
Climate change and air pollution can interact to amplify risks to human health and crop production. This has significant implications for our ability to reach the Sustainable Development Goals (e.g. SDGs 2, 3, 13, 15) and for the design of effective mitigation and adaptation policies and risk management. To be able to achieve the SDG targets, closer integration of climate change and air pollution both in terms of impact assessment for human health and agricultural productivity and respective policy development is needed. Currently, studies estimating the impacts of climate and air pollutants on human health and crops mostly treat these stressors separately, and the methods used by the health and agricultural science communities differ. Better insights into the methods applied in the different communities can help to improve existing and develop new methods to advance our knowledge about the combined impacts of climate change and air pollution on human health and crops. This topical review provides an overview of current methodologies applied in the two fields of human health and agricultural crop impact studies, ranging from empirical regression-based and experimental methods to more complex process-based models. The latter are reasonably well developed for estimating impacts on agricultural crops, but not for health impacts. We review available literature addressing the combined effects of climate and air pollution on human health or agricultural productivity to provide insights regarding state-of-the-art knowledge and currently available methods in the two fields. Challenges to assess the combined effect of climate and air pollution on human health and crops, and opportunities for both fields to learn from each other, are discussed.
New epidemiological studies acknowledge the detrimental effects of dust storms on health. The aim of this study was to systematically review the effects of dust storms on the morbidity and mortality rates of cardiovascular and respiratory diseases. The results of this study were obtained based on articles published in English-language journals. For the purpose of this study, all articles published until the end of 2020 based on the search in the “Scopus,” “Web of Science,” and “PubMed” databases were selected. Articles were searched independently by two trained researchers. Dust storms are the cause of many diseases and health-related complications, of which cardiovascular and respiratory diseases are common. It is necessary to recognize and investigate the harmful effects of dust storms to prevent serious harms to human societies. In the reviewed articles, the impact of dust storms on several diseases, including cardiovascular and respiratory diseases, has been analyzed. Most of these articles acknowledge the effect of dust storms on increasing the incidence and mortality rate of these diseases, although in some articles this effect is not statistically significant. Many studies conducted around the world confirm the harmful effects of dust storms on cardiovascular and respiratory diseases, including increase in the number and duration of hospitalizations, as well as increase in mortality and exacerbation of these diseases. However, some studies do not consider the harmful effects of dust storms on the above diseases to be statistically significant.
Climate change and obesity were considered threats to our planet long before the onset of COVID-19. The recent pandemic has enhanced the global burden of both pre-existing crises. The aim of this narrative review is to explore the interaction between the three concurrent crises and the future of our planet should they not be dealt with accordingly. A PubMed and Google Scholar literature search was performed using different combinations of search strategies and using the keywords obesity , climate/temperature change , cold/hot temperatures , and COVID-19 . High global greenhouse gas (GHG) emissions link obesity and climate change as a result of the interplay between biological and behavioural factors. COVID-19 mitigation measures have indirectly impacted obesity and GHG emissions through the shift in dietary habits, restricted mobility, the impact on healthcare services, and enhanced psychological stress. Furthermore, COVID-19 has a more detrimental effect if acquired by an obese individual, with a higher chance of hospitalization and mechanical ventilation. This leads to higher GHG emissions and negative repercussions on the climate. A tri-directional relationship exists between obesity, climate change, and COVID-19. Various factors contribute to this relationship, but unless urgent global integrated action plans are implemented that target all three calamities, and not just COVID-19, a devastating and unsustainable future may ensue.
This review paper discusses the Stockholm Paradigm (SP) as a theoretical framework and practical computational instrument for studying and assessing the risk of emerging infectious diseases (EIDs) as a result of climate change. The SP resolves the long-standing parasite paradox and explains how carbon emissions in the atmosphere increase parasites’ generalization and intensify host switches from animals to humans. The SP argues that the growing rate of novel EID occurrence caused by mutated zoonotic pathogens is related to the following factors brought together as a unified issue of humanity: (a) carbon emissions and consequent climate change; (b) resettlement/migration of people with hyper-urbanization; (c) overpopulation; and (d) human-induced distortion of the biosphere. The SP demonstrates that, in an evolutionary way, humans now play a role migratory birds once played in spreading parasite pathogens between the three Earth megabiotopes (northern coniferous forest belt; tropical/equatorial rainforest areas; and hot/cold deserts), i.e., the role of “super-spreaders” of parasitic viruses, bacteria, fungi and protozoa. This makes humans extremely vulnerable to the EID threat. The SP sees the +1.0-+1.2 °C limit as the optimal target for the slow, yet feasible curbing of the EID hazard to public health (150-200 years). Reaching merely the +2.0 °C level will obviously be an EID catastrophe, as it may cause two or three pandemics each year. We think it useful and advisable to include the SP-based research in the scientific repository of the Intergovernmental Panel on Climate Change, since EID appearance and spread are indirect but extremely dangerous consequences of climate change.
Background: It is crucial to understand the benefits to human health from decarbonisation to galvanise action among decision makers. Most of our existing evidence comes from modelling studies and little is known about the extent to which the health co-benefits of climate change mitigation actions are realised upon implementation. We aim to analyse evidence from mitigation actions that have been implemented across a range of sectors and scales, to identify those that can improve and sustain health, while accelerating progress towards a zero-carbon economy. Objectives: To understand the implementation process of actions and the role of key actors; explain the contextual elements influencing these actions; summarise what effects, both positive and negative, planned and unplanned they may have on emissions of greenhouse gases and health; and to summarise environmental, social, or economic co-benefits. Data: We will review evidence collected through partnership with existing data holders and an open call for evidence. We will also conduct a hand search of reference lists from systematic reviews and websites of organisations relevant to climate change mitigation. Screening: Screening will be done by two reviewers according to a pre-defined inclusion and exclusion criteria. Analysis: We will identify gaps where implementation or evaluation of implementation of mitigation actions is lacking. We will synthesise the findings to describe how actions were implemented and how they achieved results in different contexts, identifying potential barriers and facilitators to their design, implementation, and uptake. We will also synthesise their effect on health outcomes and other co-benefits. Quantitative synthesis will depend on the heterogeneity of outcomes and metrics. Conclusions: Findings will be used to identify lessons that can be learned from successful and unsuccessful mitigation actions, to make inferences on replicability, scalability, and transferability and will contribute to the development of frameworks that can be used by policy makers.
Polycyclic aromatic hydrocarbons (PAHs) are a large group of organic compounds that have 2-7 benzene rings. PAHs causes many complications in humans, including respirations and increased risk of cancer. The most important fixed and mobile sources (PAHs) include food, industrial pollution, and car exhaust. The most common ways of entering the body (PAHs) are through direct contact, seafood, grilled meat, inhalation of PAHs, and contaminated water. From various studies and many publications in the field, the major issue with PAHs is increased risk of cancer, such as cancer of lungs if inhaled or skin if in contact with skin, cancer of stomach or gastrointestinal in smoked or barbecued fish and meat products. The purpose of this review study was to the epidemiological literature on the side effect of Polycyclic aromatic hydrocarbons (PAHs) on respiratory diseases and the risk factors related to Cancer. Six hundred and fifty-five articles according to different databases: Google Scholar, PubMed, Web of Science, BMJ, Springer, and Science Direct were retrieved. Forty-two studies were screened after review and, 27 full-text articles were entered into the analysis process. Finally, 15 articles were selected for this study. Studies have shown the effects of PAHs in increasing the risk of infection in the respiratory system, including asthma, lung dysfunction, and various cancers, such as skin, digestive tract, lung, and blood. The results showed that polycyclic aromatic hydrocarbons could increase the probability and risk incidence of cancers of the lung, skin, bladder, and respiratory diseases, such as asthma and lung dysfunction. Reducing the emission of polycyclic aromatic hydrocarbons (PAHs) due to activities, such as cooking, car exhaust, wildfire, and power plant can be a very influential factor in reducing the health endpoint of this pollutant, especially respiratory diseases, and Cancer.
Climate change can have economic consequences, affecting the nutritional intake of populations and increasing food insecurity, as it negatively affects diet quality parameters. One way to mitigate these consequences is to change the way we produce and consume our food. A healthy and sustainable diet aims to promote and achieve the physical, mental, and social well-being of the populations at all life stages, while protecting and safeguarding the resources of the planet and preserving biodiversity. Over the past few years, several indexes have been developed to evaluate dietary sustainability, most of them based on the EAT-Lancet reference diet. The present review explains the problems that arise in human nutrition as a result of climate change and presents currently available diet sustainability indexes and their applications and limitations, in an effort to aid researchers and policy actors in identifying aspects that need improvement in the development of relevant indexes. Overall, great heterogeneity exists among the indicators included in the available indexes and their methodology. Furthermore, many indexes do not adequately account for the diets’ environmental impact, whereas others fall short in the economic impact domain, or the ethical aspects of sustainability. The present review reveals that the design of one environmentally friendly diet that is appropriate for all cultures, populations, patients, and geographic locations is a difficult task. For this, the development of sustainable and healthy diet recommendations that are region-specific and culturally specific, and simultaneously encompass all aspects of sustainability, is required.
Climate change can cause multiply potential health issues in urban areas, which is the most susceptible environment in terms of the presently increasing climate volatility. Urban greening strategies make an important part of the adaptation strategies which can ameliorate the negative impacts of climate change. It was aimed to study the potential impacts of different kinds of greenings against the adverse effects of climate change, including waterborne, vector-borne diseases, heat-related mortality, and surface ozone concentration in a medium-sized Hungarian city. As greening strategies, large and pocket parks were considered, based on our novel location identifier algorithm for climate risk minimization. A method based on publicly available data sources including satellite pictures, climate scenarios and urban macrostructure has been developed to evaluate the health-related indicator patterns in cities. The modelled future- and current patterns of the indicators have been compared. The results can help the understanding of the possible future state of the studied indicators and the development of adequate greening strategies. Another outcome of the study is that it is not the type of health indicator but its climate sensitivity that determines the extent to which it responds to temperature rises and how effective greening strategies are in addressing the expected problem posed by the factor.
Air pollution is responsible for many adverse effects on human beings. Thermal discomfort, on the other hand, is able to overload the human body and eventually provoke health implications due to the heat imbalance. Methods: The aim of the presented work is to study the behavior of two bio-climatic indices and statistical characteristics of the air quality index for Sofia city-the capital of Bulgaria for the period 2008-2014. The study is based on the WRF-CMAQ model system simulations with a spatial resolution of 1 km. The air quality is estimated by the air quality index, taking into account the influence of different pollutants and the thermal conditions by two indices, respectively, for hot and cold weather. It was found that the recurrence of both the heat and cold index categories and of the air quality categories have heterogeneous space distribution and well manifested diurnal and seasonal variability. For all of the situations, only O-3 and PM10 are the dominant pollutants-these which determine the AQI category. It was found that AQI1, AQI2, and AQI3, which fall in the “Low” band, have the highest recurrence during the different seasons, up to more than 70% in some places and situations. The recurrence of AQI10 (very high) is rather small-no more than 5% and concentrated in small areas, mostly in the city center. The Heat index of category “Danger” never appears, and the Heat index of category “Extreme caution” appears only in the spring and summer with the highest recurrence of less than 5% in the city center. For the Wind-chill index category, “Very High Risk” never appears, and the category “High Risk” appears with a frequency of about 1-2%. The above leads to the conclusion that both from a point of view of bioclimatic and air quality indices, the human health risks in the city of Sofia are not as high.
Urbanization, anthropogenic activities, and social determinants such as poverty and literacy rate greatly contribute to heat-related mortalities. The 2003 strong heat wave (Lucifer) in France resulted in catastrophic health consequences in the region that may be attributed to urbanization and other anthropogenic activities. Amiens is a medium-sized French city, where the average temperature has increased since the year 2000. In this study, we evaluated the Heat Vulnerability Index (HVI) in Amiens for extreme heat days recorded during three years (2018-2020). We used the principal component analysis (PCA) technique for fine-scale vulnerability mapping. The main types of considered data included (a) socioeconomic and demographic data, (b) air pollution, (c) land use and cover, (d) elderly heat illness, (e) social vulnerability, and (f) remote sensing data (land surface temperature (LST), mean elevation, normalized difference vegetation index (NDVI), and normalized difference water index (NDWI)). The output maps identified the hot zones through comprehensive GIS analysis. The resultant maps showed that high HVI exists in three typical areas: (1) areas with dense population and low vegetation, (2) areas with artificial surfaces (built-up areas), and (3) industrial zones. Low-HVI areas are in natural landscapes such as rivers and grasslands. Our analysis can be implemented in other cities to highlight areas at high risk of extreme heat and air pollution.
Cities are increasingly confronted with multiple environmental and climatic stressors. Especially during heatwaves, street canyons are both producers and sufferers of air pollution and urban heat island (UHI) effects, with severe risks on public health. To better design mitigation measures, it is important to consider both the microclimate behaviors as well as the perceptions of the local population. Therefore, this study examined pedestrian perceptions and microclimate modelings to understand outdoor thermal comfort conditions and air pollution dispersion in the case study neighborhood of Dortmund Marten, Germany. A field survey with measurement points at two street canyons for climatic variables and questionnaires on subjective thermal comfort and air pollution was conducted on a hot day during the heatwave period in August 2020. As a cost-effective method for modeling input generation, we extracted spatial and spectral data like albedo, roof materials and tree locations out of remote sensing imageries. Finally, we compared the modeling results of the physiological equivalent temperature (PET) index, particulate matter concentrations and air temperatures with empirical field measurement data and the questionnaire responses. Results indicate that during hot summer days with light winds from the east, the north-south orientated street canyon with tree arrangements tends to act as a tunnel for particulate matter accumulation. Coincidently, pedestrians show less thermal discomfort than calculated PET values in that particular area during morning and daytime, which underlines the dichotomy of such places. On the other hand, the low rise east-west orientated street canyon shows higher PET votes than predicted by the model. However, particulate matter concentrations were considerably underestimated by the model, while air temperature predictions provided meaningful results. The proposed workflow shows the potential to accelerate future preparations of input data for microclimate modelings, while the results can enhance wind-sensitive planning procedures and heat stress resilience in mid-latitude urban neighborhoods.
Monitoring microclimate variables within cities with high accuracy is an ongoing challenge for a better urban resilience to climate change. Assessing the intra-urban characteristics of a city is of vital importance for ensuring fine living standards for citizens. Here, a novel mobile microclimate station is applied for monitoring the main microclimatic variables regulating urban and intra-urban environment, as well as directionally monitoring shortwave radiation and illuminance and hence systematically map for the first time the effect of urban surfaces and anthropogenic heat. We performed day-time and night-time monitoring campaigns within a historical city in Italy, characterized by substantial urban structure differentiations. We found significant intra-urban variations concerning variables such as air temperature and shortwave radiation. Moreover, the proposed experimental framework may capture, for the very first time, significant directional variations with respect to shortwave radiation and illuminance across the city at microclimate scale. The presented mobile station represents therefore the key missing piece for exhaustively identifying urban environmental quality, anthropogenic actions, and data driven modelling toward risk and resilience planning. It can be therefore used in combination with satellite data, stable weather station or other mobile stations, e.g. wearable sensing techniques, through a citizens’ science approach in smart, livable, and sustainable cities in the near future.
BACKGROUND: Desert dust events in Mediterranean countries, originating mostly from the Sahara and Arabian deserts, have been linked to climate change and are associated with significant increase in mortality and hospital admissions from respiratory causes. The MEDEA clinical intervention study in children with asthma is funded by EU LIFE+ program to evaluate the efficacy of recommendations aiming to reduce exposure to desert dust and related health effects. METHODS: This paper describes the design, methods, and challenges of the MEDEA childhood asthma study, which is performed in two highly exposed regions of the Eastern Mediterranean: Cyprus and Greece-Crete. Eligible children are recruited using screening surveys performed at primary schools and are randomized to three parallel intervention groups: a) no intervention for desert dust events, b) interventions for outdoor exposure reduction, and c) interventions for both outdoor and indoor exposure reduction. At baseline visits, participants are enrolled on MEDena® Health-Hub, which communicates, alerts and provides exposure reduction recommendations in anticipation of desert dust events. MEDEA employs novel environmental epidemiology and telemedicine methods including wearable GPS, actigraphy, health parameters sensors as well as indoor and outdoor air pollution samplers to assess study participants’ compliance to recommendations, air pollutant exposures in homes and schools, and disease related clinical outcomes. DISCUSSION: The MEDEA study evaluates, for the first time, interventions aiming to reduce desert dust exposure and implement novel telemedicine methods in assessing clinical outcomes and personal compliance to recommendations. In Cyprus and Crete, during the first study period (February-May 2019), a total of 91 children participated in the trial while for the second study period (February-May 2020), another 120 children completed data collection. Recruitment for the third study period (February-May 2021) is underway. In this paper, we also present the unique challenges faced during the implementation of novel methodologies to reduce air pollution exposure in children. Engagement of families of asthmatic children, schools and local communities, is critical. Successful study completion will provide the knowledge for informed decision-making both at national and international level for mitigating the health effects of desert dust events in South-Eastern Europe. TRIAL REGISTRATION: ClinicalTrials.gov: NCT03503812 , April 20, 2018.
BACKGROUND: The evidence is sparse regarding the associations between serious mental illnesses (SMIs) prevalence and environmental factors in adulthood as well as the geographic distribution and variability of these associations. In this study, we evaluated the association between availability and proximity of green and blue space with SMI prevalence in England as a whole and in its major conurbations (Greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle). METHODS AND FINDINGS: We carried out a retrospective analysis of routinely collected adult population (≥18 years) data at General Practitioner Practice (GPP) level. We used data from the Quality and Outcomes Framework (QOF) on the prevalence of a diagnosis of SMI (schizophrenia, bipolar affective disorder and other psychoses, and other patients on lithium therapy) at the level of GPP over the financial year April 2014 to March 2018. The number of GPPs included ranged between 7,492 (April 2017 to March 2018) to 7,997 (April 2014 to March 2015) and the number of patients ranged from 56,413,719 (April 2014 to March 2015) to 58,270,354 (April 2017 to March 2018). Data at GPP level were converted to the geographic hierarchy unit Lower Layer Super Output Area (LSOA) level for analysis. LSOAs are a geographic unit for reporting small area statistics and have an average population of around 1,500 people. We employed a Bayesian spatial regression model to explore the association of SMI prevalence in England and its major conurbations (greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle) with environmental characteristics (green and blue space, flood risk areas, and air and noise pollution) and socioeconomic characteristics (age, ethnicity, and index of multiple deprivation (IMD)). We incorporated spatial random effects in our modelling to account for variation at multiple scales. Across England, the environmental characteristics associated with higher SMI prevalence at LSOA level were distance to public green space with a lake (prevalence ratio [95% credible interval]): 1.002 [1.001 to 1.003]), annual mean concentration of PM2.5 (1.014 [1.01 to 1.019]), and closeness to roads with noise levels above 75 dB (0.993 [0.992 to 0.995]). Higher SMI prevalence was also associated with a higher percentage of people above 24 years old (1.002 [1.002 to 1.003]), a higher percentage of ethnic minorities (1.002 [1.001 to 1.002]), and more deprived areas. Mean SMI prevalence at LSOA level in major conurbations mirrored the national associations with a few exceptions. In Birmingham, higher average SMI prevalence at LSOA level was positively associated with proximity to an urban green space with a lake (0.992 [0.99 to 0.998]). In Liverpool and Manchester, lower SMI prevalence was positively associated with road traffic noise ≥75 dB (1.012 [1.003 to 1.022]). In Birmingham, Liverpool, and Manchester, there was a positive association of SMI prevalence with distance to flood zone 3 (land within flood zone 3 has ≥1% chance of flooding annually from rivers or ≥0.5% chance of flooding annually from the sea, when flood defences are ignored): Birmingham: 1.012 [1.000 to 1.023]; Liverpool and Manchester: 1.016 [1.006 to 1.026]. In contrast, in Leeds, there was a negative association between SMI prevalence and distance to flood zone 3 (0.959 [0.944 to 0.975]). A limitation of this study was because we used a cross-sectional approach, we are unable to make causal inferences about our findings or investigate the temporal relationship between outcome and risk factors. Another limitation was that individuals who are exclusively treated under specialist mental health care and not seen in primary care at all were not included in this analysis. CONCLUSIONS: Our study provides further evidence on the significance of socioeconomic associations in patterns of SMI but emphasises the additional importance of considering environmental characteristics alongside socioeconomic variables in understanding these patterns. In this study, we did not observe a significant association between green space and SMI prevalence, but we did identify an apparent association between green spaces with a lake and SMI prevalence. Deprivation, higher concentrations of air pollution, and higher proportion of ethnic minorities were associated with higher SMI prevalence, supporting a social-ecological approach to public health prevention. It also provides evidence of the significance of spatial analysis in revealing the importance of place and context in influencing area-based patterns of SMI.
Desert dust storms (DDS) are natural events that impact not only populations close to the emission sources but also populations many kilometers away. Countries located across the main dust sources, including countries in the Eastern Mediterranean, are highly affected by DDS. In addition, climate change is expanding arid areas exacerbating DDS events. Currently, there are no intervention measures with proven, quantified exposure reduction to desert dust particles. As part of the wider “MEDEA” project, co-funded by LIFE 2016 Programme, we examined the effectiveness of an indoor exposure-reduction intervention (i.e., decrease home ventilation during DDS events and continuous use of air purifier during DDS and non-DDS days) across homes and/or classrooms of schoolchildren with asthma and adults with atrial fibrillation in Cyprus and Crete-Greece. Participants were randomized to a control or intervention groups, including an indoor intervention group with exposure reduction measures and the use of air purifiers. Particle sampling, PM(10) and PM(2.5,) was conducted in participants’ homes and/or classrooms, between 2019 and 2022, during DDS-free weeks and during DDS days for as long as the event lasted. In indoor and outdoor PM(10) and PM(2.5) samples, mass and content in main and trace elements was determined. Indoor PM(2.5) and PM(10) mass concentrations, adjusting for premise type and dust conditions, were significantly lower in the indoor intervention group compared to the control group (PM(2.5-intervention)/PM(2.5-control) = 0.57, 95% CI: 0.47, 0.70; PM(10-intervention)/PM(10-control) = 0.59, 95% CI: 0.49, 0.71). In addition, the PM(2.5) and PM(10) particles of outdoor origin were significantly lower in the intervention vs. the control group (PM(2.5) infiltration intervention-to-control ratio: 0.49, 95% CI: 0.42, 0.58; PM(10) infiltration intervention-to-control ratio: 0.68, 95% CI: 0.52, 0.89). Our findings suggest that the use of air purifiers alongside decreased ventilation measures is an effective protective measure that reduces significantly indoor exposure to particles during DDS and non-DDS in high-risk population groups.
The cold season is usually accompanied by an increased incidence of respiratory infections and increased air pollution from combustion sources. As we are facing growing numbers of COVID-19 cases caused by the novel SARS-CoV-2 coronavirus, an understanding of the impact of air pollutants and meteorological variables on the incidence of respiratory infections is crucial. The incidence of influenza-like illness (ILI) can be used as a close proxy for the circulation of influenza viruses. Recently, SARS-CoV-2 has also been detected in patients with ILI. Using distributed lag nonlinear models, we analyzed the association between ILI, meteorological variables and particulate matter concentration in Bialystok, Poland, from 2013-2019. We found an exponential relationship between cumulative PM(2.5) pollution and the incidence of ILI, which remained significant after adjusting for air temperatures and a long-term trend. Pollution had the greatest effect during the same week, but the risk of ILI was increased for the four following weeks. The risk of ILI was also increased by low air temperatures, low absolute humidity, and high wind speed. Altogether, our results show that all measures implemented to decrease PM(2.5) concentrations would be beneficial to reduce the transmission of SARS-CoV-2 and other respiratory infections.
This study examines whether climate change-associated environmental stressors, including air and noise pollution, local heat levels, as well as a lack of surrounding greenspace, mediate the effects of local poverty on mental health, using the 28-item General Health Questionnaire. We recruited 478 adults who were representative of eleven of Berlin’s inner-city neighborhoods. The relationship of individual-level variables, neighborhood-level sociodemographic and environmental data from the Berlin Senate (Department for Urban Development, Building and Housing) to mental health was assessed in a multilevel model using SPSS. We found that neither local exposure to environmental stressors, nor available greenspace as a protective factor, mediated the effects of local poverty on variance in mental health (all p values > 0.2). However, surrounding greenspace (r = -0.24, p < 0.001), nitrogen dioxide levels (r = 0.10, p < 0.05), noise pollution (rho = 0.15, p < 0.01), and particle pollution (r = 0.12, p < 0.001) were associated with local poverty, which, more strongly than individual factors, accounted for variance in mental health (β = 0.47, p < 0.001). Our analysis indicates that the effects of local poverty on mental health are not mediated by environmental factors. Instead, local poverty was associated with both an increased mental health burden and the exposure to climate-related environmental stressors.
Ultrafine particles (UFP), harmful to human health, are emitted at high levels from motorized traffic. Bicycle commuting is increasingly encouraged to reduce traffic emissions and increase physical activity, but higher breathing rates increase inhaled UFP concentrations while in traffic. We assessed exposure to UFP while cycling along a fixed 8.5 km inner-city route in Copenhagen, on weekdays over six weeks (from September to October 2020), during morning and afternoon rush-hour, as well as morning non-rush-hour, traffic time periods starting from 07:45, 15:45, and 09:45 h, respectively. Continuous measurements were made (each second) of particle number concentration (PNC) and location. PNC levels were summarized and compared across time periods. We used generalized additive models to adjust for meteorological factors, weekdays and trends. A total of 61 laps were completed, during 28 days (∼20 per time period). Overall mean PNC was 18,149 pt/cm^(3) (range 256-999,560 pt/cm^(3)) with no significant difference between morning rush-hour (18003 pt/cm^(3)), afternoon rush-hour (17560 pt/cm^(3)) and late morning commute (17560 pt/cm^(3)) [p = 0.85]. There was substantial spatial variation of UFP exposure along the route with highest PNC levels measured at traffic intersections (∼38,000-42000 pt/cm^(3)), multiple lane roads (∼38,000-40000 pt/cm^(3)) and construction sites (∼44,000-51000 pt/cm^(3)), while lowest levels were measured at smaller streets, areas with open built environment (∼12,000 pt/cm^(3)), as well as at a bus-only zone (∼15,000 pt/cm^(3)). UFP exposure in inner-city Copenhagen did not differ substantially when bicycling in either rush-hour or non-rush-hour, or morning or afternoon, traffic time periods. UFP exposure varied substantially spatially, with highest concentrations around intersections, multiple lane roads, and construction sites. This suggests that exposure to UFP is not necessarily reduced by avoiding rush-hours, but by avoiding sources of pollution along the bicycling route.
BACKGROUND: The chronic effects of ozone have only rarely been investigated in disease burden studies to date. Our goal was to determine this disease burden in Germany over the period 2007-2016, with particular attention to estimation based on effect estimates adjusted for particulate matter (PM2.5) and nitrogen dioxide (NO2). METHODS: The nationwide, high-spatial-resolution (2 km × 2 km), population-based exposure to ozone in the summer months (“summer ozone”) was calculated on the basis of modeled ozone data and population counts in Germany. Next, risk estimates derived from cohort studies were used to quantify the burden of chronic obstructive pulmonary disease (COPD). Data on population counts, life expectancy, and mortality in Germany were used to reflect the situation across the country as accurately as possible. RESULTS: The estimates of years of life lost (YLL) due to summer ozone ranged from 18.33 per 100 000 people (95% confidence interval [14.02; 22.08]) in 2007 to 35.77 per 100 000 people [27.45; 42.98] in 2015. These findings indicate that ozone affects the COPD burden independently of other harmful components of the air. No clear secular trend in the COPD burden can be seen over the period 2007 to 2016. CONCLUSION: Long-term exposure to ozone contributes to the COPD burden among the general population in Germany. As climate change may lead to a rise in the ozone concentration, more intensive research is required on the effects of ozone on health.
While many authors have described the adverse health effects of poor air quality and meteorological extremes, there remain inconsistencies on a regional scale as well as uncertainty about the single and joint effects of atmospheric predictors. In this context, we investigated the short-term impacts of weather and air quality on moderate extreme cancer-related mortality events for the urban area of Augsburg, Southern Germany, during the period 2000-2017. First, single effects were uncovered by applying a case-crossover routine. The overall impact was assessed by performing a Mann-Whitney U testing scheme. We then compared the results of this procedure to extreme noncancer-related mortality events. In a second step, we found periods with contemporaneous significant predictors and carried out an in-depth analysis of these joint-effect periods. We were interested in the atmospheric processes leading to the emergence of significant conditions. Hence, we applied the Principal Component Analysis to large-scale synoptic conditions during these periods. The results demonstrate a strong linkage between high-mortality events in cancer patients and significantly above-average levels of nitrogen dioxide (NO(2)) and particulate matter (PM(2.5)) during the late winter through spring period. These were mainly linked to northerly to easterly weak airflow under stable, high-pressure conditions. Especially in winter and spring, this can result in low temperatures and a ground-level increase and the accumulation of air pollution from heating and traffic as well as eastern lateral advection of polluted air. Additionally, above-average temperatures were shown to occur on the days before mortality events from mid-summer through fall, which was also caused by high-pressure conditions with weak wind flow and intense solar radiation. Our approach can be used to analyse medical data with epidemiological as well as climatological methods while providing a more vivid representation of the underlying atmospheric processes.C
BACKGROUND: Previous studies reported a link between short-term exposure to environmental stressors (air pollution and air temperature) and atherothrombotic cardiovascular diseases. However, only few of them reported consistent associations with venous thromboembolism (VTE). Our aim was to estimate the association between daily air temperature and particulate matter (PM) air pollution with hospital admissions for pulmonary embolism (PE) and venous thrombosis (VT) at national level in Italy. METHODS: We collected daily hospital PE and VT admissions from the Italian Ministry of Health during 2006-2015 in all the 8,084 municipalities of Italy, and we merged them with air temperature and daily PM10 concentrations estimated by satellite-based spatiotemporal models. First, we applied multivariate Poisson regression models at province level. Then, we obtained national overall effects by random-effects meta-analysis. RESULTS: This analysis was conducted on 219,952 PE and 275,506 VT hospitalizations. Meta-analytical results showed weak associations between the two exposures and the study outcomes in the full year analysis. During autumn and winter, PE hospital admissions increased by 1.07% (95% confidence intervals [CI]: 0.21%; 1.92%) and 0.96% (95% CI: 0.07%; 1.83%) respectively, per 1 °C decrement of air temperature in the previous 10 days (lag 0-10). In summer we observed adverse effects at high temperatures, with a 1% (95% CI: 0.10%; 1.91%) increasing risk per 1 °C increment. We found no association between VT and cold temperatures. CONCLUSION: Results show a significant effect of air temperature on PE hospitalizations in the cold seasons and summer. No effect of particulate matter was detected.
BACKGROUND: The impact of nitrogen dioxide (NO2) and particulate matter with an aerodynamic diameter of less than or equal to 2.5. microns (PM2.5) exposures on lung function has been investigated mainly in children and less in adults. Furthermore, it is unclear whether short-term deviations of air pollutant concentration need to be considered in long-term exposure models. OBJECTIVES: The aims of this study were to investigate the association between short-term air pollution exposure and lung function and to assess whether short-term deviations of air pollutant concentration should be integrated into long-term exposure models. METHODS: Short-term (daily averages 0-7 d prior) and long-term (1- and 4-y means) NO2 and PM2.5 concentrations were modeled using satellite, land use, and meteorological data calibrated on ground measurements. Forced expiratory volume within the first second (FEV1) of forced exhalation and forced vital capacity (FVC) were measured during a LuftiBus assessment (2003-2012) and linked to exposure information from the Swiss National Cohort for 36,085 adults (ages 18-95 y). We used multiple linear regression to estimate adjusted associations, and additionally adjusted models of long-term exposures for short-term deviations in air pollutant concentrations. RESULTS: A 10 μg/m3 increase in NO2 and PM2.5 on the day of the pulmonary function test was associated with lower FEV1 and FVC (NO2: FEV1 – 8.0 ml [95% confidence interval: – 13.4, – 2.7], FVC – 16.7 ml [ – 23.4, – 10.0]; PM2.5: FEV1 – 15.3 ml [ – 21.9, – 8.7], FVC – 18.5 ml [ – 26.5, – 10.5]). A 10 μg/m3 increase in 1-y mean NO2 was also associated with lower FEV1 ( – 7.7 ml; – 15.9, 0.5) and FVC ( – 21.6 ml; – 31.9, – 11.4), as was a 10 μg/m3 increase in 1-y mean PM2.5 (FEV1: – 42.2 ml; – 56.9, – 27.5; FVC: – 82.0 ml; – 100.1, – 63.9). These associations were robust to adjustment for short-term deviations in the concentration of each air pollutant. CONCLUSIONS: Short- and long-term air pollution exposures were negatively associated with lung function, in particular long-term PM2.5 exposure with FVC. Our findings contribute substantially to the evidence of adverse associations between air pollution and lung function in adults. https://doi.org/10.1289/EHP7529.
The short- and long-term impacts of air pollution on human health are well documented and include cardiovascular, neurological, immune system and developmental damage. Additionally, the irritant qualities of air pollutants can cause respiratory and cardiovascular distress. This can be heightened during exercise and especially so for those with respiratory conditions such as asthma. Meteorological conditions have also been shown to adversely impact athletic performance; but research has mostly examined the impact of pollution and meteorology on marathon times or running under laboratory settings. This study focuses on the half marathon distance (13.1 miles/21.1 km) and utilises the Great North Run held in Newcastle-upon-Tyne, England, between 2006 and 2019. Local meteorological (temperature, relative humidity, heat index and wind speed) and air quality (ozone, nitrogen dioxide and PM(2.5)) data is used in conjunction with finishing times of the quickest and slowest amateur participants, along with the elite field, to determine the extent to which each group is influenced in real-world conditions. Results show that increased temperatures, heat index and ozone concentrations are significantly detrimental to amateur half marathon performances. The elite field meanwhile is influenced by higher ozone concentrations. It is thought that the increased exposure time to the environmental conditions contributes to this greater decrease in performance for the slowest participants. For elite athletes that are performing closer to their maximal capacity (VO(2) max), the higher ozone concentrations likely results in respiratory irritation and decreased performance. Nitrogen dioxide and PM(2.5) pollution showed no significant relationship with finishing times. These results provide additional insight into the environmental effects on exercise, which is particularly important under the increasing effects climate change and regional air pollution. This study can be used to inform event organisation and start times for both mass participation and major elite events with the aim to reduce heat- and pollution-related incidents.
The health impacts of global climate change mitigation will affect local populations differently. However, most co-benefits analyses have been done at a global level, with relatively few studies providing local level results. We aimed to quantify the local health impacts due to fine particles (PM(2.5)) under the governance arrangements embedded in the Shared Socioeconomic Pathways (SSPs1-5) under two greenhouse gas concentration scenarios (Representative Concentration Pathways (RCPs) 2.6 and 8.5) in local populations of Mozambique, India, and Spain. We simulated the SSP-RCP scenarios using the Global Change Analysis Model, which was linked to the TM5-FASST model to estimate PM(2.5) levels. PM(2.5) levels were calibrated with local measurements. We used comparative risk assessment methods to estimate attributable premature deaths due to PM(2.5) linking local population and mortality data with PM(2.5)-mortality relationships from the literature, and incorporating population projections under the SSPs. PM(2.5) attributable burdens in 2050 differed across SSP-RCP scenarios, and sensitivity of results across scenarios varied across populations. Future attributable mortality burden of PM(2.5) was highly sensitive to assumptions about how populations will change according to SSP. SSPs reflecting high challenges for adaptation (SSPs 3 and 4) consistently resulted in the highest PM(2.5) attributable burdens mid-century. Our analysis of local PM(2.5) attributable premature deaths under SSP-RCP scenarios in three local populations highlights the importance of both socioeconomic development and climate policy in reducing the health burden from air pollution. Sensitivity of future PM(2.5) mortality burden to SSPs was particularly evident in low- and middle- income country settings due either to high air pollution levels or dynamic populations.
Frequent and severe PM2.5 pollution over China seriously harms natural environment and human health. Changes in meteorological conditions in recent decades have been recognized to contribute to the long-term increase in PM2.5 pollution in North China (NC). However, the dominant climatic factors driving the interdecadal changes of the weather conditions conducive to PM2.5 pollution remain unclear. Here we identify a potential global teleconnection mechanism: the decadal reduction in European aerosol emissions since the 1980s may have partially contributed to the interdecadal increase in weather conditions conducive to PM2.5 pollution in NC, measured by an Emission-weighted Air Stagnation Index (ASI(E)) that increases at a rate of 6.2% decade(-1) (relative to the 1981-1985 level). By regression analysis, we show that the decreased European aerosol loadings can warm the lower atmosphere and induce anomalous ascending motion in Europe, which potentially stimulates two anomalous Rossby wave trains in the upper troposphere travelling eastward across Eurasia. The teleconnection patterns project on NC by weakening the near-surface horizontal dispersion, which may be favorable to the increase in local ASI(E) and air pollution build-up. The suggested mechanism is further supported by the results from a set of large-ensemble simulations, showing that the European aerosol emission decline since the 1980s excites similar local heating and ascending motion and leads to increasing trends of 0.1-0.5 mu g m(-3) (38 year)(-1) in surface sulfate concentrations over most of NC. This proposed ‘West-to-East Aerosol-to-Aerosol’ teleconnection mechanism helps resolve opposite views on the impact of global versus local aerosol forcing on PM2.5 pollution weather in NC. The policy implication is that the sustained decline in European aerosol emissions in coming decades, in conjunction with unabated global and regional warming, could further exacerbate air pollution in NC, thus imposing stronger pressure to reduce local emission sources quicker and deeper.
BACKGROUND: Ground-level ozone is a major public health issue worldwide. An accurate assessment of ozone exposure is necessary. Modeling tools have been developed to tackle this issue in large areas. However, these models could present inaccuracies at the local scale. OBJECTIVES: The objective of this study was i) to assess whether O(3) concentrations estimated by transnational modeling at the kilometric scale (9 km(2)) could be improved, ii) to propose a potential correction of these downscaled ozone concentrations and iii) to evaluate the efficiency and applicability of such a correction. METHOD: The present work was carried out in three phases. First, the performance of a transnational modeling platform (PREV’EST) was assessed at 6 geographic points by comparison with data from 6 air quality monitoring stations. Performance indicators were used for this purpose (MBE (mean bias error), MAE (mean absolute error), RMSE (root mean square error), r (Pearson correlation coefficient), and target plots). Second, several corrections were developed using MARS (multivariate adaptive regression splines) and integrating different sets of variables (mean temperature, relative humidity, rainfall amount, wind speed, elevation, and date). Their performance was evaluated. Third, external validation of the corrections was conducted using the data from six additional air quality monitoring stations. RESULTS: The uncorrected PREV’EST model presented a lack of exactitude and precision. These concentrations did not reproduce the interday variability of the measurements, leading to a lack of temporal contrast in exposure data. For the best performance enhancement, the correction applied improved MBE, MAE, RMSE and r from 14.67, 19.23, 23.18 and 0.67 to 0.00, 8.00, 10.19 and 0.91, respectively. External validation confirmed the efficiency of the corrections at the regional scale. CONCLUSIONS: We propose a validated and efficient methodology integrating local environmental variables. The methodology is adaptable according to the context, needs and data available.
Air pollution is the fourth greatest overall risk factor for human health. Despite declining levels in Europe, air pollution still represents a major health and economic burden. We collected data from the Global Burden of Disease Study 2019 regarding overall, as well as ischemic heart disease (IHD), stroke, and tracheal, bronchus and lung cancer-specific disability adjusted life years (DALYs), years of life lost (YLL) and mortality attributable to air pollution for 43 European countries between 1990 and 2019. Concentrations of ambient particulate matter (aPM(2.5)), ozone, and household air pollution from solid fuels were obtained from State of Global Air 2020. We analysed changes in air pollution parameters, as well as DALYs, YLL, and mortality related to air pollution, also taking into account gross national income (GNI) and socio-demographic index (SDI). Using a novel calculation, aPM(2.5) ratio (PMR) change and DALY rate ratio (DARR) change were used to assess each country’s ability to decrease its aPM(2.5) pollution and DALYs to at least the extent of the European median decrease within the analysed period. Finally, we created a multiple regression model for reliably predicting YLL using aPM(2.5) and household air pollution. The average annual population-weighted aPM(2.5) exposure in Europe in 1990 was 20.8 μg/m(3) (95% confidence interval (CI) 18.3-23.2), while in 2019 it was 33.7% lower at 13.8 μg/m(3) (95% CI 12.0-15.6). There were in total 368 006 estimated deaths in Europe in 2019 attributable to air pollution, a 42.4% decrease compared to 639 052 in 1990. The majority (90.4%) of all deaths were associated with aPM(2.5). IHD was the primary cause of death making up 44.6% of all deaths attributable to air pollution. The age-standardised DALY rate and YLL rate attributable to air pollution were more than 60% lower in 2019 compared to 1990. There was a strong positive correlation (r=0.911) between YLL rate and aPM(2.5) pollution in 2019 in Europe. Our multiple regression model predicts that for 10% increase in aPM(2.5), YLL increases by 16.7%. Furthermore, 26 of 43 European countries had a positive DARR change. 31 of 43 European countries had a negative PMR change, thus not keeping up with the European median aPM(2.5) concentration decrease. When categorising countries by SDI and GNI, countries in the higher brackets had significantly lower aPM(2.5) concentration and DALY rate for IHD and stroke. Overall, air pollution levels, air pollution-related morbidity and mortality have decreased considerably in Europe in the last three decades. However, with the growing European population, air pollution remains an important public health and economic issue. Policies targeting air pollution reduction should continue to be strongly enforced to further reduce one of the greatest risk factors for human health.
Reduced telomere length (TL) has been associated with increased risk of age-related diseases, most likely through oxidative stress and inflammation, which have also been claimed as mechanisms underlying health effects of air pollution exposure. We aimed to verify whether exposure to particulate matter with diameter ≤10 µm (PM(10)) affects TL. We recruited 1792 participants with overweight/obesity in Milan (Italy) in 2010-2015 who completed a structured questionnaire on sociodemographic data, gave a blood sample for TL measurement by real-time PCR, and were assigned air pollution and meteorological data of their residential address. In multivariate mixed-effects linear models (with a random intercept on PCR plate), we observed a -0.51% change in TL (95% confidence interval (CI): -0.98; -0.05)) per 10 µg/m(3) increase in PM(10) at the day of recruitment. A similar decreasing trend in TL was observed up to two weeks before withdrawal, with percentage changes as low as -1.53% (average exposure of the 12 days before recruitment). Mean annual exposure to PM(10) was associated with -2.57% TL reduction (95%CI: -5.06; -0.08). By showing consistent associations between short- and long-term PM(10) exposures and reduced TL, our findings shed light on the potential mechanisms responsible for the excess of age-related diseases associated with air pollution exposure.
The scientific literature is scarce when referring to the influence of atmospheric pollutants on neurodegenerative diseases for present and future climate change scenarios. In this sense, this contribution evaluates the incidence of dementia (Alzheimer’s disease, AD, and dementia from unspecified cause, DU) occurring in Europe associated with the exposure to air pollution (essentially NO(2) and PM2.5) for the present climatic period (1991-2010) and for a future climate change scenario (RCP8.5, 2031-2050). The GEMM methodology has been applied to air pollution simulations using the chemistry/climate regional model WRF-Chem. Present population data were obtained from NASA’s Center for Socioeconomic Data and Applications (SEDAC); while future population projections for the year 2050 were derived from the United Nations (UN) Department of Economic and Social Affairs-Population Dynamics. Overall, the estimated incidence rate (cases per year) of AD and DU associated with exposure to air pollution over Europe is 498,000 [95% confidence interval (95% CI) 348,600-647,400] and 314,000 (95% CI 257,500-401,900), respectively. An important increase in the future incidence rate is projected (around 72% for both types of dementia) when considering the effect of climate change together with the foreseen changes in the future population, because of the expected aging of European population. The climate penalty (impacts of future climate change alone on air quality) has a limited effect on the total changes of dementia (approx. 0.5%), because the large increase in the incidence rate over southern Europe is offset by its decrease over more northern countries, favored by an improvement of air pollution caused by the projected enhancement of rainfall.
Wildland fires release substantial amounts of hazardous contaminants, contributing to a decline in air quality and leading to serious health risks. Thus, this study aimed to understand the contributions of the 2017 extreme wildland fires in Portugal on children health, compared to 2016 (with burned area, in accordance with the average of the previous 15 years). The impact of long-term exposure to PM(10) and NO(2) concentrations, associated with wildland fires, on postneonatal mortality, bronchitis prevalence, and bronchitis symptoms in asthmatic children was estimated, as well as the associated costs. The excess health burden in children attributable to exposure to PM(10) and NO(2), was calculated based on WHO HRAPIE relative risks. Fire emissions were obtained from the Fire INventory from NCAR (FINN). The results obtained indicate that the smoke from wildfires negatively impacts children’s lung function (PM(10) exposure: increase of 320 and 648 cases of bronchitis in 2016 and 2017; NO(2) exposure: 24 and 40 cases of bronchitis symptoms in asthmatic children in 2016 and 2017) and postneonatal mortality (PM(10) exposure: 0.2 and 0.4 deaths in 2016 and 2017). Associated costs were increased in 2017 by around 1 million € for all the evaluated health endpoints, compared to 2016.
Wildland fires, increasing in recent decades in the Mediterranean region due to climate change, can contribute to PM levels and composition. This study aimed to investigate biological effects of PM(2.5) (Ø < 2.5 µm) and PM(10) (Ø < 10 µm) collected near a fire occurred in the North-West of Italy in 2017 and in three other areas (urban and rural areas). Organic extracts were assessed for mutagenicity using Ames test (TA98 and TA100 strains), cell viability (WST-1 and LDH assays) and genotoxicity (Comet assay) with human bronchial cells (BEAS-2B) and estrogenic activity using a gene reporter assay (MELN cells). In all sites, high levels of PM(10) and PM(2.5) were measured during the fire suggesting that near and distant sites were influenced by fire pollutants. The PM(10) and PM(2.5) extracts induced a significant mutagenicity in all sites and the mutagenic effect was increased with respect to historical data. All extracts induced a slight increase of the estrogenic activity but a possible antagonistic activity of PM samples collected near fire was observed. No cytotoxicity or DNA damage was detected. Results confirm that fires could be relevant for human health, since they can worsen the air quality increasing PM concentrations, mutagenic and estrogenic effects.
Uncontrolled wildfires have a substantial impact on the environment, the economy and local populations. According to the European Forest Fire Information System (EFFIS), between 2000 and 2013 wildfires burned up to 740 000 ha of land annually in the south of Europe, Portugal being the country with the highest percentage of burned area per square kilometre. However, there is still a lack of knowledge regarding the impacts of the wildfire-related pollutants on the mortality of the country’s population. All wildfires occurring during the fire season (June-July-AugustSeptember) from 2001 and 2016 were identified, and those with a burned area above 1000 ha (large fires) were considered for the study. During the studied period (2001-2016), more than 2 million ha of forest (929 766 ha from June to September alone) were burned in mainland Portugal. Although large fires only represent less than 1% of the number of total fires, in terms of burned area their contribution is 46% (53% from June to September). To assess the spatial impact of the wildfires, burned areas in each region of Portugal were correlated with PM10 concentrations measured at nearby background air quality monitoring stations. Associations between PM10 and all-cause (excluding injuries, poisoning and external causes) and cause-specific mortality (circulatory and respiratory) were studied for the affected populations using Poisson regression models. A significant positive correlation between burned area and PM10 was found in some regions of Portugal, as well as a significant association between PM10 concentrations and mortality, these being apparently related to large wildfires in some of the regions. The north, centre and inland of Portugal are the most affected areas. The high temperatures and long episodes of drought expected in the future will increase the probabilities of extreme events and therefore the occurrence of wildfires.
INTRODUCTION: Fine particulate matter with an aerodynamic diameter < 2.5 μm (PM(2.5)) in the ambient air has been associated with increased blood pressure (BP) levels and new-onset hypertension. However, the association of BP with a sudden upsurge of PM(2.5) in extreme conditions has not yet been demonstrated. AIM: To evaluate the association between PM(2.5) pollutants the week before, during, and the week after the 2021 wildfires in Athens (Greece) and home BP measurements. METHODS: Home BP measurements were performed, and the readings were transferred to the doctor's office through a telemonitoring system on the patient's Smartphone application. Data from a calibrated, sensor-based PM(2.5) monitoring network assessed PM(2.5) exposure. RESULTS: PM(2.5) pollutants demonstrated a gradual surge while the particle concentration was not different in the selected air pollution measurement stations. A total of 20 consecutive patients with controlled hypertension, mean age 61 ± 9 years, were included in the analysis. For one unit in μg/m(3) increase of PM(2.5) particle concentration, an average of 2.1 mmHg increment in systolic BP was observed after adjustment for confounders (P = 0.023). CONCLUSIONS: Our findings raise the hypothesis that short-term exposure to raised PM(2.5) concentrations in the air appears to be associated with increases in systolic home BP." Telemonitoring systems of home BP recordings may provide important information for the clinical management of hypertensive patients, at least in conditions of major environmental disturbances, such as wildfires.
Wildfires are a complex environmental problem worldwide. The ashes produced during the fire bear metals and PAHs with high toxicity and environmental persistence. These are mobilized into downhill waterbodies, where they can impair water quality and human health. In this context, the present study aimed at assessing the toxicity of mimicked wildfire runoff to human skin cells, providing a first view on the human health hazardous potential of such matrices. Human keratinocytes (HaCaT) were exposed to aqueous extracts of ashes (AEA) prepared from ash deposited in the soil after wildfires burned a pine or a eucalypt forest stand. Cytotoxicity (MTT assay) and changes in cell cycle dynamics (flow cytometry) were assessed. Cell viability decreased with increasing concentrations of AEA, regardless of the ash source, the extracts preparation method (filtered or unfiltered to address the dissolved or the total fractions of contaminants, respectively) or the exposure period (24 and 48 h). The cells growth was also negatively affected by the tested AEA matrices, as evidenced by a deceleration of the progress through the cell cycle, namely from phase G0/G1 to G2. The cytotoxicity of AEA could be related to particulate and dissolved metal content, but the particles themselves may directly affect the cell membrane. Eucalypt ash was apparently more cytotoxic than pine ash due to differential ash metal burden and mobility to the water phase. The deceleration of the cell cycle can be explained by the attempt of cells to repair metal-induced DNA damage, while if this checkpoint and repair pathways are not well coordinated by metal interference, genomic instability may occur. Globally, our results trigger public health concerns since the burnt areas frequently stand in slopes of watershed that serve as recreation sites and sources of drinking water, thus promoting human exposure to wildfire-driven contamination.
Heat and cold temperatures associated with exposure to poor air quality lead to increased mortality. Using a generalized linear model with Poisson regression for overdispersion, this study quantifies the natural-caused mortality burden attributable to heat/cold temperatures and PM(10) and O(3) air pollutants in Rome and Milan, the two most populated Italian cities. We calculate local-specific mortality relative risks (RRs) for the period 2004-2015 considering the overall population and the most vulnerable age category (≥85 years). Combining a regional climate model with a chemistry-transport model under future climate and air pollution scenarios (RCP2.6 and RCP8.5), we then project mortality to 2050. Results show that for historical mortality the burden is much larger for cold than for warm temperatures. RR peaks during wintertime in Milan and summertime in Rome, highlighting the relevance of accounting for the effects of air pollution besides that of climate, in particular PM(10) for Milan and O(3) for Rome. Overall, Milan reports higher RRs while, in both cities, the elderly appear more susceptible to heat/cold and air pollution events than the average population. Two counterbalancing effects shape mortality in the future: an increase associated with higher and more frequent warmer daily temperatures – especially in the case of climate inaction – and a decrease due to declining cold-mortality burden. The outcomes highlight the urgent need to adopt more stringent and integrated climate and air quality policies to reduce the temperature and air pollution combined effects on health.
Urban Built Environments (UBE) are increasingly prone to SLow-Onset Disasters (SLODs) such as air pollution and heatwaves. The effectiveness of sustainable risk-mitigation solutions for the exposed individuals’ health should be defined by considering the effective scenarios in which emergency conditions can appear. Combining environmental (including climatic) conditions and exposed users’ presence and behaviors is a paramount task to support decision-makers in risk assessment. A clear definition of input scenarios and related critical conditions to be analyzed is needed, especially while applying simulation-based approaches. This work provides a methodology to fill this gap, based on hazard and exposure peaks identification. Quick and remote data-collection is adopted to speed up the process and promote the method application by low-trained specialists. Results firstly trace critical conditions by overlapping air pollution and heatwaves occurrence in the UBE. Exposure peaks (identified by remote analyses on the intended use of UBEs) are then merged to retrieve critical conditions due to the presence of the individuals over time and UBE spaces. The application to a significant case study (UBE in Milan, Italy) demonstrates the approach capabilities to identify key input scenarios for future human behavior simulation activities from a user-centered approach.
INTRODUCTION: Climate change is one of the 21st century’s biggest public health issues and health care contributes up to 10% of the emissions of greenhouse gases in developed countries. About 15 million laparoscopic procedures are performed annually worldwide and single-use medical equipment is increasingly used during these procedures. Little is known about costs and environmental footprint of this change in practice. METHODS: We employed Life Cycle Assessment method to evaluate and compare the environmental impacts of single-use, reusable, and mixed trocar systems used for laparoscopic cholecystectomies at three hospitals in southern Sweden. The environmental impacts were calculated using the IMPACT 2002+ method and a functional unit of 500 procedures. Monte Carlo simulations were used to estimate differences between trocar systems. Data are presented as medians and 2.5th to 97.5th percentiles. Financial costs were calculated using Life Cycle Costing. RESULTS: The single-use system had a 182% higher impact on resources than the reusable system [difference: 5160 MJ primary (4400-5770)]. The single-use system had a 379% higher impact on climate change than the reusable system [difference: 446 kg CO2eq (413-483)]. The single-use system had an 83% higher impact than the reusable system on ecosystem quality [difference: 79 PDF*m2*yr (24-112)] and a 240% higher impact on human health [difference: 2.4×10-4 DALY/person/yr (2.2×10-4-2.6×10-4)]. The mixed and single-use systems had a similar environmental impact. Differences between single-use and reusable trocars with regard to resource use and ecosystem quality were found to be sensitive to lower filling of machines in the sterilization process. For ecosystem quality the difference between the two were further sensitive to a 50% decrease in number of reuses, and to using a fossil fuel intensive electricity mix. Differences regarding effects on climate change and human health were robust in the sensitivity analyses. The reusable and mixed trocar systems were approximately half as expensive as the single-use systems (17360 € and 18560 € versus 37600 €, respectively). CONCLUSION: In the Swedish healthcare system the reusable trocar system offers a robust opportunity to reduce both the environmental impact and financial costs for laparoscopic surgery.
BACKGROUND: Unhealthy diets, the rise of non-communicable diseases, and the declining health of the planet are highly intertwined, where food production and consumption are major drivers of increases in greenhouse gas emissions, substantial land use, and adverse health such as cancer and mortality. To assess the potential co-benefits from shifting to more sustainable diets, we aimed to investigate the associations of dietary greenhouse gas emissions and land use with all-cause and cause-specific mortality and cancer incidence rates. METHODS: Using data from 443 991 participants in the European Prospective Investigation into Cancer and Nutrition (EPIC) study, a multicentre prospective cohort, we estimated associations between dietary contributions to greenhouse gas emissions and land use and all-cause and cause-specific mortality and incident cancers using Cox proportional hazards regression models. The main exposures were modelled as quartiles. Co-benefits, encompassing the potential effects of alternative diets on all-cause mortality and cancer and potential reductions in greenhouse gas emissions and land use, were estimated with counterfactual attributable fraction intervention models, simulating potential effects of dietary shifts based on the EAT-Lancet reference diet. FINDINGS: In the pooled analysis, there was an association between levels of dietary greenhouse gas emissions and all-cause mortality (adjusted hazard ratio [HR] 1·13 [95% CI 1·10-1·16]) and between land use and all-cause mortality (1·18 [1·15-1·21]) when comparing the fourth quartile to the first quartile. Similar associations were observed for cause-specific mortality. Associations were also observed between all-cause cancer incidence rates and greenhouse gas emissions, when comparing the fourth quartile to the first quartile (adjusted HR 1·11 [95% CI 1·09-1·14]) and between all-cause cancer incidence rates and land use (1·13 [1·10-1·15]); however, estimates differed by cancer type. Through counterfactual attributable fraction modelling of shifts in levels of adherence to the EAT-Lancet diet, we estimated that up to 19-63% of deaths and up to 10-39% of cancers could be prevented, in a 20-year risk period, by different levels of adherence to the EAT-Lancet reference diet. Additionally, switching from lower adherence to the EAT-Lancet reference diet to higher adherence could potentially reduce food-associated greenhouse gas emissions up to 50% and land use up to 62%. INTERPRETATION: Our results indicate that shifts towards universally sustainable diets could lead to co-benefits, such as minimising diet-related greenhouse gas emissions and land use, reducing the environmental footprint, aiding in climate change mitigation, and improving population health. FUNDING: European Commission (DG-SANCO), the International Agency for Research on Cancer (IARC), MRC Early Career Fellowship (MR/M501669/1).
In the current era of globalization, a clean environment remains a crucial factor for the health of the population. Thus, improving air quality is a major focus of environmental policies, as it affects all aspects of nature, including humans. For these reasons, it is appropriate to take into account the health risks posed by greenhouse gas (GHG) emissions released into the atmosphere. With regard to global GHG emissions, there are concerns about the loss of protection of the ozone layer and it is very likely that climate change can be expected, which multiplies the environmental threat and has potentially serious global consequences. In this regard, it is important to pay increased attention to emissions that enter the atmosphere, which include countless toxic substances. The aim of this study was to examine the associations between selected GHG emissions and the health of the European Union (EU) population represented by disability-adjusted life years (DALYs). This aim was achieved using several analytical procedures (descriptive analysis, correlation analysis, cluster analysis, and panel regression analysis), which included five environmental variables (carbon dioxide (CO(2)), methane (CH(4)) in CO(2) equivalent, nitrous oxide (N(2)O) in CO(2) equivalent, hydrofluorocarbons (HFC) in CO(2) equivalent, sulfur hexafluoride (SF(6)) in CO(2) equivalent) and one health variable (DALYs). An emphasis was placed on the use of quantitative methods. The results showed that CO(2) emissions have a dominant position among selected GHG emissions. The revealed positive link between CO(2) and DALYs indicated that a decrease in CO(2) may be associated with a decrease in DALYs, but it is also true that this cannot be done without reducing emissions of other combustion products. In terms of CO(2), the least positive scores were observed in Luxembourg and Estonia. Germany had the lowest score of DALYs, representing the most positive health outcome in the EU. In terms of total GHG emissions, Ireland and Luxembourg were considered to be less positive countries compared to the other analyzed countries. Countries should focus on reducing GHG emissions in general, but from a health point of view, reducing CO(2) emissions seems to be the most beneficial.
BACKGROUND: Evidence of the role of interactions between air pollution and pollen exposure in subjects with allergic asthma is limited and need further exploration to promote adequate preventive measures. The objective of this study was to assess effects of exposure to ambient air pollution and birch pollen on exacerbation of respiratory symptoms in subjects with asthma and allergy to birch. METHODS: Thirty-seven subjects from two Swedish cities (Gothenburg and Umeå) with large variation in exposure to both birch-pollen and air pollutants, participated in the study. All subjects had confirmed allergy to birch and self-reported physician-diagnosed asthma. The subjects recorded respiratory symptoms such as rhinitis or eye irritation, dry cough, dyspnoea, the use of any asthma or allergy medication and peak respiratory flow (PEF), daily for five consecutive weeks during two separate pollen seasons and a control season without pollen. Nitrogen oxides (NO(x)), ozone (O(3)), particulate matter (PM(2.5)), birch pollen counts, and meteorological data were obtained from an urban background monitoring stations in the study city centres. The data were analysed using linear mixed effects models. RESULTS: During pollen seasons all symptoms and medication use were higher, and PEF was reduced in the subjects. In regression analysis, exposure to pollen at lags 0 to 2 days, and lags 0 to 6 days was associated with increased ORs of symptoms and decreased RRs for PEF. Pollen and air pollution interacted in some cases; during low pollen exposure, there were no associations between air pollution and symptoms, but during high pollen exposure, O(3) concentrations were associated with increased OR of rhinitis or eye irritation, and PM(2.5) concentrations were associated with increased ORs of rhinitis or eye irritation, dyspnea and increased use of allergy medication. CONCLUSIONS: Pollen and air pollutants interacted to increase the effect of air pollution on respiratory symptoms in allergic asthma. Implementing the results from this study, advisories for individuals with allergic asthma could be improved, minimizing the morbidities associated with the condition.
BACKGROUND: Common ragweed has been spreading as a neophyte in Europe. Elevated CO(2) levels, a hallmark of global climate change, have been shown to increase ragweed pollen production, but their effects on pollen allergenicity remain to be elucidated. METHODS: Ragweed was grown in climate-controlled chambers under normal (380 ppm, control) or elevated (700 ppm, based on RCP4.5 scenario) CO(2) levels. Aqueous pollen extracts (RWE) from control- or CO(2) -pollen were administered in vivo in a mouse model for allergic disease (daily for 3-11 days, n = 5) and employed in human in vitro systems of nasal epithelial cells (HNECs), monocyte-derived dendritic cells (DCs), and HNEC-DC co-cultures. Additionally, adjuvant factors and metabolites in control- and CO(2) -RWE were investigated using ELISA and untargeted metabolomics. RESULTS: In vivo, CO(2) -RWE induced stronger allergic lung inflammation compared to control-RWE, as indicated by lung inflammatory cell infiltrate and mediators, mucus hypersecretion, and serum total IgE. In vitro, HNECs stimulated with RWE increased indistinctively the production of pro-inflammatory cytokines (IL-8, IL-1β, and IL-6). In contrast, supernatants from CO(2) -RWE-stimulated HNECs, compared to control-RWE-stimulated HNECS, significantly increased TNF and decreased IL-10 production in DCs. Comparable results were obtained by stimulating DCs directly with RWEs. The metabolome analysis revealed differential expression of secondary plant metabolites in control- vs CO(2) -RWE. Mixes of these metabolites elicited similar responses in DCs as compared to respective RWEs. CONCLUSION: Our results indicate that elevated ambient CO(2) levels elicit a stronger RWE-induced allergic response in vivo and in vitro and that RWE increased allergenicity depends on the interplay of multiple metabolites.
There is limited knowledge about how crises are framed on different social media platforms specifically in a non-Western cultural context. This study compares how extreme environmental crises-Hurricane Maria and haze-were framed on Twitter and Weibo. Through word-cloud, co-occurrence, and thematic analyses with Hurricane Maria-related tweets, this study identified two major frames of this crisis: a disaster frame and a political frame. Similarly, by analyzing haze-related posts on Sina Weibo, two major frames emerged: an environmental frame and a health frame. Both crises were largely framed as environmental issues rather than health risks or crises. Such framing helps shape the existence of Hurricane Maria and haze as legitimate facts. The findings also reveal that cultural variances, eg, power distance, collectivist-individualist culture, and uncertainty avoidance, impact crisis framing. This study indicates the importance of designing culture-fit messages and incorporating social media strategies in crisis communication while developing emergency management plans and adds knowledge to the limited literature on social-mediated crisis communication in different cultural contexts. Such knowledge will provide theoretical and practical implications for crisis scholars, emergency management practitioners, and policymakers.
This study examines point and non-point sources of air pollution and particulate matter and their associated socioeconomic and health impacts in South Asian countries, primarily India, China, and Pakistan. The legislative frameworks, policy gaps, and targeted solutions are also scrutinized. The major cities in these countries have surpassed the permissible limits defined by WHO for sulfur dioxide, carbon monoxide, particulate matter, and nitrogen dioxide. As a result, they are facing widespread health problems, disabilities, and causalities at extreme events. Populations in these countries are comparatively more prone to air pollution effects because they spend more time in the open air, increasing their likelihood of exposure to air pollutants. The elevated level of air pollutants and their long-term exposure increases the susceptibility to several chronic/acute diseases, i.e., obstructive pulmonary diseases, acute respiratory distress, chronic bronchitis, and emphysema. More in-depth spatial-temporal air pollution monitoring studies in China, India, and Pakistan are recommended. The study findings suggest that policymakers at the local, national, and regional levels should devise targeted policies by considering all the relevant parameters, including the country’s economic status, local meteorological conditions, industrial interests, public lifestyle, and national literacy rate. This approach will also help design and implement more efficient policies which are less likely to fail when brought into practice.
The consequences of climate change and global warming have become irrefutable. Scientists are working to change the alarming scenario awaiting humanity in the future. On the other hand, they have proved that the increasing trend of many life-threatening diseases, such as cancer, are caused by global warming. In this research, data collected from national and international databases were analysed and compared. The aim of this research is presenting the relationship between increasing temperature anomalies and rising cancer trend. As a result of the study, it is determined that the rising global surface temperature and increasing cancer rates are directly related. In the study, data related to Northern Cyprus were also examined. According to the findings; poor waste management and uncontrolled carbon dioxide emissions are responsible for raising cancer rates and cardiovascular diseases in North Cyprus.
BACKGROUND: Evidence from the scientific literature shows a significant variation in greenhouse gas (GHG) emissions from the diet, according to the type of food consumed. We aim to analyze the relationship between the daily dietary GHG emissions according to red meat, fruit and vegetables consumption and their relationship with risk of total mortality, and incident risk of chronic diseases. METHODS: We examined data on the EPIC-Spain prospective study, with a sample of 40 621 participants. Dietary GHG emission values were calculated for 57 food items of the EPIC study using mean emission data from a systematic review of 369 published studies. RESULTS: Dietary GHG emissions (kgCO2eq/day), per 2000 kcal, were 4.7 times higher in those with high red-meat consumption (>140 g/day) than those with low consumption (<70 g/day). The average dietary GHG emissions were similar in males and females, but it was significantly higher in youngest people and in those individuals with lower educational level, as well as for northern EPIC centers of Spain. We found a significant association with the risk of mortality comparing the third vs. the first tertile of dietary GHG emissions [hazard ratio (HR) 1.095; 95% confidence interval (CI) 1.007-1.19; trend test 0.037]. Risk of coronary heart disease (HR 1.26; 95% CI 1.08-1.48; trend test 0.003) and risk of type 2 diabetes (HR 1.24; 95% CI 1.11-1.38; trend test 0.002) showed significant association as well. CONCLUSIONS: Decreasing red-meat consumption would lead to reduce GHG emissions from diet and would reduce risk of mortality, coronary heart disease and type 2 diabetes.
The environmental pollution caused by climate change and global warming pose significant risks to health. This raises the question how environmental disturbances can affect health expenditures. Based on this, this study examines the asymmetric effect of environmental quality on health expenditures in Türkiye using the non-linear ARDL (NARDL) model for the 1975-2019 period. In addition to environmental quality, natural resources, economic growth, and trade openness variables are also included in the health expenditure model. The findings support the existence of an asymmetric cointegration relationship between the series. The findings also indicate that positive environmental pollution shocks affect health expenditures positively in the long run, while negative environmental pollution shocks do not have a statistically significant effect on health expenditures. Positive and negative natural resource shocks affect health expenditures negatively in the long run. Despite the effect of positive economic growth shocks on health expenditures is positive but statistically insignificant, the effect of negative economic growth shocks is positive and significant. Besides, positive trade openness shocks have a negative effect on health expenditures and negative trade openness shocks have a positive effect. The findings prove that the steps to be taken to protect the environment in the current period will increase the effectiveness of health expenditures in the future. This situation has a guiding feature for policy-makers in terms of policy decisions.
Air pollution and extreme heat have been responsible for more than a million deaths in China every year, especially in densely urbanized regions. While previous studies intensively evaluated air pollution episodes and extreme heat events, a limited number of studies comprehensively assessed atmospheric hot-and-polluted-episodes (HPE) – an episode with simultaneously high levels of air pollution and temperature – which have potential adverse synergic impacts on human health. This study focused on the Pearl River Delta (PRD) region of China due to its high temperature in summer and poor air quality throughout a year. We employed geostatistical downscaling to model meteorology at a spatial resolution of 1 km, and applied a machine learning algorithm (XGBoost) to estimate a high-resolution (1 km) daily concentration of particulate matter with an aerodynamic diameter ≤2.5 μm (PM(2.5)) and ozone (O(3)) for June to October over 20 years (2000-2019). Our results indicate an increasing trend (∼50%) in the frequency of HPE occurrence in the first decade (2000-2010). Conversely, the annual frequency of HPE occurrence reduced (16.7%), but its intensity increased during the second decade (2010-2019). The northern cities in the PRD region had higher levels of PM(2.5) and O(3) than their southern counterparts. During HPEs, regional daily PM(2.5) exceeded the World Health Organization (WHO) and Chinese guideline levels by 75% and 25%, respectively, while the O(3) exceeded the WHO O(3) standard by up to 69%. Overall, 567,063 (95% confidence interval (CI): 510,357-623,770) and 52,231 (95%CI: 26,116-78,346) excessive deaths were respectively attributable to exposure to PM(2.5) and O(3) in the PRD region. Our findings imply the necessity and urgency to formulate co-benefit policies to mitigate the region’s air pollution and heat problems.
INTRODUCTION: There is a large body of epidemiological evidence showing significantly increased mortality risks from air pollution and temperature. However, findings on the modification of the association between air pollution and mortality by temperature are mixed. METHODS: We used a varying coefficient distributed lag model to assess the complex interplay between air temperature and PM(2.5) on daily mortality in Guangzhou City from 2013 to 2020, with the aim of establishing the PM(2.5)-mortality association at different temperatures and exploring synergetic mortality risks from PM(2.5) and temperature on vulnerable populations. RESULTS: We observed near-linear concentration-response associations between PM(2.5) and mortality across different temperature levels. Each 10 μg/m³ increase of PM(2.5) in low, medium, and high temperature strata was associated with increments of 0.73% [95% confidence interval (CI): 0.38%, 1.09%], 0.12% (95% CI: -0.27%, 0.52%), and 0.46% (95% CI: 0.11%, 0.81%) in non-accidental mortality, with a statistically significant difference between low and medium temperatures (P=0.02). There were significant modification effects of PM(2.5) by low temperature for cardiovascular mortality and among individuals 75 years or older. CONCLUSIONS: Low temperatures may exacerbate physiological responses to short-term PM(2.5) exposure in Guangzhou, China.
Background: Preterm birth contributes to the morbidity and mortality of newborns and infants. Recent studies have shown that maternal exposure to particulate matter and extreme temperatures results in immune dysfunction, which can induce preterm birth. This study aimed to evaluate the association between fine particulate matter (PM(2.5)) exposure, temperature, and preterm birth in Seoul, Republic of Korea. Methods: We used 2010-2016 birth data from Seoul, obtained from the Korea National Statistical Office Microdata. PM(2.5) concentration data from Seoul were generated through the Community Multiscale Air Quality (CMAQ) model. Seoul temperature data were collected from the Korea Meteorological Administration (KMA). The exposure period of PM(2.5) and temperature were divided into the first (TR1), second (TR2), and third (TR3) trimesters of pregnancy. The mean PM(2.5) concentration was used in units of ×10 µg/m(3) and the mean temperature was divided into four categories based on quartiles. Logistic regression analyses were performed to evaluate the association between PM(2.5) exposure and preterm birth, as well as the combined effects of PM(2.5) exposure and temperature on preterm birth. Result: In a model that includes three trimesters of PM(2.5) and temperature data as exposures, which assumes an interaction between PM(2.5) and temperature in each trimester, the risk of preterm birth was positively associated with TR1 PM(2.5) exposure among pregnant women exposed to relatively low mean temperatures (<3.4 °C) during TR1 (OR 1.134, 95% CI 1.061-1.213, p < 0.001). Conclusions: When we assumed the interaction between PM(2.5) exposure and temperature exposure, PM(2.5) exposure during TR1 increased the risk of preterm birth among pregnant women exposed to low temperatures during TR1. Pregnant women should be aware of the risk associated with combined exposure to particulate matter and low temperatures during TR1 to prevent preterm birth.
This study aims to quantitatively identify the economic value of the comprehensive improvement of environmental degradations caused by climate change. The research method applied to that is the choice experiment. Fine particulate matter, algae bloom, and heat waves were selected as individual attributes constituting environmental problems. It was found that the willingness to pay could not be induced for any level of improvement in algal bloom. It was concluded that if heat waves improved to the medium level where the number of heat-related illnesses and estimated deaths decreased by 50% compared to the current level, there would be a loss in value by USD 13.33. The value of improving environmental problems is USD 7.69 per household per year, and the improvement of fine particulate matter was the highest value attributed by consumers. This study is significant in that it comprehensively evaluates severe environmental problems, reflects their priorities and importance, and assesses the value for each level. It provides important foundational data for establishing effective budget input strategies to maximize consumer benefits and aids in the preparation of effective policies by establishing more detailed goals to achieve net-zero carbon emissions and the Sustainable Development Goals.
Mounting studies have associated asthma with environmental and climatic factors, but their interaction during pregnancy on childhood asthma are unclear. This study aims to investigate the interaction of in utero air pollution and environmental temperature exposure on childhood asthma, to identify key timing windows for exposure. A retrospective cohort study with 2,598 pre-schoolers was conducted during 2011-2012 in Changsha, China. Maternal exposure to three critical ambient air pollutants (PM10, SO2 and NO2, as proxies of industrial and vehicular air pollution) and temperature (T), was assessed for the 40 gestational weeks, three trimesters of gestation, and entire pregnancy by an inverse distance weighted (IDW) method. Logistic regression analysis was used to examine the association of childhood asthma with air pollution and temperature exposure. Our results showed that pre-schooler’s asthma was significantly associated with SO2 and NO2 exposure in utero, ORs = 1.46 (95% CI: 1.12-1.89) and 1.67 (95% CI: 1.24-2.26) by inter quartile range (IQR) increase of their exposure respectively. Significant risk was observed for exposure of SO2 and NO2 particularly during the 1st and 2nd trimesters and their specific gestational weeks. Pre-schooler’s asthma was related with high temperature expo-sure during 1st trimester, OR = 2.33 (95% CI: 1.11-4.90) by IQR increase of T exposure. Low T and high T respectively increased the asthma risk of NO2 exposure in the 1st and 3rd trimester. Boys were more susceptible to the temperature-pollution interaction on asthma development. Our study indicates that low and high tem-perature respectively during early and late pregnancy significantly increased the impact of air pollution exposure in utero on pre-schooler’s asthma.
BACKGROUND: Though inconsistent, acute effects of ambient nitrogen oxides on cardiovascular mortality have been reported. Whereas, interactive roles of temperature on their relationships and joint effects of different indicators of nitrogen oxides were less studied. This study aimed to extrapolate the independent roles of ambient nitrogen oxides and temperature interactions on cardiovascular mortality. METHODS: Data on mortality, air pollutants, and meteorological factors in Shenzhen from 2013 to 2019 were collected. Three indicators including nitric oxide (NO), nitrogen dioxide (NO(2)), and nitrogen oxides (NO(X)) were studied. Adjusted generalized additive models (GAMs) were applied to analyse their associations with cardiovascular mortality in different groups. RESULTS: The average daily concentrations of NO, NO(2), and NO(X) were 11.7 μg/m^3, 30.7 μg/m^3, and 53.2 μg/m3, respectively. Significant associations were shown with each indicator. Cumulative effects of nitrogen oxides were more obvious than distributed lag effects. Males, population under 65 years old, and population with stroke-related condition were more susceptible to nitrogen oxides. Adverse effects of nitrogen oxides were more significant at low temperature. Impacts of NO(2) on cardiovascular mortality, and NO on stroke mortality were the most robust in the multi-pollutant models, whereas variations were shown in the other relationships. CONCLUSIONS: Low levels of nitrogen oxides showed acute and adverse impacts and the interactive roles of temperature on cardiovascular mortality. Cumulative effects were most significant and joint effects of nitrogen oxides required more attention. Population under 65 years old and population with stroke-related health condition were susceptible, especially days at lower temperature.
BACKGROUND: The concentration of air pollutants is affected by changes in climatic conditions. Air temperature is a main factor affecting the concentration of air pollutants. This study sought to examine the relationship between air temperature, air pollutants, and their interactions in elderly patients with coronary heart disease (CHD) in Liaoning Province, China. METHODS: The population data primarily comprised data on daily hospitalizations due to CHD between January 1, 2015 and December 31, 2019 at the Shengjing Hospital of China Medical University. A total of 25,461 patients, who were permanent residents of Liaoning Province, were included in the study. The meteorological data included data on the average daily temperature and air pollutant data of the average daily concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) over the hospitalization period. A multiple linear regression model was constructed to analyze the relationship between meteorological factors and CHD. RESULTS: The interaction between air temperature and SO2, NO2, and O3 concentrations was related to the number of daily CHD-related hospitalizations in elderly patients aged ≥65 years (P=0.0023); however, this correlation was lower than that of the interaction between SO2 and NO2 concentrations (P=0.0026). Additionally, age exerted a greater effect than air temperature and air pollutants. CONCLUSIONS: The incidence of CHD in elderly patients aged ≥65 years was found to be related to the interaction of SO2 and NO2 concentrations, and the interaction of air temperature and the concentrations of SO2, NO2, and O3.
No study has ever investigated how ambient temperature and PM(2.5) mediate rotavirus infection (RvI) in children. We used insurance claims data from Taiwan in 2006-2012 to evaluate the RvI characteristics in children aged ≤ 9. The RvI incidence rates were higher in colder months, reaching the highest in March (117.0/100 days), and then declining to the lowest in July (29.2/100 days). The age-sex-specific average incident cases were all higher in boys than in girls. Stratified analysis by temperature (<20, 20-24, and ≥25 °C) and PM(2.5) (<17.5, 17.5-31.4, 31.5-41.9, and ≥42.0 μg/m^3) showed that the highest incidence was 16.4/100 days at average temperatures of <20 °C and PM(2.5) of 31.5–41.9 μg/m^3, with Poisson regression analysis estimating an adjusted relative risk (aRR) of 1.26 (95% confidence interval (CI) = 1.11-1.43), compared to the incidence at the reference condition (<20 °C and PM2.5 < 17.5 μg/m^3). As the temperature increased, the incident RvI cases reduced to 4.84 cases/100 days (aRR = 0.40, 95% CI = 0.35-0.45) when it was >25 °C with PM(2.5) < 17.5 μg/m^3, or to 9.84/100 days (aRR = 0.81, 95% CI = 0.77-0.93) when it was >25 °C with PM2.5 > 42 μg/m^3). The seasonal RvI is associated with frequent indoor personal contact among children in the cold months. The association with PM(2.5) could be an alternative assessment due to temperature inversion.
Worldwide, over half of the global population is living in urban areas. The metropolitan areas are highly populated and environmentally non-green regions on the planet. In green space regions, plants, grass, and green vegetation prevent soil erosion, absorb air pollutants, provide fresh and clean air, and minimize the burden of diseases. Presently, the entire world is facing a turmoil situation due to the COVID-19 pandemic. This study investigates the effect of the green space environment on air pollutants particulate matter PM2.5, PM10, carbon monoxide (CO), ozone (O(3)), incidence and mortality of Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2) in environmentally highly green and less-green countries. We randomly selected 17 countries based on the Environmental Performance Index (EPI) data. The 60% of the EPI score is based on seven categories: biodiversity and habitat, ecosystem, fisheries, climate change, pollution emissions, agriculture, and water resources. However, 40% of the score is based on four categories: air quality, sanitation and drinking water, heavy metals, and waste management. The air pollutants and SARS-CoV-2 cases and deaths were recorded from 25 January 2020, to 11 July 2021. The air pollutants PM2.5, PM10, CO, and O(3) were recorded from the metrological websites, Air Quality Index-AQI, 2021. The COVID-19 daily cases and deaths were obtained from the World Health Organization. The result reveals that air pollutants mean values for PM2.5 110.73 ± 1.09 vs. 31.35 ± 0.29; PM10 80.43 ± 1.11 vs. 17.78 ± 0.15; CO 7.92 ± 0.14 vs. 2.35 ± 0.03 were significantly decreased (p < 0.0001) in environmentally highly green space countries compared to less-green countries. Moreover, SARS-CoV-2 cases 15,713.61 ± 702.42 vs. 3445.59 ± 108.09; and deaths 297.56 ± 11.27 vs. 72.54 ± 2.61 were also significantly decreased in highly green countries compared to less-green countries. The green environment positively impacts human wellbeing. The policymakers must implement policies to keep the living areas, surroundings, towns, and cities clean and green to minimize air pollution and combat the present pandemic of COVID-19.
Background: Existing evidence suggests that mumps epidemics, a global public health issue, are associated with meteorological factors and air pollutants at the population scale. However, the interaction effect of meteorological factors and air pollutants on mumps remains underexplored.Methods: Daily cases of mumps, meteorological factors, and air pollutants were collected in Ningxia, China, from 2015 to 2019. First, a distributed lag nonlinear model (DLNM) was employed to assess the confounding-adjusted relationship between meteorological factors, ambient air pollutants, and mumps incidences. According to the results of DLNM, stratification in both air pollutants and meteorological factors was adopted to further explore the interaction effect of particulate matter less than or equal to 2.5 mu m in aerodynamic diameter (PM2.5) and ground-level ozone (O-3) with temperature and relative humidity (RH).Results: We reported significant individual associations between mumps incidences and environmental factors, including temperature, relative humidity, PM2.5, and O-3. Evident multiplicate and additive interactions between meteorological factors and PM2.5 were found with interaction relative risk (IRR) of 1.14 (95%CI: 1.01, 1.29) and relative excess risk due to interaction (RERI) of 0.17 (95%CI: 0.02, 0.32) for a moderate level of temperature at 12 degrees C, and IRR of 1.37 (95%CI: 1.14, 1.66), RERI of 0.36 (95%CI: 0.11, 0.60) for a high level of temperature at 20 degrees C, respectively. These results indicated that PM2.5 and temperature have a significant synergistic effect on the cases of mumps, while no interaction between relative humidity and PM2.5 is observed. Regarding O-3 and meteorological factors (temperature = 12 degrees C, 20 degrees C), IRR and RERI were 1.33 (95%CI: 1.17, 1.52) and 0.30 (95%CI: 0.16, 0.45), 1.91 (95%CI: 1.46, 2.49) and 0.69 (95%CI: 0.32, 1.07), respectively. And IRR of 1.17 (95%CI: 1.06, 1.29), RERI of 0.13 (95%CI: 0.04, 0.21) for a middle level of relative humidity at 48%.Conclusion: Our findings indicated that meteorological factors and air pollutants imposed a significantly lagged and nonlinear effect on the incidence of mumps. The interaction between low temperature and O-3 showed antagonistic effects, while temperature (medium and high) with PM2.5 and O-3 presented synergistic effects. For relative humidity, the interaction with O-3 is synergistic. These results provide scientific evidence to relevant health authorities for the precise disease control and prevention of mumps in arid and semi-arid areas.
Big data can be used to correlate diseases and climatic factors. The prevalence of influenza (flu) virus, accounting for a large proportion of respiratory infections, suggests that the effect of climate variables according to seasonal dynamics of influenza virus infections should be investigated. Here, trends in flu virus detection were analyzed using data from 9,010 tests performed between January 2012 and December 2018 at Dankook University Hospital, Cheonan, Korea. We compared the detection of the flu virus in Cheonan area and its association with climate change. The flu virus detection rate was 9.9% (894/9,010), and the detection rate was higher for flu virus A (FLUAV; 6.9%) than for flu virus B (FLUBV; 3.0%). Both FLUAV and FLUBV infections are considered an epidemic each year. We identified 43.1% (n = 385) and 35.0% (n = 313) infections in children aged < 10 years and adults aged > 60 years, respectively. The combination of these age groups encompassed 78.1% (n = 698/894) of the total data. Flu virus infections correlated with air temperature, relative humidity, vapor pressure, atmospheric pressure, particulate matter, and wind chill temperature (P < 0.001). However, the daily temperature range did not significantly correlate with the flu detection results. This is the first study to identify the relationship between long-term flu virus infection with temperature in the temperate region of Cheonan.
BACKGROUND: Sentinel physician surveillance in communities has played an important role in detecting early signs of epidemics. The traditional approach is to let the primary care physician voluntarily and actively report diseases to the health department on a weekly basis. However, this is labor-intensive work, and the spatio-temporal resolution of the surveillance data is not precise at all. In this study, we built up a clinic-based enhanced sentinel surveillance system named “Sentinel plus” which was designed for sentinel clinics and community hospitals to monitor 23 kinds of syndromic groups in Taipei City, Taiwan. The definitions of those syndromic groups were based on ICD-10 diagnoses from physicians. METHODS: Daily ICD-10 counts of two syndromic groups including ILI and EV-like syndromes in Taipei City were extracted from Sentinel plus. A negative binomial regression model was used to couple with lag structure functions to examine the short-term association between ICD counts and meteorological variables. After fitting the negative binomial regression model, residuals were further rescaled to Pearson residuals. We then monitored these daily standardized Pearson residuals for any aberrations from July 2018 to October 2019. RESULTS: The results showed that daily average temperature was significantly negatively associated with numbers of ILI syndromes. The ozone and PM2.5 concentrations were significantly positively associated with ILI syndromes. In addition, daily minimum temperature, and the ozone and PM2.5 concentrations were significantly negatively associated with the EV-like syndromes. The aberrational signals detected from clinics for ILI and EV-like syndromes were earlier than the epidemic period based on outpatient surveillance defined by the Taiwan CDC. CONCLUSIONS: This system not only provides warning signals to the local health department for managing the risks but also reminds medical practitioners to be vigilant toward susceptible patients. The near real-time surveillance can help decision makers evaluate their policy on a timely basis.
The bacteria (including pathogenic bacteria) attached to road deposited sediments (RDS) may interrelate with the microbe in the atmosphere, soil and water through resuspension and wash-off, and is of great significance to human and ecological health. However, the characteristics of bacterial communities with different time scale on RDS were unknown to dates. Climate change prolonged the dry days between rain events in many areas, making the varied trend of bacterial communities might be more significant in short term. This study revealed the characteristics of bacterial communities on RDS in urban and suburban areas through seasonal and daily scale. The correlations between other factors (land use, particle size, and chemical components) and the bacterial communities were also analyzed. It was found that the season showed a higher association with the bacterial community diversity than land use and particle size in urban areas. The bacterial community diversity increased substantially throughout the short-term study period (41 days) and the variation of dominant bacteria could be fitted by quadratic function in suburbs. In addition, urbanization notably increased the bacterial community diversity, while the potential pathogenic bacteria were more abundant in the suburban areas, coarse RDS (>75 μm), and in spring. The chemical components on RDS showed special correlations with the relative abundance of dominant bacteria. The research findings would fill the knowledge gap on RDS bacterial communities and be helpful for the future research on the assembly process of bacterial communities.
This study proposed a novel ensemble analysis strategy to improve hand, foot and mouth disease (HFMD) prediction by integrating environmental data. The approach began by establishing a vector autoregressive model (VAR). Then, a dynamic Bayesian networks (DBN) model was used for variable selection of environmental factors. Finally, a VAR model with constraints (CVAR) was established for predicting the incidence of HFMD in Chengdu city from 2011 to 2017. DBN showed that temperature was related to HFMD at lags 1 and 2. Humidity, wind speed, sunshine, PM10, SO2 and NO2 were related to HFMD at lag 2. Compared with the autoregressive integrated moving average model with external variables (ARIMAX), the CVAR model had a higher coefficient of determination (R2, average difference: + 2.11%; t = 6.2051, P = 0.0003 < 0.05), a lower root mean-squared error (-24.88%; t = -5.2898, P = 0.0007 < 0.05) and a lower mean absolute percentage error (-16.69%; t = -4.3647, P = 0.0024 < 0.05). The accuracy of predicting the time-series shape was 88.16% for the CVAR model and 86.41% for ARIMAX. The CVAR model performed better in terms of variable selection, model interpretation and prediction. Therefore, it could be used by health authorities to identify potential HFMD outbreaks and develop disease control measures.
BACKGROUND: Although exposure to air pollution has been linked to many health issues, few studies have quantified the modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China. METHODS: The data of daily incidence of influenza and the relevant meteorological data and air pollution data in Ningbo from 2014 to 2017 were retrieved. Low, medium and high temperature layers were stratified by the daily mean temperature with 25th and 75th percentiles. The potential modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo was investigated through analyzing the effects of air pollutants stratified by temperature stratum using distributed lag non-linear model (DLNM). Stratified analysis by sex and age were also conducted. RESULTS: Overall, a 10 μg/m(3) increment of O(3), PM(2.5), PM(10) and NO(2) could increase the incidence risk of influenza with the cumulative relative risk of 1.028 (95% CI 1.007, 1.050), 1.061 (95% CI 1.004, 1.122), 1.043 (95% CI 1.003, 1.085), and 1.118 (95% CI 1.028, 1.216), respectively. Male and aged 7-17 years were more sensitive to air pollutants. Through the temperature stratification analysis, we found that temperature could modify the impacts of air pollution on daily incidence of influenza with high temperature exacerbating the impact of air pollutants. At high temperature layer, male and the groups aged 0-6 years and 18-64 years were more sensitive to air pollution. CONCLUSION: Temperature modified the relationship between air pollution and daily incidence of influenza and high temperature would exacerbate the effects of air pollutants in Ningbo.
Airborne bacteria have an important role in atmospheric processes and human health. However, there is still little information on the transmission and distribution of bacteria via the airborne route. To characterize the impact of foggy, haze, haze-fog (HF) and dust days on the concentration and viability of bacteria in atmospheric aerosols, size-segregated bioaerosol samples were collected in the Qingdao coastal region from March 2018 to February 2019. The total airborne microbes and viable/non-viable bacteria in the bioaerosol samples were measured using an epifluorescence microscope after staining with DAPI (4′, 6-diamidino-2-phenylindole) and a LIVE/DEAD® BacLight Bacterial Viability Kit. The average concentrations of total airborne microbes on haze and dust days were 6.75 × 10(5) and 1.03 × 10(6) cells/m(3), respectively, which increased by a factor of 1.3 and 2.5 (on average), respectively, relative to those on sunny days. The concentrations of non-viable bacteria on haze and dust days increased by a factor of 1.2 and 3.6 (on average), respectively, relative to those on sunny days. In contrast, the concentrations of viable bacteria on foggy and HF days were 7.13 × 10(3) and 5.74 × 10(3) cells/m(3), decreases of 38% and 50%, respectively, compared with those on sunny days. Foggy, haze, dust and HF days had a significant effect on the trend of the seasonal variation in the total airborne microbes and non-viable bacteria. Bacterial viability was 20.8% on sunny days and significantly higher than the 14.1% on foggy days, 11.2% on haze days, 8.6% during the HF phenomenon and 6.1% on dust days, indicating that special weather is harmful to some bacterial species. Correlation analysis showed that the factors that influenced the bacterial concentration and viability depended on different weather conditions. The main influential factors were temperature, NO(2) and SO(2) concentrations on haze days, and temperature, particulate matter (PM(2.5)) and NO(2) concentrations on foggy days. The median size of particles containing viable bacteria was 1.94 μm on sunny days and decreased to 1.88 μm and 1.74 μm on foggy and haze days, respectively, but increased to 2.18 μm and 2.37 μm on dust and HF days, respectively.
Although dust storms have been associated with adverse health outcomes, studies on the burden of dust storms on deaths are limited. As global warming has induced significant climate changes in recent decades, which have accelerated desertification worldwide, it is necessary to evaluate the burden of dust storm-induced premature mortality using a critical measure of disease burden, such as the years of life lost (YLL). The YLL attributable to dust storms have not been examined to date. This study investigated the association between Asian dust storms (ADS) and the YLL in Seoul, South Korea, during 2002-2013. We conducted a time-series study using a generalized additive model assuming a Gaussian distribution and applied a distributed lag model with a maximum lag of 5 days to investigate the delayed and cumulative effects of ADS on the YLL. We also conducted stratified analyses using the cause of death (respiratory and cardiovascular diseases) and sociodemographic status (sex, age, education level, occupation, and marital status). During the study period, 108 ADS events occurred, and the average daily YLL was 1511 years due to non-accidental causes. The cumulative ADS exposure over the 6-day lag period was associated with a significant increase of 104.7 (95% CI, 31.0-178.5 years) and 34.4 years (4.0-64.7 years) in the YLL due to non-accidental causes and cardiovascular mortality, respectively. Sociodemographic analyses revealed associations between ADS exposure and the YLL in males, both <65 and ≥65 years old, those with middle-level education, and the unemployed, unmarried, and widowed (26.5-83.8 years). This study provides new evidence suggesting that exposure to dust storms significantly increases the YLL. Our findings suggest that dust storms are a critical environmental risk affecting premature mortality. These results could contribute to the establishment of public health policies aimed at managing dust storm exposure and reducing premature deaths.
Ultra-fine dust refers to particulate matter from external sources, and modernization contributes toward increasing the presence of ultra-fine dust. Young children are particularly vulnerable to the ill effects of ultra-fine dust. Educational buildings, where young children spend the longest duration after their houses, are typically difficult to retrofit. Consequently, they are often used for a long time in the same state as they were when first completed. The buildings deteriorate due to long-term use, particularly because the openings are opened and closed frequently by occupants. Hence, architectural retrofits were performed during vacation, and the effects were evaluated. The evaluation factors include the temperature, relative humidity, and presence of ultra-fine dust. It was confirmed that the temperature and humidity inside the room decreased after the retrofit, while the airtightness performance was strengthened, thereby reducing the I/O ratio. To evaluate the sustainability of architectural remodeling with regard to not only the indoor air environment but also the enhancement of airtightness and insulation performance through the retrofit, a representative scenario was selected with reference to the Intergovernmental Panel on Climate Change’s Future Climate Report. Although it was found that improving both the main entrance and the outdoor window was appropriate, replacing only the outdoor window was the adjudged the optimal retrofit scenario in consideration of the recovery of the investment cost.
Biomass burning and dust storm have significant impacts on air pollution, aerosol properties and potential human health. In order to investigate the influences of them on the chemical component and sources of aerosols, PM2.5 are collected in spring and summer in Beijing. There are two special periods in the whole campaign. (1) Event I, from 16 to 18 April. Air quality is extremely poor during this period mainly affected by biomass burning. (2) Event II, from 4 to 5 May, the biggest dust storm happened on 4 May. In addition, we choose a relative clean period as (3) Event III, from 24 to 29 July, with the lowest PM2.5 levels (16-31 mu g m(-3)) in the whole campaign. Contributions of NO3, SO42-, and NH4+ to PM2.5 in Event I are 22.1%, 11.3%, and 8.3%, respectively, and decreased dramatically to 2.4%, 5.4%, and 0.9% in Event II, suggesting secondary aerosols are more significant in haze period. Both ratios of phytane & pristane and PAHs to OC in Event I and II are comparable, indicating contribution of local primary organic aerosols from fossil fuel combustions to PM2.5 are not significant differences between polluted and dust period. In contrast, ratio of levoglucosan to OC is much higher in Event I and ratio of trehalose to OC is much higher in Event II, suggesting the contribution of regional primary organic aerosols from biomass burning to PM2.5 is important during polluted period, while contribution of regional primary organic aerosols from dust to PM2.5 is significant in dust storm. Based on the organic markers, this work also estimates the source apportionment of PM2.5. Dust and biomass burning are the main contributors in polluted period, while vehicle and cooking are the main contributors in clean period.
OBJECTIVES: In April 2000, a series of wildfires occurred simultaneously in five adjacent small cities located on the eastern coast of Korea. These wildfires burned approximately 23,794 hectares of forestland over several days. We investigated the effects of prenatal exposure to the by-products generated by wildfire disasters on birth weight. METHODS: Birth weight data were obtained for 1999-2001 from the birth registration database of the Korean National Statistical Office and matched with the zip code and exposed/unexposed pregnancy week for days of the wildfires. Generalized linear models were then used to assess the associations between birth weight and exposure to wildfires after adjusting for fetal sex, gestational age, parity, maternal age, maternal education, paternal education, and average exposed atmospheric temperature. RESULTS: Compared with unexposed pregnancies before and after the wildfires, mean birth weight decreased by 41.4 g (95% confidence interval [CI], -72.4 to -10.4) after wildfire exposure during the first trimester, 23.2 g (95% CI, -59.3 to 13.0) for exposure during the second trimester, and 27.0 g (95% CI, -63.8 to 9.8) during the third trimester. In the adjusted model for infants exposed in utero during any trimester, the mean birth weight decreased by 32.5 g (95% CI, -53.2 to -11.7). CONCLUSIONS: We observed a 1% reduction in birth weight after wildfire exposure. Thus, exposure to by-products generated during a wildfire disaster during pregnancy may slow fetal growth and cause developmental delays.
BACKGROUND: Studies on the association between smoke haze (hereafter ‘haze’) and adverse health effects have increased in recent years due to extreme weather conditions and the increased occurrence of vegetation fires. The possible adverse health effects on under-five children (U5Y) is especially worrying due to their vulnerable condition. Despite continuous repetition of serious haze occurrence in Southeast Asia, epidemiological studies in this region remained scarce. Furthermore, no study had examined the association accounting for three important aspects (time lag, duration and intensity) concurrently. OBJECTIVE: This study aimed to examine the association between haze and U5Y mortality in Malaysia, considering time lag, duration and intensity of exposure. METHODS: We performed a time-stratified case-crossover study using a generalized additive model to examine the U5Y mortality related to haze in 12 districts in Malaysia, spanning from 2014 to 2016. A ‘haze day’ was characterized by intensity [based on concentrations of particulate matter (PM)] and duration (continuity of haze occurrence, up to 3 days). RESULTS: We observed the highest but non-significant odds ratios (ORs) of U5Y mortality at lag 4 of Intensity-3. Lag patterns revealed the possibility of higher acuteness at prolonged and intensified haze. Stratifying the districts by the 95th-percentile of PM distribution, the ‘low’ category demonstrated marginal positive association at Intensity-2 Duration-3 [OR: 1.210 (95% confidence interval: 1.000, 1.464)]. CONCLUSIONS: We found a null association between haze and U5Y mortality. The different lag patterns of the association observed over different duration and intensity suggest consideration of these aspects in future studies.
Interactions between climate change and anthropogenic activities result in increasing numbers of open fires, which have been shown to harm maternal health. However, few studies have examined the association between open fire and pregnancy loss. We conduct a self-comparison case-control study including 24,876 mothers from South Asia, the region with the heaviest pregnancy-loss burden in the world. Exposure is assessed using a chemical transport model as the concentrations of fire-sourced PM(2.5) (i.e., fire PM(2.5)). The adjusted odds ratio (OR) of pregnancy loss for a 1-μg/m(3) increment in averaged concentration of fire PM(2.5) during pregnancy is estimated as 1.051 (95% confidence intervals [CI]: 1.035, 1.067). Because fire PM(2.5) is more strongly linked with pregnancy loss than non-fire PM(2.5) (OR: 1.014; 95% CI: 1.011, 1.016), it contributes to a non-neglectable fraction (13%) of PM(2.5)-associated pregnancy loss. Here, we show maternal health is threaten by gestational exposure to fire smoke in South Asia.
Wildfires are increasing and cause health effects. The immediate and ongoing health impacts of prolonged wildfire smoke exposure in severe asthma are unknown. This longitudinal study examined the experiences and health impacts of prolonged wildfire (bushfire) smoke exposure in adults with severe asthma during the 2019/2020 Australian bushfire period. Participants from Eastern/Southern Australia who had previously enrolled in an asthma registry completed a questionnaire survey regarding symptoms, asthma attacks, quality of life and smoke exposure mitigation during the bushfires and in the months following exposure. Daily individualized exposure to bushfire particulate matter (PM(2.5)) was estimated by geolocation and validated modelling. Respondents (n = 240) had a median age of 63 years, 60% were female and 92% had severe asthma. They experienced prolonged intense PM(2.5) exposure (mean PM(2.5) 32.5 μg/m(3) on 55 bushfire days). Most (83%) of the participants experienced symptoms during the bushfire period, including: breathlessness (57%); wheeze/whistling chest (53%); and cough (50%). A total of 44% required oral corticosteroid treatment for an asthma attack and 65% reported reduced capacity to participate in usual activities. About half of the participants received information/advice regarding asthma management (45%) and smoke exposure minimization strategies (52%). Most of the participants stayed indoors (88%) and kept the windows/doors shut when inside (93%), but this did not clearly mitigate the symptoms. Following the bushfire period, 65% of the participants reported persistent asthma symptoms. Monoclonal antibody use for asthma was associated with a reduced risk of persistent symptoms. Intense and prolonged PM(2.5) exposure during the 2019/2020 bushfires was associated with acute and persistent symptoms among people with severe asthma. There are opportunities to improve the exposure mitigation strategies and communicate these to people with severe asthma.
Objective: Adults born either extremely preterm (EP, <28 weeks gestation) or extremely low birthweight (ELBW, <1000 g birthweight) have more obstructive airflow than controls of normal birthweight (>2499 g). We compared self-reported adverse respiratory health outcomes in young adults born EP/ELBW with controls following smoke exposure from the 2019/2020 wildfires in the Australian state of Victoria, and explored if any effects were mediated by airway obstruction, reflected in the forced expiratory volume in 1 second (FEV1). Methods: EP/ELBW participants were derived from all survivors born in the state of Victoria in 1991–92. Contemporaneous controls of normal birthweight (>2499 g) were recruited in the newborn period and matched for sociodemographic variables. Both groups had been assessed at intervals through childhood and into adulthood. Those who participated in the most recent follow-up assessment at 25 years of age, when FEV1 had been measured, were sent a survey when they were approximately 28 years of age asking about respiratory health related outcomes (respiratory symptoms, health services usage, medication uptake) following wildfire smoke exposure over the southern hemisphere summer of 2019–20. Results: A total of 296 participants (166 EP/ELBW; 130 controls) were sent the survey; 44% of the EP/ELBW group and 47% of the control group responded. Compared with controls, EP/ELBW respondents reported more overall respiratory problems (30%vs 20%) and specific respiratory symptoms (breathlessness, wheezing, cough and chest tightness) following wildfire smoke exposure, as well as higher health services usage (e.g. local health clinic, hospital emergency department) and medication uptake for respiratory-related problems. Higher FEV1 values were associated with lower odds of most self-reported respiratory symptoms; adjusting for FEV1 attenuated the differences between EP/ELW and control groups. Conclusion: Survivors born EP/ELBW may be at an increased risk of adverse respiratory health outcomes following wildfire smoke exposure in early adulthood, in part related to worse expiratory airflows.
INTRODUCTION: Numerous studies have reported the modification of particulate matters (PMs) on the association between cold temperature and health. However, it remains uncertain whether the modification effect may vary by size of PMs, especially in Shandong Province, China where the disease burdens associated with cold temperature and PMs are both substantial. This study aimed to examine various interactive effects of cold exposure and ambient PMs with diameters ≤1/2.5 μm (PM1 and PM2.5) on premature deaths in Shandong Province, China. METHODS: In the 2013-2018 cold seasons, data on daily mortality, PM1 and PM2.5, and weather conditions were collected from the 1822 sub-districts of Shandong Province. A time-stratified case-crossover study design was performed to quantify the cumulative association between ambient cold and mortality over lag 0-12 days, with a linear interactive term between temperature and PM1 and PM2.5 additionally added into the model. RESULTS: The mortality risk increased with temperature decline, with the cumulative OR of extreme cold (-16.9°C, the 1st percentile of temperature range) being 1.83 (95% CI: 1.66, 2.02), compared with the minimum mortality temperature. The cold-related mortality risk was 2.20 (95%CI: 1.83, 2.64) and 2.24 (95%CI: 1.78, 2.81) on high PM1 and PM2.5 days, which dropped to 1.60 (95%CI: 1.39, 1.84) and 1.60 (95%CI: 1.37, 1.88) on low PM1 and PM2.5 days. PM1 showed greater modification effect for per unit concentration increase than PM2.5. For example, for each 10?g/m3 increase in PM1 and PM2.5, the mortality risk associated with extreme cold temperature increased by 7.6% (95% CI: 1.3%, 14.2%) and 2.6% (95% CI: -0.7%, 5.9%), respectively. DISCUSSION: The increment of smaller PMs’ modification effect varied by population subgroups, which was particularly strong in the elderly aged over 75 years and individuals with middle school education and below. Specific health promotion strategies should be developed towards the greater modification effect of smaller PMs on cold effect.
Anxiety and depression are severe public health problems worldwide. The effects of ozone exposure on anxious and depressive symptoms remain largely unknown, especially in China. We evaluated the associations between ozone exposure and depression and anxiety among middle-aged and older adults across China. A multi-center community-based repeated measurement study among middle-aged and older adults was conducted from 2017 to 2018 in 11 provinces in China. The status of depression and anxiety was measured using Patient Health Questionnaire-9 (PHQ-9) and the generalized anxiety disorder seven-item (GAD-7) scale at the cut-off point of five, respectively. Concentrations of multiple ozone metrics were collected from real-time monitoring stations. The multilevel logistic regression model with random intercept was used to evaluate the effects of ambient ozone on anxiety and depression over different exposure windows. After adjusting for potential confounders, a 10 mu g /m(3) increase in the three months moving average of ozone was associated with the risk of anxiety [odds ratio (OR) = 1.25; 95% confidence interval (CI): 1.15; 1.37] and depression (OR = 1.17; 95% CI: 1.08; 1.27). A significantly positive modification effect of temperature on associations between ozone and anxiety was also found, while there is no interaction for depression. Exposure-response curves showed that there may be a threshold for the effect of ozone exposure on anxiety and depression over the three months moving average concentrations, with similar patterns observed at different temperature levels. People over 65 years old were at significantly higher risks of ozone-associated depression, while anxiety was more strongly associated with ozone in hypertensive patients. Our study supports the theory that anxiety and depression is associated with mid-term ozone exposure in China, and temperatures significantly enhanced their associations. These findings may have significant implications for promoting prevention activities regarding mental disorders and approaches in reducing the disease burden by simultaneously controlling air pollution and mitigating climate change.
WHAT IS ALREADY KNOWN ABOUT THIS TOPIC? Ozone (O(3)) is a weather-driven photochemical ambient pollutant, and its harm to human health may be affected by meteorological factors such as temperature. However, there is conflicting evidence regarding whether temperature can modify the effects of ozone on health. WHAT IS ADDED BY THIS REPORT? Short-term exposure to O(3) in the Beijing Municipality, Tianjin Municipality, Hebei Province, and surrounding areas was associated with an increased risk of human mortality and that association was positive modified by relatively higher (>75th 24 h-average temperature) or extreme cold temperature (<10th 24 h-average temperature). Under extreme temperatures (>90th 24 h-average temperature) modification, the associations were further increased. Cardiopulmonary diseases, as vulnerable diseases of air pollution, their mortality risks associated with O(3) were markedly strengthened by uncomfortable temperatures. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE? This study suggests that policymakers should pay attention to the synergistic effect between ozone and heat or extreme cold on human health, as well as provide evidence for establishing an integrated early-warning system to protect the public against both uncomfortable temperature and air pollution.
Heatwaves (HWs) paired with higher ozone (O-3) concentration at the surface level pose a serious threat to human health. Their combined modulation of synoptic patterns and urbanization remains unclear. Using 5 years of summertime temperature and O-3 concentration observation in Beijing, this study explored potential drivers of compound HWs and O-3 pollution events and their public health effects. Three favorable synoptic weather patterns were identified to dominate the compound HWs and O-3 pollution events. These weather patterns contributing to enhance those conditions are characterized by sinking air motion, low boundary layer height, and high temperatures. Under the synergy of HWs and O-3 pollution, the mortality risk from all non-accidental causes increased by approximately 12.31 % (95 % confidence interval: 4.66 %, 20.81 %). Urbanization caused a higher risk of HWs and O-3 in urban areas than at rural stations. Particularly, due to O(3 )depletion caused by NO titration at traffic and urban stations, the health risks related to O(3 )pollution in different regions are characterized as follows: suburban stations > urban stations > rural stations > traffic stations. In general, favorable synoptic patterns and urbanization enhanced the health risk of these compound events in Beijing by 33.09 % and 18.95 %, respectively. Our findings provide robust evidence and implications for forecasting compound HWs and O-3 pollution events and their health risks in Beijing or in other urban areas all over the world that have high concentrations of O-3 and high-density populations.
The 1.5 °C pathways initially promoted by the challenges presented by climate change could bring substantial air quality-related benefits. However, since there is a lack of comprehensive assessment on emissions of air pollutants, meteorology, air quality, and heatwave occurrences under different climate goals, how significant the clean air cobenefits compared with the direct climate-related impact is uncertain. In this study, we assess the cobenefits of 1.5 °C pathways for air quality in China by linking multiple shared socioeconomic pathways, ensembling simulations of regional climate-air quality dynamic downscaling and an air pollution and climate-related health assessment model, and compare different kinds of benefits: the health benefits from direct slowing climate (reduced heatwaves) versus the health cobenefits from air quality improvement (the improved air quality from reduced air pollutants versus meteorological changes). The benefit of reduced air pollution emissions associated with sustainable development under 1.5 °C pathways dominated the overall impact, which could avoid 1 589 000 PM(2.5)-related and 526 000 O(3)-related deaths in 2050. Correspondingly, the impact of changed meteorology on air quality would avoid additional 8000 PM(2.5)-related deaths in 2050 under 1.5 °C pathways yet would lead to 22 000 O(3)-related deaths. Also, the heatwave-related deaths could be avoided by 7000. The substantial anthropogenic emission reduction cobenefits of 1.5 °C pathways in improving air quality significantly exceed the direct climate (heatwave-related) benefits and completely offset the impact of meteorological changes’ impact on air pollution under climate change.
A multitude of epidemiological studies have demonstrated that both ambient temperatures and air pollution are closely related to health outcomes. However, whether temperature has modification effects on the association between ozone and health outcomes is still debated. In this study, three parallel time-series Poisson generalized additive models (GAMs) were used to examine the effects of modifying ambient temperatures on the association between ozone and mortality (including non-accidental, respiratory, and cardiovascular mortality) in Chengdu, China, from 2014 to 2016. The results confirmed that the ambient high temperatures strongly amplified the adverse effects of ozone on human mortality; specifically, the ozone effects were most pronounced at > 28 °C. Without temperature stratification conditions, a 10-μg/m(3) increase in the maximum 8-h average ozone (O(3-8hmax)) level at lag01 was associated with increases of 0.40% (95% confidence interval [CI] 0.15%, 0.65%), 0.61% (95% CI 0.27%, 0.95%), and 0.69% (95% CI 0.34%, 1.04%) in non-accidental, respiratory, and cardiovascular mortality, respectively. On days during which the temperature exceeded 28 °C, a 10-μg/m(3) increase in O(3-8hmax) led to increases of 2.22% (95% CI 1.21%, 3.23%), 2.67% (95% CI 0.57%, 4.76%), and 4.13% (95% CI 2.34%, 5.92%) in non-accidental, respiratory, and cardiovascular mortality, respectively. Our findings validated that high temperature could further aggravate the health risks of O(3-8hmax); thus, mitigating ozone exposure will be brought into the limelight especially under the context of changing climate.
Numerous epidemiological studies have reported that ozone (O(3)) and temperature are independently associated with health outcomes, but modification of the effects of O(3) on health outcomes by temperature, and vice versa, has not been fully described. This study aimed to investigate effect modification by temperature on the association between O(3) and emergency ambulance dispatches (EADs) in Japan. Data on daily air pollutants, ambient temperature, and EADs were obtained from eight Japanese cities from 2007 to 2015. A distributed lag non-linear model combined with Poisson regression was performed with temperature as a confounding factor and effect modifier to estimate the effects of O(3) on EADs at low (<25th percentile), moderate (25th-75th percentile), and high (>75th percentile) temperature for each city. The estimates obtained from each city were pooled by random-effects meta-analysis. When temperature was entered as a confounder, the estimated effects of O(3) on EADs for all acute, cardiovascular, and respiratory illnesses were largest at lag 0 (current-day lag). Therefore, this lag was used to further estimate the effects of O(3) on EADs in each temperature category. The estimated effects of O(3) on EADs for all acute, cardiovascular, and respiratory illnesses in all eight Japanese cities increased with increasing temperature. Specifically, a 10 ppb increase in O(3) was associated with 0.80 % (95 % CI: 0.25 to 1.35), 0.19 % (95 % CI: -0.85 to 1.25), and 1.14 % (95 % CI: -0.01 to 2.31) increases in the risk of EADs for all acute, cardiovascular, and respiratory illnesses, respectively, when city-specific daily temperature exceeded the 75th percentile. Our findings suggest that the association between O(3) and EADs for all acute, cardiovascular, and respiratory illnesses is the highest during high temperature. Finding of this study can be used to develop potential mitigation measures against O(3) exposure in high temperature environment to reduce its associated adverse health effects.
BACKGROUND: Numerous studies have confirmed the association of ambient temperature and air pollution with a higher risk of morbidities, yet few have addressed their effect on the ocular system. The purpose of this study was to assess the association between temperature, air pollution, and emergency room visits for conjunctivitis. METHODS: In this case-crossover study, the records of all emergency room visits to Soroka University Medical Center (SUMC) from 2009 to 2014 were reviewed for patients with conjunctivitis. Daily exposure to fine and coarse particulate matter and temperature were determined by a hybrid model involving satellite sensors. Mean relative humidity was obtained from the Ministry of Environmental Protection meteorological monitoring station located in Beer-Sheva. RESULTS: Six hundred one patients were diagnosed with conjunctivitis in the SUMC emergency room. We discovered a positive association between temperature increments and incidence of conjunctivitis. The strongest effect was found during summer and autumn, with an immediate (lag0) incidence increase of 8.1% for each 1 °C increase in temperature (OR = 1.088, 95%CI: 1.046-1.132) between 24 and 28 °C in the summer and 7.2% for each 1 °C increase in temperature (OR = 1.072, 95%CI: 1.036-1.108) between 13 and 23 °C in the autumn. There was no statistically significant association between fine and coarse particulate matter and conjunctivitis incidence. CONCLUSION: Temperature increases during summer and autumn are significantly associated with an increased risk of conjunctivitis. Conjunctivitis is not associated with non-anthropogenic air pollution. These findings may help community clinics and hospital emergency rooms better predict conjunctivitis cases and will hopefully lead to improved prevention efforts that will lower the financial burden on both the individual and the public.
The Australian 2019/2020 bushfires were unprecedented in their extent and intensity, causing a catastrophic loss of habitat, human and animal life across eastern-Australia. We use a regional air quality model to assess the impact of the bushfires on particulate matter with a diameter less than 2.5 μm (PM(2.5)) concentrations and the associated health impact from short-term population exposure to bushfire PM(2.5). The mean population Air Quality Index (AQI) exposure between September and February in the fires and no fires simulations indicates an additional ∼437,000 people were exposed to “Poor” or worse AQI levels due to the fires. The AQ impact was concentrated in the cities of Sydney, Newcastle-Maitland, Canberra-Queanbeyan and Melbourne. Between October and February 171 (95% CI: 66-291) deaths were brought forward due to short-term exposure to bushfire PM(2.5). The health burden was largest in New South Wales (NSW) (109 (95% CI: 41-176) deaths brought forward), Queensland (15 (95% CI: 5-24)), and Victoria (35 (95% CI: 13-56)). This represents 38%, 13% and 30% of the total deaths brought forward by short-term exposure to all PM(2.5). At a city-level 65 (95% CI: 24-105), 23 (95% CI: 9-38) and 9 (95% CI: 4-14) deaths were brought forward from short-term exposure to bushfire PM(2.5), accounting for 36%, 20%, and 64% of the total deaths brought forward from all PM(2.5.) Thus, the bushfires caused substantial AQ and health impacts across eastern-Australia. Climate change is projected to increase bushfire risk, therefore future fire management policies should consider this.
This study investigated the contributions of particulate matter (PM) from various emission sources during the dry season, which resulted from frequent fires occurring in degraded forests and peatlands in Indonesia. Samples of fine (PM2.5) and coarse (PM2.5-10) particles collected during the dry season in Riau, Indonesia were analyzed to determine the mass concentrations of metallic trace elements, ionic compound, black carbon (BC), and organic carbon (OC). The average concentrations of PM2.5 and PM2.5-10 at Riau, Indonesia were 63.85 +/- 3.22 mu g m(-3) and 27.72 +/- 2.40 mu g m(-3), respectively. The positive matrix factorization (PMF) model was adopted to identify possible PM sources and their contributions to the ambient PM level. The PMF results identified six major PM2.5 sources, including biomass burning (BB) (28.7%), secondary aerosols (SA) (26.9%), vehicle exhaust (VE) (12.8%), industrial emissions (IE) (12.3%), soil dust (SD) (11.9%), and sea salt (SS) (7.5%). Moreover, there were five primary PM2.5-10 sources, including VE (28.6%) and BB (24%), followed by IE (19.9%), SD (17.2%), and SA (15.3%). A conditional probability function (CPF) analysis revealed that the southeast sector dominated among source direction-dependent contributions. The noncarcinogenic health risks for both adults and children resulting from exposure to PM2.5 were mainly contributed by Co, Ni, and Mn, and carcinogenic risks were caused by the toxic metals Cr and Co. Both noncarcinogenic and carcinogenic health risks resulting from cumulative multielement exposure for both adults and children exceeded acceptable levels. Clearly, more attention should be devoted to reducing the noncarcinogenic and carcinogenic health risks caused by particulate-bound toxic elements through inhalation exposure.
Over the past 30 years, forest fire has been one of main ecological issues in Indonesia. Human-caused deforestation was accused to be the reason behind this matter, apart from the drastic changing in global climate. Palangkaraya is one of the citiesaffected by haze of the forest fire in 2015; considered to be the worst year of forest fire with the value of PM10 was above the normal threshold. As the impact to the community wellbeing, the prevalence of acute respiratory infection (ARI) in October 2015was increasing especially in children. The research aimed to analyse the spatial distribution of children with ARI in October 2015 at Palangkaraya City. Data onARI number were collected from Primary Care under Public Health Office of Palangkaraya City. The PM 10 value was collected bythe Environmental Agency of Palangkaraya City. The spatial analyse method was conducted using theAverage Nearest Neighbour (ANN) method. The result shows that the number of ANN ratio is 0.761801. It means that the distribution pattern of children with ARI in Central Kalimantan during the forest fire in October 2015 was in cluster form.
BACKGROUND: Climate change has resulted in an increase in ambient temperatures during the summer months as well as an increase in risk of associated air pollution and of potentially disastrous bushfires throughout much of the world. The increasingly frequent combination of elevated summer temperatures and bushfires may be associated with acute increases in risks of cardiovascular events, but this relationship remains unstudied. We evaluated the individual and cumulative impacts of daily fluctuations in temperature, fine particulate matter of less than 2.5 µm (PM(2.5)) pollution and presence of bushfires on incidence of acute coronary syndromes and Takotsubo syndrome. METHODS: From November 1, 2019, to February 28, 2020, all admissions with acute coronary syndromes or Takotsubo syndrome to South Australian tertiary public hospitals were evaluated. Univariate and combined associations were sought among each of 1) maximal daily temperature, 2) PM(2.5) concentrations, and 3) presence of active bushfires within 200 km of the hospitals concerned. RESULTS: A total of 504 patients with acute coronary syndromes and 35 with Takotsubo syndrome were studied. In isolation, increasing temperature was associated (r(s) = 0.26, P = .005) with increased incidence of acute coronary syndromes, while there were similar, but nonsignificant correlations for PM(2.5) and presence of bushfires. Combinations of all these risk factors were also associated with a doubling of risk of acute coronary syndromes. No significant associations were found for Takotsubo syndrome. CONCLUSION: The combination of high temperatures, presence of bushfires and associated elevation of atmospheric PM(2.5) concentrations represents a substantially increased risk for precipitation of acute coronary syndromes; this risk should be factored into health care planning including public education and acute hospital preparedness.
BACKGROUND: Air pollution including particulate matter with an aerodynamic diameter ≤2.5 µm (PM2.5) increases the risk of acute myocardial infarction. However, whether short-term exposure to PM2.5 triggers the onset of myocardial infarction with nonobstructive coronary arteries, compared with myocardial infarction with coronary artery disease, has not been elucidated. This study aimed to estimate the association between short-term exposure to PM2.5 and admission for acute myocardial infarction, myocardial infarction with coronary artery disease, and myocardial infarction with nonobstructive coronary arteries. DESIGN: This was a time-stratified case-crossover study and multicenter validation study. METHODS: This study used a nationwide administrative database in Japan between April 2012-March 2016. Of 137,678 acute myocardial infarction cases, 123,633 myocardial infarction with coronary artery disease and 14,045 myocardial infarction with nonobstructive coronary arteries were identified by a validated algorithm combined with International Classification of Disease (10th revision), diagnostic, and procedure codes. Air pollutants and meteorological data were obtained from the monitoring station nearest to the admitting hospital. RESULTS: In spring (March-May), the short-term increase of 10 µg/m3 in PM2.5 2 days before admission was significantly associated with admission for acute myocardial infarction, myocardial infarction with nonobstructive coronary arteries, and myocardial infarction with coronary artery disease after adjustment for meteorological variables (odds ratio 1.060, 95% confidence interval 1.038-1.082; odds ratio 1.151, 1.079-1.227; odds ratio 1.049, 1.026-1.073, respectively), while the association was not significant in other variables. These associations were also observed after adjustment for other co-pollutants. The risk for myocardial infarction with nonobstructive coronary arteries (vs myocardial infarction with coronary artery disease) was associated with an even lower concentration of PM2.5 under the current environmental standards. CONCLUSIONS: This study showed the seasonal difference of acute myocardial infarction risk attributable to PM2.5 and the difference in the threshold of triggering the onset of acute myocardial infarction subtype.
BACKGROUND: Previous reports indicate an association between ambient temperature (Ta) and air pollution exposure during pregnancy and preterm birth (PTB). Nevertheless, information regarding the association between environmental factors and specific precursors of spontaneous preterm birth is lacking. We aimed to determine the association between Ta and air pollution during gestation and the precursors of spontaneous preterm parturition, i.e. preterm labor (PTL) and preterm prelabor rupture of membranes (PPROM). METHODS: From 2003 to 2013 there were 84,476 deliveries of singleton gestation that comprised the study cohort. Exposure data during pregnancy included daily measurements of temperature and particulate matter <2.5 μm and <10 μm, PM(2.5) and PM(10), respectively. Deliveries were grouped into PPROM, PTL and non-spontaneous preterm and term deliveries. Exposure effect was tested in windows of a week and two days prior to admission for delivery and adjusted to gestational age and socio-economic status. Poisson regression models were used for analyses. RESULTS: There is an association of environmental exposure with the precursors of spontaneous preterm parturition; PPROM was more sensitive to Ta fluctuations than PTL. This effect was modified by the ethnicity, Bedouin-Arabs were susceptible to elevated Ta, especially within the last day prior to admission with PPROM (Relative Risk (RR) =1.19 [95% CI, 1.03; 1.37]). Jews, on the other hand, were susceptible to ambient pollutants, two (RR=1.025 [1.010; 1.040]) and one (RR= 1.017 [1.002; 1.033]) days prior to spontaneous PTL with intact membranes resulting in preterm birth. CONCLUSION: High temperature is an independent risk factor for PPROM among Bedouin-Arabs; ambient pollution is an independent risk factor for spontaneous PTL resulting in preterm birth. Thus, the precursors of spontaneous preterm parturition differ in their association with environmental factors.
The differential effect of meteorological factors and air pollutants on pediatric epistaxis in younger and older children has not been evaluated. We evaluated the distribution of pediatric epistaxis cases between younger (0-5 years) and older children (6-18 years). Subsequently, we assessed and compared the effects of meteorological variables and the concentration of particulate matter measuring ≤ 10 μm in diameter (PM10) on hospital epistaxis presentation in younger and older children. This retrospective study included pediatric patients (n = 326) who presented with spontaneous epistaxis between January 2015 and August 2019. Meteorological conditions and PM10 concentration were the exposure variables, and data were obtained from Korea Meteorological Administration 75. The presence and cumulative number of epistaxis presentations per day were considered outcome variables. Air temperature, wind speed, sunshine duration, and PM10 concentration in younger children, and sunshine duration and air pressure in older children, significantly correlated with the presence of and cumulative number of epistaxis presentations per day. The PM10 concentration was not a significant factor in older children. Thus, meteorological factors and PM10 concentration may differentially affect epistaxis in younger (0-5-year-olds) and older (6-18-year-olds) children. Risk factors for pediatric epistaxis should be considered according to age.
BACKGROUND: Positive associations between ambient PM(2.5) and cardiorespiratory disease have been well demonstrated during the past decade. However, few studies have examined the adverse effects of PM(2.5) based on an entire population of a megalopolis. In addition, most studies in China have used averaged data, which results in variations between monitoring and personal exposure values, creating an inherent and unavoidable type of measurement error. METHODS: This study was conducted in Wuhan, a megacity in central China with about 10.9 million people. Daily hospital admission records, from October 2016 to December 2018, were obtained from the Wuhan Information center of Health and Family Planning, which administrates all hospitals in Wuhan. Daily air pollution concentrations and weather variables in Wuhan during the study period were collected. We developed a land use regression model (LUR) to assess individual PM(2.5) exposure. Time-stratified case-crossover design and conditional logistic regression models were adopted to estimate cardiorespiratory hospitalization risks associated with short-term exposure to PM(2.5). We also conducted stratification analyses by age, sex, and season. RESULTS: A total of 2,806,115 hospital admissions records were collected during the study period, from which we identified 332,090 cardiovascular disease admissions and 159,365 respiratory disease admissions. Short-term exposure to PM(2.5) was associated with an increased risk of a cardiorespiratory hospital admission. A 10 μg/m(3) increase in PM(2.5) (lag0-2 days) was associated with an increase in hospital admissions of 1.23% (95% CI 1.01-1.45%) and 1.95% (95% CI 1.63-2.27%) for cardiovascular and respiratory diseases, respectively. The elderly were at higher PM-induced risk. The associations appeared to be more evident in the cold season than in the warm season. CONCLUSIONS: This study contributes evidence of short-term effects of PM(2.5) on cardiorespiratory hospital admissions, which may be helpful for air pollution control and disease prevention in Wuhan.
Air Pollution is an emerging disaster and considered one of the biggest challenges of the world to effectively con-trol, mitigate and forecast due to abrupt variability, stochastic, and chaotic pattern of particulate matter (PM) in terms of time and space of the pollutants. Composition of ambient PM not only causes serious damage to public health but also emerging as a global hazard particularly for urban environment with negative impact on human health including morbidity. Mortality and ultimately towards unstable economy. In this study, hourly short-term trends of PM2.5 and air quality index (AQI) of Lahore city of Pakistan is monitored and mitigated by the design of fractional order Lorenz based physics informed hybrid computing paradigm SARFIMA-NARX for forecasting hourly pattern of next two days. The complex dynamics of earth system and its weather forecast are character-ized by combination of biological, physical, and chemical processes governed by the different laws of science that provides additional information for the climate variation in terms of physics inform intelligence. The perfor-mance index based on statistical indicator of RMSE confirmed the high accuracy and efficiency of designed model to predict the pattern. The early predictions based on computational intelligence paradigm may serve as a surveillance system to reduce the air pollution through cost-effectiveness planning by environmental monitor-ing agencies.(c) 2022 Elsevier Ltd. All rights reserved.
The rapid development of industrialization and urbanization has had a substantial impact on the increasing air pollution in many populated cities around the globe. Intensive research has shown that ambient aerosols, especially the fine particulate matter PM2.5, are highly correlated with human respiratory diseases. It is critical to analyze, forecast, and mitigate PM2.5 concentrations. One of the typical meteorological phenomena seducing PM2.5 concentrations to accumulate is temperature inversion which forms a warm-air cap to blockade the surface pollutants from dissipating. This paper analyzes the meteorological patterns which coincide with temperature inversion and proposes two machine learning classifiers for temperature inversion classification. A separate multivariate regression model is trained for the class with or without manifesting temperature inversion phenomena, in order to improve PM2.5 forecasting performance. We chose Puli township as the studied site, which is a basin city easily trapping PM2.5 concentrations. The experimental results with the dataset spanning from 1 January 2016 to 31 December 2019 show that the proposed temperature inversion classifiers exhibit satisfactory performance in F1-Score, and the regression models trained from the classified datasets can significantly improve the PM2.5 concentration forecast as compared to the model using a single dataset without considering the temperature inversion factor.
The impact of atmospheric concentration of particulate matter ≤10 μm in diameter (PM(10)) continues to attract research attention. This study aimed to evaluate the effects of meteorological factors, including PM(10) concentration, on epistaxis presentation in children and adults. We reviewed the data from 1557 days and 2273 cases of epistaxis between January 2015 and December 2019. Eligible patients were stratified by age into the children (age ≤17 years) and adult groups. The main outcome was the incidence and cumulative number of epistaxis presentations in hospital per day and month. Meteorological factors and PM(10) concentration data were obtained from the Korea Meteorological Administration. Several meteorological factors were associated with epistaxis presentation in hospital; however, these associations differed between children and adults. Only PM(10) concentration was consistently associated with daily epistaxis presentation in hospital among both children and adults. Additionally, PM(10) concentration was associated with the daily cumulative number of epistaxis presentations in hospital in children and adults. Furthermore, the monthly mean PM(10) concentration was significantly associated with the total number of epistaxis presentations in the corresponding month. PM(10) concentration should be regarded as an important environmental factor that may affect epistaxis in both children and adults.
OBJECTIVE: The associations between climate variables and diseases such as respiratory infections, influenza, pediatric seizure, and gastroenteritis have been long appreciated. Infection is the main reason for acute otitis media (AOM) incidence. However, few previous studies explored the correlation between climatic parameters and AOM infections. The most important meteorological factors, temperature, relative humidity, and fine particulate matter (PM2.5), were included in this study. We studied the relationship between these meteorological factors and the AOM visits. MATERIALS AND METHODS: It was a retrospective cross-sectional study. A linear correlation and a linear regression model were used to explore the AOM visits and meteorological factors. RESULTS: A total of 7075 emergency department visits for AOM were identified. Relative humidity was found an independent risk factor for the AOM visits in preschool children (regression coefficient = -10.841<0, P = .039 < .05), but not in infants and school-age children. Average temperature and PM2.5 were not correlated with AOM visits. CONCLUSION: Humidity may have a significant inverse impact on the incidence of AOM in preschool-age children.
Low-carbon pathways consistent with the 2 degrees C and 1.5 degrees C long-term climate goals defined in the Paris Agreement are likely to induce substantial co-benefits for air pollution and associated health impacts. In this analysis, using five global integrated assessment models, we quantify the emission reductions in key air pollutants resulting from the decarbonization of energy systems and the resulting changes in premature mortality attributed to the exposure to ambient concentrations of fine particulate matter. The emission reductions differ by sectors. Sulfur emissions are mainly reduced from power plants and industry, cuts in nitrogen oxides are dominated by the transport sector, and the largest abatement of primary fine particles is achieved in the residential sector. The analysis also shows that health benefits are the largest when policies addressing climate change mitigation and stringent air pollution controls are coordinated. We decompose the key factors that determine the extent of health co-benefits, focusing on Asia: changes in emissions, urbanization rates, population growth and ageing. Demographic processes, particularly due to ageing population, counteract in many regions the mortality reductions realized through lower emissions.
The objective of this study was to evaluate the influence of exposure to meteorological conditions, including air pollution, on thyroid cancer. A nested case-control study was conducted utilizing 4632 patients with thyroid cancer and 18,528 control subjects who were matched at a 1:4 ratio by age group, sex, income, and region of residence. Korean National Health Insurance Service-Health Screening Cohort data from 2002 to 2015 were used. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for thyroid cancer correlated with meteorological and air pollution exposure over a moving average of 3 years before the index dates. For all participants, the adjusted ORs associated with relative humidity (1.01, 95% CI 1.00-1.03, P value = 0.023), ambient atmospheric pressure (1.02, 95% CI 1.01-1.03, P value < 0.001), and sunshine duration (1.17, 95% CI 1.04-1.31, P value = 0.007) indicated correlations with the occurrence of thyroid cancer; however, these results were inconsistent in the subgroup analyses. Overall, exposure to nitrogen dioxide (NO(2)) (1.33, 95% CI 1.24-1.43, P value < 0.001) and particulate matter (PM(10)) (0.64, 95% CI 0.60-0.69, P value < 0.001) were related to thyroid cancer. These relationships persisted in the subgroup analyses. In conclusion, thyroid cancer occurrence was positively associated with NO(2) exposure and negatively associated with PM(10) exposure.
Meeting the Paris Agreement on climate change requires substantial investments in low-emissions energy and significant improvements in end-use energy efficiency. These measures can also deliver improved air quality and there is broad recognition of the health benefits of decarbonising energy. Monetising these health benefits is an important part of a robust assessment of the costs and benefits of renewable energy and energy efficiency programs (clean energy programs (CEP)) and a variety of methods have been used to estimate health benefits at national, regional, continental and global scales. Approaches, such as unit damage cost estimates and impact pathways, differ in complexity and spatial coverage and can deliver different estimates for air pollution costs/benefits. To date, the monetised health benefits of CEP in Australia have applied international and global estimates that can range from 2-229USD/tCO2 (USD 2016). Here, we calculate the current health damage costs of coal-fired power in New South Wales (NSW), Australia’s most populous state, and the health benefits of CEP. Focusing on PM2.5 pollution, we estimate the current health impacts of coal-fired power at 3.20USD/MWh, approximately 10% of the generation costs, and much lower than previous estimates. We demonstrate the need for locally specific assessment of the air pollution benefits of CEP and illustrate that without locally specific information, the relative costs/benefits of CEP may be significantly over- or understated. We estimate that, for NSW, the health benefits from CEP are 1.80USD/MWh and that the current air pollution health costs of coal-fired power in NSW represent a significant unpriced externality.
BACKGROUND: Bushfire smoke is a major ongoing environmental hazard in Australia. In the summer of 2019-2020 smoke from an extreme bushfire event exposed large populations to high concentrations of particulate matter (PM) pollution. In this study we aimed to estimate the effect of bushfire-related PM of less than 2.5 μm in diameter (PM(2.5)) on the risk of mortality in Sydney, Australia from 2010 to 2020. METHODS: We estimated concentrations of PM(2.5) for three subregions of Sydney from measurements at monitoring stations using inverse-distance weighting and cross-referenced extreme days (95th percentile or above) with satellite imagery to determine if bushfire smoke was present. We then used a seasonal and trend decomposition method to estimate the Non-bushfire PM(2.5) concentrations on those days. Daily PM(2.5) concentrations above the Non-bushfire concentrations on bushfire smoke days were deemed to be Bushfire PM(2.5). We used distributed-lag non-linear models to estimate the effect of Bushfire and Non-bushfire PM(2.5) on daily counts of mortality with sub-analyses by age. These models controlled for seasonal trends in mortality as well as daily temperature, day of week and public holidays. RESULTS: Within the three subregions, between 110 and 134 days were identified as extreme bushfire smoke days within the subregions of Sydney. Bushfire-related PM(2.5) ranged from 6.3 to 115.4 µg/m(3). A 0 to 10 µg/m(3) increase in Bushfire PM(2.5) was associated with a 3.2% (95% CI 0.3, 6.2%) increase in risk of all-cause death, cumulatively, in the 3 days following exposure. These effects were present in those aged 65 years and over, while no effect was observed in people under 65 years. CONCLUSION: Bushfire PM(2.5) exposure is associated with an increased risk of mortality, particularly in those over 65 years of age. This increase in risk was clearest at Bushfire PM(2.5) concentrations up to 30 µg/m(3) above background (Non-bushfire), with possible plateauing at higher concentrations of Bushfire PM(2.5).
We examine 512 Australian newspaper articles published over a five-year period (2016-2021) that report on air pollution due to bushfire smoke and resulting human health impacts. We analyze to what extent these articles provide information on the possible range of negative health impacts due to bushfire smoke pollution, and to what extent they report on climate change as a driver behind increased bushfire risk. A temporary surge in articles in our sample occurs during the unusually severe 2019/2020 Black Summer bushfires. However, most articles are limited to general statements about the health impacts of bushfire smoke, with only 50 articles in the sample (9%) mentioning an explicit link between bushfire smoke inhalation and cardiovascular and respiratory problems or increases in mortality risk. About 148 of the 512 articles in the sample (29%) established a connection between bushfire risk and climate change. We carry out a further keyword analysis to identify differences in reporting by Australia’s two main publishing groups (News Corp Australia and Nine Entertainment), which shows that articles in News Corp Australia outlets offered the lowest climate change coverage. We suggest that more detailed communication strategies are needed to strengthen public preparedness for future impacts.
Smoke from forest fires can reach hazardous levels for extended periods of time. We aimed to determine if there is an association between particulate matter ≤2.5 µm in aerodynamic diameter (PM2.5) and living in a forest fire–prone province and cognitive function. We used data from the Indonesian Family and Life Survey. Cognitive function was assessed by the Ravens Colored Progressive Matrices (RCPM). We used regression models to estimate associations between PM2.5 and living in a forest fire–prone province and cognitive function. In multivariable models, we found very small positive relationships between PM2.5 levels and RCPM scores (PM2.5 level at year of survey: β = 0.1%; 95% confidence interval (CI) [0.01, 0.19%]). There were no differences in RCPM scores for children living in forest fire–prone provinces compared with children living in non-forest fire–prone provinces (mean difference = −1.16%, 95% CI [–2.53, 0.21]). RCPM scores were lower for children who had lived in a forest fire–prone province all their lives compared with children who lived in a non-forest fire–prone province all their life (β = −1.50%; 95% CI [–2.94, –0.07]). Living in a forest fire–prone province for a prolonged period of time negatively affected cognitive scores after adjusting for individual factors.
Smoke haze due to vegetation and peatland fires in Southeast Asia is a serious public health concern. Several approaches have been applied in previous studies; however, the concepts and interpretations of these approaches are poorly understood. In this scoping review, we addressed issues related to the application of epidemiology (EPI), health burden estimation (HBE), and health risk assessment (HRA) approaches, and discussed the interpretation of findings, and current research gaps. Most studies reported an air quality index exceeding the ‘unhealthy’ level, especially during smoke haze periods. Although smoke haze is a regional issue in Southeast Asia, studies on its related health effects have only been reported from several countries in the region. Each approach revealed increased health effects in a distinct manner: EPI studies reported excess mortality and morbidity during smoke haze compared to non-smoke haze periods; HBE studies estimated approximately 100,000 deaths attributable to smoke haze in the entire Southeast Asia considering all-cause mortality and all age groups, which ranged from 1,064-260,000 for specified mortality cause, age group, study area, and study period; HRA studies quantified potential lifetime cancer and non-cancer risks due to exposure to smoke-related chemicals. Currently, there is a lack of interconnection between these three approaches. The EPI approach requires extensive effort to investigate lifetime health effects, whereas the HRA approach needs to clarify the assumptions in exposure assessments to estimate lifetime health risks. The HBE approach allows the presentation of health impact in different scenarios, however, the risk functions used are derived from EPI studies from other regions. Two recent studies applied a combination of the EPI and HBE approaches to address uncertainty issues due to the selection of risk functions. In conclusion, all approaches revealed potential health risks due to smoke haze. Nonetheless, future studies should consider comparable exposure assessments to allow the integration of the three approaches.
Due to climate change, catastrophic events such as landscape fires are increasing in frequency and severity. However, relatively little is known about the longer-term mental health outcomes of such events. Follow-up was conducted of 709 adults exposed to smoke from the 2014 Hazelwood mine fire in Morwell, Victoria, Australia. Participants completed two surveys evaluating posttraumatic distress, measured using the Impact of Events Scale-Revised (IES-R), three and six years after the mine fire. Mixed-effects regression models were used to evaluate longitudinal changes in distress. IES-R total scores increased on average by 2.6 points (95%CI: 1.2 to 3.9 points) between the two survey rounds, with increases across all three posttraumatic distress symptom clusters, particularly intrusive symptoms. This increase in distress was evident across all levels of fine particulate matter (PM(2.5)) exposure to the mine fire smoke. Age was an effect modifier between mine fire PM(2.5) exposure and posttraumatic distress, with younger adults impacted more by exposure to the mine fire. Greater exposure to PM(2.5) from the mine fire was still associated with increased psychological distress some six years later, with the overall level of distress increasing between the two survey rounds. The follow-up survey coincided with the Black Summer bushfire season in south-eastern Australia and exposure to this new smoke event may have triggered distress sensitivities stemming from exposure to the earlier mine fire. Public health responses to disaster events should take into consideration prior exposures and vulnerable groups, particularly younger adults.
The 2019-20 bushfires that raged in eastern Australia were an overwhelming natural disaster leading to lives lost or upended, and communities destroyed. For almost a month, Canberra, Australia’s capital city in the Australian Capital Territory (ACT), was obscured by smoke from fires which threatened the outer suburbs. While smoke itself is experientially different from many natural disasters, it nevertheless poses a significant public health threat. As the impact of extended bushfire smoke in an urban setting is relatively unexplored we aimed to capture the individual and community-level experiences of the event and their importance for community and social functioning. We responded rapidly by conducting semi-structured interviews with a range of Canberra residents who, due to their personal or social circumstances, were potentially vulnerable to the effects of the smoke. Three major themes emerging from the narratives depicted disruption to daily life, physical and psychological effects, and shifting social connectedness. This study highlighted the ambiguous yet impactful nature of a bushfire smoke event, and identified four simple key messages that may be critically relevant to policy making in preparation for similar smoke events in the future.
The 2019-2020 summer wildfire event on the east coast of Australia was a series of major wildfires occurring from November 2019 to end of January 2020 across the states of Queensland, New South Wales (NSW), Victoria and South Australia. The wildfires were unprecedent in scope and the extensive character of the wildfires caused smoke pollutants to be transported not only to New Zealand, but also across the Pacific Ocean to South America. At the peak of the wildfires, smoke plumes were injected into the stratosphere at a height of up to 25 km and hence transported across the globe. The meteorological and air quality Weather Research and Forecasting with Chemistry (WRF-Chem) model is used together with the air quality monitoring data collected during the bushfire period and remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellites to determine the extent of the wildfires, the pollutant transport and their impacts on air quality and health of the exposed population in NSW. The results showed that the WRF-Chem model using Fire Emission Inventory (FINN) from National Center for Atmospheric Research (NCAR) to simulate the dispersion and transport of pollutants from wildfires predicted the daily concentration of PM2.5 having the correlation (R-2) and index of agreement (IOA) from 0.6 to 0.75 and 0.61 to 0.86, respectively, when compared with the ground-based data. The impact on health endpoints such as mortality and respiratory and cardiovascular diseases hospitalizations across the modelling domain was then estimated. The estimated health impact on each of the Australian Bureau of Statistics (ABS) census districts (SA4) of New South Wales was calculated based on epidemiological assumptions of the impact function and incidence rate data from the 2016 ABS and NSW Department of Health statistical health records. Summing up all SA4 census district results over NSW, we estimated that there were 247 (CI: 89, 409) premature deaths, 437 (CI: 81, 984) cardiovascular diseases hospitalizations and 1535 (CI: 493, 2087) respiratory diseases hospitalizations in NSW over the period from 1 November 2019 to 8 January 2020. The results are comparable with a previous study based only on observation data, but the results in this study provide much more spatially and temporally detailed data with regard to the health impact from the summer 2019-2020 wildfires.
Persistent and intensive wildland dense-fires (DFs) release substantial amounts of airborne pollutants, resulting in a sharp increase in emissions and leading to serious impacts on the environment and human health over extensive geographical areas. It is challenging to thoroughly investigate patterns of fire occurrence and fire distribution for predicting wildfire behaviour, and it is especially difficult to distinguish the characteristics of human-caused and climate-driven fires. Here, we identify and assess dense-fire (DF) from the perspective of spatiotemporally integrated processes using a machine-learning method based on a density-based clustering algorithm with noise constraint ratio. DFs represent collections of fires with homogenous behaviour and therefore allow the study of their internal features, which can reveal fixed patterns of fire occurrence and dis-tribution as well as the evolution of fires over time. We estimated and labelled thousands of fire clusters on the Indochina Peninsula between 2010 and 2020, most of which occurred between December and May. For large-scale DFs, the number of fires contained and amount of atmospheric pollutants emitted were accounted for throughout most of the region, and the time, location and scale of their occurrence each year were relatively stable and predictable. Furthermore, the results of a secondary cluster analysis of fire interactions over the past decade showed two extreme fire events, labelled “north ” and “south ” groups, whose activities significantly impacted the atmospheric environment of the Indochina Peninsula. Additionally, we predicted their start/end dates and daily emissions. The study also found that the recurrence of high-density fires and the correlation between the DF edge and administrative border suggested a positive anthropogenic influence. To the authors’ knowledge, this study is the first to analyze fires in a spatiotemporal Euclidean space by using density-based clustering, with high-density fires as independent subjects to study fire behaviour. The method proposed in this study can provide a reference for wildfire prediction and emission forecasting and fire control work.
Evidence of the acute effects of air pollutants on ischemic heart disease (IHD) hospitalizations based on the entire population of a megacity in central China is lacking. All IHD hospitalization records from 2017 to 2018 were obtained from the Wuhan Information Center of Health and Family Planning. Daily air pollutant concentrations and meteorological data were synchronously collected from the Wuhan Environmental Protection Bureau. A time-series study using generalized additive models was conducted to systematically examine the associations between air pollutants and IHD hospitalizations. Stratified analyses by gender, age, season, hypertension, diabetes, and hyperlipidemia were performed. In total, 139,616 IHD hospitalizations were included. Short-term exposure to air pollutants was positively associated with IHD hospitalizations. The age group ≥ 76 was at higher exposure risk, and the associations appeared to be more evident in cold seasons. PM(2.5) and PM(10) appeared to have greater effects on males and those without hypertension or diabetes, whereas NO(2) and SO(2) had greater effects on females and those with hypertension or diabetes. The risk of IHD hospitalization due to air pollutants was greater in people without hyperlipidemia. Our study provides new evidence of the effects of air pollution on the increased incidence of IHD in central China.
Recent evidence shows that carbon emissions in China are likely to peak ahead of 2030. However, the social and economic impacts of such an early carbon peak have rarely been assessed. Here we focus on the economic costs and health benefits of different carbon mitigation pathways, considering both possible socio-economic futures and varying ambitions of climate policies. We find that an early peak before 2030 in line with the 1.5 °C target could avoid ~118,000 and ~614,000 PM(2.5) attributable deaths under the Shared Socioeconomic Pathway 1, in 2030 and 2050, respectively. Under the 2 °C target, carbon mitigation costs could be more than offset by health co-benefits in 2050, bringing a net benefit of $393-$3,017 billion (in 2017 USD value). This study not only provides insight into potential health benefits of an early peak in China, but also suggests that similar benefits may result from more ambitious climate targets in other countries.
Background: Previous studies suggested that exposure to air pollution could increase risk of asthma attacks in children. The aim of this study is to investigate the short-term effects of exposure to ambient air pollution on asthma hospital admissions in children in Beijing, a city with serious air pollution and high-quality medical care at the same time. Methods: We collected hospital admission data of asthma patients aged ?ëñ 18 years old from 56 hospitals from 2013 to 2016 in Beijing, China. Time-stratified case-crossover design and conditional Poisson regression were applied to explore the association between risk of asthma admission in children and the daily concentration of six air pollutants [particulate matter ?ëñ 2.5 ??m (PM(2.5)), particulate matter ≤ μm (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), carbon monoxide (CO), and ozone (O(3))], adjusting for meteorological factors and other pollutants. Additionally, stratified analyses were performed by age, gender, and season. Results: In the single-pollutant models, higher levels of PM(2.5), SO(2), and NO(2) were significantly associated with increased risk of hospital admission for asthma in children. The strongest effect was observed in NO(2) at lag06 (RR = 1.25, 95%CI: 1.06-1.48), followed by SO(2) at lag05 (RR = 1.17, 95%CI: 1.05-1.31). The robustness of effects of SO(2) and NO(2) were shown in two-pollutant models. Stratified analyses further indicated that pre-school children (aged ≤ 6 years) were more susceptible to SO(2). The effects of SO(2) were stronger in the cold season, while the effects of NO(2) were stronger in the warm season. No significant sex-specific differences were observed. Conclusions: These results suggested that high levels of air pollution had an adverse effect on childhood asthma, even in a region with high-quality healthcare. Therefore, it will be significant to decrease hospital admissions for asthma in children by controlling air pollution emission and avoiding exposure to air pollution.
Electric vehicle (EV) adoption promises potential air pollutant and greenhouse gas (GHG) reduction co-benefits. As such, China has aggressively incentivized EV adoption, however much remains unknown with regard to EVs’ mitigation potential, including optimal vehicle type prioritization, power generation contingencies, effects of Clean Air regulations, and the ability of EVs to reduce acute impacts of extreme air quality events. Here, we present a suite of scenarios with a chemistry transport model that assess the potential co-benefits of EVs during an extreme winter air quality event. We find that regardless of power generation source, heavy-duty vehicle (HDV) electrification consistently improves air quality in terms of NO2 and fine particulate matter (PM2.5), potentially avoiding 562 deaths due to acute pollutant exposure during the infamous January 2013 pollution episode (similar to 1% of total premature mortality). However, HDV electrification does not reduce GHG emissions without enhanced emission-free electricity generation. In contrast, due to differing emission profiles, light-duty vehicle (LDV) electrification in China consistently reduces GHG emissions (similar to 2 Mt CO2), but results in fewer air quality and human health improvements (145 avoided deaths). The calculated economic impacts for human health endpoints and CO2 reductions for LDV electrification are nearly double those of HDV electrification in present-day (155M vs. 87M US$), but are within similar to 25% when enhanced emission-free generation is used to power them. Overall, we find only a modest benefit for EVs to ameliorate severe wintertime pollution events, and that continued emission reductions in the power generation sector will have the greatest human health and economic benefits.
The epidemiological evidence on relationships between air pollution, temperature, and stroke remains inconclusive. Limited evidence is available for the effect modification by apparent temperature, an indicator reflecting reactions to the thermal environment, on short-term associations between air pollution and hospital admissions for stroke. We used a generalized additive model with Poisson regression to estimate the relative risk (RR) of stroke admissions in Shanghai, China, between 2014 and 2016 associated with air pollutants, with subgroup analyses by age, sex, apparent temperature, and season. During the study period, changes in the daily number of stroke admissions per 10 μg/m(3) increase in nitrogen dioxide (at lags 0, 1, 0-1, and 0-2) ranged from 1.05 (95% CI: 0.82%, 2.88%) to 2.24% (95% CI: 0.84%, 3.65%). For each 10 μg/m(3) increase in sulfur dioxide concentrations at lags 1, 2, 0-1, and 0-2, the RR of daily stroke admissions increased by 3.34 (95% CI: 0.955%, 5.79%), 0.32 (95% CI: -1.97%, 2.67%), 3.33 (95% CI: 0.38%, 6.37%), and 2.86% (95% CI: -0.45%, 6.28%), respectively. The associations of same-day exposure to nitrogen dioxide with stroke admissions remained significant after adjustment for ozone levels. These associations were not modified by sex, age, apparent temperature, or season. More research is warranted to determine whether apparent temperature modifies the associations between air pollution and stroke admissions.
Chronic obstructive pulmonary disease (COPD) is the fourth major cause of mortality and morbidity worldwide and is projected to be the third by 2030. However, there is little evidence available on the associations of COPD hospitalizations with meteorological factors and air pollutants in developing countries/regions of Asia. In particular, no study has been done in western areas of China considering the nonlinear and lagged effects simultaneously. This study aims to evaluate the nonlinear and lagged associations of COPD hospitalizations with meteorological factors and air pollutants using time-series analysis. The modified associations by sex and age were also investigated. The distributed lag nonlinear model was used to establish the association of daily COPD hospitalizations of all 441 public hospitals in Chengdu, China from Jan/2015-Dec/2017 with the ambient meteorological factors and air pollutants. Model parameters were optimized based on quasi Akaike Information Criterion and model diagnostics was conducted by inspecting the deviance residuals. Subgroup analysis by sex and age was also performed. Temperature, relative humidity, wind and Carbon Monoxide (CO) have statistically significant and consistent associations with COPD hospitalizations. The cumulative relative risk (RR) was lowest at a temperature of 19℃ (relative humidity of 67%). Both extremely high and low temperature (and relative humidity) increase the cumulative RR. An increase of wind speed above 4 mph (an increase of CO above 1.44 mg/m(3)) significantly decreases (increases) the cumulative RR. Female populations were more sensitive to low temperature and high CO level; elderly (74+) populations are more sensitive to high relative humidity; younger populations (< = 74) are more susceptible to CO higher than 1.44 mg/m(3). Therefore, people with COPD should avoid exposure to adverse environmental conditions of extreme temperatures and relative humidity, low wind speed and high CO level, especially for female and elderly patients who were more sensitive to extreme temperatures and relative humidity.
South Korea had the highest annual average PM2.5 exposure levels in the Organization for Economic Co-operation and Development (OECD) in 2019, and air pollution is consistently ranked as citizens’ top environmental concern. South Korea is also one of the world’s top ten emitter countries of CO2. Co-benefit mitigation policies can address both air pollution and climate change. Utilizing an alternative co-benefit approach, which views air pollution reduction as the primary goal and climate change mitigation as secondary, this research conducts a scenario analysis to forecast the health and climate benefits of fuel substitution in South Korea’s electricity generation sector. Health benefits are calculated by avoided premature mortality and years of life lost (YLL) due to ischemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), lung cancer, and acute lower respiratory infections (ALRI). The study finds that use of liquefied natural gas (LNG) instead of coal over the 2022-2050 period would result in an average of 116 fewer premature deaths (1152 YLL) and 80.8 MTCO(2)e fewer emissions per year. Over the same period, maintaining and maximizing the use of its nuclear energy capacity, combined with replacing coal use with LNG, would result in an average of 161 fewer premature deaths (1608 YLL) and 123.7 MTCO(2)e fewer emissions per year.
This article quantifies the environmental, health, and economic co-benefits from the use of solar electricity and heat generation in the Ger area (a sub-district of traditional residences and private houses) in Ulaanbaatar (UB), Mongolia. The quantification of the featured co-benefits is based on calculating emissions reductions from the installation of the solar photovoltaic (PV) and solar water heaters. A user-friendly spreadsheet tool is developed to shed much-needed light on the steps involved in estimating these co-benefits. The tool simulates the hourly electricity and thermal energy generation, taking into account local meteorological conditions, local geographical data, and technical specifications of the solar power and heat generation systems. The tool is then employed to evaluate two intervention scenarios: (1) Installing 100 MW solar electricity, including both rooftop PV and community grids, to reduce the peak-load burden on the grid; (2) Providing solar thermal heaters for 20,000 households to replace the heating load demand from the existing heat only boilers (HOBs) in UB. The modelling results reveal a significant reduction in GHG emissions and fine particulate matter (PM(2.5)) (PM that is 2.5 microns or less in diameter) by 311,000 tons and 767 tons, respectively, as well as nearly 6500 disability-adjusted life years (DALYs) and an annual saving of USD 7.7 million for the local economy. The article concludes that the mainstreaming spreadsheet-based estimation tools like the one used in this article into decision-making processes can fill important research gaps (e.g., usability of assessment tools) and help translate co-benefits analyses into action in Mongolia and beyond.
Pollution of the environment is increasing and threatens the health and wellbeing of adults and children around the globe. The impact of air pollution on pulmonary and cardiovascular disease has been well documented, but it also has a deleterious effect on reproductive health. Ulaanbaatar, the capital city of Mongolia, has one of the highest levels of air pollution in the world. During the extreme winters when temperatures routinely fall below -20 degrees C the level of air pollution can reach 80 times the WHO recommended safe levels. Heating mainly comes from coal, which is burned both in power stations, and in stoves in the traditional Ger housing. We studied the impact of air pollution on conception rates and birth outcomes in Ulaanbaatar using a retrospective analysis of health data collected from the Urguu Maternity hospital in Ulaanbaatar, Mongolia. Daily levels of SO2, NO2, PM10, and PM2.5 were collected from the government Air Quality Monitoring Stations in Ulaanbaatar for the same period as the study. In January, the month of highest pollution, there is a 3.2-fold decrease in conceptions that lead to the successfully delivered infants compared to October. The seasonal variations in conceptions resulting in live births in this study in Ulaanbaatar are shown to be 2.03 +/- 0.20 (10-sigma) times greater than those in the Denmark/North America study of Wesselink et al., 2020. The two obvious differences between Ulaanbaatar and Europe/North America are pollution and temperature both of which are extreme in Ulaanbaatar. The extreme low temperature is mitigated by burning coal, which is the main source of domestic heat especially in the ger districts. This drives the level of pollution so the two are inextricably linked. Infants conceived in the months of June-October had the greatest cumulative PM2.5 pollution exposure over total gestation, yet these were also the pregnancies with the lowest PM2.5 exposure for the month of conception and three months prior to conception. The delivered-infant conception rate shows a markedly negative association with exposure to PM2.5 prior to and during the first month of pregnancy. This overall reduction in fecundity of the population of Ulaanbaatar is therefore a preventable health risk. It is of great consequence that the air pollution in Ulaanbaatar affects health over an entire lifespan including reproductive health. This could be remedied with a clean source of heating.
OBJECTIVES: To investigate associations between long-term exposure to PM(2.5), NO(2), mortality and morbidity in New Zealand, a country with low levels of exposure. DESIGN: Retrospective cohort study. SETTING: The New Zealand resident population. METHOD: The main analyses included all adults aged 30 years and over with complete data on covariates: N = 2,223,507. People who died, or were admitted to hospital, (2013-2016) were linked anonymously to the 2013 census, and to estimates of ambient PM(2.5), and NO(2) concentration. We fitted Poisson regression models of mortality and morbidity in adults (≥30) for all natural causes of death, and by sub- group of major cause. Person-time of exposure, censored at the time of death, was included as an offset. We adjusted for confounding by age, sex, ethnicity, income, education, smoking status and ambient temperature. Further analyses stratified by ethnic group, and investigated respiratory hospital admissions in children. RESULTS: There were statistically significant positive associations between pollutants and natural causes of death: RR (per 10 μg/m(3)) for PM(2.5) 1.11 (1.07 to 1.15) and for NO(2) 1.10 (1.07 to 1.12). For morbidity, the strongest associations were for PM(2.5) and ischaemic heart disease in adults, RR: 1.29 (1.23 to 1.35) and for NO(2) and asthma in children, RR: 1.18 (1.09 to 1.28). In models restricted to specific ethnic groups, we found no consistent differences in any of the associations. CONCLUSIONS: The results for NO(2) are higher than those published previously. Other studies have reported that the dose-response for PM(2.5) may be higher at low concentrations, but less is known about NO(2). It is possible NO(2) is acting as a proxy for other traffic-related pollutants that are causally related to health impacts. This study underlines the importance of controlling pollution caused by motor vehicles.
This study examines how human capital develops in response to early-life weather and pollution exposures in the Philippines. Both pollution and weather are examined in relation to short- and long-term human capital outcomes. We combine a three-decade longitudinal survey measuring human capital development, a database of historical weather, and multiple databases characterizing carbon monoxide and ozone in the Philippines during the 1980s. We find evidence that extreme precipitation and temperature affect short-term anthropometric outcomes, but long-term outcomes appear unaffected. For long-term cognitive outcomes, we find that early-life pollution exposures negatively affect test scores and schooling. These long-term responses to early-life pollution exposures extend to the labor market with reduced hours worked and earnings. The implication is that a 25 per cent reduction in early-life ozone exposure would increase per person discounted lifetime earnings by $1,367, which would scale to $2.05 billion at the national level (or 2 per cent of 2005 GDP).
There is a dearth of research on the hourly risk of ambulance dispatches with respect to ambient conditions. We evaluated hourly relative risks (RR) and 95% confidence interval (CI) of ambulance dispatches in Taiwan to treat respiratory distress, coma and unconsciousness, and out-of-hospital cardiac arrest (OHCA), from 2006 to 2015. We considered island-wide ambient temperatures, fine particulate matter (PM(2.5)), and ozone (O(3)) at lag 0-180 h while using a distributed lag nonlinear model and meta-analysis. Results showed the pooled risks peaked at lag 16-18 h for all ambulance dispatches at 99th percentile of hourly temperature (32 °C, versus reference temperature of 25 °C), with significant excess risk of 0.11% (95% CI; 0.06, 0.17) for coma and unconsciousness, and 0.06% (95% CI; 0.01, 0.11) for OHCA. The risks of exposure to 90th percentile of hourly O(3) of 52.3 ppb relative to the Q1 level of 17.3 ppb peaked at lag 14 h, with excess risk of 0.17% (95% CI; 0.11, 0.23) for respiratory distress, 0.11% (95% CI; 0.06, 0.16) for coma and unconsciousness, and 0.07% (95% CI; 0.01, 0.14) for OHCA. The population exposed to reference temperatures of 28 °C, 20 °C, and 26 °C were exposed to the lowest levels of ambulance dispatches risk for respiratory distress, coma and unconsciousness, and OHCA, respectively; the highest cumulative 0-96 h RRs of ambulance dispatches were 1.27 (95% CI; 1.19, 1.35) for OHCA at 5th percentile temperatures and 1.25 (95% CI; 1.11, 1.41) for OHCA at 99th percentile temperatures. Following an accumulating lag of 0-96 h, no significant risk was identified for hourly levels of PM(2.5) and O(3). In conclusion, the analytical results of hourly data speak to immediate and real-time responses to environmental changes, rather than to short-term relationships. In our analyses, we emphasized health events in extreme heat; thus, we recommend a comparative study of daily versus hourly associations.
OBJECTIVE: To determine the association of meteorological factors and air pollutants (MFAPs) with fracture and to estimate the effect size/time lag. DESIGN: This is a nationwide population-based ecological study from 2008 to 2017. SETTING: Eight large metropolitan areas in Korea. PARTICIPANTS: Of 8 093 820 patients with fractures reported in the Korea National Health Insurance database, 2 129 955 were analysed after the data set containing patient data (age, sex and site of fractures) were merged with MFAPs. Data on meteorological factors were obtained from the National Climate Data Center of the Korea Meteorological Administration. Additionally, data on air pollutants (atmospheric particulate matter ≤2.5 µm in diameter (PM(2.5)), PM(10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide) were obtained from the Air Korea database. PRIMARY AND SECONDARY OUTCOME MEASURES: We hypothesised that there would be an association between MFAPs and the incidence of fracture. A generalised additive model was used while factoring in the non-linear relationship between MFAPs and fractures as well as a time lag ≤7 days. Multivariate analysis was performed. Backward elimination with an Akaike information criterion was used to fit the multivariate model. RESULTS: Overall, in eight urban areas, 2 129 955 patients with fractures were finally analysed. These included 370 344, 187 370, 173 100, 140 358, 246 775, 6501, 228 346, 57 183 and 719 978 patients with hip, knee, shoulder, elbow, wrist, hand, ankle, foot and spine fractures, respectively. Various MFAPs (average temperature, daily rain, wind speed, daily snow and PM(2.5)) showed significant association with fractures, with positive correlations at time lags 7, 5-7, 5-7, 3-7 and 6-7 days, respectively. CONCLUSIONS: Various MFAPs could affect the occurrence of fractures. The average temperature, daily rain, wind speed, daily snow and PM(2.5) were most closely associated with fracture. Thus, improved public awareness on these MFAPs is required for clinical prevention and management of fractures.
The biological mechanisms underlying the associations between atmospheric ozone exposure and adverse cardiometabolic outcomes are yet to be identified. Imbalanced autonomic nervous system (ANS) as well as activations of the sympatho-adrenomedullary (SAM) and hypothalamic-pituitary-adrenal (HPA) axes are among possible early biological responses triggered by ozone, and may eventually lead to cardiometabolic abnormalities. To determine whether acute ozone exposure causes ANS imbalance and increases the secretion of neuroendocrine stress hormones, we conducted a randomized, double-blind, crossover trial, under controlled 2-hour exposure to either ozone (200 ppb) or clean air with intermittent exercise among 22 healthy young adults. Here we found that, compared to clean air exposure, acute ozone exposure significantly decreased the high-frequency band of heart rate variability, even after adjusting for heart rate and pre-exposure to ambient air pollutants and meteorological factors. Ozone exposure also significantly increased the serum levels of stress hormones, including corticotrophin-releasing factor, adrenocorticotropic hormone, adrenaline, and noradrenaline. Metabolomics analysis showed that acute ozone exposure led to alterations in stress hormones, systemic inflammation, oxidative stress, and energy metabolism. Our results suggest that acute ozone exposure may trigger ANS imbalance and activate the HPA and SAM axes, offering potential biological explanations for the adverse cardiometabolic effects following acute ozone exposure.
Air pollution causes adverse effects not only on the environment but also on human health. This study evaluated the excess mortalities in continental Southeast Asia that are related to future O-3 and PM2.5 ambient concentration changes attributed to future climate change and emission change. The Environmental Benefits Mapping and Analysis Program -Community Edition (BenMAP-CE) was applied as a health impact assessment tool. In BenMAP-CE simulations, baseline scenarios presenting for the present year (2014) were compared against the control scenarios presenting for the future year (2050). The air pollutant concentrations for the simulations were collected from modeled data. The future population data and baseline incidence rates were as same as the 2014 levels. In four calculating countries namely Laos, Cambodia, Thailand, and Vietnam, on average, impacted by climate change alone, the avoided mortalities of -1164 and -3358 under Representative Concentration Pathway (RCP) 4.5 scenario and the additional mortalities of +758 and +2562 under RCP8.5 scenario were calculated for O-3 and PM2.5, respectively. Future emission change alone under Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants current legislation (ECLIPSE CLE) scenario induces +7113 and +11072 additional O-3 and PM2.5 related mortalities, respectively. Combined change in climate and emission produces additional O-3 and PM2.5 related mortalities of +6067 and +7830 under RCP4.5 and ECLIPSE CLE combined scenario and +8763 and +14580 under RCP8.5 and ECLIPSE CLE combined scenario, respectively. The results of this study provided meaningful information for understanding the public health attributed to air pollution in the region.
BACKGROUND/AIMS: Weather and air pollution are associated with the exacerbation of respiratory diseases. We investigated patterns of medical care use according to meteorological factors and air pollution in patients with asthma or chronic obstructive pulmonary disease (COPD). METHODS: We analyzed the medical care utilization patterns of patients with asthma or COPD registered in the Korea Health Insurance Review and Assessment database for the period 2007 to 2013. The patterns were divided into hospitalization and emergency department (ED) use. RESULTS: The medical care use of patients with asthma or COPD increased when the mean temperature and relative humidity were lower, and the temperature difference and atmospheric pressure were greater. Medical care use increased with the concentrations of particulate matter and ozone. Among age groups, sensitivity to pollutants was greatest in patients aged ≥ 65 years. The effect of being elderly was greater for asthma than for COPD, with a higher hospitalization rate. ED utilization affected by environmental factors was significantly greater for females and hospitalization was significantly more common for males. CONCLUSION: Meteorological factors and air pollutants were shown to contribute to increased medical care utilization by patients with asthma and COPD, particularly elderly patients. The overall effect was greater for COPD, but the effect in elderly patients was greater for asthma. In addition, the patterns of change in medical care use due to environmental factors differed according to sex.
With the development of the economy and the accumulation of social wealth, urban residents have begun to give more attention to quality of life than to material needs. Consequently, environmental factors that affect human health, such as air quality, have become a new focus when traveling. A travel scheme with relatively low pollutant exposure to travelers can not only improve their health and satisfy their goals but also benefit social stability and sustained progress. However, low spatiotemporal resolution and coarse spatial details of the distribution of PM2.5 (particles with an aerodynamic diameter of 2.5 mu m or less) educe the success rate of short distance healthy travel route planning. This paper proposes a short-distance healthy route planning approach that is based on PM2.5 retrieval with high spatiotemporal resolution and a dynamic Dijkstra algorithm. First, fine spatial resolution images, meteorological data, and socioeconomic data are used to retrieve the spatial distribution of PM2.5 concentration in hourly intervals via a back-propagation neural network (BPNN). Second, a PM2.5 concentration value is obtained for each road section, and the harm degree to the human body is calculated as the weight of each road section. Then, the healthiest route is obtained based on the Dijkstra algorithm. Finally, the route planning effectiveness is verified by comparing the PM2.5 potential dose descending rate between the healthy route and the shortest route. The results show that the coefficient of determination (R2) of the PM2.5 retrieval approach that is based on multisource data and BPNN is 0.85, which can ensure the accuracy of the PM2.5 data at the street level. On this basis, the potential dose reduction rate of the healthy route can reach up to 20%, which proves that our approach can perform well. It can effectively improve the safety of travel and alleviate the anxiety that is caused by air pollution. In addition, it provides an easy implementation strategy for software for health management.
Over the past few decades, due to human activities, industrialization, and urbanization, air pollution has become a life-threatening factor in many countries around the world. Among air pollutants, Particulate Matter with a diameter of less than 2.5 μm ( PM2.5 ) is a serious health problem. It causes various illnesses such as respiratory tract and cardiovascular diseases. Hence, it is necessary to accurately predict the PM2.5 concentrations in order to prevent the citizens from the dangerous impact of air pollution beforehand. The variation of PM2.5 depends on a variety of factors, such as meteorology and the concentration of other pollutants in urban areas. In this paper, we implemented a deep learning solution to predict the hourly forecast of PM2.5 concentration in Beijing, China, based on CNN-LSTM, with a spatial-temporal feature by combining historical data of pollutants, meteorological data, and PM2.5 concentration in the adjacent stations. We examined the difference in performances among Deep learning algorithms such as LSTM, Bi-LSTM, GRU, Bi-GRU, CNN, and a hybrid CNN-LSTM model. Experimental results indicate that our method hybrid CNN-LSTM multivariate enables more accurate predictions than all the listed traditional models and performs better in predictive performance.
BACKGROUND: Smaller sizes of ambient particulate matter (PM) can be more toxic and can be breathed into lower lobes of a lung. Children are particularly vulnerable to PM air pollution because of their adverse effects on both lung functions and lung development. However, it remains unknown whether a smaller PM has a greater short-term impact on childhood pneumonia. AIMS: We compared the short-term effects on childhood pneumonia from PM with aerodynamic diameters ≤1 μm (PM(1)), ≤2.5 μm (PM(2.5)), and ≤10 μm (PM(10)), respectively. METHODS: Daily time-series data (2016-2018) on pneumonia hospitalizations in children aged 0-17 years, records of air pollution (PM(1), PM(2.5), PM(10), and gaseous pollutants), and weather conditions were obtained for Hefei, China. Effects of different PM were quantified using a quasi-Poisson generalized additive model after controlling for day of the week, holiday, seasonality and long-term time trend, and weather variables. Stratified analyses (gender, age, and season) were also performed. RESULTS: For each 10 μg/m(3) increase in PM(1), PM(2.5), and PM(10) concentrations over the past three days (lag 0-2), the risk of pneumonia hospitalizations increased by 10.28% (95%CI: 5.88%-14.87%), 1.21% (95%CI: 0.34%-2.09%), and 1.10% (95%CI: 0.44%-1.76%), respectively. Additionally, both boys and girls were at risk of PM(1) effects, while PM(2.5) and PM(10) effects were only seen in boys. Children aged ≤12 months and 1-4 years were affected by PM(1), but PM(2.5) and PM(10) were only associated with children aged 1-4 years. Furthermore, PM(1) effects were greater in autumn and winter, while greater PM(2.5) and PM(10) effects were evident only in autumn. CONCLUSION: This study suggests a greater short-term impact on childhood pneumonia from PM(1) in comparison to PM(2.5) and PM(10). Given the serious PM pollution in China and other rapid developing countries due to various combustions and emissions, more investigations are needed to determine the impact of different PM on childhood respiratory health.
OBJECTIVE: Acute tonsillitis is a common disease in otorhinolaryngology. Meteorological factors can affect the incidence of many infectious diseases. This study aims to analyze the correlation between acute tonsillitis and meteorological conditions. MATERIALS AND METHODS: We collected the meteorological data, including daily temperature, humidity, and fine particulate matter (PM(2.5)) of Shanghai, China, from 2014 to 2015. The monthly number of acute tonsillitis cases in our hospital was also calculated and used as the outcome variable. The associations between them were evaluated, respectively. RESULTS: The average number of patients diagnosed with acute tonsillitis in our hospital per month was 68.67 ± 18.67 from 2014 to 2015. The average temperature, humidity, and PM(2.5) of Shanghai during the defined period was 16.84 °C ± 7.80 °C, 75.93% ± 5.45%, and 52.38 ± 14.23 μg/m(3), respectively. The temperature was significantly positively associated with the acute tonsillitis cases number both in Pearson correlation analysis (R = 0.423, P = .039) and in multivariate regression analysis (coefficient =2.194, P = .012). However, no correlation between the acute tonsillitis cases number and relative humidity or PM(2.5) was found through a multivariate regression model (P = .225 and P = .243), respectively. CONCLUSION: The high temperature was associated with an increased incidence of acute tonsillitis.
An outdoor solar assisted large-scale cleaning system (SALSCS) was constructed to mitigate the levels of fine particulate matter (PM(2.5)) in urban areas of Xi’an China, providing a quasi-experimental opportunity to examine the biologic responses to the changes in pollution level. We conducted this outdoor SALSCS based real-world quasi-interventional study to examine the associations of the SALSCS intervention and changes in air pollution levels with the biomarkers of systemic inflammation and oxidative stress in healthy elders. We measured the levels of 8-hydrox-2-deoxyguanosine (8-OHdG), Interlukin-6 (IL-6), as well as tumor necrosis factor alpha (TNF-α) from urine samples, and IL-6 from saliva samples of 123 healthy retired participants from interventional/control residential areas in two sampling campaigns. We collected daily 24-h PM(2.5) samples in two residential areas during the study periods using mini-volume samplers. Data on PM(10), gaseous pollutants and weather factors were collected from the nearest national air quality monitoring stations. We used linear mixed-effect models to examine the percent change in each biomarker associated with the SALSCS intervention and air pollution levels, after adjusting for time trend, seasonality, weather factors and personal characteristics. Results showed that the SALSCS intervention was significantly associated with decreases in the geometric mean of biomarkers by 47.6% (95% confidence interval: 16.5-67.2%) for 8-OHdG, 66% (31.0-83.3%) for TNF-α, 41.7% (0.2-65.9%) and 43.4% (13.6-62.9%) for urinary and salivary IL-6, respectively. An inter-quartile range increase of ambient PM(2.5) exposure averaged on the day of the collection of bio-samples and the day before (34.1 μg/m(3)) was associated, albeit non-significantly so, with 22.8%-37.9% increases in the geometric mean of these biomarkers. This study demonstrated that the SALSCS intervention and decreased ambient air pollution exposure results in lower burden of systemic inflammation and oxidative stress in older adults.
BACKGROUND: Evidences have shown that the stroke risk associated with long-term exposure to particulate matter with an aerodynamic diameter of ≤2.5 μm (PM(2.5)) varies among people in North America, Europe and Asia, but studies in Asia rarely evaluated the association by stroke type. We examined whether long-term exposure to PM(2.5) is associated with developing all strokes, ischemic stroke and hemorrhagic stroke. METHODS: The retrospective cohort study consisted of 1,362,284 adults identified from beneficiaries of a universal health insurance program in 2011. We obtained data on air pollutants and meteorological measurements from air quality monitoring stations across Taiwan in 2010-2015. Annual mean levels of all environmental measurements in residing areas were calculated and assigned to cohort members. We used Cox proportional hazards models to estimate hazard ratio (HR) and 95% confidence interval (CI) of developing stroke associated with 1-year mean levels of PM(2.5) at baseline in 2010, and yearly mean levels from 2010 to 2015 as the time-varying exposure, adjusting for age, sex, income and urbanization level. RESULTS: During a median follow-up time of 6.0 years, 12,942 persons developed strokes, 9919 (76.6%) were ischemic. The adjusted HRs (95% CIs) per interquartile range increase in baseline 1-year mean PM(2.5) were 1.03 (1.00-1.06) for all stroke, 1.06 (1.02-1.09) for ischemic stroke, and 0.95 (0.89-1.10) for hemorrhagic stroke. The concentration-response curves estimated in the models with and without additional adjustments for other environmental measurements showed a positively linear association between baseline 1-year mean PM(2.5) and ischemic stroke at concentrations greater than 30 μg/m(3), under which no evidence of association was observed. There was an indication of an inverse association between PM(2.5) and hemorrhagic stroke, but the association no longer existed after controlling for nitrogen dioxide or ozone. We found similar shape of the concentration-response association in the Cox regression models with time-varying PM(2.5) exposures. CONCLUSION: Long-term exposure to PM(2.5) might be associated with increased risk of developing ischemic stroke. The association with high PM(2.5) concentrations remained significant after adjustment for other environmental factors.
What is already known about this topic? Climate change and air pollution are two important environmental issues in China. It is important to investigate particulate matter with aerodynamic diameter less than 2.5 μm (PM(2.5))-related health impacts from climate change and air pollution emission control. What is added by this report? Deaths and years of life lost related to PM(2.5) would increase in climate change scenario, although emission control would outweigh the influence of climate change. What are the implications for public health practice? More targeted actions should be taken to meet challenges of exacerbated PM(2.5) pollutions and its health impacts related to climate change in the future.
BACKGROUND: Scientific studies have identified various adverse effects of particulate matter (PM) on respiratory disease (RD) and type 2 diabetes (T2D). However, whether short-term exposure to PM triggers the onset of RD with T2D, compared with RD without T2D, has not been elucidated. METHODS: A two-stage time-series study was conducted to evaluate the acute adverse effects of PM on admission for RD and for RD with and without T2D in Beijing, China, from 2014 to 2020. District-specific effects of PM(2.5) and PM(10) were estimated using the over-dispersed Poisson generalized addictive model after adjusting for weather conditions, day of the week, and long-term and seasonal trends. Meta-analyses were applied to pool the overall effects on overall and cause-specific RD, while the exposure-response (E-R) curves were evaluated using a cubic regression spline. RESULTS: A total of 1550,154 admission records for RD were retrieved during the study period. Meta-analysis suggested that per interquartile range upticks in the concentration of PM(2.5) corresponded to 1.91% (95% CI: 1.33-2.49%), 2.16% (95% CI: 1.08-3.25%), and 1.92% (95% CI: 1.46-2.39%) increments in admission for RD, RD with T2D, and RD without T2D, respectively, at lag 0-8 days, lag 8 days, and lag 8 days. The effect size of PM(2.5) was statistically significantly higher in the T2D group than in the group without T2D (z = 3.98, P < 0.01). The effect sizes of PM(10) were 3.86% (95% CI: 2.48-5.27%), 3.73% (95% CI: 1.72-5.79%), and 3.92% (95% CI: 2.65-5.21%), respectively, at lag 0-13 days, lag 13 days, and lag 13 days, respectively, and no statistically significant difference was observed between T2D groups (z = 0.24, P = 0.81). Significant difference was not observed between T2D groups for the associations of PM and different RD and could be found between three groups for effects of PM(10) on RD without T2D. The E-R curves varied by sex, age and T2D condition subgroups for the associations between PM and daily RD admissions. CONCLUSIONS: Short-term PM exposure was associated with increased RD admission with and without T2D, and the effect size of PM(2.5) was higher in patients with T2D than those without T2D.
Most studies on the short-term local benefits of carbon mitigation technologies on air quality improvement and health focus on specific technologies such as biofuels or carbon sequestration technologies, while ignoring the overall role of the growing scale of low-carbon technologies. Based on STIRPAT model and EKC hypothesis, this paper takes 30 provinces in China from 2004 to 2016 as research samples. We builded the panel double fixed effect model to empirical analysis of climate change on carbon mitigation tech-innovation suppressing the influence of haze pollution, on this basis, the mediating effect model was used to explore the mediation function of industrial structure and energy structure. Meanwhile, we drawed on the existing studies on air quality and health benefits, and quantify the co-benefits of carbon mitigation tech-innovation on health through the equivalent substitution formula. It shows that a 1% increase in the number of low-carbon patent applications can reduce haze pollution by 0.066%. According to this estimate, to 2029, China’s carbon mitigation tech-innovation could reduce PM2.5 concentration to 15 μg/m(3) preventing 5.597 million premature deaths. Moreover, carbon mitigation tech-innovation can also indirectly inhibit haze pollution by triggering more systematic economic structure changes such as energy and industrial structure. Additionally, we found that the role of gray tech-innovation (GT) related to improving the efficiency of fossil energy is stronger than that of clean technology (CT) related to the use of renewable energy. This suggests that for a large economy such as China, where coal is still the dominant source of energy consumption, the short-term local benefits of improving air quality and health through the use of gray tech-innovation to improve energy and industrial structure are still important to balance the cost of carbon mitigation.
BACKGROUND: Pneumonia is one of the principal reasons for incidence and death in the world. The former research mainly concentrated on specific sources of patients. Besides, due to the heterogeneity among regions, there are inconsistencies in the outcome of these surveys. To explore the relationship between atmospheric pollution and hospital visits for pneumonia under the climate and pollution conditions in Qingdao, we carried out this study. METHODS: The medical records of pneumonia patients were gathered from the affiliated hospital of Qingdao University during Jan 1st, 2014, and Dec 31st,2018. Daily concentrations of PM(2.5), PM(10), SO(2), NO(2), as well as CO, were collected from the national air quality monitoring stations in Qingdao. Case-crossover study design and conditional logistic regression model were used to estimate the associations. Daily temperature, relative humidity, and atmospheric pressure were adjusted as the covariates in all models. A principal component analysis was used to solve the multicollinearity between atmospheric pollutants and investigate the relationship between various air pollutants and pneumonia occurs. RESULTS: In the single pollutant model, with interquartile range increment of the density of PM(2.5), PM(10), NO(2) and SO(2) at the lag2 days, the odds ratio of hospital visits for pneumonia patients increased by 6.4% (95%CI, 2.3-10.7%), 7.7% (95%CI, 3.2-12.4%), 6.7% (95%CI, 1.0-12.7%), and 7.2% (95%CI, 1.1-13.5%). Stratified analysis showed that pollutants were more significant in the cold period. Besides, the impact of atmospheric particulates on different ages mainly occurs in the young child (0 to 3-year-old). The odds ratio was 1.042 (95%CI, 1.012-1.072) when the principal components of atmospheric pollutants were included in the conditional logistic model. CONCLUSIONS: Our study found a significant relationship between short-term uncovering to PM(2.5), PM(10), NO(2), SO(2), and hospital visits for pneumonia in Qingdao. The effect of atmospheric pollutants mainly arose in a cold period. The particulate matter might be the principal reason in inducing hospital visits for pneumonia.
The national lockdown policies have drastically disrupted socioeconomic activities during the COVID-19 pandemic in China, which provides a unique opportunity to investigate the air quality response to such anthropogenic disruptions. And it is meaningful to evaluate the potential health impacts of air quality changes during the lockdown, especially for PM(2.5) with adverse health effects. In this study, by using PM(2.5) observations from 1388 monitoring stations nationwide in China, we examine the PM(2.5) variations between the COVID-19 lockdown (February and March in 2020) and the same period in 2015-2019, and find that the national average of PM(2.5) decreases by 18 μg/m(3), and mean PM(2.5) for most sites (about 75%) decrease by 30%-60%. The anthropogenic and meteorological contributions to these PM(2.5) variations are also determined by using a stepwise multiple linear regression (MLR) model combined with the Kolmogorov-Zurbenko filter. Our results show that the change of anthropogenic emissions is a leading contributor to those widespread PM(2.5) reductions, and meteorological conditions have the negative influence on PM(2.5) reductions for some regions, such as Beijing-Tianjin-Hebei (BTH). Additionally, the avoided premature death due to PM(2.5) reduction is estimated as a predicted number based on a log-linear concentration-response function. The total avoided premature death is 9952 in China, with dominant contribution (94%) from anthropogenic emission changes. For BTH, Yangtze River Delta, Pearl River Delta and Hubei regions, the reductions of PM(2.5) are 24.1, 24.3, 13.5 and 29.5 μg/m(3), with the avoided premature deaths of 1066, 1963, 454 and 583, respectively.
Interests in evaluation of the effect of air pollution and weather conditions on cardiovascular disease have increased. However, the relationship between short-term particulate matter (PM) exposure and first incident ST-elevation myocardial infarction (STEMI) remains unclear. Medical records were collected from December 2013 to December 2016. A total of 1354 patients with first incident STEMI were included. The daily average of air pollution and weather conditions were calculated. In this case-crossover study, conditional logistic regression was performed to assess the association between daily concentrations of PM and first incident STEMI. The daily average of PM(2.5) and PM(10) were 58.9 μg/m(3) and 80.2 μg/m(3), respectively. In this case-crossover study, single-pollutant models showed that each 10 μg/m(3) increase in PM(2.5) was associated with a percent change of 3.36, 95% confidence interval (CI): (1.01-5.77), or in PM(10) percent change of 2.1%, 95%CI: (0.2-4.04) for patients with first incident STEMI. The association remained stable after adjusting for ozone (O(3)). The results from subgroup analysis showed the association slightly enhanced in women, elder patients, patients with history of diabetes, patients without history of smoking, and cold seasons. The p values were not significant between these strata, which may be due to small sample size. This investigation showed that short-term PM exposure associated with first incident STEMI in Suzhou. Given the effect of PM on the first incident STEMI, strategies to decrease PM should be considered.
Purpose The association between atmospheric particulate matter and emergency room visits for cerebrovascular disease were evaluated in Beijing. Methods A generalized additive model was used to evaluate the associations between particulate matter and cerebrovascular disease, based on the daily data of meteorological elements, PM concentrations, and emergency room (ER) visits for cerebrovascular disease in Beijing from 2009 to 2012. Long-term trends and the effects of holidays, the day of the week, and confounding factors were controlled to determine the lag effect at 0-6 days. Single- and double-pollutant models were employed for different age and sex groups. Results The effect of PM2.5 concentration on the number of daily ER visits for cerebrovascular disease was much stronger than that of PM10 concentration. PM2.5 and PM10 had maximum RR values of 1.096 and 1.054 at lag 6 for patients aged 61-75 years. For each inter-quartile range (IQR) increase in PM10 concentration, the maximum RR values for the total, males, females, aged 15-60 years, aged 61-75 years, and aged > 75 years were 1.024, 1.044, 1.043, 1.038, 1.054, and 1.032, respectively. For each IQR increase in PM2.5 concentration, the maximum RR values for the total, males, females, aged 15-60 years, aged 61-75 years, and aged > 75 years were 1.038, 1.064, 1.076, 1.054, 1.096, and 1.049, respectively. The RR values of the double-pollutant models were lower than those of the single-pollutant models. Conclusion This study showed that the effects of PM pollution on cerebrovascular disease were different among different gender and age groups, and aged 61-75 years were mostly sensitive to particulate matters. The effects of PM2.5 on cerebrovascular disease were stronger than those of PM10. Our results can provide scientific evidence for the local government to take effective measures to improve air quality and the health of residents.
BACKGROUND: The hospitalization for asthma exacerbation has varied with seasons, however, the underlying weather reasons have not been fully explored yet. This study is aimed to explore the effect of weather factors on increased number of hospitalization due to worsening of asthma symptoms. This will provide more information to the relevant authorities to allocate appropriate medical resources as per the weather conditions in Qingdao, China. METHODS: All adult patients admitted for asthma exacerbation from 1 January, 2017 to 31 December, 2019 were enrolled from 13 main hospitals of Qingdao. The clinical data, including age, sex, smoking history, etc., were collected from the electronic medical record (EMR) systems. The hourly air quality of Qingdao from 2017-2019, including the air quality index (AQI), PM(2.5) and PM(10), was obtained from the China National Environmental Monitoring Centre. All these parameters during 2017-2019 were compared monthly. For meteorological data, the monthly horizontal wind at 850 hPa and vertical velocity at 500 hPa during 1960-2020 were obtained from National Center for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) global reanalysis dataset. The correlation analysis was applied to determine the association between asthma hospitalizations and the environmental factors, including atmospheric pressure, humidity, vertical visibility, and etc., monthly. RESULTS: In all, 10,549 asthmatic inpatients (45.7% males, 54.3% females) were included in the study. The inpatients number for asthma exacerbation had a plateau lasting from March to June of 2019, accompanied with high PM(2.5) and PM(10), as well as bad air quality from January to March of 2019, potentially governed by the El Niño event in 2018. However, there was no significance correlation between the number of asthma hospitalizations and the average value of all environmental factors. CONCLUSIONS: The high rate of hospitalization for asthma exacerbation in Qingdao during the spring of 2019 was associated with the unfavorable weather conditions, which might be linked to the atmospheric circulation in East Asia.
Particulate matter (PM) has been proved to be a risk factor for the development of circulatory system diseases (CSDs) around the world. In this study, we collected daily air pollutants, emergency room (ER) visits for CSDs, and meteorological data from 2009 to 2012 in Beijing, China. After controlling for the long-term trend and eliminating the influence of confounding factors, the generalized additive model (GAM) was used to evaluate the short-term effects of PM(10) on CSDs and cause-specific diseases. The results showed that for every 10 μg/m(3) increase in PM(10), the largest effect estimates in ER visits of total CSDs, arrhythmia, cerebrovascular diseases, high blood pressure, ischemic heart disease and other related diseases were 0.14% (95% CI: 0.06-0.23%), 0.37% (95% CI: – 0.23 to 0.97%), 0.20% (95% CI: 0.00-0.40%), 0.15% (95% CI: 0.02-0.27%), 0.18% (95% CI: 0.02-0.35%) and 0.35% (95% CI: – 0.04 to 0.79%), respectively. When NO(2) or SO(2) was added into the model, the effect estimates of PM(10) were mostly attenuated, while in those models with PM(2.5) added, the effect estimates of PM(10) were mostly increased. Stratified analysis indicated that PM(10) had a greater effect on males and the elderly.
BACKGROUND: Particulate matter (PM) pollution is a well-known risk factor of stroke. However, little is known about the association between PM(1) (aerodynamic diameter ≤ 1.0 μm) and stroke. We estimated the associations of short-term exposure to PM(1) with hospital admission and recurrence of stoke in China. METHODS: Stroke data were derived from the Chinese Stroke Center Alliance (CASA) program conducted in 1458 hospitals in 292 Chinese cities from 2015 to 2019. Daily air pollution and meteorological data were collected in the cities where studied hospitals were located. Daily PM(1) concentration was estimated by a generalized additive model (GAM) using PM(2.5) and meteorological variables. A time-stratified case-crossover design was applied to estimate the associations of short-term exposure to PM(1) with hospital admission of stroke. A GAM model was used to estimate the association between average PM(1) exposure during hospitalization and the recurrence of stroke. RESULTS: A total of 989,591 stroke cases were included in the study. Each 10 μg/m(3) increase in PM(1) (lag06-day) was associated with a 0.53% (95%CI, 0.39%, 0.67%) increment in hospital admission for stroke. The adverse effects of PM(1) on ischemic stroke was stronger than on intracerebral hemorrhage. We found the associations were significant in Northeast (0.94%, 95%CI, 0.51%, 1.38%), North (0.47%, 95%CI, 0.20%, 0.75%), Central (0.57%, 95%CI, 0.30%, 0.85%), and East China (0.63%, 95%CI, 0.27%, 0.99%). Of all stroke cases, 62,988 (6.4%) had recurrent stoke attack during their hospitalization. Each 10 μg/m(3) increase in PM(1) was associated with a 1.64% (95%CI, 1.28%, 2.01%) increment in recurrence of stroke during hospitalization. CONCLUSIONS: Short-term exposure to PM(1) may increase the risk of incidence and recurrence of stroke in China, and the effects varied across different types of stroke and regions. Geographically targeted strategies and measures are needed to control air pollution for reducing the burden of stroke from PM(1).
BACKGROUND: Nationwide studies that examine climatic modification effects on the association between air pollution and health outcome are limited in developing countries. Moreover, few studies focus on PM1 pollution despite its greater health effect. OBJECTIVES: This study aims to determine the modification effects of climatic factors on the associations between PM1 and the incidence rates of lung cancer for males and females in China. METHODS: We conducted a nationwide analysis in 345 Chinese counties (districts) from 2014 to 2015. Mean air temperature and relative humidity over the study period were used as the proxies of climatic conditions. In terms of the multivariable linear regression model, we examined climatic modification effects in the stratified and combined datasets according to the three-category and binary divisions of climatic factors. Moreover, we performed three sensitivity analyses to test the robustness of climatic modification effects. RESULTS: We found a stronger association between PM1 and the incidence rate of male lung cancer in counties with high levels of air temperature or relative humidity. If there is a 10 μg/m(3) shift in PM1, then the change in male incidence rate relative to its mean was higher by 4.39% (95% CI: 2.19, 6.58%) and 8.37% (95% CI: 5.18, 11.56%) in the middle and high temperature groups than in the low temperature group, respectively. The findings of climatic modification effects were robust in the three sensitivity analyses. No significant modification effect was discovered for female incidence rate. CONCLUSIONS: Male residents in high temperature or humidity counties suffer from a larger effect of PM1 on the incidence rate of lung cancer in China. Future research on air pollution-related health impact assessment should consider the differential air pollution effects across different climatic conditions.
RATIONALE & OBJECTIVE: Increasing evidence has linked ambient fine particulate matter (ie, particulate matter no larger than 2.5 μm [PM(2.5)]) to chronic kidney disease (CKD), but their association has not been fully elucidated, especially in regions with high levels of PM(2.5) pollution. This study aimed to investigate the long-term association of high PM(2.5) exposure with incident CKD in mainland China. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: 72,425 participants (age ≥18 years) without CKD were recruited from 121 counties in Hunan Province, China. EXPOSURE: Annual mean PM(2.5) concentration at the residence of each participant derived from a long-term, full-coverage, high-resolution (1 × 1 km(2)), high-quality dataset of ground-level air pollutants in China. OUTCOMES: Incident CKD during the interval between the baseline examination of each participant (2005-2017) and the end of follow-up through 2018. ANALYTICAL APPROACH: Cox proportional hazards models were used to estimate the independent association of PM(2.5) with incident CKD and the joint association of PM(2.5) with temperature or humidity on the development of PM(2.5)-related CKD. Restricted cubic splines were used to model exposure-response relationships. RESULTS: Over a median follow-up of 3.79 (IQR, 2.03-5.48) years, a total of 2,188 participants with incident CKD were identified. PM(2.5) exposure was associated with incident CKD with an adjusted hazard ratio of 1.71 (95% CI, 1.58-1.85) per 10-μg/m(3) greater long-term exposure. Multiplicative interactions between PM(2.5) and humidity or temperature on incident CKD were detected (all P < 0.001 for interaction), whereas an additive interaction was detected only for humidity (relative risk due to interaction, 3.59 [95% CI, 0.97-6.21]). LIMITATIONS: Lack of information on participants' activity patterns such as time spent outdoors. CONCLUSIONS: Greater long-term ambient PM(2.5) pollution is associated with incident CKD in environments with high PM(2.5) exposure. Ambient humidity has a potentially synergetic effect on the association of PM(2.5) with the development of CKD. PLAIN-LANGUAGE SUMMARY: Exposure to a form of air pollution known as fine particulate matter (ie, particulate matter ≤2.5 μm [PM(2.5)]) has been linked to an increased risk of chronic kidney disease (CKD), but little is known about how PM(2.5) affects CKD in regions with extremely high levels of PM(2.5) pollution. This longitudinal cohort study in China investigates the effect of PM(2.5) on the incidence of CKD and whether temperature or humidity interact with PM(2.5). Our findings suggest that long-term exposure to high levels of ambient PM(2.5) significantly increased the risk of CKD in mainland China, especially in terms of cumulative average PM(2.5). The associations of PM(2.5) and incident CKD were greater in high-humidity environments. These findings support the recommendation that reducing PM(2.5) pollution should be a priority to decrease the burden of associated health risks, including CKD.
Facing the dual challenges of air pollution and climate change, China has set ambitious goals and made decisive efforts to reduce its carbon emission and win the ‘Battle for Blue Sky’. However, how the low-carbon transition and air quality targets could be simultaneously achieved at the sub-national levels remains unclear. The questions arise whether province-level climate change mitigation strategies could help ease the air pollution and close the air quality gap, and how these co-benefits can be compared with the cost of the green transition. Here, using an integrated modeling framework, we combined with local air pollutant emission inventories and issued policy documents to quantitatively evaluated the current situation and targets of the air quality and health co-benefits of deep carbon mitigation in Sichuan, a fast-developing inland province in China. We found that by 2035, without system-wide energy transformation induced by carbon mitigation policies, the improvement in air quality in Sichuan Province might be limited, even under stringent end-of-pipe emission control measures. On the contrary, the co-benefits of low-carbon policies would be significant. On top of stringent end-of-pipe controls, the implementation of carbon mitigation policy in line with China’s enhanced climate target could further reduce the average PM2.5 concentration in Sichuan by as much as 2.8 mu g m(-3), or the population-weighted PM2.5 concentration by 5.9 mu g m(-3) in 2035. The monetized health co-benefits in Sichuan Province would amount to 23 billion USD under the stringent carbon mitigation scenario, exceeding 1.7 billion USD of the mitigation cost by 2035. The results indicate that significant air quality and health benefits could both be achieved from carbon mitigation at the provincial level. Both air-pollution or carbon-reduction oriented policies would be important for improving environmental quality and public health.
INTRODUCTION: PM(2.5) and climate change are two major public health concerns, with majority of the research on their interaction focused on the synergistic effect, particularly for extreme events such as hot or cold temperatures. The climate sustainability index (CLS) was introduced to comprehensively explore the impact of climate change and the interactive effect on human health with air pollution. METHODS: In this study, a county-level panel data in China was collected and used. The generalized additive model (GAM) and geographically and temporally weighted regression (GTWR) was used to explore the interactive and spatial effect on mortality between CLS and PM(2.5). RESULTS AND DISCUSSIONS: Individually, when CLS is higher than 150 or lower than 50, the mortality is higher. Moreover, when PM(2.5) is more than 35 μg/m(3), the influence on mortality is significantly increased as PM(2.5) concentration rises; when PM(2.5) is above 70 μg/m(3), the trend is sharp. A nonlinear antagonistic effect between CLS and PM(2.5) was found in this study, proving that the combined adverse health effects of climate change and air pollution, especially when CLS was lower (below 100) and PM(2.5) was higher (above 35 μg/m(3)), the antagonistic effect was much stronger. From a spatial perspective, the impact of CLS and PM(2.5) on mortality varies in different geographical regions. A negative and positive influence of CLS and PM(2.5) was found in east China, especially in the northeastern and northern regions, -which were heavily polluted. This study illustrated that climate sustainability, at certain level, could mitigate the adverse health influence of air pollution, and provided a new perspective on health risk mitigation from pollution reduction and climate adaptation.
In China, the rapid development of the economy and implementation of multiple emission control policies in recent decades have been accompanied by dramatic changes in air quality. In this study, PM(2.5) concentrations estimated by using MERRA-2 reanalysis data were integrated into the Global Exposure Mortality Model (GEMM) to explore the spatiotemporal variation of nationwide PM(2.5)-related premature mortality from 1990 to 2019, and the driving factors behind decadal changes were evaluated. Since 2000, as a result of PM(2.5) pollution, air quality in China has deteriorated substantially, especially in the fast-developing eastern and southern parts. In 2009, the nationwide population-weighted (PW) PM(2.5) concentration peaked at 41.4 μg/m(3) (95% confidence interval [CI], 36.7-46.2). Simultaneously, the GEMM results revealed that nationwide PM(2.5)-related deaths increased remarkably from 1089 (95% CI, 965-1210) thousand in 1990 to 1795 (1597-1986) thousand in 2009. The implementation of the toughest-ever Air Pollution Prevention and Control Action Plan (APPCAP) in 2013 effectively controlled PM(2.5) pollution in China. By 2018, the nationwide PW PM(2.5) concentration had decreased to 34.0 (29.2-38.9) μg/m(3). Dynamic trend prediction revealed that, although the APPCAP achieved substantial health benefits, the policy did not result in further remarkable reductions in PM(2.5)-related deaths; in 2019, deaths peaked at 1932 (1716-2140) thousand. PM(2.5)-related deaths in 2030 were projected for each of four emission control scenarios. The results of the driving factor analysis and the future projections indicated that the health benefits from improving air quality are likely to be counterbalanced by changes in the population age structure. Because population ageing is becoming more and more rapid in China and the challenge of climate change is increasing, the results of this study imply that policymakers need to implement more stringent measures and set more ambitious emission control targets to reduce nationwide PM(2.5)-related premature mortality in the future.
Exposure to fine particulate matter (PM(2.5)) has become a major global health concern. Although modeling exposure to PM(2.5) has been examined in China, accurate long-term assessment of PM(2.5) exposure with high spatiotemporal resolution at the national scale is still challenging. We aimed to establish a hybrid spatiotemporal modeling framework for PM(2.5) in China that incorporated extensive predictor variables (satellite, chemical transport model, geographic, and meteorological data) and advanced machine learning methods to support long-term and short-term health studies. The modeling framework included three stages: (1) filling satellite aerosol optical depth (AOD) missing values; (2) modeling 1 km × 1 km daily PM(2.5) concentrations at a national scale using extensive covariates; and (3) downscaling daily PM(2.5) predictions to 100-m resolution at a city scale. We achieved good model performances with spatial cross-validation (CV) R(2) of 0.92 and temporal CV R(2) of 0.85 at the air quality sites across the country. We then estimated daily PM(2.5) concentrations in China from 2013 to 2019 at 1 km × 1 km grid cells. The downscaled predictions at 100 m resolution greatly improved the spatial variation of PM(2.5) concentrations at the city scale. The framework and data set generated in this study could be useful to PM(2.5) exposure assessment and epidemiological studies.
Previous studies demonstrated that global warming can lead to deteriorated air quality even when anthropogenic emissions were kept constant, which has been called a climate change penalty on air quality. It is expected that anthropogenic emissions will decrease significantly in the future considering the aggressive emission control actions in China. However, the dependence of climate change penalty on the choice of emission scenario is still uncertain. To fill this gap, we conducted multiple independent model simulations to investigate the response of PM2.5 to future (2050) climate warming (RCP8.5) in China but with different emission scenarios, including the constant 2015 emissions, the 2050 CLE emissions (based on Current Legislation), and the 2050 MTFR emissions (based on Maximum Technically Feasible Reduction). For each set of emissions, we estimate climate change penalty as the difference in PM2.5 between a pair of simulations with either 2015 or 2050 meteorology. Under 2015 emissions, we find a PM2.5 climate change penalty of 1.43 mu g m(-3) in Eastern China, leading to an additional 35,000 PM2.5-related premature deaths [95% confidence interval (CI), 21,000-40,000] by 2050. However, the PM2.5 climate change penalty weakens to 0.24 mu g m(-3) with strict anthropogenic emission controls under the 2050 MTFR emissions, which decreases the associated PM2.5-related deaths to 17,000. The smaller MTFR climate change penalty contributes 14% of the total PM2.5 decrease when both emissions and meteorology are changed from 2015 to 2050, and 24% of total health benefits associated with this PM2.5 decrease in Eastern China. This finding suggests that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM2.5 and its associated premature deaths, even though a climate change penalty still occurs even under MTFR. Strengthened controls on anthropogenic emissions are key to attaining air quality targets and protecting human health in the context of future global climate change. (C) 2020 Elsevier B.V. All rights reserved.
OBJECTIVES: Evidence of childhood asthma hospitalizations associated with temperature variability (TV) and the attributable risk are limited in China. We aim to use a comprehensive index that reflected both intra- and inter-day TV to assess the TV-childhood asthma relationship and disease burden, further to identify seasonality vulnerable populations, and to explore the effect modification of PM(2.5). METHODS: A quasi-distributed lagged nonlinear model (DLNM) combined with a linear threshold function was applied to estimate the association between TV and childhood asthma hospitalizations during 2013-2016 in Hefei, China. Subgroup analysis was conducted by age and sex. Disease burden is reflected by the attributable fraction and attributable number. Besides, modifications of PM(2.5) were tested by introducing the cross-basis of TV and binary PM(2.5) as an interaction term. RESULTS: The risk estimates peaked at TV(0-3) and TV(0-4) in the cool and the warm season separately, with RR of 1.051 (95%CI: 1.021-1.081) and 1.072 (95%CI: 1.008-1.125), and the effects lasted longer in the cool season. The school-age children in the warm season and all subgroups except pre-school children in the cool season were vulnerable to TV. It is estimated that the disease burden related to TV account for 6.2% (95% CI: 2.7%-9.4%) and 4% (95% CI: 0.6%-7.1%) during the cool and warm seasons in TV(0-3). In addition, the risks of TV were higher under the high PM(2.5) level compared with the low PM(2.5) level in the cool season, although no significant differences between them. CONCLUSIONS: TV exposure significantly increases the risk and disease burden of childhood asthma hospitalizations, especially in the cool season. More medical resources should be allocated to school-age children. Giving priority to pay attention to TV in the cool season in practice could obtain the greatest public health benefits and those days with high TV and high PM(2.5) need more attention.
Global warming increases the probability of extreme events and heat waves triggering severe impacts on human health, especially the elderly. Taiwan is an aged society, so residential buildings, which cannot withstand extreme temperature events, increase the risk of harm for the elderly. Furthermore, Taiwanese prefer to open the windows to reduce indoor high temperatures, which causes high levels of outdoor PM2.5 to flow indoors, leading to health risks. Therefore, this research proposes a strategy to create a house with a low temperature and a low PM2.5 health risk for the elderly based on building envelope renovation and windows user behavior patterns. The risk day is demonstrated as an index to evaluate the indoor environment quality, which is based on the number of days that exceed the health risk threshold. The results show that the performance improvement of the building envelope and control of the window opening timing can effectively reduce the risk days by 48.5%. This means that passive strategies cannot fully control health risks, and the use of equipment is necessary. Finally, if the current situation is maintained without any adjustment or strategy improvement, an additional 41.3% energy consumption must be paid every year to control health risks.
Mental health conditions have the potential to be worsened by air pollution or other climate-sensitive factors. Few studies have empirically examined those associations when we faced to co-exposures, as well as interaction effects. There would be an urgent need to use deep learning to handle complex co-exposures that might interact in multiple ways, and the model performance reinforced by SHapely Additive exPlanations (SHAP) enabled our predictions interpretable and hence actionable. Here, to evaluate the mixed effect of short-term co-exposure, we conducted a time-series analysis using approximately 1.47 million hospital outpatient visits of mental disorders (i.e., depressive disorder-DD, Schizophrenia-SP, Anxiety Disorder-AD, Bipolar Disorder-BD, Attention Deficit and Hyperactivity Disorder-ADHD, Autism Spectrum Disorder-ASD), with matched meteorological observations from 2015 through 2019 in Nanjing, China. The global insights of gated recurrent unit model revealed that most of input features with similar effect size caused the illness risk of SP and ASD increase, and most markedly, 73% of relative humidity, 44.6 µg/m(3) of NO(2), and 14.1 µg/m(3) of SO(2) at 5-year average level associated with 2.27, 1.14, and 1.29 visits increase for DD, SP, and AD, respectively. Both synergic and antagonistic effect among informative paired-features were distinguished from local feature dependence. Interestingly, variation tendencies of excessive visits of bipolar disorder when atmospheric pressure, PM(2.5), and O(3) interacted with one another were inconsistent. Our results provided added qualitative and quantitative support for the conclusion that short-term co-exposure to ambient air pollutants and meteorological conditions posed threats to human mental health.
To examine Beijing residents’ risk perception of contracting smog-related diseases, we proposed a model in which air-pollution knowledge is a theoretical mechanism accounting for the influence on risk perception of exposure to environmental news and exposure to Under the Dome, an environmental documentary about smog in China, which has been censored. Data (N = 523) were collected from Beijing residents from February to March in 2017. We analyzed the data using Hayes’ PROCESS macro. Findings revealed that environmental-news exposure is positively associated with both air-pollution knowledge and risk perception. Exposure to environmental news has an indirect effect on risk perception through air-pollution knowledge. Exposure to Under the Dome is positively related to risk perception but is not related to air-pollution knowledge. We contributed to the literature by empirically testing the impact of Under the Dome, which has been largely studied via the critical theory approach. Implications included that Under the Dome is a successful risk communication model and that its impact goes beyond increasing public risk perception of smog.
The coupling effects of sandstorm and dust from coal bases themselves can have a major impact on the atmospheric environment as well as on human health. The typical coal resource city of Wuhai in Inner Mongolia was selected in order to study these impacts during a severe sandstorm event in March 2021. Particulate matter (PM1, PM2.5 and PM10) and total suspended particulate matter (TSP) samples were collected during the sandstorm event of 15-19 March 2021 and non-sandstorm weather (11-13 March 2021) and analyzed for their chemical composition. The concentrations of PM1, PM2.5, PM10 and TSP in Wuhai city during the sandstorm were 2.2, 2.6, 4.8 and 6.0 times higher than during non-sandstorm days, respectively. Trace metals concentrations in particles of different sizes generally increased during the sandstorm, while water-soluble ions decreased. Positive matrix fraction (PMF) results showed that the main sources of particles during both sandstorm and non-sandstorm days were industrial emissions, traffic emissions, combustion sources and dust. The proportion of industrial emissions and combustion sources increased compared with non-sandstorm days, while traffic emissions and dust decreased. The backward trajectory analysis results showed that airflows were mainly transported over short distances during non-sandstorm days, and high concentration contribution source areas were from southern Ningxia, southeast Gansu and western Shaanxi. The airflow was mainly transported over long distances during the sandstorm event, and high concentration contribution source areas were from northwestern Inner Mongolia, southern Russia, northern and southwestern Mongolia, and northern Xinjiang. A health risk analysis showed that the risk to human health during sandstorm days related to the chemical composition of particles was generally 1.2-13.1 times higher than during non-sandstorm days. Children were more susceptible to health risks, about 2-6.3 times more vulnerable than adults to the risks from heavy metals in the particles under both weather conditions.
BACKGROUND: Fine particulate matter (PM(2.5)) pollution is one of the most critical environmental and public health problems in China and has caused an enormous disease burden, especially long-term PM(2.5) exposure. Global climate change represents another environmental challenge in the coming decades and is also an essential factor affecting PM(2.5) pollution. Moreover, China has an aging population with a changing population size and falling age-standardized mortality rates. However, little evidence exists evaluating the potential impacts from climate change and population aging on the long-term PM(2.5) exposure-related disease burden. This study quantifies the impacts of climate and population changes on changes in the disease burden attributed to long-term PM(2.5) exposure from 2015 to 2030 in mainland China, which could add evidence for the revision of relevant environmental standards and health policies. METHODS: This modeling study investigated long-term PM(2.5) exposure-related mortality across China based on PM(2.5) projections under Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) and population scenarios from shared socioeconomic pathways (SSPs). PM(2.5) concentrations were simulated by the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) modeling systems. In addition, three types of population projections in 2030 relative to 2015 were set up as follows: (i) the population remained the same as that in 2015; (ii) the population size changed under SSPs, but the age structure remained the same; (iii) both the population size and age structure changed under SSPs. The global exposure mortality model (GEMM) was adopted to estimate PM(2.5)-related premature deaths. RESULTS: Ambient PM(2.5) concentrations decreased from 2015 to 2030 under the two climate and emission scenarios. Estimates of related premature mortality in 2030 declined compared with that in 2015 due to lower PM(2.5) concentrations (RCP4.5: -16.8%; RCP8.5: -16.4%). If the age structure of the population remained unchanged and the population size changed under SSPs, the nonaccidental premature mortality also showed a decrease ranging from -18.6% to -14.9%. When both population size and age structure changed under SSPs, the population in China would become older. Nonaccidental premature mortality would sharply increase by 35.7-52.3% (with a net increase of 666-977 thousand) in 2030. CONCLUSION: The PM(2.5) pollution in 2030 under both RCP4.5 and RCP8.5 would slightly improve. The population sizes in 2030 projected by SSPs are relatively stable compared with that in 2015. However, the modest decrease due to air pollution improvement and stable population size would be offset by population aging.
This study examines the impact of air pollution from straw burning on human cognitive health in China by linking household health surveys with PM2.5 emissions derived from remote sensing data on fire activity. The identification strategy leverages the spatial dispersion of air pollutants due to exogenous wind directions. The results indicate that PM2.5 emissions from upwind straw burning have a negative impact on cognitive functions of respondents aged 55 and above, but PM2.5 emissions from downwind fires do not. The impact is transitory and caused by contemporaneous PM2.5 emissions on the day of cognitive testing. Our findings demonstrate a link from air pollution to cognitive declines and suggest that through this link, climate change could result in additional health costs by increasing the risk of wildfires.
Hypertension (HTN) was a major preventable cause of cardiovascular disease (CVD), contributing to a huge disease burden. Ambient temperature, air pollution and green space were important influencing factors of HTN, and few studies have assessed the effects and interactions of ambient temperature, air pollution and green space on HTN in rural areas. In this study, we selected 8400 individuals randomly in rural areas of Anhui Province by a multi-stage stratified cluster sampling. A total of 8383 individuals were included in the final analysis. We collected particulate pollutants and meteorological data from the local air quality monitoring stations and National Center for Meteorological Science from January 1 to December 31, 2020, respectively. The normalized differential vegetation index (NDVI) of Anhui Province in 2020 was produced and processed by remote sensing inversion on the basis of medium resolution satellite images. The average annual mean exposure concentrations of air pollution, meteorological factors, and NDVI were calculated for each individual based on the geocoded residential address. HTN was defined according the Chinese Guidelines for Prevention and Treatment of HTN. The effects and interactions of ambient temperature, air pollution and green space on HTN were evaluated by generalized linear model and interaction model, respectively. In this study, the prevalence of HTN was 24.14%. The adjusted odd ratio of HTN for each 1 μg/m(3) increasing in PM(2.5) and PM(10), 1 °C of ambient temperature, and 0.1 of NDVI were:1.276 (1.013, 1.043), 1.012 (1.006, 1.018), 0.862 (0.862, 0.981) and 0.669 (0.611, 0.733), respectively. The results showed that air pollutants were positively correlated with HTN, while ambient temperature and green space were negatively correlated with HTN. Meanwhile, the negative associations of green space on HTN could decrease with the increasing concentrations of air pollution, but increase with the rising of ambient temperature.
BACKGROUND: While temperature changes have been confirmed as one of the contributory factors affecting human health, the association between high-frequency temperature variability (HFTV, i.e., temperature variation at short time scales such as 1, 2, and 5 days) and the hospitalization of chronic obstructive pulmonary disease (COPD) was rarely reported. OBJECTIVES: To evaluate the associations between high-frequency temperature variabilities (i.e., at 1, 2, and 5-day scales) and daily COPD hospitalization. METHODS: We collected daily records of COPD hospitalization and meteorological variables from 2013 to 2017 in 21 cities of Guangdong Province, South China. A quasi-Poisson regression with a distributed lag nonlinear model was first employed to quantify the effects of two HFTV measures, i.e., the day-to-day (DTD) temperature change and the intraday-interday temperature variability (IITV), on COPD morbidity for each city. Second, we used multivariate meta-analysis to pool the city-specific estimates, and stratified analyses were performed by age and sex to identify vulnerable groups. Then, the meta-regression with city-level characteristics was employed to detect the potential sources of the differences among 21 cities. RESULTS: A monotonic increasing curve of the overall exposure-response association was observed, suggesting that positive HFTV (i.e., increased DTD and IITV) will significantly increase the risk of COPD admission. Negative DTD was associated with reduced COPD morbidity while positive DTD elevated the COPD risk. An interquartile range (IQR) increase in DTD was associated with a 24% (95% CI: 12-38%) increase in COPD admissions. An IQR increase in IITV(0-1) was associated with 18% (95% CI: 7-27%) increase in COPD admissions. Males and people aged 0-64 years appeared to be more vulnerable to the DTD effect than others. Potential sources of the disparity among different cities include urbanization level, sex structure, industry structure, gross domestic product (GDP), health care services, and air quality. CONCLUSIONS: The increases of DTD and IITV have significant adverse impacts on COPD hospitalization. As climate change intensifies, precautions need to be taken to mitigate the impacts of high-frequency temperature changes.
OBJECTIVE: Most evidence comes from studies show that ambient ozone(O(3)) pollution has become a big issue in China. Few studies have investigated the impact of ozone spatiotemporal patterns on respiratory mortality and cardiovascular mortality in Nanchang city. Thus, this study aimed to explore the health effect of ozone exposure on respiratory mortality and cardiovascular mortality in Nanchang, Jiangxi Province. METHODS: Using the daily mortality data, atmospheric routine monitoring data and meteorological data in Nanchang from 2014 to 2020, we performed a generalized additive model (GAM) based on the poisson distribution in which time-series analysis to calculate the risk correlation between respiratory mortality and cardiovascular mortality and ozone exposure level (8h average ozone concentration, O(3)-8h). Besides, analyses were also stratified by season, age and sex. RESULTS: In the single-pollutant model, for every 10 μg/m(3) increase in ozone, respiratory mortality increased 1.04% with 95% confidence interval (CI) between 0.04 and 1.68%, and cardiovascular mortality increased 1.26% (95%CI: 0.68 ~ 1.83%). In the multi-day moving average lag model, the mortality of respiratory diseases and cardiovascular diseases reached a relative risk peak on the cumulative lag5 (1.77%,95%CI: 0.99 ~ 2.57%) and the cumulative lag3 (1.68%,95%CI: 0.93 ~ 2.45%), respectively. The differences were statistically significant (P < 0.05). Results of the stratified analyses showed the effect value of respiratory mortality in people aged ≥65 years was higher than aged <65 years, whereas the greatest effect of cardiovascular mortality in people aged <65 years than aged ≥65 years. Ozone had a more profound impact on females than males in respiratory diseases and cardiovascular diseases. In winter and spring, ozone had a obvious impact on respiratory mortality, and effects of ozone pollution on cardiovascular mortality were stronger in summer and winter. There was a statistically significant difference of respiratory mortality in winter and spring and of cardiovascular mortality in summer and winter (P < 0.05). CONCLUSIONS: In the long run, the more extreme the pollution of ozone exposure, the higher the health risk of residents' respiratory mortality and cardiovascular mortality. Therefore, the government should play an important role in the prevention and control ways of decreasing and eliminating the ozone pollution to protect the resident's health. The findings provide valuable data for further scientific research and improving environmental policies in Nanchang city.
Ambient ozone (O(3)) has emerged as an important public health issue worldwide. Previous studies found an association between O(3) and cardiorespiratory mortality. However, evidence was limited regarding the risk of O(3) on mortality from other diseases. In this study, we aimed to estimate the association between O(3) and mortality from a broad spectrum of diseases in Guangzhou, China, which has experienced a rapid increase in O(3) concentration over the past decades. Daily data were obtained on cause-specific mortality, air pollutant concentrations and weather conditions during 2013-2018. A generalized additive model with quasi-Poisson regression was applied to examine the association between O(3) and mortality from 10 broad causes and 26 refined subcategories, with adjustment of long-term and seasonal trends, weather conditions, public holidays and days of the week. We found that the threshold concentrations of O(3) were 40 μg/m(3) for all-cause, non-accidental, cardiovascular and respiratory mortality. Mortality risk increased monotonically with O(3) concentrations above the threshold. Per 10 μg/m(3) increase of O(3) at lag 0-3 days was associated with 0.54% (95%CI: 0.34-0.74%), 0.56% (95%CI: 0.36-0.76%), 0.59% (95%CI: 0.30-0.88%), 0.78% (95%CI: 0.33-1.24%) and 0.52% (95%CI: 0.21-0.83%) elevated risk of death from all causes, non-accidental causes, cardiovascular diseases, respiratory diseases and neoplasms, respectively. Among the subcategories, the largest effect estimate was observed in people with chronic obstructive pulmonary disease. The elderly suffered from a higher mortality risk from O(3). Stringent emission control strategies and multi-sectoral collaborations are needed to reduce the detrimental impact of O(3) on vulnerable populations.
Facing the dual challenges of climate change and air pollution, China has made great efforts to explore the co-control strategies for the both. We assessed the benefits of carbon and pollution control policies on air quality and human health, with an integrated framework combining an energy-economic model, an air quality model and a concentration-response model. With a base year 2015, seven combined scenarios were developed for 2030 based on three energy scenarios and three end-of-pipe control ones. Policy-specific benefits were then evaluated, indicated by the reduced emissions, surface concentrations of major pollutants, and premature deaths between scenarios. Compared to the 2030 baseline scenario, the nationwide PM(2.5)- and O(3)-related mortality was expected to decline 23% or 289 (95% confidence interval: 220-360) thousand in the most stringent scenario, and three quarters of the avoided deaths were attributed to the end-of-pipe control measures. Provinces in heavily polluted and densely populated regions would benefit more from carbon and pollution control strategies. The population fractions with PM(2.5) exposure under the national air quality standard (35 μg/m(3)) and WHO guideline (10 μg/m(3)) would be doubled from 2015 to 2030 (the most stringent scenario), while still very few people would live in areas with the WHO guideline achieved for O(3) (100 μg/m(3)). Increased health impact of O(3) suggested a great significance of joint control of PM(2.5) and O(3) in future policy-making.
Background This study investigated risks of mortality from and morbidity (emergency room visits (ERVs) and outpatient visits) of asthma and chronic obstructive pulmonary disease (COPD) associated with extreme temperatures, fine particulate matter (PM2.5), and ozone (O3) by sex, and age, from 2005 to 2016 in 6 metropolitan cities in Taiwan. Methods The distributed lag non-linear model was employed to assess age (0–18, 19–39, 40–64, and 65 years and above), sex-cause-specific deaths, ERVs, and outpatient visits associated with extreme high (99th percentile) and low (5th percentile) temperatures and PM2.5 and O3 concentrations at 90th percentile. Random-effects meta-analysis was adopted to investigate cause-specific pooled relative risk (RR) and 95% confidence intervals (CI) for the whole
studied areas. Results Only the mortality risk of COPD in the elderly men was significantly associated with the extreme low temperatures. Exposure to the 90th percentile PM2.5 was associated with outpatient visits for asthma in 0–18 years old boys [RR = 1.15 (95% CI: 1.09–1.22)]. Meanwhile, significant elevation of ERVs of asthma for females aged 40–64 years was associated with exposure to ozone, with the highest RR of 1.21 (95% CI: 1.05–1.39). Conclusions This study identified vulnerable subpopulations who were at risk to extreme events associated with ambient environments deserving further evaluation for adaptation.
BACKGROUND: The health effect of particulate matter pollution on stroke has been widely examined; however, the effect among patients with comorbid type 2 diabetes (T2D) in developing countries has remained largely unknown. METHODS: A time-series study was conducted to investigate the short-term effect of fine particulate matter (PM(2.5)) and inhalable particulate matter (PM(10)) on hospital admissions for stroke among patients with T2D in Beijing, China, from 2014 to 2018. An over-dispersed Poisson generalized additive model was employed to adjust for important covariates, such as weather conditions and long-term and seasonal trends. RESULTS: A total of 159,298 hospital admissions for stroke comorbid with T2D were reported. Approximately linear exposure-response curves were observed for PM(2.5) and PM(10) in relation to stroke admissions among T2D patients. A 10 μg/m(3) increase in the four-day moving average of PM(2.5) and PM(10) was associated with 0.14% (95% confidence interval [CI]: 0.05-0.23%) and 0.14% (95% CI: 0.06-0.22%) incremental increases in stroke admissions among T2D patients, respectively. A 10 μg/m(3) increase in PM(2.5) in the two-day moving average corresponded to a 0.72% (95% CI: 0.02-1.42%) incremental increase in hemorrhagic stroke, and a 10 μg/m(3) increase in PM(10) in the four-day moving average corresponded to a 0.14% (95% CI: 0.06-0.22%) incremental increase in ischemic stroke. CONCLUSIONS: High particulate matter might be a risk factor for stroke among patients with T2D. PM(2.5) and PM(10) have a linear exposure-response relationship with stroke among T2D patients. The study provided evidence of the risk of stroke due to particulate matter pollution among patients with comorbid T2D.
OBJECTIVE: To explore the relationship between ambient PM(2.5) level and outpatient visits of children with respiratory diseases in a megacity, Zhengzhou, in central China. METHODS: We collected daily outpatient visit data, air pollutant data, and meteorological data at the monitoring points of Zhengzhou from the time period 2018 to 2020 and used Spearman’s rank correlation to analyze the correlation between children’s respiratory outpatient visits and air pollutants and meteorological factors. Generalized additive models were used to analyze the association between PM(2.5) exposures and children’s respiratory outpatient visits. A stratified analysis was further carried out for the seasons. RESULTS: From 2018 to 2020, the total number of outpatients with children’s respiratory diseases was 79,1107, and the annual average concentrations of PM(2.5), PM(10), SO(2), NO(2), CO, and O(3)-8h in Zhengzhou were respectively 59.48 μg/m(3), 111.12 μg/m(3), 11.10 μg/m(3), 47.77 μg/m(3), 0.90 mg/m(3) and 108.81 μg/m(3). The single-pollutant model showed that the risk of outpatient visits for children with respiratory disease increased by 0.341% (95%CI: 0.274-0.407%), 0.532% (95%CI: 0.455-0.609%) and 0.233% (95%CI: 0.177-0.289%) for every 10 μg/m(3) increase in PM(2.5) with a 3-day lag, 1-day lag, and 1-day lag respectively for the whole year, heating period, and non-heating period. The multi-pollutant model showed that the risk of PM(2.5) on children’s respiratory disease visits was robust. The excess risk of PM(2.5) on children’s respiratory disease visits increased by 0.220% (95%CI: 0.147-0.294%) when SO(2) was adjusted. However, the PM(2.5) effects were stronger during the heating period than during the non-heating period. CONCLUSION: The short-term exposure to PM(2.5) was significantly associated with outpatient visits for children’s respiratory diseases. It is therefore necessary to strengthen the control of air pollution so as to protect children’s health.
Atmospheric coarse particulate matter (PM(10)) enriched with heavy metal(loid)s could pose potentially significant health risk to humans, while accurate health risk assessment calls for characterization of their bioaccessibility, besides the total contents. The health risk of major toxic heavy metal(loid)s in the PM(10) from four large cities in northern China via inhalation was investigated based on their total contents and bioaccessibility. The annual mean concentrations of PM-bound Zn, As, Pb, and Mn in the atmosphere of the four cities were 650, 305, 227, and 177 ng⋅m(-3), respectively. The levels of heavy metal(loid)s in the PM(10) were generally higher in winter but lower in summer in all four cities, which resulted primarily from the emissions associated with coal combustion for district and household heating and the unfavorable meteorological conditions in winter. The bioaccessibility of heavy metal(loid)s in the PM(10) ranged from 0.9 to 48.7%, following the general order of Mn > Co > Ni > Cd > Cu > As > Cr > Zn > Pb. Based on their total contents in the PM(10), most heavy metal(loid)s posed significant public health risk via inhalation exposure in the four cities. However, after accounting for the bioaccessibility of metal(loid)s, the non-carcinogenic risk of most metal(loid)s was negligible, except for As in the PM(10) of Jinzhong, while only the carcinogenic risk posed by Cr and As in the PM(10) exceeded the acceptable level. These findings demonstrate the importance of characterizing the bioaccessibility of airborne PM-bound heavy metal(loid)s in health risk assessment and could guide the on-going efforts on reducing the public health risk of PM(10) in northern China.
Air pollution has a serious fallout on human health, and the influences of the different urban morphological characteristics on air pollutants cannot be ignored. In this study, the relationship between urban morphology and air quality (wind speed, CO, and PM(2.5)) in residential neighborhoods at the meso-microscale was investigated. The changes in the microclimate and pollutant diffusion distribution in the neighborhood under diverse weather conditions were simulated by Computational Fluid Dynamics (CFD). This study identified five key urban morphological parameters (Building Density, Average Building Height, Standard Deviation of Building Height, Mean Building Volume, and Degree of Enclosure) which significantly impacted the diffusion and distribution of pollutants in the neighborhood. The findings of this study suggested that three specific strategies (e.g. volume of a single building should be reduced, DE should be increased) and one comprehensive strategy (the width and height of the single building should be reduced while the number of single buildings should be increased) could be illustrated as an optimized approach of urban planning to relief the air pollution. The result of the combined effects could provide a reference for mitigating air pollution in sustainable urban environments.
Evidence is still limited for the role of long-term PM(2.5) exposure in cerebrovascular diseases among residents in high pollution regions. The study is aimed to investigate the long-term effects of PM(2.5) exposure on stroke mortality, and further explore the effect modification of temperature variation on the PM(2.5)-mortality association in northern China. Based on a cohort data with an average follow-up of 9.8 years among 38,435 urban adults, high-resolution estimates of PM(2.5) derived from a satellite-based model were assigned to each participant. A Cox regression model with time-varying exposures and strata of geographic regions was employed to assess the risks of stroke mortality associated with PM(2.5), after adjusting for individual risk factors. The cross-product term of PM(2.5) exposure and annual temperature range was further added into the regression model to test whether the long-term temperature variation would modify the association of PM(2.5) with stroke mortality. Among the study participants, the annual mean level of PM(2.5) concentration was 66.3 μg/m(3) ranging from 39.0 μg/m(3) to 100.6 μg/m(3). For each 10 μg/m(3) increment in PM(2.5), the hazard ratio (HR) was 1.31 (95% CI: 1.04-1.65) for stroke mortality after multivariable adjustment. In addition, the HRs of PM(2.5) decreased gradually as the increase of annual temperature range with the HRs of 1.95 (95% CI: 1.36-2.81), 1.53 (95% CI: 1.06-2.22), and 1.11 (95% CI: 0.75-1.63) in the low, middle, and high group of annual temperature range, respectively. The findings provided further evidence of long-term PM(2.5) exposure on stroke mortality in high-exposure settings such as northern China, and also highlighted the view that assessing the adverse health effects of air pollution might not ignore the role of temperature variations in the context of climate change.
Ozone (O(3)) is a reactive oxidant exerting both inflammatory and oxidative damages to the respiratory system. With the ground-level O(3) progressively increasing in the past decade, the reevaluation of the pneumonia hospitalization risk from exposure to O(3) is of public health interest. We conducted an ecological time-series study to examine the city-specific association between short-term O(3) exposure and pneumonia hospitalizations in Hong Kong and Taipei, respectively. We linked the daily pneumonia hospitalization count to air pollution concentrations and weather conditions according to the date of admission during 2010-2017. We applied a generalized additive distributed lag model to examine the association while adjusting for time-varying covariates. Stratified analysis by age group and the potential harvesting effect of O(3) were evaluated. We observed the harvesting effects of O(3) on pneumonia hospitalizations in children in both cities and adults in Taipei. The short-term effect of O(3) lasted for around one week. An interquartile range (IQR) increment of daytime 8-hour mean concentration of O(3) distributed over 0-6 lag days in Hong Kong (42.4 μg/m(3)) was associated with a 7.04% (95% CI: 5.35-8.76%) increase in hospital admissions for elderly pneumonia, while the corresponding cumulative excess risk per IQR increment of O(3) in Taipei (38.7 μg/m(3)) was 3.41% (95% CI: 1.63-5.22%). Different O(3) metrics, varying degrees of freedom for filtering the temporal trend, and three-pollutant models supported the robustness of the associations. We concluded that short-term O(3) exposure was associated with pneumonia hospitalizations in the elderly population. Understanding the pneumonia hospitalization risk of O(3) will help to inform public health policies in the planning of ozone control strategies and intervention measures to prevent ozone-related pneumonia in vulnerable elderly populations.
Background: Health effects associated with extreme temperature and elevated air pollutants have been concerns. The present study examined mortality from and morbidity of chronic kidney disease (CKD) associated with extreme temperature and exposure to fine particulate matter (PM2.5) and ozone (O-3) by sex and age in 2005-2016 in metropolitans of Taiwan. Methods: The distributed lag non-linear model was applied to analyze roles of extreme high (99th percentile) and low (5th percentile) temperatures, and 90th percentile PM2.5 and ozone (O3) in association with CKD risks of deaths, emergency room visits (ERVs), and outpatient visits by age (40-64 and 65 years and above) and sex. Pooled relative risk (RR) and 95% confidence intervals (CI) for all studied areas were estimated using random -effects meta-analysis. Results: Cold spells (< 14 C) showed a higher risk on mortality from CKD for the elderly. Middle-aged population was more vulnerable to high temperature (31.3 C) with the highest risk for women admitted to outpatient visits [RR = 1.25; (95% CI; 1.17-1.34)]. Women aged 65 years and above had the highest risk after exposing to higher levels of PM2.5 (55 mu g/m(3)) [RR = 1.07; (95% CI; 1.03-1.12)] and O-3 (43 ppb) [RR = 1.07; (95% CI; 1.00-1.15)]. Conclusions: The elderly CKD patients were more prone to the adverse effect of low temperature and high levels of PM2.5 and O-3. Middle aged groups were more prone to health risks related to the high temperature. Men are more susceptible to the high temperature, meanwhile women are sensitive to higher levels of PM2.5 and O-3.
How to mitigate greenhouse gas emission and achieve human development remain major sustainability issues, particularly in China. Empirical research on the effects of climate warming and social change on human health and wellbeing is quite fragmented. This study examines the impact of environmental issues and social changes on health and human wellbeing using a time series data of China from 1991 to 2020. Findings show that environmental issues have a negative impact on health and human wellbeing in long run. While the internet is a form of social change that tends to improve health and human wellbeing in the long run. FDI exerts a positive effect on human health, but it does not improve wellbeing in the long run. In contrast, financial development does not improve human health but it has a significant positive impact on wellbeing in the long run. Our empirical insights have important implications for achieving human wellbeing through the pursuit of environmental sustainability and social change.
As the most common mental disorder, anxiety heavily damages human mental health and leads to heavy health burdens. However, evidence concerning the impact of NO2 on anxiety is limited. In this study, we aimed to further explore the association between short-term NO2 exposure and anxiety outpatient visits in Xi’an, a city located in Northwest China with relatively heavy air pollution. Daily data of anxiety outpatient visits, air pollutants (PM2.5, PM10, SO2, NO2, CO, and O-3), and meteorological conditions (daily mean temperature and relative humidity) from 2013 to 2019 were gathered. Then generalized additive models (GAM) was adopted to investigate the relationship between short-term NO2 exposure and the number of anxiety outpatient visits after controlling for long-term effects, holiday effects, day of the week, and weather conditions. The results showed that NO2 exposure was positively correlated with the number of daily anxiety outpatient visits: A 10 mu g/m(3) increase of NO2 concentration corresponded to 1.94% (95%CI: 1.19%, 2.68%) and 3.72% (95%CI: 2.35%, 5.08%) increase in anxiety outpatient visits at lag 1 and lag 07, respectively. Such a relationship showed gender differences (more obvious in females) but no age differences. More interestingly, the association between NO2 and anxiety outpatient visits showed to be more obvious during cool seasons than during warm seasons. In summary, short-term ambient NO2 exposure, especially during cool seasons, may be related to a higher risk of anxiety outpatient visits.
A reduction in the energy-related emissions of air pollutants would not only mitigate climate change but would also improve local air quality and public health. This paper aimed to analyze the trends of air quality index (AQI) and greenhouse gas (GHG) emissions in Taiwan by using the latest official statistics. In addition, this study also summarized regulatory measures for controlling air pollution from the energy sector with relevance to sustainable development goals (SDGs). With the joint efforts by the public and private sectors, the change in the total GHG emissions did not vary much with the exception of 2009, ranging from 250 to 272 million metric tons of CO2 equivalent from 2005 through 2019. Based on the data on AQI, the percentage of AQI by station-day with AQI > 100 has decreased from 18.1% in 2017 to 10.1% in 2020, indicating a decreasing trend for all criteria air pollutants. On the other hand, the coronavirus disease (COVID-19) lockdown, in 2019, has positively impacted Taiwan’s urban air quality, which was consistent with those observed in other countries. This consistent situation could be attributed to the climate change mitigation policies and promotional actions under the revised Air Pollution Control Act and the Greenhouse Gas Reduction and Management Act of 2015. In response to the SDGs launched by the Taiwan government in 2018, achieving the relevant targets by 2030 can be prospective.
The purpose of this paper is to evaluate the monetary GHG reduction benefits and health co-benefits for the industrial sector under the imposition of a carbon charge in Taiwan. The evaluation proceeds from 2023-2030 for different rates of carbon charge for the GHGs by a model of “Taiwan Economic Input Output Life Cycle Assessment and Environmental Value” constructed in this study. It is innovative in the literature to simulate the benefits of GHG reductions and health co-benefits of air pollutions for the industrial sector under the imposition of a carbon charge comprehensively. The results consistently show benefits whether the charge is imposed on the scope 1 and scope 2 GHG emissions or on the scope 1 emissions only. The health co-benefits are on average about 5 times those of GHG reductions benefits in 2023-2030. The average total benefits with the summation of GHG reduction benefits and health co-benefits are 821.9 million US dollars and 975.1 US million US dollars per year, respectively. However, both the GHG reduction benefits and health co-benefits are consistently increasing at a decreasing rate in 2023-2030. The increased multiple for the rate of the carbon charge is higher than the increased multiple of the total benefits and this result shows that the increase of the carbon charge becomes less effective.
Previous observational studies have shown that exposure to ambient temperature and air pollution were associated with the incidence of gestational diabetes mellitus (GDM). However, the susceptible time window of non-optimal temperature on GDM is still unknown, and the interaction with air pollution has not been examined. We conducted a prospective cohort study in Guangzhou, China to investigate the windows of susceptibility of temperature extremes and variability on the risk of GDM and to explore any interaction effect with air pollution. Daily maximum (T(max)), minimum temperature (T(min)) and diurnal temperature range (DTR) were obtained from Guangdong Meteorological Service. Distributed lag non-linear models with a logistic regression were applied to assess the effect of temperature extremes and DTR in different weeks of gestation on GDM. To examine the interaction effect, relative excess risk due to interaction index, attributable proportion and synergy index were calculated. There were 5,165 pregnant women enrolled, of which 604 were diagnosed with GDM (11.7%). Compared with a reference temperature (50th percentile of T(max)), we found that extreme high temperature (99th percentile of T(max)) exposure during 21st and 22nd gestational weeks was associated with an increased risk of GDM. Extreme low temperature (1st percentile of T(max)) exposure during 14th to 17th weeks increased the risk of GDM. We observed that per 1 °C increment of DTR during 21st to 24th weeks was associated with an elevated GDM risk. No interaction effect of temperature extremes or variability with air pollution on GDM were observed. Our results suggested that non-optimal temperature is an independent risk factor of GDM. The time window of susceptibility for extreme temperatures and DTR exposure on the risk of GDM generally occurred in second trimester of pregnancy. In the context of climate change, our study has important implications for reproductive health and justifies more research in different climate zones.
The independent associations of extreme temperature and ambient air pollutant with the admission to hospital and mortality of ischemic stroke have been widely investigated. However, knowledge about the modification effects of variation in season and temperature on the association between exposure to nitrogen dioxide (NO(2)) and ischemic stroke onset is still limited. This study purposed to explore the effect of NO(2) on daily ischemic stroke onset modified by season and ambient temperature, and identify the potential population that susceptible to ischemic stroke onset connected with NO(2) and ambient temperature. Data on daily ischemic stroke counts, weather conditions, and ambient air pollutant concentrations in Shenzhen were collected between January 1, 2008, and December 31, 2014. The seasonal effect on the NO(2)-associated onset was measured by a distributed-lag linear model. Furthermore, a generalized additive model that incorporated with stratification analyses was used to calculate the interactive effects between NO(2) and ambient temperature. During the winter, the average percentage increase in daily ischemic stroke onset for each 10 μg/m(3) increment in NO(2) concentration on lagged 2 days was 3.05% (95% CI: 1.31-4.82%), while there was no statistically significant effect of NO(2) during summer. And the low-temperature days ([Formula: see text] mean temperature), with a 2.23% increase in incidence (95% CI: 1.18-3.29%) for the same concentration increase in NO(2), were significant higher than high temperature days ([Formula: see text] mean temperature). The modification effects of temperature on the study association were more pronounced in individuals aged 65 years or more and in males. The adverse health effects of NO(2) on ischemic stroke are more pronounced during winter or low temperature periods. Elderly adults or males presented higher risks with these exposures.
BACKGROUND: The relationship between air pollution and meteorological factors on diseases has become a research hotspot recently. Nevertheless, few studies have touched the inferences of nitrogen dioxide (NO(2)) and atmospheric pressure (AP) on hospitalization risk for chronic obstructive pulmonary disease (COPD). OBJECTIVES: To investigate the short-term impact of particulate air pollutants and meteorology factors on hospitalizations for COPD and quantify the corresponding risk burden of hospital admission. METHODS: In our study, COPD cases were collected from Guangzhou Panyu Central Hospital (n = 11,979) from Dec of 2013 to Jun 2019. The 24-h average temperature, relative humidity (RH), wind speed (V), AP and other meteorological data were obtained from Guangzhou Meteorological Bureau. Air pollution data were collected from Guangzhou Air Monitoring Station. The influence of different NO(2) and AP values on COPD risk was quantified by a distributed lag nonlinear model (DLNM) combined with Poisson Regression and Time Series analysis. RESULTS: We found that NO(2) had a non-linear relationship with the incidence of COPD, with an approximate “M” type, appearing at the peaks of 126 μg/m³ (RR = 1.32, 95%CI, 1.07 to 1.64) and 168 μg/m³ (RR = 1.21, 95%CI, 0.94 to 1.55), respectively. And the association between AP and COPD incidence exhibited an approximate J-shape with a peak occurring at 1035 hPa (RR = 1.16, 95% CI, 1.02 to 1.31). CONCLUSIONS: The nonlinear relationship of NO(2) and AP on COPD admission risk in different periods of lag can be used to establish an early warning system for diseases and reduce the possible outbreaks and burdens of COPD in a sensitive population.
There are increasing concerns with regard to spontaneous abortion (SAB), the loss of pregnancy without external intervention before 20 weeks of gestation, among reproductive-aged women. To date, limited evidence is available concerning the association between SAB and air pollutants, especially in developing countries. Daily baseline outpatient data for SAB from January 1, 2014, to December 31, 2018 (1826 days) were obtained in Chongqing, a metropolis of southwest China. The over-dispersed Poisson generalized additive model with control of meteorological conditions and day of week was used to estimate the short-term effects of ambient air pollution on the daily number of SAB outpatients. A total of 42,334 SAB outpatient visits for SAB were recorded. No statistically significant association was observed between SAB and CO, PM(2.5), PM(10), O(3), and SO(2). The positive association only appeared for NO(2): positive associations between SAB and NO(2) were observed in both single-day models (lag 0, lag 1, lag 3, and lag 4) and cumulative exposure models (lag 01, lag 03, and lag 05) and the most significant effects were observed at lag 05 (3.289%; 95% CI: 1.568%, 5.011%). Moreover, the women with higher ages (30-39 and > 39) were more sensitive than those with lower ages (18-29), and the effect estimates were more evident in cool seasons. Collectively, our results suggested that short-term NO(2) exposure was associated with higher risk of SAB, especially in elder women and cool seasons, which may contribute to further understand the role of air pollution on SAB and other adverse obstetric outcomes.
Energy is considered a vital factor of economic growth that contributes to improve quality of life and health status. However, global warming, climate change, and environmental degradation are due primarily because of energy emissions, whereas environmental degradation is detrimental to health. Since one-fifth of the population lives in South Asia, it is necessary to analyze the impact of energy and environmental degradation on health status in this region. For this purpose, health status in South Asia is proxy with health expenditure, life expectancy, and infant mortality, and this study investigates the effect of energy intensity, income, and carbon emissions on health status, whereas urbanization is considered a control variable. The cointegration test indicates South Asia’s long-term health status factors are energy intensity, income, carbon emissions, and urbanization. Long-run results suggest that energy intensity and income improve health status as these factors reduce health expenditure, improve life expectancy, and decrease infant mortality. Environmental degradation not only increases health expenditure but also hinders life expectancy and increases mortality. Moreover, an increase in income diminishes health expenditure and is responsible for high life expectancy and low mortality in South Asia.
International trade’s impact on the pollution reduction, especially varied reduction effects dealing with global or local pollutants has not been thoroughly researched empirically. We explored effects of international trade participation on both the carbon dioxide emission intensity and sulfur dioxide emission intensity with a panel data of 179 major countries during 20 years when globalization thrived. Carbon dioxide causing climate change is a global concern. While sulfur dioxide is one major air pollutant causing local health problems. Empirically, international trade participation mainly reduces carbon dioxide emission intensity but not sulfur dioxide emission intensity. Also, trade in goods form is more effective than in service form. However, international trade participation does little to improving a country’s overall technology level, implying that regulation enhancement under international norm is the main mechanism. Compared with developed countries, developing countries can reduce both kinds of pollutant emission intensities more effectively by participating into international trade. A case study of China’s entering into World Trade Organization (WTO)’s impact on pollutant reduction can provide more evidence. Also, developing countries with higher industrialization level experiences a bigger improvement in cleaner production. And developing countries with higher democratization level pay more attention to reduce local environmental concerns.
Polycyclic aromatic hydrocarbons (PAHs) are hazardous compounds associated with respiratory disease and lung cancer. Increasing fossil fuel consumption, which causes climate change, has accelerated the emissions of PAHs. However, potential risks by PAHs have not been predicted for Korea, and appropriate PAH regulations under climate change have yet to be developed. This study assesses the potential risks posed by PAHs using climate change scenarios based on deep learning, and a multimedia fugacity model was employed to describe the future fate of PAHs. The multimedia fugacity model describes the dynamics of sixteen PAHs by reflecting inter-regional meteorological transportation. A deep neural network predicts future environmental and economic conditions, and the potential risks posed by PAHs, in the year 2050, using a prediction model and climate change scenarios. The assessment indicates that cancer risks would increase by more than 50%, exceeding the lower risk threshold in the southern and western regions. A mix of strategies for developing PAH regulatory policies highlighted the necessity of increasing PAHs monitoring stations and controlling fossil fuel usage based on the domestic and global conditions under climate change scenarios.
Exposure to polycyclic aromatic hydrocarbons (PAHs) are a cause of chronic cough occurrence in adult patients. In order to clear the relationship between transboundary transport of PAH and health effects, this study investigates the relationship between atmospheric particulate PAHs (p-PAHs), cough occurrence by epidemiological research, and meteorological conditions using a chemical transport model. Source receptor relationship (SRR) analysis revealed that a higher cough occurrence was caused by exposure to high p-PAH levels in air masses transported from central China (CCHN, 30-40 degrees N) under westerly conditions. The p-PAHs transported from northern China (NCHN, >40 degrees N) and the eastern part of Russia (ERUS) under north-westerly conditions also contributed to cough occurrence. The low equivalent potential temperature (ePT) and geopotential height anomaly suggested that the p-PAHs emitted near the surface were suppressed to upward transport under the colder air mass but were instead transported horizontally near the surface in the boundary layer, resulting in high p-PAH concentrations arriving in Kanazawa. Our study’s findings suggest that the air mass transport pattern associated with meteorology strongly influences the high p-PAH concentrations causing adult chronic cough occurrence.
BACKGROUND: Climate change models predict that atmospheric carbon dioxide [CO2] levels will be between 700 and 900 ppm within the next 80 y. Despite this, the direct physiological effects of exposure to slightly elevated atmospheric CO2 (as compared with ∼ 410 ppm experienced today), especially when exposures extend from preconception to adulthood, have not been thoroughly studied. OBJECTIVES: In this study we aimed to assess the respiratory structure and function effects of long-term exposure to 890 ppm CO2 from preconception to adulthood using a mouse model. METHODS: We exposed mice to CO2 ( ∼ 890 ppm) from prepregnancy, through the in utero and early life periods, until 3 months of age, at which point we assessed respiratory function using the forced oscillation technique, and lung structure. RESULTS: CO2 exposure resulted in a range of respiratory impairments, particularly in female mice, including higher tissue elastance, longer chord length, and lower lung compliance. Importantly, we also assessed the lung function of the dams that gave birth to our experimental subjects. Even though these mice had been exposed to the same level of increased CO2 for a similar amount of time ( ∼ 8 wk), we measured no impairments in lung function. This suggests that the early life period, when lungs are undergoing rapid growth and development, is particularly sensitive to CO2. DISCUSSION: To the best of our knowledge, this study, for the first time, shows that long-term exposure to environmentally relevant levels of CO2 can impact respiratory function in the mouse. https://doi.org/10.1289/EHP7305.
Severe volatile organic compound (VOC) pollution has become an urgent problem during the heating season in the North China Plain (NCP), as exposure to hazardous VOCs can lead to chronic or acute diseases. A campaign with online VOC measurements was conducted at a rural site in Wangdu, NCP during the 2018 heating season to characterize the compositions and associated sources of VOCs and to assess their potential health risks. The total concentration of VOCs with 94 identified species was 77.21 +/- 54.39 ppb. Seven source factors were identified by non-negative matrix factorization, including coal combustion (36.1%), LPG usage (21.1%), solvent usage (13.9%), biomass burning and secondary formation (142%), background (7.0%), industrial emissions (4.5%), and vehicle emissions (3.3%). The point estimate approach and Monte Carlo simulation were used to estimate the carcinogenic and non-carcinogenic risks of harzadous VOCs. The results showed that the cumulative health risk of VOCs was above the safety level. Acrolein, 1.2-dichlorprothane, 12-dichloropropane, chloroform, 1,3-butadiene, and benzene were identified as the key hazardous VOCs in Wangdu. Benzene had the highest average carcinogenic risk. Solvent usage and secondary formation were the dominant sources of adverse health effects. During the Spring Festival, most sources were sharply reduced; and VOC concentration declined by 49%. However, coal and biomass consumptions remained relatively large, probably due to heating demand. This study provides important references for the control strategies of VOCs during the heating season in heavily polluted rural areas in the NCP. (C) 2021 Elsevier B.V. All rights reserved.
Los productos suministrados son: concentraciones en superficie con salidas gráficas horarias de las concentraciones en superficie de NO2, NO, O3, SO2, CO, PM10 y PM2.5 expresadas en µg/m3; índice previsto diario de calidad del aire
calculado a partir de valores de concentración, utilizando la información procedente de las directivas vigentes relacionadas con los distintos contaminantes atmosféricos, e Índice previsto horario de calidad del aire con un horizonte temporal de 48 horas
Izmerjeni podatki o kakovosti zraka in napovedi
South African Air Quality Information System (SAAQIS) is a web based interactive air quality information system which seeks to provide the state of air quality information to citizens, and it is a research portal for strengthening policy development related to air quality issues.
The growing concerns over urbanization and climate change have resulted in an exponential growth in publications on urban climatology in recent decades. However, an advanced synthesis that characterizes the existing studies is lacking. In this review, we used citation network analysis and a text mining approach to identify research trends and extract common research topics and the emerging domains in urban climatology. Based on the clustered networks, we found that aerosols and ozone, and urban heat island are the most popular topics. Together with other clusters, four emerging topical fields were identified: secondary organic aerosols, urban precipitation, flood risk and adaptation, and greenhouse gas emissions. The city case studies’ geographical information was analyzed to explore the spatial-temporal patterns, especially in the emerging topical fields. Interdisciplinary research grew in recent years as the field of urban climatology expanded to interact with urban hydrology, health, energy issues, and social sciences. A few knowledge gaps were proposed: the lack of long-term high-temporal-resolution observational data of organic aerosols for model validation and improvements, the need for predictions of urban effects on precipitation and extreme flooding events under climate change, and the lack of a framework for cooperation between physical sciences and social sciences under urban settings. To fill these gaps, we call for more observational data with high spatial and temporal resolution, using high-resolution models that adequately represent urban processes to conduct scenario analyses for urban planning, and the development of intellectual frameworks for better integration of urban climatology and social-economical systems in cities. This article is categorized under: Climate, History, Society, Culture > Disciplinary Perspectives
Speciated ground-level aerosol concentrations are required to understand and mitigate health impacts from dust storms, wildfires, and other aerosol emissions. Globally, surface monitoring is limited due to cost and infrastructure demands. While remote sensing can help estimate respirable (i.e. ground level) concentrations, current observations are restricted by inadequate spatiotemporal resolution, uncertainty in aerosol type, particle size, and vertical profile. One key issue with current remote sensing datasets is that they are derived from reflectances observed by polar-orbiting imagers, which means that aerosol is only derived during the daytime and only once or twice per day. Newer quantification methods using geostationary infrared (IR) data have focussed on detecting the presence, or absence, of an event. The determination of aerosol composition or particle size using IR exclusively has received little attention. This manuscript summarizes four scientific papers, published as part of a larger study, and identifies requirements for (a) using infrared radiance observations to obtain continual (i.e. day and night) concentration estimates; (b) increasing temporal resolution by using geostationary satellites; (c) utilizing all infrared channels to maximize spectral differences due to compositional changes; and (d) applying a high-pass filter (brightness temperature differences) to identify compositional variability. Additionally, (e) a preliminary calibration methodology was tested against three severe air quality case study incidents, namely, a dust storm, smoke from prescribed burns, and an ozone smog incident, near Sydney in eastern Australia which highlighted the ability of the method to determine atmospheric stability, clouds, and particle size. Geostationary remote sensing provides near-continuous data at a temporal resolution comparable to monitoring equipment. The spatial resolution (~?4 km(2) at NADIR) is adequate for large sources but coarse for localized sources. The spectral sensitivity of aerosol is limited and appears to be dominated by humidity changes rather than concentration or compositional changes. Geostationary remote sensing can be used to determine the timing, duration, and spatial extent of an air quality event. Brightness temperature differences can assist in qualifying composition with an order of magnitude estimate of concentration.
Pollens are a major cause of seasonal allergic diseases. Weather may alter the production of pollens. Increased atmospheric temperatures lead to earlier pollination of many plants and longer duration of pollination, resulting in extended pollen seasons, with early spring or late winter. Longer pollen seasons increase duration of exposure, resulting in more sensitization, and higher pollen concentrations may lead to more severe symptoms. Climate changes in contact to pollens may affect both allergic sensitization and symptom prevalence with severity. The future consequences of climate change, however, are speculative, because the influence on humans, is complex.
Purpose of reviewThe purpose of this chapter is to review allergic disease and how it is potentially impacted by climate change. It is difficult to measure the direct impact climate change has on allergic disease. This is difficult because there are many variables impacting human health as well as what capacity humans have to adapt to these changes. Asthma is tightly associated with allergies and environmental factors, especially in children. In this review, we will explore evidence of environmental changes associated with climate change and the potential impacts on allergy and associated respiratory disease. Furthermore, this paper is to review the impact of climate change on allergy to atmospheric fungi which are known to cause a common allergic response. In this review, we will explore evidence of environmental changes associated with climate change and the potential impacts on allergy.Recent findingsThe climate has been measurably changing for the past 100 years and has been described as the most significant health threat of the twenty-first century. How climate change impacts human health is varied and coming more into focus. While direct effects, such as heatwaves, severe weather, drought, and flooding, are well reported, effects that are indirect or secondary impacts involving changes in ecosystems are less obvious, though the body of data is growing and becoming more robust. It is these changes in ecosystems that may have the greatest impact on allergic and respiratory diseases. Otherwise, the airborne pollens and spores have also been linked with upper and lower respiratory conditions. Atmospheric pollen and spore concentrations are influenced by a wide array of environmental, meteorological, and biological factors and various interspecies interactions. Pollen and spores underlie seasonal variations. Especially climatic factors and circadian patterns influence the spectrum of their species and their concentrations in the environment. It may have the greatest impact on respiratory allergic diseases.SummaryThis review will explore some of the impacts our changing climate, current and predicted, has which influences upper and lower respiratory allergic diseases. The discussion will focus on changing pollination with altered pollen patterns, as well as alteration of the composition and transformation of atmospheric allergic fungi with increased CO2 air pollution and heat stress. The sporulation of fungi is likely to be amplified as CO2 concentration increases with climate change, potentially contributing to the increasing prevalence and severity of asthma and other respiratory allergies.
BACKGROUND: Climate change is broadly affecting human health, with grave concern that continued warming of the earth’s atmosphere will result is serious harm. Since the mid-20th century, skin cancer incidence rates have risen at an alarming rate worldwide. OBJECTIVE: This review examines the relationship between climate change and cutaneous carcinogenesis. METHODS: A literature review used the National Institutes of Health databases (PubMed and Medline), the Surveillance, Epidemiology, and End Results and International Agency for Research on Cancer registries, and published reports by federal and international agencies and consortia, including the Australian Institute of Health and Welfare, Climate and Clean Air Coalition, U.S. Environmental Protection Agency, Intergovernmental Panel on Climate Change, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, United Nations Environment Programme, World Health Organization, and World Meteorological Organization. RESULTS: Skin cancer risk is determined by multiple factors, with exposure to ultraviolet radiation being the most important. Strong circumstantial evidence supports the hypothesis that factors related to climate change, including stratospheric ozone depletion, global warming, and ambient air pollution, have likely contributed to the increasing incidence of cutaneous malignancy globally and will continue to impose a negative on influence skin cancer incidence for many decades to come. CONCLUSION: Because much of the data are based on animal studies and computer simulations, establishing a direct and definitive link remains challenging. More epidemiologic studies are needed to prove causality in skin cancer, but the evidence for overall harm to human health as a direct result of climate change is clear. Global action to mitigate these negative impacts to humans and the environment is imperative.
The coronavirus disease 2019 (COVID-19) pandemic caused a crisis worldwide, due to both its public health impact and socio-economic consequences. Mental health was consistently affected by the pandemic, with the emergence of newly diagnosed psychiatric disorders and the exacerbation of pre-existing ones. Urban areas were particularly affected by the virus spread. In this review, we analyze how the urban environment may influence mental health during the COVID-19 pandemic, considering two factors that profoundly characterize urbanization: air pollution and migration. Air pollution serves as a possibly risk factor for higher viral spread and infection severity in the context of urban areas and it has also been demonstrated to play a role in the development of serious mental illnesses and their relapses. The urban environment also represents a complex social context where minorities such as migrants may live in poor hygienic conditions and lack access to adequate mental health care. A global rethinking of the urban environment is thus required to reduce the impact of these factors on mental health. This should include actions aimed at reducing air pollution and combating climate change, promoting at the same time a more inclusive society in a sustainable development perspective.
Extreme weather and climate events are likely to increase in frequency and severity as a consequence of global climate change. These are events that can include flooding rains, prolonged heat waves, drought, wildfires, hurricanes, severe thunderstorms, tornadoes, storm surge, and coastal flooding. It is important to consider these events as they are not merely meteorologic occurrences but are linked to our health. We aim to address how these events are interconnected with asthma outcomes associated with thunderstorm asthma, pollen production, mold infestation from flooding events, and poor air quality during wildfires.
PURPOSE OF REVIEW: Atopic dermatitis (AD) is a chronic inflammatory skin disorder affecting up to 20% of children and up to 5% of adults worldwide, contributing to significant disease-related morbidity in this patient cohort. Its aetiopathogenesis is underpinned by multiple factors, including genetic susceptibility, skin barrier defects, a skewed cutaneous immune response and microbiome perturbation in both the skin and the gut. In this review, we aim to examine the biological effects of key environmental exposures (the sum of which is termed the “exposome”) at the population, community and individual levels in order to describe their effect on AD pathogenesis. RECENT FINDINGS: It is now understood that as well as considering the type of environmental exposure with regard to its effect on AD pathogenesis, the dosage and timing of the exposure are both critical domains that may lead to either exacerbation or amelioration of disease. In this review, we consider the effects of population-wide exposures such as climate change, migration and urbanization; community-specific exposures such as air pollution, water hardness and allergic sensitisation; and individual factors such as diet, microbiome alteration, psychosocial stress and the impact of topical and systemic therapy. SUMMARY: This review summarises the interaction of the above environmental factors with the other domains of AD pathogenesis, namely, the inherent genetic defects, the skin barrier, the immune system and the cutaneous and gut microbiota. We specifically emphasise the timing and dosage of exposures and its effect on the cellular and molecular pathways implicated in AD.
Recent pandemic outbreak of the corona-virus disease 2019 (COVID-19) has raised widespread concerns about the importance of the bioaerosols. They are atmospheric aerosol particles of biological origins, mainly including bacteria, fungi, viruses, pollen, and cell debris. Bioaerosols can exert a substantial impact on ecosystems, climate change, air quality, and public health. Here, we review several relevant topics on bioaerosols, including sampling and detection techniques, characterization, effects on health and air quality, and control methods. However, very few studies have focused on the source apportionment and transport of bioaerosols. The knowledge of the sources and transport pathways of bioaerosols is essential for a comprehensive understanding of the role microorganisms play in the atmosphere and control the spread of epidemic diseases associated with them. Therefore, this review comprehensively summarizes the up to date progress on the source characteristics, source identification, and diffusion and transport process of bioaerosols. We intercompare three types of diffusion and transport models, with a special emphasis on a widely used mathematical model. This review also highlights the main factors affecting the source emission and transport process, such as biogeographic regions, land-use types, and environmental factors. Finally, this review outlines future perspectives on bioaerosols.
BACKGROUND: In the rapidly shifting Canadian climate, an ageing population, and increased migration, a greater understanding of how local climate and air pollution hazards impact older adults and immigrant populations will be necessary for mitigating and adapting to adverse health impacts. OBJECTIVES: To explore the reported health impacts of climate change and air pollution exposures in older adults and immigrant people living in Canada, identify known factors influencing risk and resilience in these populations and gaps in the literature. METHODS: We searched for research focused on older adults and immigrants living in Canada, published from 2010 onward, where the primary exposures were related to climate or air pollution. We extracted data on setting, exposures, health outcomes, and other relevant contextual factors. RESULTS AND DISCUSSION: We identified 52 eligible studies, most focused in Ontario and Quebec. Older people in Canada experience health risks due to climate and air pollution exposures. The extent of the risk depends on multiple factors. We found little information about the climate- and air pollution-related health impacts experienced by immigrant communities. CONCLUSIONS: Further research about climate- and air pollution-related exposures, health, and which factors promote or reduce resiliency in Canada’s older adults and immigrant communities is necessary.
Heart failure is a major contributor to healthcare expenditures. Many clinical risk factors for the development and exacerbation of heart failure had been reported, including diabetes, renal dysfunction, and respiratory disease. In addition to these clinical parameters, the effects of social factors, such as occupation or lifestyle, and environmental factors may have a great impact on disease development and progression of heart failure. However, the current understanding of social and environmental factors as contributors to the clinical course of heart failure is insufficient. To present the knowledge of these factors to date, this comprehensive review of the literature sought to identify the major contributors to heart failure within this context. Social factors for the risk of heart failure included occupation and lifestyle, specifically in terms of the effects of specific occupations, occupational exposure to toxicities, work style, and sleep deprivation. Socioeconomic factors focused on income and education level, social status, the neighborhood environment, and marital status. Environmental factors included traffic and noise, air pollution, and other climate factors. In addition, psychological stress and behavior traits were investigated. The development of heart failure may be closely related to these factors; therefore, these data should be summarized for the context to improve their effects on patients with heart failure. The present study reviews the literature to summarize these influences.
Climate change is one of the biggest challenges humanity is facing in the 21st century. Two recognized sequelae of climate change are global warming and air pollution. The gradual increase in ambient temperature, coupled with elevated pollution levels have a devastating effect on our health, potentially contributing to the increased rate and severity of numerous neurological disorders. The main aim of this review paper is to shed some light on the association between the phenomena of global warming and air pollution, and two of the most common and debilitating neurological conditions: stroke and neurodegenerative disorders. Extreme ambient temperatures induce neurological impairment and increase stroke incidence and mortality. Global warming does not participate in the etiology of neurodegenerative disorders, but it exacerbates symptoms of dementia, Alzheimer’s disease (AD) and Parkinson’s Disease (PD). A very close link exists between accumulated levels of air pollutants (principally particulate matter), and the incidence of ischemic rather than hemorrhagic strokes. People exposed to air pollutants have a higher risk of developing dementia and AD, but not PD. Oxidative stress, changes in cardiovascular and cerebrovascular haemodynamics, excitotoxicity, microglial activation, and cellular apoptosis, all play a central role in the overlap of the effect of climate change on neurological disorders. The complex interactions between global warming and air pollution, and their intricate effect on the nervous system, imply that future policies aimed to mitigate climate change must address these two challenges in unison.
Numerous studies have linked outdoor levels of PM2.5, PM10, NO2, O-3, SO2, and other air pollutants to significantly higher rates of Covid 19 morbidity and mortality, although the rate in which specific concentrations of pollutants increase Covid 19 morbidity and mortality varies widely by specific country and study. As little as a 1-mu g/m(3) increase in outdoor PM2.5 is estimated to increase rates of Covid 19 by as much as 0.22 to 8%. Two California studies have strongly linked heavy wildfire burning periods with significantly higher outdoor levels of PM2.5 and CO as well as significantly higher rates of Covid 19 cases and deaths. Active smoking has also been strongly linked significantly increased risk of Covid 19 severity and death. Other exposures possibly related to greater risk of Covid 19 morbidity and mortality include incense, pesticides, heavy metals, dust/sand, toxic waste sites, and volcanic emissions. The exact mechanisms in which air pollutants increase Covid 19 infections are not fully understood, but are probably related to pollutant-related oxidation and inflammation of the lungs and other tissues and to the pollutant-driven alternation of the angiotensin-converting enzyme 2 in respiratory and other cells.
Male fertility and semen quality have declined over recent decades. Among other causes, exposure to environmental and occupational pollution has been linked to adverse reproductive outcomes, but effects on male semen quality are still uncertain. Therefore, the aim of the present study was to conduct a systematic review and meta-analysis to assess current evidence regarding the impact of exposure to tobacco smoke and environmental and occupational pollution on sperm quality in humans. In the meta-analysis, 22 studies are included showing that environmental and occupational pollutants may affect sperm count, volume, concentration, motility, vitality and sperm DNA, and chromatin integrity. All included articles reported significant alterations in at least one of the outcomes studied in association with at least one of the pollutants studied. Considering that sperm quality can be considered a proxy for general health and that pollutants have a dramatic impact on climate change, it would be strongly recommended to better understand the role of pollutants on human, animal, and planetary health.
Anthropogenic climate change is adversely impacting people and contributing to suffering and increased costs from climate-related diseases and injuries. In responding to this urgent and growing public health crisis, mitigation strategies are in place to reduce future greenhouse gas emissions (GHGE) while adaptation strategies exist to reduce and/or alleviate the adverse effects of climate change by increasing systems’ resilience to future impacts. While these strategies have numerous positive benefits on climate change itself, they also often have other positive externalities or health co-benefits. This knowledge can be harnessed to promote and improve global public health, particularly for the most vulnerable populations. Previous conceptual models in mitigation and adaptation studies such as the shared socioeconomic pathways (SSPs) considered health in the thinking, but health outcomes were not their primary intention. Additionally, existing guidance documents such as the World Health Organization (WHO) Guidance for Climate Resilient and Environmentally Sustainable Health Care Facilities is designed primarily for public health professionals or healthcare managers in hospital settings with a primary focus on resilience. However, a detailed cross sectoral and multidisciplinary conceptual framework, which links mitigation and adaptation strategies with health outcomes as a primary end point, has not yet been developed to guide research in this area. In this paper, we briefly summarize the burden of climate change on global public health, describe important mitigation and adaptation strategies, and present key health benefits by giving context specific examples from high, middle, and low-income settings. We then provide a conceptual framework to inform future global public health research and preparedness across sectors and disciplines and outline key stakeholders recommendations in promoting climate resilient systems and advancing health equity.
PURPOSE OF REVIEW: Climate change remains a major threat to the health and well-being of children globally. This article reviews the myriad health effects of climate change on children throughout their lives and discusses ways in which the general pediatrician can be an advocate for climate solutions. RECENT FINDINGS: Rising atmospheric temperatures, increased air pollution, and destabilized weather patterns all lead to adverse health outcomes for children and adverse obstetric outcomes. However, the impact of climate change is not evenly distributed. Children living in poverty are more likely to be adversely impacted by the changing climate. SUMMARY: Ongoing and emerging research suggests that children are particularly vulnerable to the effects of climate change. The primary care pediatrician is encouraged to see this irrefutable evidence as a call to action for advocacy on behalf of our patients and the planet.
Climatic change will have an impact on production and release of pollen, with consequences for the duration and magnitude of aeroallergen seasonal exposure and allergic diseases. Evaluations of pollen aerobiology in the southern hemisphere have been limited by resourcing and the density of monitoring sites. This review emphasizes inconsistencies in pollen monitoring methods and metrics used globally. Research should consider unique southern hemisphere biodiversity, climate, plant distributions, standardization of pollen aerobiology, automation, and environmental integration. For both hemispheres, there is a clear need for better understanding of likely influences of climate change and comprehending their impact on pollen-related health outcomes.
Air pollution disproportionately affects marginalized populations of lower socioeconomic status. There is little literature on how socioeconomic status affects the risk of exposure to air pollution and associated health outcomes, particularly for children’s health. The objective of this article was to review the existing literature on air pollution and children’s health and discern how socioeconomic status affects this association. The concept of environmental injustice recognizes how underserved communities often suffer from higher air pollution concentrations in addition to other underlying risk factors for impaired health. This exposure then exerts larger effects on their health than it does in the average population, affecting the whole body, including the lungs and the brain. Children, whose organs and mind are still developing and who do not have the means of protecting themselves or creating change, are the most vulnerable to the detrimental effects of air pollution and environmental injustice. The adverse health effects of air pollution and environmental injustice can harm children well into adulthood and may even have transgenerational effects. There is an urgent need for action in order to ensure the health and safety of future generations, as social disparities are continuously increasing, due to social discrimination and climate change.
Background: Environmental health is a growing area of knowledge, continually increasing and updating the body of evidence linking the environment to human health. Aim: This study summarizes the epidemiological evidence on environmental risk factors from meta-analyses through an umbrella review. Methods: An umbrella review was conducted on meta-analyses of cohort, case-control, case-crossover, and time-series studies that evaluated the associations between environmental risk factors and health outcomes defined as incidence, prevalence, and mortality. The specific search strategy was designed in PubMed using free text and Medical Subject Headings (MeSH) terms related to risk factors, environment, health outcomes, observational studies, and meta-analysis. The search was limited to English, Spanish, and French published articles and studies on humans. The search was conducted on September 20, 2020. Risk factors were defined as any attribute, characteristic, or exposure of an individual that increases the likelihood of developing a disease or death. The environment was defined as the external elements and conditions that surround, influence, and affect a human organism or population’s life and development. The environment definition included the physical environment such as nature, built environment, or pollution, but not the social environment. We excluded occupational exposures, microorganisms, water, sanitation and hygiene (WASH), behavioral risk factors, and no-natural disasters. Results: This umbrella review found 197 associations among 69 environmental exposures and 83 diseases and death causes reported in 103 publications. The environmental factors found in this review were air pollution, environmental tobacco smoke, heavy metals, chemicals, ambient temperature, noise, radiation, and urban residential surroundings. Among these, we identified 65 environmental exposures defined as risk factors and 4 environmental protective factors. In terms of study design, 57 included cohort and/or case-control studies, and 46 included time-series and/or case-crossover studies. In terms of the study population, 21 included children, and the rest included adult population and both sexes. In this review, the largest body of evidence was found in air pollution (91 associations among 14 air pollution definitions and 34 diseases and mortality diagnoses), followed by environmental tobacco smoke with 24 associations. Chemicals (including pesticides) were the third larger group of environmental exposures found among the meta-analyses included, with 19 associations. Conclusion: Environmental exposures are an important health determinant. This review provides an overview of an evolving research area and should be used as a complementary tool to understand the connections between the environment and human health. The evidence presented by this review should help to design public health interventions and the implementation of health in all policies approach aiming to improve populational health.
Climate change (CC) is the most challenging environmental health (EH) concern. Air pollution is closely linked to CC. However, many CC-health-related conditions (i.e., allergic diseases, asthma, hypertension, fluid and electrolyte disorders, child and adult obesity, type 2 diabetes, vector-borne diseases) are not usually counted, either because they do not cause death or require hospital admission/emergency triage. They are the vast majority of health care seeking generally treated by family doctors (FDs) and family pediatricians (FPs). FDs/FPs are often not aware of CC-health-impacts. Their potential role in tackling such a global challenge through their local influence on individual and collective attitudes and policies is not considered. Proper FD training could fill these gaps, raise awareness of their role, and implement EH FDs/FPs-based surveillance networks to collect, analyze, interpret, and report EH data to inform EH-related Policy. FDs and FPs, organized in sentinel physicians’ networks, could play a key role in advising policymakers at the local and regional level in designing interventions adapted to climate-related issues. Such experiences are rare worldwide and not well known. We will describe and discuss them in detail to share successful local examples.
Pollen, a major causal agent of respiratory allergy, is mainly affected by weather conditions. In Korea, pollen and weather data are collected by the national observation network. Forecast models and operational services are developed and provided based on the national pollen data base. Using the pollen risk forecast information will help patients with respiratory allergy to improve their lives. Changes in temperature and CO(2) concentration by climate change affect the growth of plants and their capacity of producing more allergenic pollens, which should be considered in making the future strategy on treating allergy patients.
BACKGROUND: Although the frequency and magnitude of climate change-related health hazards (CCRHHs) are likely to increase, the population vulnerabilities and corresponding health impacts are dependent on a community’s exposures, pre-existing sensitivities, and adaptive capacities in response to a hazard’s impact. To evaluate spatial variability in relative vulnerability, we: 1) identified climate change-related risk factors at the dissemination area level; 2) created actionable health vulnerability index scores to map community risks to extreme heat, flooding, wildfire smoke, and ground-level ozone; and 3) spatially evaluated vulnerability patterns and priority areas of action to address inequity. METHODS: A systematic literature review was conducted to identify the determinants of health hazards among populations impacted by CCRHHs. Identified determinants were then grouped into categories of exposure, sensitivity, and adaptive capacity and aligned with available data. Data were aggregated to 4188 Census dissemination areas within two health authorities in British Columbia, Canada. A two-step principal component analysis (PCA) was then used to select and weight variables for each relative vulnerability score. In addition to an overall vulnerability score, exposure, adaptive capacity, and sensitivity sub-scores were computed for each hazard. Scores were then categorised into quintiles and mapped. RESULTS: Two hundred eighty-one epidemiological papers met the study criteria and were used to identify 36 determinant indicators that were operationalized across all hazards. For each hazard, 3 to 5 principal components explaining 72 to 94% of the total variance were retained. Sensitivity was weighted much higher for extreme heat, wildfire smoke and ground-level ozone, and adaptive capacity was highly weighted for flooding vulnerability. There was overall varied contribution of adaptive capacity (16-49%) across all hazards. Distinct spatial patterns were observed – for example, although patterns varied by hazard, vulnerability was generally higher in more deprived and more outlying neighbourhoods of the study region. CONCLUSIONS: The creation of hazard and category-specific vulnerability indices (exposure, adaptive capacity and sensitivity sub-scores) supports evidence-based approaches to prioritize public health responses to climate-related hazards and to reduce inequity by assessing relative differences in vulnerability along with absolute impacts. Future studies can build upon this methodology to further understand the spatial variation in vulnerability and to identify and prioritise actionable areas for adaptation.
The Fourth National Climate Assessment (NCA4) is the most comprehensive report to date assessing climate change science, impacts, risks, and adaptation in the United States. The 1,500 page report covers a breadth of topics, ranging from foundational physical science to climate change response options. Here we present information on indicators and impacts of climate change in the human environment featured in NCA4 Volume II, focusing on: air quality, forest disturbance and wildfire, energy systems, and water resources. Observations, trends, and impacts of these aspects of our changing climate will be discussed, along with implications for the future. Implications: People of the United States are already being affected by our changing climate. Information on observed changes and impacts that affect human welfare and society, along with projections for the future, is highly valuable for informing decision-makers, including utility managers, emergency planners, and other stakeholders, about climate risk assessment, adaptation, and mitigation options.
Converging data would indicate the existence of possible relationships between climate change, environmental pollution and epidemics/pandemics, such as the current one due to SARS-CoV-2 virus. Each of these phenomena has been supposed to provoke detrimental effects on mental health. Therefore, the purpose of this paper was to review the available scientific literature on these variables in order to suggest and comment on their eventual synergistic effects on mental health. The available literature report that climate change, air pollution and COVID-19 pandemic might influence mental health, with disturbances ranging from mild negative emotional responses to full-blown psychiatric conditions, specifically, anxiety and depression, stress/trauma-related disorders, and substance abuse. The most vulnerable groups include elderly, children, women, people with pre-existing health problems especially mental illnesses, subjects taking some types of medication including psychotropic drugs, individuals with low socio-economic status, and immigrants. It is evident that COVID-19 pandemic uncovers all the fragility and weakness of our ecosystem, and inability to protect ourselves from pollutants. Again, it underlines our faults and neglect towards disasters deriving from climate change or pollution, or the consequences of human activities irrespective of natural habitats and constantly increasing the probability of spillover of viruses from animals to humans. In conclusion, the psychological/psychiatric consequences of COVID-19 pandemic, that currently seem unavoidable, represent a sharp cue of our misconception and indifference towards the links between our behaviour and their influence on the “health” of our planet and of ourselves. It is time to move towards a deeper understanding of these relationships, not only for our survival, but for the maintenance of that balance among man, animals and environment at the basis of life in earth, otherwise there will be no future.
BACKGROUND: Climate change impacts are associated with dramatic consequences for human health and threaten physical activity (PA) behaviors. OBJECTIVE: The aims of this systematic review were to present the potential bidirectional associations between climate change impacts and PA behaviors in humans and to propose a synthesis of the literature through a conceptual model of climate change and PA. METHODS: Studies published before October 2020 were identified through database searches in PubMed, PsycARTICLES, CINAHL, SPORTDiscus, GreenFILE, GeoRef, Scopus, JSTOR and Transportation Research Information Services. Studies examining the associations between PA domains and climate change (e.g., natural disasters, air pollution, and carbon footprint) were included. RESULTS: A narrative synthesis was performed and the 74 identified articles were classified into 6 topics: air pollution and PA, extreme weather conditions and PA, greenhouse gas emissions and PA, carbon footprint among sport participants, natural disasters and PA and the future of PA and sport practices in a changing world. Then, a conceptual model was proposed to identify the multidimensional associations between climate change and PA as well as sport practices. Results indicated a consistent negative effect of air pollution, extreme temperatures and natural disasters on PA levels. This PA reduction is more severe in adults with chronic diseases, higher body mass index and the elderly. Sport and PA communities can play an important mitigating role in post-natural disaster contexts. However, transport related to sport practices is also a source of greenhouse gas emissions. CONCLUSION: Climate change impacts affect PA at a worldwide scale. PA is observed to play both a mitigation and an amplification role in climate changes. TRIAL REGISTRATION NUMBER: PROSPERO CRD42019128314.
Climate change is one of the major global health threats to the world’s population. It is brought on by global warming due in large part to increasing levels of greenhouse gases resulting from human activity, including burning fossil fuels (carbon dioxide), animal husbandry (methane from manure), industry emissions (ozone, nitrogen oxides, sulfur dioxide), vehicle/factory exhaust, and chlorofluorocarbon aerosols that trap extra heat in the earth’s atmosphere. Resulting extremes of weather give rise to wildfires, air pollution, changes in ecology, and floods. These in turn result in displacement of populations, family disruption, violence, and major impacts on water quality and availability, food security, public health and economic infrastructures, and limited abilities for civil society to maintain citizen safety. Climate change also has direct impacts on human health and well-being. Particularly vulnerable populations are affected, including women, pregnant women, children, the disabled, and the elderly, who comprise the majority of the poor globally. Additionally, the effects of climate change disproportionally affect disadvantaged communities, including low income and communities of color, and lower-income countries that are at highest risk of adverse impacts when disasters occur due to inequitable distribution of resources and their socioeconomic status. The climate crisis is tilting the risk balance unfavorably for women’s sexual and reproductive health and rights as well as newborn and child health. Obstetrician/gynecologists have the unique opportunity to raise awareness, educate, and advocate for mitigation strategies to reverse climate change affecting our patients and their families. This article puts climate change in the context of women’s reproductive health as a public health issue, a social justice issue, a human rights issue, an economic issue, a political issue, and a gender issue that needs our attention now for the health and well-being of this and future generations. FIGO joins a broad coalition of international researchers and the medical community in stating that the current climate crisis presents an imminent health risk to pregnant people, developing fetuses, and reproductive health, and recognizing that we need society-wide solutions, government policies, and global cooperation to address and reduce contributors, including fossil fuel production, to climate change.
Several climate change-related predictions and observations have been documented for the Australian continent. Extreme weather events such as cycles of severe drought and damaging flooding are occurring with greater frequency and have a severe impact on human health. Two specific aspects of climate change affecting allergic and other respiratory disorders are outlined: firstly, the consequences of extreme weather events and secondly, the change in distribution of airborne allergens that results from various climate change factors.
Climate and weather directly impact plant phenology, affecting airborne pollen. The objective of this systematic review is to examine the impacts of meteorological variables on airborne pollen concentrations and pollen season timing. Using PRISMA methodology, we reviewed literature that assessed whether there was a relationship between local temperature and precipitation and measured airborne pollen. The search strategy included terms related to pollen, trends or measurements, and season timing. For inclusion, studies must have conducted a correlation analysis of at least 5 years of airborne pollen data to local meteorological data and report quantitative results. Data from peer-reviewed articles were extracted on the correlations between seven pollen indicators (main pollen season start date, end date, peak date, and length, annual pollen integral, average daily pollen concentration, and peak pollen concentration), and two meteorological variables (temperature and precipitation). Ninety-three articles were included in the analysis out of 9,679 articles screened. Overall, warmer temperatures correlated with earlier and longer pollen seasons and higher pollen concentrations. Precipitation had varying effects on pollen concentration and pollen season timing indicators. Increased precipitation may have a short-term effect causing low pollen concentrations potentially due to “wash out” effect. Long-term effects of precipitation varied for trees and weeds and had a positive correlation with grass pollen levels. With increases in temperature due to climate change, pollen seasons for some taxa in some regions may start earlier, last longer, and be more intense, which may be associated with adverse health impacts, as pollen exposure has well-known health effects in sensitized individuals.
This paper highlights the important leadership role of the public health sector, working with other governmental sectors and nongovernmental entities, to advance environmental public health in Latin America and the Caribbean toward the achievement of 2030 Sustainable Development Goal 3: Health and Well-Being. The most pressing current and future environmental public health threats are discussed, followed by a brief review of major historical and current international and regional efforts to address these concerns. The paper concludes with a discussion of three major components of a regional environmental public health agenda that responsible parties can undertake to make significant progress toward ensuring the health and well-being of all people throughout Latin America and the Caribbean.
Allergic diseases are caused by the immune system’s response to innocent antigens called allergens. Recent decades have seen a significant increase in the prevalence of allergic diseases worldwide, which has imposed various socio-economic effects in different countries. Various factors, including genetic factors, industrialization, improved hygiene, and climate change contribute to the development of allergic diseases in many parts of the world. Moreover, changes in lifestyle and diet habits play pivotal roles in the prevalence of allergic diseases. Dietary changes caused by decreased intake of antioxidants such as vitamin E lead to the generation of oxidative stress, which is central to the development of allergic diseases. It has been reported in many articles that oxidative stress diverts immune responses to the cells associated with the pathogenesis of allergic diseases. The aim of this short review was to summarize current knowledge about the anti-allergic properties of vitamin E.
Corona virus is highly uncertain and complex in space and time. Atmospheric parameters such as type of pollutants and local weather play an important role in COVID-19 cases and mortality. Many studies were carried out to understand the impact of weather on spread and severity of COVID-19 and vice-versa. A review study is conducted to understand the impact of weather and atmospheric pollution on morbidity and mortality. Studies show that aerosols containing corona virus generated by sneezes and coughs are major route for spread of virus. Viability and virulence of SARS-CoV-2 stuck on the surface of particulate matter is not yet confirmed. Studies found that an increase in particulate matter concentration causes more COVID-19 cases and mortality. Gaseous pollutant and COVID-19 cases are positively correlated. Local meteorology plays crucial role in the spread of corona virus and thus mortality. Decline in number of cases with rising temperature observed. Few studies also find that lowest and highest temperatures were related to lesser number of cases. Similarly humidity shows negative or no relationship with COVID-19 cases. Rainfall was not related whilst wind-speed plays positive role in spread of COVID-19. Solar radiation threats survival of virus, areas with lower solar radiation showed high exposure rate. Air quality tremendously improved during lockdown. A significant reduction in PM10, PM2.5, BC, NOx, SO(2), CO and VOCs concentration were observed. Lockdown had a healing effect on ozone; significant increase in its concentration was observed. Aerosols Optical Depths were found to decrease up to 50%.
INTRODUCTION: Exacerbations of chronic obstructive pulmonary disease (COPD) are associated with a significant health burden both for patients and healthcare systems. Exposure to various environmental factors increases the risk of exacerbations. AREAS COVERED: We searched PubMed and assessed literature published within the last 10 years to include epidemiological evidence on the relationships between air pollution, temperature and COPD exacerbation risk as well as the implications of extreme weather events on exacerbations. EXPERT OPINION: Ongoing climate change is expected to increase air pollution levels, global temperature and the frequency and severity of extreme weather events, all of which are associated with COPD exacerbations. Further research is needed using patient-focused methodological approaches to better understand and quantify these relationships, so that effective mitigation strategies that decrease the risk of exacerbations can be developed.
Climate change is a crisis of vast proportions that has serious implications for pulmonary health. Increasing global temperatures influence respiratory health through extreme weather events, wildfires, prolonged allergy seasons, and worsening air pollution. Children, elderly patients, and patients with underlying lung disease are at elevated risk of complications from these effects of climate change. This paper summarizes the myriad ways in which climate change affects the respiratory health of patients at home and in outdoor environments and outlines measures for patients to protect themselves.
Background Air-pollution and weather exposure beyond certain thresholds have serious effects on public health. Yet, there is lack of information on wider aspects including the role of some effect modifiers and the interaction between air-pollution and weather. This article aims at a comprehensive review and narrative summary of literature on the association of air-pollution and weather with mortality and hospital admissions; and to highlight literature gaps that require further research. Methods We conducted a scoping literature review. The search on two databases (PubMed and Web-of-Science) from 2012 to 2020 using three conceptual categories of “environmental factors”, “health outcomes”, and “Geographical region” revealed a total of 951 records. The narrative synthesis included all original studies with time-series, cohort, or case cross-over design; with ambient air-pollution and/or weather exposure; and mortality and/or hospital admission outcomes. Results The final review included 112 articles from which 70 involved mortality, 30 hospital admission, and 12 studies included both outcomes. Air-pollution was shown to act consistently as risk factor for all-causes, cardiovascular, respiratory, cerebrovascular and cancer mortality and hospital admissions. Hot and cold temperature was a risk factor for wide range of cardiovascular, respiratory, and psychiatric illness; yet, in few studies, the increase in temperature reduced the risk of hospital admissions for pulmonary embolism, angina pectoris, chest, and ischemic heart diseases. The role of effect modification in the included studies was investigated in terms of gender, age, and season but not in terms of ethnicity. Conclusion Air-pollution and weather exposure beyond certain thresholds affect human health negatively. Effect modification of important socio-demographics such as ethnicity and the interaction between air-pollution and weather is often missed in the literature. Our findings highlight the need of further research in the area of health behaviour and mortality in relation to air-pollution and weather, to guide effective environmental health precautionary measures planning.
The impact of climate change on the environment, biosphere, and biodiversity has become more evident in the recent years. Human activities have increased atmospheric concentrations of carbon dioxide (CO(2) ) and other greenhouse gases. Change in climate and the correlated global warming affects the quantity, intensity, and frequency of precipitation type as well as the frequency of extreme events such as heat waves, droughts, thunderstorms, floods, and hurricanes. Respiratory health can be particularly affected by climate change, which contributes to the development of allergic respiratory diseases and asthma. Pollen and mold allergens are able to trigger the release of pro-inflammatory and immunomodulatory mediators that accelerate the onset the IgE-mediated sensitization and of allergy. Allergy to pollen and pollen season at its beginning, in duration and intensity are altered by climate change. Studies showed that plants exhibit enhanced photosynthesis and reproductive effects and produce more pollen as a response to high atmospheric levels of carbon dioxide (CO(2) ). Mold proliferation is increased by floods and rainy storms are responsible for severe asthma. Pollen and mold allergy is generally used to evaluate the interrelation between air pollution and allergic respiratory diseases, such as rhinitis and asthma. Thunderstorms during pollen seasons can cause exacerbation of respiratory allergy and asthma in patients with hay fever. A similar phenomenon is observed for molds. Measures to reduce greenhouse gas emissions can have positive health benefits.
Air pollution and climate change have a significant impact on human health and well-being and contribute to the onset and aggravation of allergic rhinitis and asthma among other chronic respiratory diseases. In Westernized countries, households have experienced a process of increasing insulation and individuals tend to spend most of their time indoors. These sequelae implicate a high exposure to indoor allergens (house dust mites, pets, molds, etc), tobacco smoke, and other pollutants, which have an impact on respiratory health. Outdoor air pollution derived from traffic and other human activities not only has a direct negative effect on human health but also enhances the allergenicity of some plants and contributes to global warming. Climate change modifies the availability and distribution of plant- and fungal-derived allergens and increases the frequency of extreme climate events. This review summarizes the effects of indoor air pollution, outdoor air pollution, and subsequent climate change on asthma and allergic rhinitis in children and adults and addresses the policy adjustments and lifestyle changes required to mitigate their deleterious effects.
BACKGROUND: Exposure to heat, air pollution, and pollen are associated with health outcomes, including cardiovascular and respiratory disease. Studies assessing the health impacts of climate change have considered increased exposure to these risk factors separately, though they may be increasing simultaneously for some populations and may act synergistically on health. Our objective is to systematically review epidemiological evidence for interactive effects of multiple exposures to heat, air pollution, and pollen on human health. METHODS: We systematically searched electronic literature databases (last search, April 29, 2019) for studies reporting quantitative measurements of associations between at least two of the exposures and mortality from any cause and cardiovascular and respiratory morbidity and mortality specifically. Following the Navigation Guide systematic review methodology, we evaluated the risk of bias of individual studies and the overall quality and strength of evidence. RESULTS: We found 56 studies that met the inclusion criteria. Of these, six measured air pollution, heat, and pollen; 39 measured air pollution and heat; 10 measured air pollution and pollen; and one measured heat and pollen. Nearly all studies were at risk of bias from exposure assessment error. However, consistent exposure-response across studies led us to conclude that there is overall moderate quality and sufficient evidence for synergistic effects of heat and air pollution. We concluded that there is overall low quality and limited evidence for synergistic effects from simultaneous exposure to (1) air pollution, pollen, and heat; and (2) air pollution and pollen. With only one study, we were unable to assess the evidence for synergistic effects of heat and pollen. CONCLUSIONS: If synergistic effects between heat and air pollution are confirmed with additional research, the health impacts from climate change-driven increases in air pollution and heat exposure may be larger than previously estimated in studies that consider these risk factors individually.
Since the publication of the last American Heart Association scientific statement on air pollution and cardiovascular disease in 2010, unequivocal evidence of the causal role of fine particulate matter air pollution (PM2.5, or particulate matter <= 2.5 mu m in diameter) in cardiovascular disease has emerged. There is a compelling case to provide the public with practical personalized approaches to reduce the health effects of PM2.5. Such interventions would be applicable not only to individuals in heavily polluted countries, high-risk or susceptible individuals living in cleaner environments, and microenvironments with higher pollution exposures, but also to those traveling to locations with high levels of PM2.5. The overarching motivation for this document is to summarize the current evidence supporting personal-level strategies to prevent the adverse cardiovascular effects of PM2.5, guide the use of the most proven/viable approaches, obviate the use of ineffective measures, and avoid unwarranted interventions. The significance of this statement relates not only to the global importance of PM2.5, but also to its focus on the most tested interventions and viable approaches directed at particulate matter air pollution. The writing group sought to provide expert consensus opinions on personal-level measures recognizing the current uncertainty and limited evidence base for many interventions. In doing so, the writing group acknowledges that its intent is to assist other agencies charged with protecting public health, without minimizing the personal choice considerations of an individual who may decide to use these interventions in the face of ongoing air pollution exposure.
PURPOSE OF REVIEW: Climate change will affect mortality associated with both ambient temperature and air pollution. Because older adults have elevated vulnerability to both non-optimal ambient temperature (heat and cold) and air pollution, population aging can amplify future population vulnerability to these stressors through increasing the number of vulnerable older adults. We aimed to review recent evidence on projections of temperature- or air pollution-related mortality burden (i.e., number of deaths) under combined climate change and population aging scenarios, with a focus on evaluating the role of population aging in assessing these health impacts of climate change. We included studies published between 2014 and 2019 with age-specific population projections. RECENT FINDINGS: We reviewed 16 temperature projection studies and 15 air pollution projection studies. Nine of the temperature studies and four of the air pollution studies took population aging into account by performing age-stratified analyses that utilized age-specific relationships between temperature or air pollution exposures and mortality (i.e., age-specific exposure-response functions (ERFs)). Population aging amplifies the projected mortality burden of temperature and air pollution under a warming climate. Compared with a constant population scenario, population aging scenarios lead to less reduction or even increases in cold-related mortality burden, resulting in substantial net increases in future overall (heat and cold) temperature-related mortality burden. There is strong evidence suggesting that to accurately assess the future temperature- and air pollution-related mortality burden of climate change, investigators need to account for the amplifying effect of population aging. Thus, all future studies should incorporate age-specific population size projections and age-specific ERFs into their analyses. These studies would benefit from refinement of age-specific ERF estimates.
The world is currently shadowed by the pandemic of COVID-19. Confirmed cases and the death toll has reached more than 12 million and more than 550,000 respectively as of 10 July 2020. In the unsettling pandemic of COVID-19, the whole Earth has been on an unprecedented lockdown. Social distancing among people, interrupted international and domestic air traffic and suspended industrial productions and economic activities have various far-reaching and undetermined implications on air quality and the climate system. Improvement in air quality has been reported in many cities during lockdown, while the death rate of COVID-19 has been found to be higher in more polluted cities. The relationship between the spread of the SARS-CoV-2 virus and air quality is under investigation. In addition, the battle against COVID-19 could bring short-lived and long-lasting and positive and negative impacts to the warming climate. The impacts on the climate system and the role of the climate in modulating the COVID-19 pandemic are the foci of scientific inquiry. The intertwined relationship among environment, climate change and public health is exemplified in the pandemic of COVID-19. Further investigation of the relationship is imperative in the Anthropocene, in particular, in enhancing disaster preparedness. This short article intends to give an up-to-date glimpse of the pandemic from air quality and climate perspectives and calls for a follow-up discussion.
Research on air quality and human health “co-benefits” from climate mitigation strategies represents a growing area of policy-relevant scholarship. Compared to other aspects of climate and energy policy evaluation, however, there are still relatively few of these co-benefits analyses. This sparsity reflects a historical disconnect between research quantifying energy and climate, and research dealing with air quality and health. The air quality co-benefits of climate, clean energy, and transportation electrification policies are typically assessed with models spanning social, physical, chemical, and biological systems. This review article summarizes studies to date and presents methods used for these interdisciplinary analyses. Studies in the peer-reviewed literature (n = 26) have evaluated carbon pricing, renewable portfolio standards, energy efficiency, renewable energy deployment, and clean transportation. A number of major findings have emerged from these studies: [1] decarbonization strategies can reduce air pollution disproportionally on the most polluted days; [2] renewable energy deployment and climate policies offer the highest health and economic benefits in regions with greater reliance on coal generation; [3] monetized air quality health co-benefits can offset costs of climate policy implementation; [4] monetized co-benefits typically exceed the levelized cost of electricity (LCOE) of renewable energies; [5] Electric vehicle (EV) adoption generally improves air quality on peak pollution days, but can result in ozone dis-benefits in urban centers due to the titration of ozone with nitrogen oxides. Drawing from these published studies, we review the state of knowledge on climate co-benefits to air quality and health, identifying opportunities for policy action and further research.
India is urbanizing at an alarming rate and the impact of climate change is becoming more visible each passing day. The rapid urbanization and climate change have severe direct and indirect consequences, such as increasing poverty, inequality, massive displacement, public health concerns, and challenges of urban governance, among others. This paper identifies some of the most pressing issues faced by urban India in the context of climate change. It also details the interventions undertaken at the local, national, and international levels to counter the effect of the climate change. In addition, it critically evaluates the role of government organizations, especially in terms of undertaking regulatory and planning functions. The paper argues that the implementation of institutional reforms would enable the government to reach out to the private sector to improve urban service delivery. It also provides examples of best practices from India and the world in combating climate change through adaptation and mitigation approaches.
Allergic rhinitis affects the quality of life of millions of people worldwide. Air pollution not only causes morbidity, but nearly 3 million people per year die from unhealthy indoor air exposure. Furthermore, allergic rhinitis and air pollution interact. This report summarizes the discussion of an International Expert Consensus on the management of allergic rhinitis aggravated by air pollution. The report begins with a review of indoor and outdoor air pollutants followed by epidemiologic evidence showing the impact of air pollution and climate change on the upper airway and allergic rhinitis. Mechanisms, particularly oxidative stress, potentially explaining the interactions between air pollution and allergic rhinitis are discussed. Treatment for the management of allergic rhinitis aggravated by air pollution primarily involves treating allergic rhinitis by guidelines and reducing exposure to pollutants. Fexofenadine a non-sedating oral antihistamine improves AR symptoms aggravated by air pollution. However, more efficacy studies on other pharmacological therapy of coexisting AR and air pollution are currently lacking.
Mesquite (Prosopis juliflora (Sw.) DC), is an medium-sized tree (family Fabaceae, subfamily Mimosoideae), that has been intorcuded around the world. It is a noxious invasive species in Africa, Asia, and the Arabian Peninsula and a source of highly allergenic pollen in. The present article reviews the adverse allergenic effects of P. juliflora pollen on human and animal health. Several studies have diagnosed that allergenic pollens from Prosopis spp. can provoke respiratory problems. Prosopis pollen extracts have 16 allergenic components of which nine proteins were recognized as major allergens with some of them showing cross-reactivity. Clinically, understanding Prosopis pollen production, flowering seasonality, pollen load, and dispersal in the atmosphere are important to avoid allergic consequences for local inhabitants. Climate change and other pollution can also help to further facilitate allergenic issues. Furthermore, we document other human and animal health problems caused by invasive Prosopis trees. This includes flesh injuries, dental and gastric problems, and the facilitation of malaria. This review summarizes and enhances the existing knowledge about Prosopis flowering phenology, aeroallergen, and other human and animal health risks associated with this noxious plant.
Future air quality will be driven by changes in air pollutant emissions, but also changes in climate. Here, we review the recent literature on future air quality scenarios and projected changes in effects on human health, crops and ecosystems. While there is overlap in the scenarios and models used for future projections of air quality and climate effects on human health and crops, similar efforts have not been widely conducted for ecosystems. Few studies have conducted joint assessments across more than one sector. Improvements in future air quality effects on human health are seen in emission reduction scenarios that are more ambitious than current legislation. Larger impacts result from changing particulate matter (PM) abundances than ozone burdens. Future global health burdens are dominated by changes in the Asian region. Expected future reductions in ozone outside of Asia will allow for increased crop production. Reductions in PM, although associated with much higher uncertainty, could offset some of this benefit. The responses of ecosystems to air pollution and climate change are long-term, complex, and interactive, and vary widely across biomes and over space and time. Air quality and climate policy should be linked or at least considered holistically, and managed as a multi-media problem. This article is part of a discussion meeting issue ‘Air quality, past present and future’.
Air pollution has broad effects on human health involving many organ systems. The ocular surface is an excellent model with which to study the effects of air pollution on human health as it is in constant contact with the environment, and it is directly accessible, facilitating disease monitoring. Effects of air pollutants on the ocular surface typically manifest as dry eye (DE) symptoms and signs. In this review, we break down air pollution into particulate matter (organic and inorganic) and gaseous compounds and summarize the literature regarding effects of various exposures on DE. Additionally, we examine the effects of weather (relative humidity, temperature) on DE symptoms and signs. To do so, we conducted a PubMed search using key terms to summarize the existing literature on the effects of air pollution and weather on DE. While we tried to focus on the effect of specific exposures on specific aspects of DE, environmental conditions are often studied concomitantly, and thus, there are unavoidable interactions between our variables of interest. Overall, we found that air pollution and weather conditions have differential adverse effects on DE symptoms and signs. We discuss these findings and potential mitigation strategies, such as air purifiers, air humidifiers, and plants, that may be instituted as treatments at an individual level to address environmental contributors to DE.
The recognition and documentation of climatic change effects on human health remains one of the most important challenges of the 21st century. While myriad in scope, one of the most recognised impacts is related to pollen, specifically its production, release and duration, and the consequences for allergic diseases, including asthma and allergic rhinitis. At present, the bulk of efforts to understand and document these links have been conducted by scientists in the Northern Hemisphere. However, the link between climate change and aeroallergenic pollen is global and international in scope. For this reason, more recent efforts to provide similar evaluations have been initiated by scientists in the Southern Hemisphere. The current review acknowledges northern enquiries, but also emphasises research gaps and inconsistencies which should be avoided by southern investigators. To remedy these deficiencies, some suggestions are offered, including a greater emphasis on plant demographics, the standardisation of pollen metrics, automation and environmental integration. It is hoped that this perspective will be able to provide support to efforts of scientists in the Southern Hemisphere to evaluate better climate shifts and aeroallergen consequences. Overall, there is a clear and pressing need to understand these likely changes while simultaneously comprehending their impact on pollen-related health outcomes – for both hemispheres.
Urban vegetation provides undeniable benefits to urban climate, health, thermal comfort and environmental quality of cities and represents one of the most considered urban heat mitigation measures. Despite the plethora of available scientific information, very little is known about the holistic and global impact of a potential increase of urban green infrastructure (GI) on urban climate, environmental quality and health, and their synergies and trade-offs. There is a need to evaluate globally the extent to which additional GI provides benefits and quantify the problems arising from the deployment of additional greenery in cities which are usually overlooked or neglected. The present paper has reviewed and analysed 55 fully evaluated scenarios and case studies investigating the impact of additional GI on urban temperature, air pollution and health for 39 cities. Statistically significant correlations between the percentage increase of the urban GI and the peak daily and night ambient temperatures are obtained. The average maximum peak daily and night-time temperature drop may not exceed 1.8 and 2.3 degrees C respectively, even for a maximum GI fraction. In parallel, a statistically significant correlation between the peak daily temperature decrease caused by higher GI fractions and heat-related mortality is found. When the peak daily temperature drops by 0.1 degrees C, then the percentage of heat-related mortality decreases on average by 3.0% The impact of additional urban GI on the concentration of urban pollutants is analysed, and the main parameters contributing to decrease or increase of the pollutants’ concentration are presented.
Children’s bodies are in dynamic stages of development that make them more susceptible to harm from exposure to environmental agents. Children’s physical, physiological and behavioral traits can lead to increased exposure to toxic chemicals or pathogens. In addition, the social determinants of health interact with this exposure and create an increasing risk for further disparities among children. In Indonesia, the fourth most populated country in the world, children are under threat of exposure to contaminated water, air, food and soil, which can cause gastrointestinal and respiratory diseases, birth defects and neurodevelopmental disorders. A safe and balanced nutrition is still an unmet need for too many children. At the same time, the prevalence of obesity and the risk of later development of metabolic diseases, including diabetes and cardiovascular diseases, are increasing as a consequence of both unhealthy diets and inadequate physical activity. The risks of potential long-term toxicity, including carcinogenic, neurotoxic, immunotoxic, genotoxic, endocrine-disrupting and allergenic effects of many chemicals, are also close to their lives. This paper provides an overview of common disease risks in Indonesian children, including: acute hepatitis A, diarrheal diseases, dengue and malaria due to lack of water supply and sanitation, vectors, and parasites; asthma, bronchopneumonia, chronic obstructive pulmonary disease (COPD) and acute respiratory infections (ARIs) due to air pollution and climate change; some chronic diseases caused by toxic and hazardous waste; and direct or indirect consequences due to the occurrence of disasters and health emergencies.
Since air pollutants are difficult and expensive to control, a strong scientific underpinning to policies is needed to guide mitigation aimed at reducing the current burden on public health. Much of the evidence concerning hazard identification and risk quantification related to air pollution comes from epidemiological studies. This must be reinforced with mechanistic confirmation to infer causality. In this review we focus on data generated from four contrasting sources of particulate air pollution that result in high population exposures and thus where there remains an unmet need to protect health: urban air pollution in developing megacities, household biomass combustion, wildfires and desert dust storms. Taking each in turn, appropriate measures to protect populations will involve advocating smart cities and addressing economic and behavioural barriers to sustained adoption of clean stoves and fuels. Like all natural hazards, wildfires and dust storms are a feature of the landscape that cannot be removed. However, many efforts from emission containment (land/fire management practices), exposure avoidance and identifying susceptible populations can be taken to prepare for air pollution episodes and ensure people are out of harm’s way when conditions are life-threatening. Communities residing in areas affected by unhealthy concentrations of any airborne particles will benefit from optimum communication via public awareness campaigns, designed to empower people to modify behaviour in a way that improves their health as well as the quality of the air they breathe.
In 2010, the American Heart Association published a statement concluding that the existing scientific evidence was consistent with a causal relationship between exposure to fine particulate matter and cardiovascular morbidity and mortality, and that fine particulate matter exposure is a modifiable cardiovascular risk factor. Since the publication of that statement, evidence linking air pollution exposure to cardiovascular health has continued to accumulate and the biological processes underlying these effects have become better understood. This increasingly persuasive evidence necessitates policies to reduce harmful exposures and the need to act even as the scientific evidence base continues to evolve. Policy options to mitigate the adverse health impacts of air pollutants must include the reduction of emissions through action on air quality, vehicle emissions, and renewable portfolio standards, taking into account racial, ethnic, and economic inequality in air pollutant exposure. Policy interventions to improve air quality can also be in alignment with policies that benefit community and transportation infrastructure, sustainable food systems, reduction in climate forcing agents, and reduction in wildfires. The health care sector has a leadership role in adopting policies to contribute to improved environmental air quality as well. There is also potentially significant private sector leadership and industry innovation occurring in the absence of and in addition to public policy action, demonstrating the important role of public-private partnerships. In addition to supporting education and research in this area, the American Heart Association has an important leadership role to encourage and support public policies, private sector innovation, and public-private partnerships to reduce the adverse impact of air pollution on current and future cardiovascular health in the United States.
Worldwide, diabetes mellitus (DM) represents a major public-health problem due to its increasing prevalence in tandem with the rising trend of obesity. However, climate change, with its associated negative health effects, also constitutes a worrisome problem. Patients with DM are experiencing more visits to emergency departments, hospitalizations, morbidity and mortality during heat waves at ever-increasing numbers. Such patients are particularly vulnerable to heat waves due to impaired thermoregulatory mechanisms in conjunction with impaired autonomous nervous system responses at high temperatures, electrolyte imbalances and rapid deterioration of kidney function, particularly among those aged > 80 years and with preexisting chronic kidney disease (CKD). Moreover, exposure to cold temperatures is associated with increased rates of acute myocardial infarction as well as poor glycaemic control, although results are conflicting regarding cold-related mortality among patients with DM. In addition to extremes of temperature, air pollution as a consequence of the climate crisis may also be implicated in the increased prevalence and incidence of DM, particularly gestational DM (GDM), and lead to deleterious effects in patients with DM. Thus, more large-scale studies are now required to elucidate the association between specific air pollutants and risk of DM. This review presents the currently available evidence for the detrimental effects of climate change, particularly those related to weather variables, on patients with DM (both type 1 and type 2) and GDM. Specifically, the effects of heat waves and extreme cold, and pharmaceutical and therapeutic issues and their implications, as well as the impact of air pollution on the risk for DM are synthesized and discussed here.
The preliminary determination of the article is to investigate the effects of pollution and climate change. In this regard, the authors want to highlight that this real and critical issue must take seriously because each of us contributes to pollution and climate change, which is very real, and which will be aggravated by not taking action. Global warming currently involves two major problems for humanity: on the one hand, the need to dramatically diminish greenhouse gas emissions to stabilize the concentration of these gases in the atmosphere to prevent anthropogenic influence on the climate system and enable ecosystems, contrastingly the need to accommodate to the consequence of climate change, given that these effects are already visible and inevitable due to the activity of the climate system, regardless of the outcome of emission reduction actions. The main problem with pollution is air quality, which has fallen considerably, especially in urban areas. The” World Health Organization” approximates, more than seven million people die each year from air pollution. The authors also conducted a case study on the local effects of climate change – Timisoara and its peri-urban area. Therefore, we concluded that if Timisoara is successful in reducing greenhouse gas emissions, this will create a test market for Romania’s ecological technologies and help the environmental industries to locate in Timisoara.
Featured Application The data and analysis can be applied to shipping emissions issues at five governmental levels: local (ports and port cities), subnational regional (port authorities), national (Italy and other countries), international regional (European Union and Mediterranean Sea coastal areas), and global (IMO). Ships’ emissions of air pollutants pose problems for local and regional public health and agricultural production, as well as global climate change. The Italian government’s endorsement in 2019 of the creation of a Mediterranean Emission Control Area is a reflection of increasing concern about the emissions. Also, ongoing developments in the International Maritime Organization and in the European Union add to the Italian government’s maritime shipping agenda and increase its complexity and uncertainty. In that context, this review paper addresses two central questions: What are the consequences for human health and agricultural production of ships’ emissions in Italian ports and coastal areas? How can their emissions be reduced? The approach to these questions is inter-disciplinary. It applies the results of studies in atmospheric chemistry and physics; maritime shipping engineering; public health; agriculture; economics; and international law and policymaking to assess current and prospective policy issues in Italy. The principal conclusions are that: (1) Black carbon emissions are threats to human health and agricultural production in Italy, as well as to the global climate. (2) It is important that black carbon emissions receive more serious attention in policymaking processes in order to reflect the significant analytic progress that has been made in terms of understanding the problems it poses and the technological and policy solutions. (3) There are cost-effective, emission-reducing measures that are readily available, as well as other measures needing more time before full-scale implementation. (4) Although existing multi-level governance systems pose complex analytic and policymaking challenges, they also offer opportunities to institute new policies with significant short-term and long-term co-benefits from reductions in emissions.
Our aim is to review current asthma epidemiology, achievements from the last 10 years, and persistent challenges of asthma management and control in low-middle income countries (LMICs). Despite global efforts, asthma continues to be an important public health problem worldwide, particularly in poorly resourced settings. Several epidemiological studies in the last decades have shown significant variability in the prevalence of asthma globally, but generally a marked increase in LMICs resulting in significant morbidity and mortality. Poverty, air pollution, climate change, exposure to indoor allergens, urbanization and diet are some of the factors that contribute to inadequate control and poor outcomes in developing countries. Although asthma guidelines have been developed to raise awareness and improve asthma diagnosis and treatment, problems with underdiagnosis and undertreatment are still common. In addition, important social, financial, cultural and healthcare barriers are common obstacles in LMICs in achieving control. Given the high burden of asthma in these countries, adaptation and implementation of national asthma guidelines tailored to local needs should be a public health priority. Governmental commitment, education, better health system infrastructure, access to care and effective asthma medications are the cornerstone of achieving success. CONCLUSION: Asthma poses significant challenges to LMICs. Whilst there are ongoing efforts in improving asthma diagnosis and decreasing asthma burden in LMICs; reasons for inadequate asthma control are also common and difficult to tackle. Improving asthma diagnosis, access to appropriate treatment and decreasing risk factors should be key goals to reduce asthma morbidity and mortality worldwide.
Since the 2003 heatwave in Europe, evidence has been rapidly increasing on the association between extreme temperature and all-cause mortality. Little is known, however, about cause-specific cardiovascular mortality, effect modification by air pollution and aircraft noise, and which population groups are the most vulnerable to extreme temperature. We conducted a time-stratified case-crossover study in Zurich, Switzerland, including all adult cardiovascular deaths between 2000 and 2015 with precise individual exposure estimates at home location. We estimated the risk of 24,884 cardiovascular deaths associated with heat and cold using distributed non-linear lag models. We investigated potential effect modification of temperature-related mortality by fine particles, nitrogen dioxide, and night-time aircraft noise and performed stratified analyses across individual and social characteristics. We found increased risk of mortality for heat (odds ratio OR = 1.28 [95% confidence interval: 1.11-1.49] for 99th percentile of daily Tmean (24 °C) versus optimum temperature at 20 °C) and cold (OR = 1.15 [0.95-1.39], 5th percentile of daily Tmean (-3 °C) versus optimum temperature at 20 °C). Heat-related mortality was particularly strong for myocardial infarctions and hypertension related deaths, and among older women (>75 years). Analysis of effect modification also indicated that older women with lower socio-economic position and education are at higher risk for heat-related mortality. PM(2.5) increased the risk of heat-related mortality for heart failure, but not all-cause cardiovascular mortality. This study provides useful information for preventing cause-specific cardiovascular temperature-related mortality in moderate climate zones comparable to Switzerland.
OBJECTIVE: The objective of the study was to explore the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures. METHODS: Outpatient and inpatient data from the National Health Insurance Database of Taiwan from 2009 to 2013, meteorological data from the Meteorological Bureau, and air pollution exposure data from the Taiwan Air Quality Monitoring Stations were collected and integrated into daily time series data. The following data processing and analysis results are based on the mean of the 7?days’ lag data of the 18 meteorological condition/air pollution exploratory factors to identify the critical meteorological conditions and air pollution exposure factors by executing univariate analysis. The average hospital visits for seizure per day by month were used as an index of observation. The effect of seasonality has also been examined. RESULTS: The average visits per day by month had a significant association with 10 variables. Overall, the number of visits due to these factors has been estimated to be 71.529 (13.7%). The most obvious factors affecting the estimated number of visits include ambient temperature, CH(4), and NO. Six air pollutants, namely CH(4), NO, CO, NO(2), PM2.5, and NMHC had a significantly positive correlation with hospital visits due to seizures. Moreover, the average daily number of hospital visits was significantly high in January and February (winter season in Taiwan) than in other months (R(2)?=?0.422). CONCLUSION: The prediction model obtained in this study indicates the necessity of rigorous monitoring and early warning of these air pollutants and climate changes by governments. Additionally, the study provided a firm basis for establishing prediction models to be used by other countries or for other diseases.
Epidemiological studies have suggested an association between particulate air pollution, increased temperatures, and morbidity related to pregnancy outcomes. However, the roles of desert dust storms and climatological factors have not been fully addressed. The objectives of the present study were to investigate the association between desert dust storms, particulate matter with a diameter ?10 ?m (PM(10)), daily temperatures, and toxemia of pregnancy and spontaneous abortion in Gaziantep, South East Turkey. The study was conducted retrospectively at emergency department of two hospitals in Gaziantep city. Data from January 1, 2009, to March 31, 2014, were collected. Patients, who were diagnosed with toxemia of pregnancy and spontaneous abortion by radiological imaging modalities, were included in the study. Daily temperature ranges, mean temperature values, humidity, pressure, wind speed, daily PM10 levels, and records of dust storms were collected. A generalized additive regression model was designed to assess variable effects on toxemia of pregnancy and spontaneous abortion, while adjusting for possible confounding factors. Our findings demonstrated that presence of dust storms was positively associated with the toxemia of pregnancy both in outpatient admissions (OR=1.543 95% CI=1.186-2.009) and inpatient hospitalizations (OR=1.534; 95% CI=1.162-2.027). However, neither PM(10) nor maximum temperature showed a marked association with spontaneous abortion or toxemia of pregnancy in our study population. Our findings suggest that desert dust storms may have an impact on the risk for adverse pregnancy outcomes such as toxemia of pregnancy. Health authorities should take necessary measures to protect pregnant women against detrimental effects of these storms.
Cold spells have been associated with mortality from a few broad categories of diseases or specific diseases. However, there is a lack of data about the health effects of cold spells on mortality from a wide spectrum of plausible diseases which can reveal a more comprehensive contour of the mortality burden of cold spells. We collected daily mortality data in Guangzhou during 2010-2018 from the Guangzhou Center for Disease Control and Prevention. The quasi-Poisson generalized linear regression model mixed with the distributed lag non-linear model (DLNM) was conducted to examine the health impacts of cold spells for 11 broad causes of death groupings and from 35 subcategories in Guangzhou. Then, we examined the effect modification by age group (0-64 and 65+ years) and sex. Effects of cold spells on mortality generally delayed for 3-5 d and persisted up to 27 d. Cold spells were significantly responsible for increased mortality risk for most categories of deaths, with cumulative relative risk (RR) over 0-27 lagged days of 1.57 [95% confidence interval (CI): 1.48-1.67], 1.95 (1.49-2.55), 1.58 (1.39-1.79), 1.54 (1.26-1.88), 1.92 (1.15-3.22), 1.75, (1.14-2.68), 2.02 (0.78-5.22), 1.92 (1.49-2.48), 1.48 (1.18-1.85), and 1.18 (1.06-1.30) for non-accidental causes, cardiovascular diseases, respiratory diseases, digestive diseases, nervous system diseases, genitourinary diseases, mental diseases, endocrine diseases, external cause and neoplasms, respectively. The magnitudes of the effects of cold spells on mortality varied remarkably among the 35 subcategories, with the largest cumulative RR of 2.87 (1.72-4.79) estimated for pulmonary heart diseases. The elderly and females were at a higher risk of mortality for most diseases after being exposed to cold spells. Increased mortality from a wide range of diseases was significantly linked with cold spells. Our findings may have important implications for formulating effective preventive strategies and early warning response plans that mitigate the health burden of cold spells.
Along with climate change, unstable weather patterns are becoming more frequent. However, the temporal trend associated with the effect of temperature variation on schizophrenia (SCZ) is not clear. Daily time-series data on SCZ and meteorological factors for 15-year between January 1, 2005 and December 31, 2019 were collected. And we used the Poisson regression model combined with the time-varying distribution lag nonlinear model (DLNM) to explore the temporal trend of the association between three temperature variation indicators (diurnal temperature range, DTR; temperature variability, TV; temperature change between neighboring days, TCN) and SCZ hospitalizations, respectively. Meanwhile, we also explore the temporal trend of the interaction between temperature and temperature variation. Stratified analyses were performed in different gender, age, and season. Across the whole population, we found a decreasing trend in the risk of SCZ hospitalizations associated with high DTR (from 1.721 to 1.029), TCN (from 1.642 to 1.066), and TV (TV0-1, from 1.034 to 0.994; TV0-2, from 1.041 to 0.994, TV0-3, from 1.044 to 0.992, TV0-4, from 1.049 to 0.992, TV0-5, from 1.055 to 0.993, TV0-6, from 1.059 to 0.991, TV0-7, from 1.059 to 0.990), but an increasing trend in low DTR (from 0.589 to 0.752). Subgroup analysis results further revealed different susceptible groups. Besides, the interactive effect suggests that temperature variation may cause greater harm under low-temperature conditions. There was a synergy between TCN and temperature on the addition and multiplication scales, which were 1.068 (1.007, 1.133) and 0.067 (0.009, 0.122), respectively. Our findings highlight public health interventions to mitigate temperature variation effects needed to focus not only on high temperature variations but also moderately low temperature variations. Future hospitalizations for SCZ associated with temperature variation may be more severely affected by temperature variability from low temperature environments. The temporal trend is associated with the effect of temperature variation on schizophrenia (SCZ).
Urban air pollution can have negative short- and long-term impacts on health, including cardiovascular, neurological, immune system and developmental damage. The irritant qualities of pollutants such as ozone (O(3)), nitrogen dioxide (NO(2)) and particulate matter (PM) can cause respiratory and cardiovascular distress, which can be heightened during physical activity and particularly so for those with respiratory conditions such as asthma. Previously, research has only examined marathon run outcomes or running under laboratory settings. This study focuses on elite 5-km athletes performing in international events at nine locations. Local meteorological and air quality data are used in conjunction with race performance metrics from the Diamond League Athletics series to determine the extent to which elite competitors are influenced during maximal sustained efforts in real-world conditions. The findings from this study suggest that local meteorological variables (temperature, wind speed and relative humidity) and air quality (ozone and particulate matter) have an impact on athletic performance. Variation between finishing times at different race locations can also be explained by the local meteorology and air quality conditions seen during races.
The effects of daily mean temperature on health outcomes have been discussed in many previous studies, but few have considered the adverse impacts on upper respiratory tract infection (URTI) due to variance of temperature in one day. Diurnal temperature range (DTR) was a novel indicator calculated as maximum temperature minus minimum temperature on the same day. In this study, generalized additive model (GAM) with quasi-Poisson distribution was used to investigate the association between DTR and the number of daily outpatient visits for URTI among college students. Data about meteorological factors and air pollutants were provided by Hubei Meteorological Bureau and Wuhan Environmental Protection Bureau, respectively. Outpatient visits data were collected from the Hospital of Wuhan University from January 1, 2016, to December 31, 2018. Short-term exposure to DTR was associated with the increased risk of outpatient for URTI among all college students. Per 1 °C increased in DTR was associated with 0.73% (95%CI: 0.24, 1.21) increased in outpatient visits of all college students for URTI at lag 0 day. The greatest effect values were observed in males [1.35% (95%CI: 0.33,2.39)] at lag 0-6 days, and in females [0.86% (95%CI: 0.24, 1.49)] at lag 0-1 days. DTR had more adverse health impact in autumn and winter. Public health departments should consider the negative effect of DTR to formulate more effective prevention and control measures for protecting vulnerable people.
PURPOSE: Diurnal temperature range (DTR) is a meteorological indicator closely associated with global climate change. Thus, we aim to explore the effects of DTR on the outpatient and emergency room (O&ER) admissions for cardiovascular diseases (CVDs), and related predictive research. METHODS: The O&ER admissions data for CVDs from three general hospitals in Jinchang of Gansu Province were collected from 2013 to 2016. A generalized additive model (GAM) with Poisson regression was employed to analyze the effect of DTR on the O&ER admissions for all cardiovascular diseases, hypertension, ischemic heart disease (IHD) and stoke. GAM was also used to preform predictive research of the effect of DTR on the O&ER admissions for CVDs. RESULTS: There were similar positive linear relationships between DTR and the O&ER visits with the four cardiovascular diseases. And the cumulative lag effects were higher than the single lag effects. A 1 °C increase in DTR corresponded to a 1.30% (0.99-1.62%) increase in O&ER admissions for all cardiovascular diseases. Males and elderly were more sensitivity to DTR. The estimates in non-heating season were higher than in heating season. The trial prediction accuracy rate of CVDs based on DTR was between 59.32 and 74.40%. CONCLUSIONS: DTR has significantly positive association with O&ER admissions for CVDs, which can be used as a prediction index of the admissions of O&ER with CVDs.
We herein report a 56-year-old woman who developed allergic bronchopulmonary aspergillosis (ABPA) possibly due to fungal exposure after disastrous heavy rainfall in Western Japan in 2018. She was diagnosed with ABPA complicated with asthma, increased peripheral blood eosinophil count, elevation of specific immunoglobulin E for Aspergillus fumigatus, positive Aspergillus fumigatus precipitation antibody reaction test results, and notable chest computed tomography findings. After treatment with benralizumab, her symptoms, peripheral blood eosinophil count, radiological findings, and respiratory function dramatically improved. The administration of benralizumab appears to be an effective treatment strategy for ABPA.
To date, research evidence suggests that extreme ambient temperatures may lead to preterm birth. Since the results of studies in subtropical humid monsoon climate are inconclusive, we investigated the association between extreme ambient temperatures and the risk of preterm birth in Xuzhou, China. We analyzed the association between the birth data of 103,876 singleton deliveries (from July 1, 2016 to June 30, 2019) and ambient temperature. We used a quasi-Poisson model with distributed lag nonlinear models (DLNM) to investigate the delay and nonlinear effects of temperature, taking into account the effects of air pollutants and relative humidity. During the study period, the number of hospitalizations for preterm birth was 4623. Taking the median temperature (16.8 °C) as a reference, the highest risk estimate at extreme cold temperature (- 2.8 °C, 1st percentile) was found at lag 0-1 days. Exposure to extreme cold (- 2.8 °C, 1st percentile), or moderate cold (6.8 °C, 25th percentile) were associated with 1.659 (95% confidence interval [CI] 1.177-2.338) and 1.456 (95% CI 1.183-1.790) increased risks of preterm birth, respectively. In the further stratified analysis of the age of pregnant women, we found that there were significant associations between cold temperatures and preterm birth in both groups (older group ? 35; younger group < 35). In a subtropical humid monsoon climate, low ambient temperatures may lead to preterm birth, suggesting that women should stay away from low temperatures during pregnancy.
Temperature change is an important meteorological indicator reflecting weather stability. This study aimed to examine the effects of ambient temperature change on non-accidental mortality using diurnal temperature change (DTR) and temperature change between neighboring days (TCN) from two perspectives, intra-day and inter-day temperature change, and further, to explore seasonal variations of mortality, identify the susceptible population and investigate the interaction between temperature change and apparent temperature (AT). We collected daily data on cause-specific mortality, air pollutants and meteorological indicators in Shenzhen, China, from 1 January 2013 to 29 December 2017. A Quasi-Poisson generalized linear regression combined with distributed lag non-linear models (DLNMs) were conducted to estimate the effects of season on temperature change-related mortality. In addition, a non-parametric bivariate response surface model was used to explore the interaction between temperature change and AT. The cumulative effect of DTR was a U-shaped curve for non-accidental mortality, whereas the curve for TCN was nearly monotonic. The overall relative risks (RRs) of non-accidental, cardiovascular and respiratory mortality were 1.407 (95% CI: 1.233-1.606), 1.470 (95% CI: 1.220-1.771) and 1.741 (95% CI: 1.157-2.620) from exposure to extreme large DTR (99th) in cold seasons. However, no statistically significant effects were observed in warm seasons. As for TCN, the effects were higher in cold seasons than warm seasons, with the largest RR of 1.611 (95% CI: 1.384-1.876). The elderly and females were more sensitive, and low apparent temperature had a higher effect on temperature change-related non-accidental mortality. Temperature change was positively correlated with an increased risk of non-accidental mortality in Shenzhen. Both female and elderly people are more vulnerable to the potential adverse effects, especially in cold seasons. Low AT may enhance the effects of temperature change.
Considering the increasing rate of hospitalization due to the symptoms intensification, and the increasing trend of air pollution, this study aimed to determine the relationship between the amount of air pollutants and the incidence of cardiovascular disease leading to hospitalization. This case-crossover study was carried out on the data of admitted patients with cardiovascular disease such as hypertension, ischemic heart disease, and cerebrovascular disease in Urmia during 2011-2016. Weather data about air pollutants (NO2, PM10, SO2, and CO) were obtained from the meteorological department of Urmia. The data were coded for each patient and matched with the meteorological data for statistical modeling. The data were analyzed through STATA version 14. Conditional logistic regression was used to estimate the effects of air pollutants on cardiovascular disease adjusted to air temperature, relative humidity, and air pollutants. The final analysis was performed on 43,424 patients with cardiovascular disease using code I10-I99 including ischemic heart disease, hypertension, and cerebrovascular disease adjusted to air temperature and relative humidity. Of all pollutants, CO with each increase 10 ?g/m(3) had a meaningful relationship with the incidence of cardiovascular hospitalization. By selecting the window of exposure, 1, 2, and 6 days before admission, lag 6 (6 days) was the best estimation for exposure time in the patients with cardiovascular patients (OR 1.0056, CI 1.0041-1.007), and in the patients with ischemic heart disease (OR 1.000055, CI 1.000036-1.000075) and in the patients with hypertension (OR 1.000076, CI 1.00002-1.000132). Regarding cerebrovascular disease, no statistically significant association was observed. The results showed that only CO was associated with an increased risk of admission in patients with cardiovascular disease, ischemic heart disease, and hypertension, and there was no clear evidence for pollution effects on cerebrovascular diseases.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors, and the daily reported infected cases caused by novel coronavirus in India. The daily positive infected cases, concentrations of air pollutants, and meteorological factors in 288 districts were collected from January 30, 2020, to April 23, 2020, in India. Spearman’s correlation and generalized additive model (GAM) were applied to investigate the correlations of four air pollutants (PM(2.5), PM(10), NO(2), and SO(2)) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS, and WD) with COVID-19-infected cases. The study indicated that a 10 ?g/m(3) increase during (Lag0-14) in PM(2.5), PM(10), and NO(2) resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01), and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of Coronavirus Disease 2019 (COVID 19)-infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19-infected cases respectively. In addition, SO(2) and relative humidity were negatively associated with COVID-19-infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO(2) and for relative humidity respectively. The study recommended that there are significant correlations between air pollutants and meteorological factors with COVID-19-infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.
PURPOSE: The aim of the present study was to investigate the effect of short-term exposure to ambient black carbon (BC) on daily cause-specific mortality, including mortality due to respiratory, cardiovascular, ischemic heart and cerebrovascular diseases in Tehran, Iran. MATERIALS AND METHODS: Daily non-accidental death counts, meteorological data and hourly concentrations of air pollutants from 2014 to 2017 were collected in Tehran. A distributed lag non-linear model was used to assess the association between exposure to BC and daily mortality. RESULTS: The mean daily BC concentration during the study period was 3.96?±?1.19 µg/m(3). The results indicated that BC was significantly associated with cardiovascular, ischemic heart disease, and cerebrovascular mortality, but not with respiratory mortality. In first model, each 10 µg/m(3) increase in at lag 3, lag 4 and lag 5 were associated with cardiovascular mortality in 16-65 year age group with the relative risks (RRs) of 1.17 (95?% CI: 1.02-1.33), 1.17 (95?% CI: 1.04-1.31) and 1.12 (95?% CI: 1.02-1.24), respectively. The highest mortality rate per 10 µg/m(3) increase in exposure was found for ischemic heart diseases with RR of 3.98 (95?% CI: 1.04-1.81, lag 01) for 16-65 age group. Cerebrovascular mortality was associated with 10 µg/m(3) increases in non-cumulative exposure with RR of 1.17 (95?% 1.009-1.35, lag 5) in the age group ? 65 years. In the second model for a 10 µg/m(3) increase in BC, cardiovascular mortality at specific lag days (5 and 6 days) in the age group ? 16 years were associated with RR of 1.34 (95?% CI 1.08-1.66) and 1.35(95?% CI 1.02-1.77), respectively. CONCLUSIONS: This study in Tehran found significant effects of BC exposure on daily mortality for cardiovascular, ischemic heart disease, cerebrovascular disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40201-021-00659-0.
Ischemic stroke is one of the most common causes of death worldwide, and uncomfortable meteorological and built environments may increase its risk. Residents in different built environments are exposed to different risks of ischemic stroke in cold and hot weather. By using the data from 3547 patients hospitalized, a distributed lag non-linear model was established to compare the differences in the risk of ischemic stroke in urban areas with respect to different Building Height, Building Density, Normalized Differential Vegetation Index, and Distance to Water under the meteorological condition. The results showed that lower Building Height is related to the negative cold effects in winter, and higher Building Height is related to increased risks at high temperatures. Built environments with Building Heights of 10-15 m in hot weather and above 15 m in cold weather have low risks. Higher Building Density was found to be associated with reduced negative cold effects; however, the negative hot effects increased in summer. Built environments with a Building Density of more than 0.3 showed low risks, regardless of the weather conditions. Increasing NDVI seemed to mitigate negative effects in uncomfortable weather, and built environments with higher NDVI were found to be associated with lower risks of ischemic stroke. Built environments with shorter Distance to Water seemed to pose higher risks in summer, and longer Distance to Water was correlated with higher risks in winter. Built environments with Distance to Water in the range of 0.65-2.30 km showed low risks. The research results could have some implications for urban planners to form reasonable built environments under certain meteorological factors which can be beneficial for the mitigation of incidence of ischemic stroke. (C) 2020 Elsevier B.V. All rights reserved.
During the summer of 2018 Sweden experienced a high occurrence of wildfires, most intense in the low-densely populated Jämtland Härjedalen region. The aim of this study was to investigate any short-term respiratory health effects due to deteriorated air quality generated by the smoke from wildfires. For each municipality in the region Jämtland Härjedalen, daily population-weighted concentrations of fine particulate matter (PM(2.5)) were calculated through the application of the MATCH chemistry transport model. Modelled levels of PM(2.5) were obtained for two summer periods (2017, 2018). Potential health effects of wildfire related levels of PM(2.5) were examined by studying daily health care contacts concerning respiratory problems in each municipality in a quasi-Poisson regression model, adjusting for long-term trends, weekday patterns and weather conditions. In the municipality most exposed to wildfire smoke, having 9 days with daily maximum 1-h mean of PM(2.5) > 20 ?g/m(3), smoke days resulted in a significant increase in daily asthma visits the same and two following days (relative risk (RR) = 2.64, 95% confidence interval (CI): 1.28-5.47). Meta-estimates for all eight municipalities revealed statistically significant increase in asthma visits (RR = 1.68, 95% CI: 1.09-2.57) and also when grouping all disorders of the lower airways (RR = 1.40, 95% CI: 1.01-1.92).
Desert dust transported from the Saharan-Sahel region to the Caribbean Sea is responsible for peak exposures of particulate matter (PM). This study explored the potential added value of satellite aerosol optical thickness (AOT) measurements, compared to the PM concentration at ground level, to retrospectively assess exposure during pregnancy. MAIAC MODIS AOT retrievals in blue band (AOT(470)) were extracted for the French Guadeloupe archipelago. AOT(470) values and PM(10) concentrations were averaged over pregnancy for 906 women (2005-2008). Regression modeling was used to examine the AOT(470)-PM(10) relationship during pregnancy and test the association between dust exposure estimates and preterm birth. Moderate agreement was shown between mean AOT(470) retrievals and PM(10) ground-based measurements during pregnancy (R(2)?=?0.289). The magnitude of the association between desert dust exposure and preterm birth tended to be lower using the satellite method compared to the monitor method. The latter remains an acceptable trade-off between epidemiological relevance and exposure misclassification, in areas with few monitoring stations and complex topographical/meteorological conditions, such as tropical islands.
Previous studies demonstrated that global warming can lead to deteriorated air quality even when anthropogenic emissions were kept constant, which has been called a climate change penalty on air quality. It is expected that anthropogenic emissions will decrease significantly in the future considering the aggressive emission control actions in China. However, the dependence of climate change penalty on the choice of emission scenario is still uncertain. To fill this gap, we conducted multiple independent model simulations to investigate the response of PM(2.5) to future (2050) climate warming (RCP8.5) in China but with different emission scenarios, including the constant 2015 emissions, the 2050 CLE emissions (based on Current Legislation), and the 2050 MTFR emissions (based on Maximum Technically Feasible Reduction). For each set of emissions, we estimate climate change penalty as the difference in PM(2.5) between a pair of simulations with either 2015 or 2050 meteorology. Under 2015 emissions, we find a PM(2.5) climate change penalty of 1.43 ?g m(-3) in Eastern China, leading to an additional 35,000 PM(2.5)-related premature deaths [95% confidence interval (CI), 21,000-40,000] by 2050. However, the PM(2.5) climate change penalty weakens to 0.24 ?g m(-3) with strict anthropogenic emission controls under the 2050 MTFR emissions, which decreases the associated PM(2.5)-related deaths to 17,000. The smaller MTFR climate change penalty contributes 14% of the total PM(2.5) decrease when both emissions and meteorology are changed from 2015 to 2050, and 24% of total health benefits associated with this PM(2.5) decrease in Eastern China. This finding suggests that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM(2.5) and its associated premature deaths, even though a climate change penalty still occurs even under MTFR. Strengthened controls on anthropogenic emissions are key to attaining air quality targets and protecting human health in the context of future global climate change.
OBJECTIVES: The primary objective was to evaluate the association between weather variables and joint pain in patients with chronic rheumatic diseases (CRD: rheumatoid arthritis (RA), osteoarthritis (OA), and spondyloarthritis (SpA)). A secondary objective was to study the impact of air pollution indicators on CRD pain. METHOD: The study is prospective, correlational, with time-series analysis. Patients with CRD, living in a predefined catchment area, filled their level of pain daily using a 0-10 numerical scale (NS), for 1 year. Weather (temperature, relative humidity (H), atmospheric pressure (P)) and air pollution indicators (particulate matters (PM(10), PM(2.5)), nitrogen dioxide (NO(2)), and ozone (O(3))) were recorded daily using monitoring systems positioned in the same area. Association between pain and weather and air pollution indicators was studied using Pearson’s correlation. Time-series analysis methodology was applied to determine the temporal relationship between pain and indicators. RESULTS: The study included 94 patients, 82% reported they were weather-sensitive. Pain variation was similar across diseases over a year. Pain was associated negatively with temperature, H, and O(3,) and positively with P and NO(2). However, the strength of correlation was moderate; temperature explained 22% of pain variance. A drop of 10°C in temperature corresponded to an increase of 0.5 points in pain NS. Also, there was a significant interaction among environmental factors. In time-series analysis, temperature and NO(2) remained independently associated with pain. CONCLUSIONS: The perception of joint pain in patients with CRD was correlated with weather and air pollution. The strength of association was moderate and independent of underlying disease. Key Points •Weather variation was moderately correlated with joint pain in chronic rheumatic diseases, with an inverse association with temperature, humidity, and O(3). • Air pollution indicators, mainly nitrogen dioxide and ozone, were correlated with joint pain; particulate matters were also correlated but to a lesser extent. • The influence of these environmental factors was independent of the type of rheumatic disease, thus raising the hypothesis of their impact on pain perception mechanisms.
Exposure to air pollution has been suggested to be associated with an increased risk of women’s health disorders. However, it remains unknown to what extent changes in ambient air pollution affect gynecological cancer. In our case-control study, the logistic regression model was combined with the restricted cubic spline to examine the association of short-term exposure to air pollution with gynecological cancer events using the clinical data of 35,989 women in Beijing from December 2008 to December 2017. We assessed the women’s exposure to air pollutants using the monitor located nearest to each woman’s residence and working places, adjusting for age, occupation, ambient temperature, and ambient humidity. The adjusted odds ratios (ORs) were examined to evaluate gynecologic cancer risk in six time windows (Phase 1-Phase 6) of women’s exposure to air pollutants (PM(2.5), CO, O(3), and SO(2)) and the highest ORs were found in Phase 4 (240 days). Then, the higher adjusted ORs were found associated with the increased concentrations of each pollutant (PM(2.5), CO, O(3), and SO(2)) in Phase 4. For instance, the adjusted OR of gynecological cancer risk for a 1.0-mg m(-3) increase in CO exposures was 1.010 (95% CI: 0.881-1.139) below 0.8 mg m(-3), 1.032 (95% CI: 0.871-1.194) at 0.8-1.0 mg m(-3), 1.059 (95% CI: 0.973-1.145) at 1.0-1.4 mg m(-3), and 1.120 (95% CI: 0.993-1.246) above 1.4 mg m(-3). The ORs calculated in different air pollution levels accessed us to identify the nonlinear association between women’s exposure to air pollutants (PM(2.5), CO, O(3), and SO(2)) and the gynecological cancer risk. This study supports that the gynecologic risks associated with air pollution should be considered in improved public health preventive measures and policymaking to minimize the dangerous effects of air pollution.
Exposure to air pollution is of great concern for public health although studies on the associations between exposure estimates and personal exposure are limited and somewhat inconsistent. The aim of this study was to quantify the associations between personal nitrogen oxides (NO(x)), ozone (O(3)) and particulate matter (PM(10)) exposure levels and ambient levels, and the impact of climate and time spent outdoors in two cities in Sweden. Subjects (n?=?65) from two Swedish cities participated in the study. The study protocol included personal exposure measurements at three occasions, or waves. Personal exposure measurements were performed for NO(x) and O(3) for 24 h and PM(10) for 24 h, and the participants kept an activity diary. Stationary monitoring stations provided hourly data of NO(x), O(3) and PM, as well as data on air temperature and relative humidity. Data were analysed using mixed linear models with the subject-id as a random effect and stationary exposure and covariates as fixed effects. Personal exposure levels of NO(x), O(3) and PM(10) were significantly associated with levels measured at air pollution monitoring stations. The associations persisted after adjusting for temperature, relative humidity, city and wave, but the modelled estimates were slightly attenuated from 2.4% (95% CI 1.8-2.9) to 2.0% (0.97-2.94%) for NO(x), from 3.7% (95% CI 3.1-4.4) to 2.1% (95% CI 1.1-2.9%) for O(3) and from 2.6% (95% 0.9-4.2%) to 1.3% (95% CI?-?1.5-4.0) for PM(10). After adding covariates, the degree of explanation offered by the model (coefficient of determination, or R(2)) did not change for NO(x) (0.64 to 0.63) but increased from 0.46 to 0.63 for O(3), and from 0.38 to 0.43 for PM(10). Personal exposure to NO(x), O(3) and PM has moderate to good association with levels measured at urban background sites. The results indicate that stationary measurements are valid as measure of exposure in environmental health risk assessments, especially if they can be refined using activity diaries and meteorological data. Approximately 50-70% of the variation of the personal exposure was explained by the stationary measurement, implying occurrence of misclassification in studies using more crude exposure metrics, potentially leading to underestimates of the effects of exposure to ambient air pollution.
Although Ahvaz is considered as one of the warmest cities around the world, few epidemiological studies have been conducted on the adverse effects of temperature on human health using thermal indices in this city. This study investigates the relation between physiologically equivalent temperature (PET) and respiratory hospital admissions in Ahvaz. Distributed lag non-linear models (DLNMs) combined with quasi-Poisson regression models were used to investigate the relation between PET and respiratory disease hospital admissions, adjusted for the effect of time trend, air pollutants (NO(2), SO(2), and PM(10)), and weekdays. The analysis was performed by utilizing R software. Low PET values significantly decreased the risk of hospital admissions for total respiratory diseases, respiratory diseases in men and women, chronic obstructive pulmonary diseases (COPD), and bronchiectasis. However, low PET (16.9°C) in all lags except lag 0-30 significantly increased the risk of hospital admissions for asthma. The results indicate that in Ahvaz, which has a warm climate, cold weather decreased overall respiratory hospital admissions, except for asthma.
Air pollution in large cities produces numerous diseases and even millions of deaths annually according to the World Health Organization. Pollen exposure is related to allergic diseases, which makes its prediction a valuable tool to assess the risk level to aeroallergens. However, airborne pollen concentrations are difficult to predict due to the inherent complexity of the relationships among both biotic and environmental variables. In this work, a stochastic approach based on supervised machine learning algorithms was performed to forecast the daily Olea pollen concentrations in the Community of Madrid, central Spain, from 1993 to 2018. Firstly, individual Light Gradient Boosting Machine (LightGBM) and artificial neural network (ANN) models were applied to predict the day of the year (DOY) when the peak of the pollen season occurs, resulting the estimated average peak date 149.1?±?9.3 and 150.1?±?10.8 DOY for LightGBM and ANN, respectively, close to the observed value (148.8?±?9.8). Secondly, the daily pollen concentrations during the entire pollen season have been calculated using an ensemble of two-step GAM followed by LightGBM and ANN. The results of the prediction of daily pollen concentrations showed a coefficient of determination (r(2)) above 0.75 (goodness of the model following cross-validation). The predictors included in the ensemble models were meteorological variables, phenological metrics, specific site-characteristics, and preceding pollen concentrations. The models are state-of-the-art in machine learning and their potential has been shown to be used and deployed to understand and to predict the pollen risk levels during the main olive pollen season.
According to the European Environment Agency, the year 2015 was the warmest on record to that point, with a series of heat waves from May to September resulted in high levels of tropospheric ozone. The implications of such a year on the human well-being and health are therefore of multiple nature and can be quantified referring to the exceedances of the corresponding thresholds. This work focused on the analysis of the May-September period of 2015 in the city of Milan (Italy) in terms of Mediterranean Outdoor Comfort Index (MOCI) and ozone concentrations, recorded by monitoring stations and modeled through the Weather Research and Forecasting model. Main findings show that thermo-hygrometric stress events (periods of at least six consecutive days characterized by daily maximum values of the MOCI higher than 0.5) are characterized by daily ozone higher than the guideline level of the World Health Organization (equal to 100 ?gm(-3)). This means that thermo-hygrometric stress conditions are added up to poor air quality conditions, with severe risks for human health. Moreover, a daily MOCI-daily ozone correlation coefficient equal to 0.6 was found for the whole period. The degree of correspondence between ozone events (defined according to the European Air Quality Directive) and MOCI events was also investigated pointing out that 86% and 95% of days during ozone events are correctly predicted by events of recorded and modeled MOCI respectively, with a corresponding false alarm rate of 3% and 9%.
Schizophrenia (SCZ) hospital re-admissions constitute a serious disease burden worldwide. Some studies have reported an association between air pollutants and hospital admissions for SCZ. However, evidence is scarce regarding the effects of ambient particulate matter (PM) on SCZ hospital re-admissions, especially in coastal cities in China. The purpose of this study was to examine whether PM affects the risk of SCZ hospital re-admission in the coastal Chinese city of Qingdao. Daily SCZ hospital re-admissions, daily air pollutants, and meteorological factors from 2015 to 2019 were collected. A quasi-Poisson generalized linear regression model combined with distributed lag non-linear model (DLNM) was applied to model the exposure-lag-response relationship between PM and SCZ hospital re-admissions. The relative risks (RRs) were estimated for an inter-quartile range (IQR) increase in PM concentrations. Subgroup analyses by age and gender were conducted to identify the vulnerable subgroups. There were 6220 SCZ hospital re-admissions during 2015-2019. The results revealed that PM, including PM(10) (particles with an aerodynamic diameter ?10 ?m), PM(c) (particles >2.5 ?m but <10 ?m), and PM(2.5) (particles ?2.5 ?m), was positively correlated with SCZ hospital re-admissions. The strongest single-day effects all occurred on lag3 day, and the corresponding RRs were 1.07 (95% CI: 1.02-1.11) for PM(10), 1.03 (95% CI: 1.00-1.07) for PM(c), and 1.05 (95% CI: 1.01-1.09) for PM(2.5) per IQR increase. Stronger associations were observed in males and younger individuals (<45 years). Our findings suggest that PM exposure is associated with increased risk of SCZ hospital re-admission. Active intervention measures against PM exposure should be taken to reduce the risk of SCZ hospital re-admission, especially for males and younger individuals.
The short-term effects of ambient temperature on mortality have been widely investigated. However, the epidemiological evidence on the long-term effects of temperature on mortality is rare. In present study, we conducted a nationwide quasi-experimental design, which based on a variant of difference-in-differences (DID) approach, to examine the association between long-term exposure to ambient temperature and mortality risk in China, and to analyze the effect modification of population characteristics and socioeconomic status. Data on mortality were collected from 364 communities across China during 2006-2017, and environmental data were obtained for the same period. We estimated a 2.93 % (95 % CI: 2.68 %, 3.18 %) increase in mortality risk per 1 °C decreases in annual temperature, the greater effects were observed on respiratory diseases (5.16 %, 95 % CI: 4.53 %, 5.79 %) than cardiovascular diseases (3.43 %, 95 % CI: 3.06 %, 3.80 %), and on younger people (4.21 %, 95 % CI: 3.73 %, 4.68 %) than the elderly (2.36 %, 95 % CI: 2.06 %, 2.65 %). In seasonal analysis, per 1 °C decreases in average temperature was associated with 1.55 % (95 % CI: 1.23 %, 1.87 %), -0.53 % (95 % CI: -0.89 %, -0.16 %), 2.88 % (95 % CI: 2.45 %, 3.31 %) and 4.21 % (95 % CI: 3.98 %, 4.43 %) mortality change in spring, summer, autumn and winter, respectively. The effects of long-term temperature on total mortality were more pronounced among the communities with low urbanization, low education attainment, and low GDP per capita. In total, the decrease of average temperature in summer decreased mortality risk, while increased mortality risk in other seasons, and the associations were modified by demographic characteristics and socioeconomic status. Our findings suggest that populations with disadvantaged characteristics and socioeconomic status are vulnerable to long-term exposure of temperature, and targeted policies should be formulated to strengthen the response to the health threats of temperature exposure.
Livability, resilience, and justice in cities are challenged by climate change and the historical legacies that together create disproportionate impacts on human communities. Urban green infrastructure has emerged as an important tool for climate change adaptation and resilience given their capacity to provide ecosystem services such as local temperature regulation, stormwater mitigation, and air purification. However, realizing the benefits of ecosystem services for climate adaptation depend on where they are locally supplied. Few studies have examined the potential spatial mismatches in supply and demand of urban ecosystem services, and even fewer have examined supply-demand mismatches as a potential environmental justice issue, such as when supply-demand mismatches disproportionately overlap with certain socio-demographic groups. We spatially analyzed demand for ecosystem services relevant for climate change adaptation and combined results with recent analysis of the supply of ecosystem services in New York City (NYC). By quantifying the relative mismatch between supply and demand of ecosystem services across the city we were able to identify spatial hot- and coldspots of supply-demand mismatch. Hotspots are spatial clusters of census blocks with a higher mismatch and coldspots are clusters with lower mismatch values than their surrounding blocks. The distribution of mismatch hot- and coldspots was then compared to the spatial distribution of socio-demographic groups. Results reveal distributional environmental injustice of access to the climate-regulating benefits of ecosystem services provided by urban green infrastructure in NYC. Analyses show that areas with lower supply-demand mismatch tend to be populated by a larger proportion of white residents with higher median incomes, and areas with high mismatch values have lower incomes and a higher proportion of people of color. We suggest that urban policy and planning should ensure that investments in “nature-based” solutions such as through urban green infrastructure for climate change adaptation do not reinforce or exacerbate potentially existing environmental injustices.
Statistical models to evaluate the relationships between large-scale meteorological conditions, prevailing air pollution levels and combined ozone and temperature events, were developed during the 1993-2012 period with Central Europe as regional focus. Combined ozone and temperature events were defined based on the high frequency of coinciding, health-relevant elevated levels of daily maximum tropospheric ozone concentrations (based on running 8-h means) and daily maximum temperature values in the peak ozone and temperature season from April to September. By applying two different modeling approaches based on lasso, logistic regression, and multiple linear regression mean air temperatures at 850 hPa, ozone persistence, surface thermal radiation, geopotential heights at 850 hPa, meridional winds at 500 hPa, and relative humidity at 500 hPa were identified as main drivers of combined ozone and temperature events. Statistical downscaling projections until the end of the twenty-first century were assessed by using the output of seven models of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Potential frequency shifts were evaluated by comparing the mid- (2031-2050) and late-century (2081-2100) time windows to the base period (1993-2012). A sharp increase of ozone-temperature events was projected under RCP4.5 and RCP8.5 scenario assumptions with respective multi-model mean changes of 8.94% and 16.84% as well as 13.33% and 37.52% for mid- and late-century European climate.
BACKGROUND: Short-term exposure to PM(2.5) has been widely associated with human morbidity and mortality. However, most up-to-date research was conducted at a daily timescale, neglecting the intra-day variations in both exposure and outcome. As an important fraction in PM(2.5), PM(1) has not been investigated about the very acute effects within a few hours. METHODS: Hourly data for size-specific PMs (i.e., PM(1), PM(2.5), and PM(10)), all-cause emergency department (ED) visits and meteorological factors were collected from Guangzhou, China, 2015-2016. A time-stratified case-crossover design with conditional logistic regression analysis was performed to evaluate the hourly association between size-specific PMs and ED visits, adjusting for hourly mean temperature and relative humidity. Subgroup analyses stratified by age, sex and season were conducted to identify potential effect modifiers. RESULTS: A total of 292,743 cases of ED visits were included. The effects of size-specific PMs exhibited highly similar lag patterns, wherein estimated odds ratio (OR) experienced a slight rise from lag 0-3 to 4-6 h and subsequently attenuated to null along with the extension of lag periods. In comparison with PM(2.5) and PM(10), PM(1) induced slightly larger effects on ED visits. At lag 0-3 h, for instance, ED visits increased by 1.49% (95% confidence interval: 1.18-1.79%), 1.39% (1.12-1.66%) and 1.18% (0.97-1.40%) associated with a 10-?g/m(3) rise, respectively, in PM(1), PM(2.5) and PM(10). We have detected a significant effect modification by season, with larger PM(1)-associated OR during the cold months (1.017, 1.013 to 1.021) compared with the warm months (1.010, 1.005 to 1.015). CONCLUSIONS: Our study provided brand-new evidence regarding the adverse impact of PM(1) exposure on human health within several hours. PM-associated effects were significantly more potent during the cold months. These findings may aid health policy-makers in establishing hourly air quality standards and optimizing the allocation of emergency medical resources.
PM(2.5) pollution has adverse health effects on humans. Urbanization and long-term meteorological variations play important roles in influencing the PM(2.5) concentration and its associated health effects. Our results indicate that the urbanization process can enhance the PM(2.5) concentration globally. The PM(2.5)-caused mortality density (deaths/100 km(2)) is also positively correlated with the urbanization degree in both developed and developing countries. The results from machine learning technique revealed that the meteorology-driven variation in PM(2.5)-caused health burden has increased with the increase in the urbanization degree from 1980 to 2018, suggesting that residents living in urban areas are more vulnerable to experiencing unfavorable meteorological conditions (e.g. low wind speed and planetary boundary layer height). The maximum difference in PM(2.5)-caused mortality due to the variation in annual meteorological conditions (between 2013 and 1986) was 270 600 (196 800-317 900). Our findings indicate an urgent need to understand the driving force behind the appearance of unfavorable meteorological situations and propose suitable climate mitigation measures.
The aim of this study was to compare airborne levels of Phl p 1 and Phl p 5, with Poaceae pollen concentrations inside and outside of the pollen season, and to evaluate their association with symptoms in grass allergic patients and the influence of climate and pollution. The Hirst and the Burkard Cyclone samplers were used for pollen and allergen quantification, respectively. The sampling period ran from 23 March 2009 to 27 July 2010. Twenty-three patients with seasonal allergic asthma and rhinitis used an electronic symptom card. The aerosol was extracted and quantified for Phl p 1 and Phl p 5 content. Descriptive statistics, non-parametric paired contrast of Wilcoxon, Spearman’s correlations, and a categorical principal component analysis (CatPCA) were carried out. Significant variations in pollen, aeroallergen levels, pollen allergen potency, and symptoms score were observed in this study. Phl p 5 pollen allergen potency was higher at the beginning of the 2010 grass pollen season. Presence of Phl p 1 outside the pollen season with positive O(3) correlation was clinically relevant. 45.5% of the variance was explained by two dimensions in the CatPCA analysis, showing the symptom relationships dissociated in two dimensions. In the first one, the more important relationship was with grass pollen grains concentration and Phl p 5 and to a lesser extent with Phl p 1 and levels of NO(2) and O(3), and in the second dimension, symptoms were associated with humidity and SO(2). Clinically relevant out-season Phl p 1 was found with a positive O(3) correlation. The effect of climate and pollution may have contributed to the higher seasonal allergic rhinitis symptom score recorded in 2009.
Particulate matter (PM) has been occurring regularly during the dry season in the upper north of Thailand including Lamphun Province that might be influenced by various factors including climatologic and other pollutants. This paper aims to investigate the climatologic and gaseous factors influencing the occurrence of PM(10) concentration using Pollution Control Department (PCD) data. The secondary data of 2009 to 2017 obtained from the PCD was used for analysis. We used descriptive statistics, Pearson’s correlation coefficient, multiple regression and graphic presentation using R program (R packages of ‘open air’ and ‘ncdf4’) and Microsoft Excel Spreadsheet®. In addition, the periodic measurement of PM(2.5) and PM(10) were investigated to determine the ratio of PM(2.5)/PM(10). The results indicated that haze episodes (daily PM(10) concentration always over the PCD standard) normally occur during the dry season from February to April. The maximum concentration was always found in March. The PM(10) concentration was negatively associated with relative humidity and temperature while the PM(10) concentration showed a strongly positive association with CO and NO(2) concentration with correlation values of 0.70 and 0.57, respectively. Furthermore, we found CO and PM(10) concentration was associated with ozone concentration. This finding will benefit local communities and the public health sector to provide a warning system for preparation and response plans to react to PM(10) episodes in their responsible areas.
The International Agency for Research on Cancer (IARC) classifies benzene in group 1 (carcinogenic to humans). Particulate matter (PM) has recently also been classified in this category. This was an advance toward prioritizing the monitoring of particles in urban areas. The aim of the present study was to assess levels of PM(2.5) and BTEX (benzene, toluene, ethylbenzene, and xylene), the influence of meteorological variables, the planetary boundary layer (PBL), and urban variables as well as risks to human health in the city of Fortaleza, Brazil, in the wet and dry periods. BTEX compounds were sampled using the 1501 method of NIOSH and determined by GC-HS-PID/FID. PM(2.5) was monitored using an air sampling pump with a filter holder and determined by the gravimetric method. Average concentrations of BTEX ranged from 1.6 to 45.5 ?g m(-3), with higher values in the wet period, which may be explained by the fact that annual distribution is influenced by meteorological variables and the PBL. PM(2.5) levels ranged from 4.12 to 33.0 ?g m(-3) and 4.18 to 86.58 ?g m(-3) in the dry and wet periods, respectively. No seasonal pattern was found for PM(2.5), probably due to the influence of meteorological variables, the PBL, and urban variables. Cancer risk ranged from 2.46E(-04) to 4.71E(-03) and 1.72E(-04) to 2.01E(-03) for benzene and from 3.07E(-06) to 7.04E(-05) and 3.08E(-06) to 2.85E(-05) for PM(2.5) in the wet and dry periods, respectively. Cancer risk values for benzene were above the acceptable limit established by the international regulatory agency in both the dry and wet periods. The results obtained of the noncarcinogenic risks for the compounds toluene, ethylbenzene, and xylene were within the limits of acceptability. The findings also showed that the risk related to PM is always greater among smokers than nonsmokers.
In order to assess the influence of atmospheric conditions and particulate matter (PM) on the seasonally varying incidence of influenza-like illnesses (ILI) in the capital of Poland-Warsaw, we analysed time series of ILI reported for the about 1.75 million residents in total and for different age groups in 288 approximately weekly periods, covering 6 years 2013-2018. Using Poisson regression, we predicted ILI by the Universal Thermal Climate Index (UTCI) as biometeorological indicator, and by PM2.5 and PM10, respectively, as air quality measures accounting for lagged effects spanning up to 3 weeks. Excess ILI incidence after adjusting for seasonal and annual trends was calculated by fitting generalized additive models. ILI morbidity increased with rising PM concentrations, for both PM2.5 and PM10, and with cooler atmospheric conditions as indicated by decreasing UTCI. While the PM effect focused on the actual reporting period, the atmospheric influence exhibited a more evenly distributed lagged effect pattern over the considered 3-week period. Though ILI incidence adjusted for population size significantly declined with age, age did not significantly modify the effect sizes of both PM and UTCI. These findings contribute to better understanding environmental conditionings of influenza seasonality in a temperate climate. This will be beneficial to forecasting future dynamics of ILI and to planning clinical and public health resources under climate change scenarios.
Tropospheric ozone is known to have adverse effects on human health. Ozone pollution events are often associated with specific atmospheric circulation conditions. Therefore, studying the relationship between atmospheric circulation and ozone is particularly important for early warning and forecasting of ozone pollution events. Focusing on the Yangtze River Delta region, particularly in four important large industrial cities (Xuzhou, Nanjing, Shanghai, and Hangzhou) in the Yangtze River Delta, the T-mode objective classification method was applied to classify the weather circulation that mainly affects the Yangtze River Delta region into nine types. Local wind fields for the four industrial cities were classified according to their propensity for ventilation, stagnation, and recirculation based on the Allwine and Whiteman method. Based on the analysis of large-scale atmospheric circulation, we concluded that certain circulation patterns correspond to excessive ozone concentrations, while other circulation patterns correspond to good air quality. Moreover, ozone pollution was not closely related to local regional transmission. The importance of high temperatures in potentiating ozone pollution was also identified in the study area, whereas the effect of relative humidity was negligible. Finally, the importance of the different scale atmospheric motions was analyzed by studying two specific ozone pollution events in Xuzhou area (March, 2019) and Nanjing area (July-August, 2017). This analysis was complemented by HYSPLIT model’s outputs to simulate the pollutant diffusion path. Regarding the first episode, ozone concentration is often closely related to the slowly approaching thermal high-pressure system. In the second episode, local transmission had little effect on the generation and spread of ozone pollution. Furthermore, and comparing the circulation conditions with local meteorological factors, it was found that the increase in ozone concentration was often accompanied by higher temperature, and the response to humidity was not clear.
This study aimed to estimate morbidity risk/number attributed to air extreme temperatures using time-stratified case crossover study and distributed lag non-linear model in a region of Iran during 2015-2019. A time-stratified case crossover design based on aggregated exposure data was used in this study. In order to have no overlap bias in the estimations, a fixed and disjointed window by using 1-month strata was used in the design. A conditional Poisson regression model allowing for over dispersion (Quasi-Poisson) was applied into Distributed Lag Non-linear Model (DLNM). Different approaches were applied to estimate Optimum Temperature (OT). In the model, the interaction effect between temperature and humidity was assessed to see if the impact of heat or cold on Hospital Admissions (HAs) are different between different levels of humidity. The cumulative effect of heat during 21 days was not significant and it was the cold that had significant cumulative adverse effect on all groups. While the number of HAs attributed to any ranges of heat, including medium, high, extreme, and even all values were negligible, but a large number was attributable to cold values; about 10000 HAs were attributable to all values of cold temperature, of which about 9000 were attributed to medium range and about 1000 and less than 500 were attributed to high and extreme values of cold, respectively. This study highlights the need for interventions in cold seasons by policymakers. The results inform researchers as well as policy makers to address both men and women and elderly when any plan or preventive program is developed in the area under study.
The occurrence of long-lasting severe heat stress, such as in July-August 2003, July 2010, or in April-May 2018 has been one of the biggest meteorological threats in Europe in recent years. The paper focuses on the biometeorological and mortality effects of the hot June that was observed in Central Europe in 2019. The basis of the study was hourly and daily Universal Thermal Climate Index (UTCI) values at meteorological stations in Poland for June 2019. The average monthly air temperature and UTCI values from 1951 to 2018 were analysed as background. Grosswetterlagen calendar of atmospheric circulation was used to assess synoptic conditions of heat wave. Several heat strain measures were applied : net heat storage (S), modelled heart rate (HR), sultriness (HSI), and UTCI index. Actual total mortality (TM) and modelled strong heat-related mortality (SHRM) were taken as indicators of biometeorological consequences of the hot June in 2019. The results indicate that prolonged persistence of unusually warm weather in June 2019 was determined by the synoptic conditions occurring over the European region and causing advection of tropical air. They led to the emergence of heat waves causing 10% increase in TM and 5 times bigger SHRM then in preceding 10 years. Such increase in SHRM was an effect of overheating and overload of circulatory system of human organism.
In this study, 30 subjects were exposed to different combinations of air temperature (T(a) : 24, 27, and 30°C) and CO(2) level (8000, 10 000, and 12 000 ppm) in a high-humidity (RH: 85%) underground climate chamber. Subjective assessments, physiological responses, and cognitive performance were investigated. The results showed that as compared with exposure to T(a) = 24°C, exposure to 30°C at all CO(2) levels caused subjects to feel uncomfortably warm and experience stronger odor intensity, while increased mental effort and greater intensity of acute health symptoms were reported. However, no significant effects of T(a) on task performance or physiological responses were found. This indicated that subjects had to exert more effort to maintain their performance in an uncomfortably warm environment. Increasing CO(2) from 8000 to 12 000 ppm at all T(a) caused subjects to report higher rates of headache, fatigue, agitation, and feeling depressed, although the results were statistically significant only at 24 and 27°C. The text typing performance and systolic blood pressure (SBP) decreased significantly at this exposure, whereas diastolic blood pressure (DBP) and thermal discomfort increased significantly. These effects suggest higher arousal/stress. No significant interaction effect of T(a) and CO(2) concentration on human responses was identified.
Extreme fine particulate matter (PM2.5) events heavily impact residents, incurring high social and medical costs. As such, it is important to understand the characteristics of extreme PM2.5 events. This study used hourly PM2.5 and meteorological data to elucidate the effects, and predict the occurrence of these extreme weather events in Taiwan. The results show that synoptic conditions are unique for extreme PM2.5 events. During the maximum mean PM2.5 concentrations, weather conditions in Taiwan were dominated by synoptic weather patterns and the north-easterly monsoon. The maximum mean surface air pressure indicator had also occurred at this time. The azimuth of the resultant surface air pressure was 36.8 degrees + 7.6 degrees, while 96.2% of winds were in the north-north-easterly and north-easterly direction. The back trajectories suggest that the cold continental high air pressure system introduced dry and cold air masses with PM2.5. The SImax (mu g/m(3)/h)(,) relative humidity (%), global solar radiation (MJ/m(2)), visibility (km), weather type I, and weather type II predictor variables of the multi-regression model accounted for 80.6% of the variance in the magnitude of maximum hourly PM2.5 events. Extreme PM2.5 events were related to synoptic weather characteristics including type, strength, and position. The new quantitative variables aid the development of an efficient alarm system for extreme PM2.5 events that will help protect public health.
BACKGROUND: Climate change and increasing risks of extreme weather events affect human health and lead to changes in the emergency department (ED) admissions and the emergency medical services (EMS) operations. For a better allocation of resources in the healthcare system, it is essential to predict ED numbers based on environmental variables. This publication aims to quantify weather, air pollution and calendar-related effects on daily ED admissions. METHODS: Analyses were based on 575,725 admissions from the web-based IVENA system recording all patients in the greater Munich area with pre-hospital emergency care in ambulance operations during 2014-2018. Linear models were used to identify statistically significant associations between daily ED admissions and calendar, meteorological and pollution factors, allowing for lag effects of one to three days. Separate analyses were performed for seasons, with additional subset analyses by sex, age and surgical versus internal department. RESULTS: ED admissions were exceptionally high during the three-week Oktoberfest, particularly for males and on the weekends, as well as during the New Year holiday. Admissions significantly increased during the years of study, decreased in spring and summer holidays, and were lower on Sundays while higher on Mondays. In the warmer seasons, admissions were significantly associated with higher temperature, adjusting for the effects of sunshine and humidity in all age groups except for the elderly. Adverse weather conditions in non-summer seasons were either linked to increasing ED admissions (from storms, gust) or decreasing them from rain. Mostly, but not exclusively, in winter, increasing ED admissions were associated with colder minimum temperatures as well as with higher NO and PM(10) concentrations. CONCLUSIONS: In addition to standard calendar-related factors, incorporating seasonal weather, air pollutant and interactions with patient demographics into resource planning models can improve the daily allocation of resources and staff of EMS operations at hospital and city levels.
BACKGROUND: Tuberculosis (TB) is a serious public health problem in China. There is evidence to prove that meteorological factors and exposure to air pollutants have a certain impact on TB. But the evidence of this relationship is insufficient, and the conclusions are inconsistent. METHODS: Descriptive epidemiological methods were used to describe the distribution characteristics of TB in Shijiazhuang in the past five years. Through the generalized linear regression model (GLM) and the generalized additive model (GAM), the risk factors that affect the incidence of TB are screened. A combination of GLM and distribution lag nonlinear model (DLNM) was used to evaluate the lag effect of environmental factors on the TB. Results were tested for robustness by sensitivity analysis. RESULTS: The incidence of TB in Shijiazhuang showed a downward trend year by year, with seasonality and periodicity. Every 10 ?g/m(3) of PM(10) changes, the RR distribution is bimodal. The first peak of RR occurs on the second day of lag (RR = 1.00166, 95% CI: 1.00023, 1.00390); the second risk period starts from 13th day of lag and peaks on15th day (RR = 1.00209, 95% CI: 1.00076, 1.00341), both of which are statistically significant. The cumulative effect of increasing 10 ?g/m(3) showed a similar bimodal distribution. Time zones where the RR makes sense are days 4-6 and 13-20. RR peaked on the 18th day (RR = 1.02239, 95% CI: 1.00623, 1.03882). The RR has a linear relationship with the concentration. Under the same concentration, the RR peaks within 15-20 days. CONCLUSION: TB in Shijiazhuang City showed a downward trend year by year, with obvious seasonal fluctuations. The air pollutant PM(10) increases the risk of TB. The development of TB has a short-term lag and cumulative lag effects. We should focus on protecting susceptible people from TB in spring and autumn, and strengthen the monitoring and emission management of PM(10) in the atmosphere.
The present study was planned to explore the pollution characteristics, health risks, and influence of atmospheric fine particulate matter (PM(2.5)) and its components on blood routine parameters in a typical industrial city (Xinxiang City) in China. In this study, 102 effective samples 28 (April-May), 19 (July-August), 27 (September-October), 28 (December-January) of PM(2.5) were collected during different seasons from 2017 to 2018. The water-soluble ions and metal elements in PM(2.5) were analyzed via ion chromatography and inductively coupled plasma-mass spectrometry. The blood routine physical examination parameters under different polluted weather conditions from January to December 2017 and 2018, the corresponding PM(2.5) concentration, temperature, and relative humidity during the same period were collected from Second People’s Hospital of Xinxiang during 2017-2018. Risk assessment was carried out using the generalized additive time series model (GAM). It was used to analyze the influence of PM(2.5) concentration and its components on blood routine indicators of the physical examination population. The “mgcv” package in R.3.5.3 statistical software was used for modeling and analysis and used to perform nonparametric smoothing on meteorological indicators such as temperature and humidity. When Akaike’s information criterion (AIC) value is the smallest, the goodness of fit of the model is the highest. Additionally, the US EPA exposure model was used to evaluate the health risks caused by different heavy metals in PM(2.5) to the human body through the respiratory pathway, including carcinogenic risk and non-carcinogenic risk. The result showed that the air particulate matter and its chemical components in Xinxiang City were higher in winter as compared to other seasons with an overall trend of winter > spring > autumn > summer. The content of nitrate (NO(3)(-)) and sulfate (SO(4)(2)(-)) ions in the atmosphere were higher in winter, which, together with ammonium, constitute the main components of water-soluble ions in PM(2.5) in Xinxiang City. Source analysis reported that mobile pollution sources (coal combustion emissions, automobile exhaust emissions, and industrial emissions) in Xinxiang City during the winter season contributed more to atmospheric pollution as compared to fixed sources. The results of the risk assessment showed that the non-carcinogenic health risk of heavy metals in fine particulate matter is acceptable to the human body, while among the carcinogenic elements, the order of lifetime carcinogenic risk is arsenic (As) > chromium(Cr) > cadmium (Cd) > cobalt(Co) > nickel (Ni). During periods of haze pollution, the exposure concentration of PM(2.5) has a certain lag effect on blood routine parameters. On the day when haze pollution occurs, when the daily average concentration of PM(2.5) rises by 10 ?g·m(-3), hemoglobin (HGB) and platelet count (PLT) increase, respectively, by 9.923% (95% CI, 8.741-11.264) and 0.068% (95% CI, 0.067-0.069). GAM model analysis predicted the maximum effect of PM(2.5) exposure concentration on red blood cell count (RBC) and PLT was reached when the hysteresis accumulates for 1d (Lag0). The maximum effect of exposure concentration ofPM(2.5) on MONO is reached when the lag accumulation is 3d (Lag2). When the hysteresis accumulates for 6d (Lag5), the exposure concentration of PM(2.5) has the greatest effect on HGB. The maximum cumulative effect of PM(2.5) on neutrophil count (NEUT) and lymphocyte (LMY) was strongest when the lag was 2d (Lag1). During periods of moderate to severe pollution, the concentration of water-soluble ions and heavy metal elements in PM(2.5) increases significantly and has a significant correlation with some blood routine indicators.
BACKGROUND: Previous studies have reported that fine particulate matter (PM(2.5)) affects the incidence of premature births. In addition, recent studies have suggested that heat waves have a negative impact on birth outcomes. However, the combined effect of PM(2.5) and heat waves on the incidence of premature birth is controversial. This study investigated the independent and combined effects of PM(2.5) and heat wave exposures during the 1st and 2nd trimesters on premature birth. METHODS: The National Statistical Office of Korea provided birth data from 2010 to 2016. Preterm birth was defined as birth between 22 and 36 weeks. To assess the exposure to PM(2.5) and heat waves, we used PM(2.5) data estimated by the Community Multiscale Air Quality Modeling System (CMAQ) and heat wave warning data provided by the Korea Meteorological Administration. A multivariate logistic regression was used to investigate the risk of preterm birth according to the exposure to PM(2.5) and heat waves during the 1st and 2nd trimesters, and it was adjusted for residential area, year of birth, season of birth, parity, education level of the mother, age of the mother, and sex of the baby. RESULTS: In the 2nd trimester, compared with the 0 h of heat wave exposure (?67 percentile), 62.50-314.00 h (79-88 percentile) and>315.00 h of heat wave exposure (>88 percentile) were both significantly associated with preterm birth (OR for 79-88 percentile, 1.037, 95% CI, 1.003-1.073; OR for > 88 percentile, 1.174, 95% CI, 1.134-1.215). However, PM(2.5) exposure was not significantly associated with preterm birth. On the other hand, in the analysis to evaluate the combined effect of PM(2.5) and heat wave exposures of the 2nd trimester, compared with 0 h of heat wave exposure (?67 percentile) and<11.64 ?g/m(3) (?25 percentile) of PM(2.5), 11.64-22.74 ?g/m(3) (?25 percentile), 22.74-27.58 ?g/m(3) (26-50 percentile), and 27.57-32.39 ?g/m(3) (51-75 percentile) of PM(2.5) exposure combined with>315.00 h of heat wave exposure (>88 percentile) were all significantly associated with preterm birth. In addition, the effect size was increased with an increase of PM(2.5) exposure (OR for ? 25 percentile, 1.148, 95% CI, 1.095-1.203; OR for 26-50 percentile, 1.248, 95% CI, 1.178-1.323; OR for 51-75 percentile, 1.370, 95% CI, 1.245-1.507). CONCLUSION: Our findings suggest that the combined effect of heat wave and PM(2.5) exposure during the 2nd trimester on the risk of preterm birth was greater than that of each exposure alone. In other words, exposure to PM(2.5) increases the impact of heat waves on the risk of preterm birth. These results indicate that control of prenatal exposure to fine particular matter and extreme temperatures is important for the prevention of preterm birth.
Heatwaves and greenness have been shown to affect health, but the evidence on their joint effects is limited. We aim to assess the associations of the combined exposure to greenness and heatwaves. We utilized five waves (February 2000-October 2014) of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), a prospective cohort of older adults aged 65. We defined heatwaves as the daily maximum temperature ?92.5th percentile with duration ?3 days. We calculated the number of heatwave days in one year before death to and cumulative Normalized Difference Vegetation Index (NDVI) during follow-up to assess individual long-term exposure to heatwaves and greenness. Cox proportional hazards models were used to assess the effects of greenness, heatwaves, and their interaction on mortality, adjusted for covariates. We conducted subgroup analyses by residence, gender, and age. There were 20,758 participants in our study, totaling 67,312 person-years of follow-up. The mean NDVI was 0·41 (SD 0.13), and the mean number of heatwave days was 8.92 (2.04). In the adjusted model, the mortality hazard ratio (HR) for each 3-day increase in heatwave days was 1.04 (95% CI 1.04, 1.05), each 0.1-unit decrease in cumulative NDVI was 1.06 (1.05, 1.07). In the adjusted model with an interaction term, the HR for the interaction term was 1.01 (1.01, 1.02) with a p-value less than 0.001. In our subgroup analyses, the HR for each 3-day increase in heatwave days was higher in urban areas than in rural areas (1.06 vs. 1.03), and the HR for 0.1-unit decrease in NDVI was higher in urban areas than in rural areas (1.08 vs. 1.04). Greenness can protect against the effect of heatwaves on mortality, and heatwaves affect the health effects of greenness. Urban dwellers have a higher response to the detrimental effect of heatwaves and a higher marginal benefit from greenness exposure.
BACKGROUND/AIM: Previous studies have suggested that the short-term ambient air pollution and temperature are associated with myocardial infarction. In this study, we aimed to conduct a time-series analysis to assess the impact of fine particulate matter (PM2.5) and temperature on acute myocardial infarction (AMI) among adults over 20 years of age in Korea by using the data from the Korean National Health Information Database (KNHID). METHODS: The daily data of 192,567 AMI cases in Seoul were collected from the nationwide, population-based KNHID from 2005 to 2014. The monitoring data of ambient PM2.5 from the Seoul Research Institute of Public Health and Environment were also collected. A generalized additive model (GAM) that allowed for a quasi-Poisson distribution was used to analyze the effects of PM2.5 and temperature on the incidence of AMI. RESULTS: The models with PM2.5 lag structures of lag 0 and 2-day averages of lag 0 and 1 (lag 01) showed significant associations with AMI (Relative risk [RR]: 1.011, CI: 1.003-1.020 for lag 0, RR: 1.010, CI: 1.000-1.020 for lag 01) after adjusting the covariates. Stratification analysis conducted in the cold season (October-April) and the warm season (May-September) showed a significant lag 0 effect for AMI cases in the cold season only. CONCLUSIONS: In conclusion, acute exposure to PM2.5 was significantly associated with AMI morbidity at lag 0 in Seoul, Korea. This increased risk was also observed at low temperatures.
The health, economic, and social impact of COVID-19 has been significant across the world. Our objective was to evaluate the association between air pollution (through NO(2) and PM(2.5) levels) and COVID-19 mortality in Spanish provinces from February 3, 2020, to July 14, 2020, adjusting for climatic parameters. An observational and ecological study was conducted with information extracted from Datadista repository (Datadista, 2020). Air pollutants (NO(2) and PM(2.5) levels) were analyzed as potential determinants of COVID-19 mortality. Multilevel Poisson regression models were used to analyze the risk of mortality after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Models were adjusted by four climatic variables (hours of solar radiation, precipitation, daily temperature and wind speed) and population size. The mean levels of PM(2.5) and NO(2) across all provinces and time in Spain were 8.7 ?g/m(3) (SD 9.7) and 8.7 ?g/m(3) (SD 6.2), respectively. High levels of PM(2.5) (IRR?=?1.016, 95% CI: 1.007-1.026), NO(2) (IRR?=?1.066, 95% CI: 1.058-1.075) and precipitation (IRR(NO2)?=?0.989, 95% CI: 0.981-0.997) were positively associated with COVID-19 mortality, whereas temperature (IRR(PM2.5)?=?0.988, 95% CI: 0.976-1.000; and IRR(NO2)?=?0.771, 95% CI: 0.761-0.782, respectively) and wind speed (IRR(NO2)?=?1.095, 95% CI: 1.061-1.131) were negatively associated with COVID-19 mortality. Air pollution can be a key factor to understand the mortality rate for COVID-19 in Spain. Furthermore, climatic variables could be influencing COVID-19 progression. Thus, air pollution and climatology ought to be taken into consideration in order to control the pandemic. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11869-021-01062-2.
The present study explored the association between daily ambient air pollution and daily emergency room (ER) visits due to acute respiratory symptoms in children of Delhi. The daily counts of ER visits (ERV) of children (?15 years) having acute respiratory symptoms were obtained from two hospitals of Delhi for 21 months. Simultaneously, data on daily concentrations of particulate matter (PM(10) and PM(2.5)), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), carbon monoxide (CO), and ozone (O(3)) and weather variables were provided by the Delhi Pollution Control Committee. K-means clustering with time-series approach and multi-pollutant generalized additive models with Poisson link function was used to estimate the 0-6-day lagged change in daily ER visits with the change in multiple pollutants levels. Out of 1,32,029 children screened, 19,120 eligible children having acute respiratory symptoms for ?2 weeks and residing in Delhi for the past 4 weeks were enrolled. There was a 29% and 21% increase in ERVs among children on high and moderate level pollution cluster days, respectively, compared to low pollution cluster days on the same day and previous 1-6 days of exposure to air pollutants. There was percentage increase (95% CI) 1.50% (0.76, 2.25) in ERVs for acute respiratory symptoms for 10 ?g/m(3) increase of NO(2) on previous day 1, 46.78% (21.01, 78.05) for 10 ?g/m(3) of CO on previous day 3, and 13.15% (9.95, 16.45) for 10 ?g/m(3) of SO(2) on same day of exposure. An increase in the daily ER visits of children for acute respiratory symptoms was observed after increase in daily ambient air pollution levels in Delhi.
Eczema resulting from external and internal factors accounts for the biggest global burden of disability owing to skin disease. This study aimed to determine an association between environmental factors and outpatient clinic visits for eczema. We collected data on dermatology clinic outpatient visits for eczema between January 2013 and July 2019. Data concerning environmental factors during this period were collated using national air quality network and air monitoring measurement parameters, namely barometric pressure, relative humidity, air temperature, and air pollutant concentrations, such as sulfur dioxide (SO(2)) and particulate matter (PM(10)). A distributed lag nonlinear model was used to investigate the relationship among eczema, environmental factors, and lagged effects. In total, 27,549 outpatient visits for eczema were recorded. In both single-factor and multiple-factor lag models, the effects of a 10-µg/m(3) increase in PM(10) and SO(2) values had significantly positive effects on the number of daily outpatient visits over a total 5 days of lag after adjusting for temperature, the number of daily outpatient visits increased with 0.87%, 7.65% and 0.69%, 5.34%, respectively. Relative humidity (RR?=?1.3870, 95% CI 1.3117-1.4665) and pressure (RR?=?1.0394, 95% CI 1.0071-1.0727) had significantly positive effects on the number of daily outpatients in single-factor lag models. However temperature had a significantly negative effect on them in the number of daily outpatients (RR?=?0.9686, 95% CI 0.9556-0.9819). Exposure to air pollution exacerbated eczema. Outpatient visits for eczema were found to have strong positive associations with changes in PM(10) levels.
Rotavirus A is the most common cause of infectious diarrhea worldwide. This study aimed to retrospectively study and analyze 4009 stool samples that were tested for viruses causing diarrhea, using multiplex reverse transcription PCR at Dankook University Hospital between 2010 and 2019. Furthermore, we determined the correlation between these factors and various climatic factors, including wind-chill temperature, relative humidity, rate of sunshine, and particulate matter. Rotavirus A infections occurred frequently in February, March, and April on an annual basis. Furthermore, during the study, the detection rate was highest at 17.0% (n=61/359) in 2011. Based on an analysis of weather big data, patient age, and period-specific infection during the summer, when the wind-chill temperature and relative humidity were high, the Rotavirus A infection rate was very low. Relative humidity (p=0.020) and particulate matter (p=0.049) were associated with the average number of monthly cases of Rotavirus A infection. However, wind chill temperature (p=0.074) and rate of sunshine (p=0.993) were not associated with the average monthly distribution of Rotavirus A cases. These results indicate that Rotavirus A infection was correlated with relative humidity and particulate matter during the study period and further the current understanding of the distribution of Rotavirus A infections resulting from climatic factors and particulate matter. This could help establish climate-related health policies to reduce the incidence of diarrhea and guide the development of vaccines against Rotavirus A.
Growing studies have shown that high temperature is a potential risk factor of schizophrenia occurrence. Therefore, elaborate analysis of different temperature exposure patterns, such as cumulative heat exposure within a time period and transient exposure at a particular time point, is of important public health significance. This study aims to utilize hourly temperature data to better capture the effects of cumulative and transient heat exposures on schizophrenia during the warm season in Hefei, China. We included the daily mean temperature and daily schizophrenia hospitalizations into the distributed lag non-linear model (DLNM) to simulate the exposure-response curve and determine the heat threshold (19.4 °C). We calculated and applied a novel indicator-daily excess hourly heat (DEHH)-to examine the effects of cumulative heat exposure over a day on schizophrenia hospitalizations. Temperature measurements at each time point were also incorporated in the DLNM as independent exposure indicators to analyze the impact of transient heat exposure on schizophrenia. Each increment of interquartile range (IQR) in DEHH was associated with elevated risk of schizophrenia hospitalizations from lag 1 (RR = 1.036, 95% confidence interval (CI): 1.016, 1.057) to lag 4 (RR = 1.025, 95% CI: 1.005, 1.046). Men and people over 40 years old were more susceptible to DEHH. Besides, we found a greater risk of heat-related schizophrenia hospitalizations between 0 a.m. and 6 a.m. This study revealed the adverse effects of accumulated and transient heat exposures on schizophrenia hospitalizations. Our findings need to be further tested in other regions with distinct regional features.
Industrialization and urbanization have aggravated the contradiction between environmental protection and economic growth, leading to health issues. While there are considerable interests in understanding the health effects of carbon emissions in the context of climate change, little is observed at regional scale and by econometric methods. Applying regression analysis on 2002-2017 Chinese provincial-level panel data, this study explores the intermediary mechanisms and regional differences of carbon emissions on residents’ health. The results indicate that: (1) Carbon emissions have a long-term adverse impact on residents’ health-a 1% rise in carbon emission adds 0.298% more outpatients and 0.162% more inpatients; (2) The rise in carbon emissions impairs residents’ health mainly by raising the temperature; (3) In areas with high levels of industrialization and urbanization, increased carbon emissions bring greater health risks; and (4) In terms of China’s unique “leading industrialization and lagging urbanization” situation, only by upgrading industrial structure, improving urbanization quality, and promoting coordinated industrialization and urbanization can the harm of carbon emissions to residents’ health be reduced. Therefore, the “one-size-fits-all” policy model is not suitable for China’s current situation. To address global “climate change” issues, China must act according to local conditions by applying mitigating (adaptive) measures in economically developed (less developed) regions. Simultaneously, the authorities must focus on the interaction and synergy between industrialization and urbanization.
Many methods have been developed to verify the correlation between meteorological conditions and air pollutants; however, all have limitations that lead to biased or incomplete conclusions. Hence, improved methods are urgently required to describe this correlation comprehensively and accurately. In this study, we demonstrated the ability of the Copula function to apply time-varying correlations between meteorological factors and atmospheric pollutants. A mixed Copula model was constructed using meteorological monitoring data for Beijing and Guangzhou from 2014 to 2019 to dynamically analyse the correlation characteristics and tail dependence between these factors. We then performed a correlation analysis for the data from the average, lower, and upper tails to obtain a more accurate and comprehensive correlation description. Dynamic analysis results demonstrated significant seasonal fluctuations between meteorological conditions and pollutants relationships. Moreover, the correlation coefficient variations differ according to their average and tail values. High humidity is more likely to be accompanied by increased NO2 compared with average summer humidity. Our proposed model represents a novel application of the Copula function for determining the factors influencing air pollution. This model emphasizes the tail dependence between meteorological conditions and air pollutant concentrations and can be used to guide more targeted prevention and control strategies.
Air pollution has been a rising concern of the 21st due to its effects to public health. Air Monitoring Stations are state-of-the-art equipment used to measure airborne pollutants concentration i.e. carbon monoxide, nitrogen oxide, sulphur dioxide, particulate matter (PM10) and ozone (O-3), as well as the meteorological parameters (i.e. ambient air temperature, relative humidity, wind speed and wind direction). Effects of climate change will affect the ambient temperature and humidity, which may induce a direct effect on air quality. In light of this, feed forward artificial neural network was employed to simulate the dynamic variations of PM10 and O-3 with relative humidity, temperature, and windspeed data being the inputs under 12 different training algorithms. Based on the results obtained, Bayesian regularization with 12 hidden neurons is the optimized network structure, with mean absolute percentage error in testing dataset of O-3 and PM10 at 51.31% and 36.49%, respectively. The models performed better in O-3 prediction as it is a photochemical reaction where ozone concentration varies according to temperature, the effect of meteorological parameters is significant. On the other hand, PM10 is not heavily dependent on meteorological parameters as the diversity of particulate matter components where most of its sources are dormant to changes in climate.
The impacts of wildfires in the western United States have been increasing for decades. Combining physical, epidemiological and economic models, this study finds that the economic damage of California wildfires in 2018 was roughly 1.5% of California’s annual gross domestic product. Recent increases in the frequency and scale of wildfires worldwide have raised concerns about the influence of climate change and associated socioeconomic costs. In the western United States, the hazard of wildfire has been increasing for decades. Here, we use a combination of physical, epidemiological and economic models to estimate the economic impacts of California wildfires in 2018, including the value of destroyed and damaged capital, the health costs related to air pollution exposure and indirect losses due to broader economic disruption cascading along with regional and national supply chains. Our estimation shows that wildfire damages in 2018 totalled $148.5 (126.1-192.9) billion (roughly 1.5% of California’s annual gross domestic product), with $27.7 billion (19%) in capital losses, $32.2 billion (22%) in health costs and $88.6 billion (59%) in indirect losses (all values in US$). Our results reveal that the majority of economic impacts related to California wildfires may be indirect and often affect industry sectors and locations distant from the fires (for example, 52% of the indirect losses-31% of total losses-in 2018 were outside of California). Our findings and methods provide new information for decision makers tasked with protecting lives and key production sectors and reducing the economic damages of future wildfires.
Climate change affects the reproductive life cycles of plants, including pollen production, which has consequences for allergic respiratory diseases. We examined climatic trends at eight locations in Bavaria, Southern Germany, with pollen time series of at least 10 years (up to 30 years in Munich). Climate change in Bavaria was characterized by a rise in temperature, but not during the winter. There is also a trend towards a more continental climate in Bavaria, which is significant in the Alps in the south of the territory. The influence of climate change depended on pollen type. Wind-pollinated arboreal species (e.g. Alnus, Betula and Cupressaceae/Taxaceae) showed advances in the start and end dates of pollen seasons and an increase in pollen load. These changes correlated negatively with late-winter (February) and spring temperatures (April). For herbaceous species, like Poaceae and Urticaceae, an earlier season was observed. Although precipitation is not a limiting factor in Southern Germany, water availability in the spring did influence the magnitude of grass pollen seasons. The effect of climatic change on the characteristics of pollen seasons was also more pronounced at higher altitudes, significant at > 800 m above sea level. Our results show that trends for start, end dates and intensity were similar at all locations, but only statistically significant at some. If we assume that earlier and more intense pollen seasons result in increases in prevalence and severity of allergic diseases, then the effect of climate change on public health in Bavaria may be significant.
Air Quality assessment and forecasting are the essentials today and they attracted many researchers. Environmental organizations regularly monitor and predict the air contaminants to make the public awareness, provide a better environment, and suitable for human health. Physical factors like climate changes, Industrialization, Fires and Urbanization are some of the factors which directly affect and reduce the air quality. All these data are time-series and real-time data. The primary pollutant is PMx that affect the respiratory systems and cardiac activity of humans. The secondary pollutants are SO2, CO, NOx, and O-3. Each has allowable range of concentration levels. In this work, meteorological elements are collected in different locations in last 5 years, with time window of 24 h and mapped to the concentration level of pollutants. The Machine Learning(ML) Methods such as Non-Linear Artificial Neural Network(ANN), Statistical Multilevel Regression, Neuro- Fuzzy and Deep Learning Long-Short-Term Memory (DL-LSTM) are used; to find the current concentration level of pollutants and will be useful for Real Time Correction (RTC) to give a feedback that can be used to reduce the contaminants in air for further days. The results are compared with the parameters such as R-2, RMSE and MAPE. Using these methods, the concentration level of contaminants is predicted with the deviation of R-2 in the range of 0.71-0.89. The results proved that DL-LSTM suits well when comparing to the ANN, Neuro-fuzzy and regression algorithms.
BACKGROUND: The impact of simultaneous adverse climate conditions in the risk of myocardial infarction (MI) was not tested before. The aim of the present study was to investigate the impact of the combination of climate and air pollution features in the number of admissions and mortality due to acute myocardial infarction in 39 municipalities of São Paulo from 2012 to 2015. METHODS: Data about MI admissions were obtained from the Brazilian public health system (DataSUS). Daily information on weather were accessed from the Meteorological Database for Teaching and Research. Additionally, daily information on air pollution were obtained from the Environmental Company of the State of São Paulo. A hierarchical cluster analysis was applied for temperature, rainfall patterns, relative air humidity, nitrogen dioxide, particulate matter 2.5 and particulate matter 10. MI admissions and in-hospital mortality were compared among the clusters. RESULTS: Data analysis produced 3 clusters: High temperature variation-Low humidity-high pollution (n=218 days); Intermediate temperature variation/high humidity/intermediate pollution (n=751 days) and low temperature variation/intermediate humidity-low pollution (n=123 days). All environmental variables were significantly different among clusters. The combination of high temperature variation, dry weather and high pollution resulted in a significant 9% increase in hospital admissions for MI [30.5 (IQR 25.0-36.0)]; patients/day; P<0.01). The differences in weather and pollution did not have impact on in-hospital mortality (P=0.88). CONCLUSION: The combination of atmospheric conditions with high temperature variation, lower temperature, dryer weather and increased inhalable particles was associated with a marked increase of hospital admissions due to MI.
Epidemiological studies have reported significant associations between weather situations and health. Cardiovascular disease is a serious chronic non-communicable disease which causes mortality and morbidity, bringing large economic burden to patients’ families. This study explored the relationship between cardiovascular disease (CVD) and weather conditions in Changchun, northeast China. The frequency distributions of 13 main circulation weather types (CWTs) were analyzed, and a comparison between air mass classification and hospital admissions was performed for various groups using an admission index (AI). The results indicated that women had a lower risk of CVD than men did. The risk of CVD for older people (aged???65 years) was lower than that for young people (aged?
IMPORTANCE: Future changes in climate are likely to adversely affect human health by affecting concentrations of particulate matter sized less than 2.5 ?m (PM2.5) and ozone (O3) in many areas. However, the degree to which these outcomes may be mitigated by reducing air pollutant emissions is not well understood. OBJECTIVE: To model the associations between future changes in climate, air quality, and human health for 2 climate models and under 2 air pollutant emission scenarios. DESIGN, SETTING, AND PARTICIPANTS: This modeling study simulated meteorological conditions over the coterminous continental US during a 1995 to 2005 baseline and over the 21st century (2025-2100) by dynamically downscaling representations of a high warming scenario from the Community Earth System Model (CESM) and the Coupled Model version 3 (CM3) global climate models. Using a chemical transport model, PM2.5 and O3 concentrations were simulated under a 2011 air pollutant emission data set and a 2040 projection. The changes in PM2.5 and O3-attributable deaths associated with climate change among the US census-projected population were estimated for 2030, 2050, 2075, and 2095 for each of 2 emission inventories and climate models. Data were analyzed from June 2018 to June 2020. MAIN OUTCOMES AND MEASURES: The main outcomes were simulated change in summer season means of the maximum daily 8-hour mean O3, annual mean PM2.5, population-weighted exposure, and the number of avoided or incurred deaths associated with these pollutants. Results are reported for 2030, 2050, 2075, and 2095, compared with 2000, for 2 climate models and 2 air pollutant emissions data sets. RESULTS: The projected increased maximum daily temperatures through 2095 were up to 7.6 °C for the CESM model and 11.8 °C for the CM3 model. Under each climate model scenario by 2095, compared with 2000, an estimated additional 21?000 (95% CI, 14?000-28?000) PM2.5-attributable deaths and 4100 (95% CI, 2200-6000) O3-attributable deaths were projected to occur. These projections decreased to an estimated 15?000 (95% CI, 10?000-20?000) PM2.5-attributable deaths and 640 (95% CI, 340-940) O3-attributable deaths when simulated using a future emission inventory that accounted for reduced anthropogenic emissions. CONCLUSIONS AND RELEVANCE: These findings suggest that reducing future air pollutant emissions could also reduce the climate-driven increase in deaths associated with air pollution by hundreds to thousands.
Since 2001, a synthesizing element in Intergovernmental Panel on Climate Change assessment reports has been a summary of how risks in a particular system could change with additional warming above pre-industrial levels, generally accompanied by a figure called the burning embers. We present a first effort to develop burning embers for climate change risks for heat-related morbidity and mortality, ozone-related mortality, malaria, diseases carried by Aedes sp., Lyme disease, and West Nile fever. We used an evidence-based approach to construct the embers based on a comprehensive global literature review. Projected risks for these health outcomes under 1.5 degrees C, 2 degrees C, and >2 degrees C of warming were used to estimate at what temperatures risk levels increased from undetectable to medium, high, and very high, from the pre-industrial baseline, under three adaptation scenarios. Recent climate change has likely increased risks from undetectable to moderate for heat-related morbidity and mortality, ozone-related mortality, dengue, and Lyme disease. Recent climate change also was assessed as likely beginning to affect the burden of West Nile fever. A detectable impact of climate change on malaria is not yet apparent but is expected to occur with additional warming. The risk for each climate-sensitive health outcome is projected to increase as global mean surface temperature increases above pre-industrial levels, with the extent and pace of adaptation expected to affect the timing and magnitude of risks. The embers may be an effective tool for informing efforts to build climate-resilient health systems including through vulnerability, capacity, and adaptation assessments and the development of national adaptation plans. The embers also can be used to raise awareness of future threats from climate change and advocate for mitigation actions to reduce the overall magnitude of health risks later this century and to expand current adaptation efforts to protect populations now.
Current models for flu-like epidemics insufficiently explain multi-cycle seasonality. Meteorological factors alone, including the associated behavior, do not predict seasonality, given substantial climate differences between countries that are subject to flu-like epidemics or COVID-19. Pollen is documented to be allergenic, it plays a role in immuno-activation and defense against respiratory viruses, and seems to create a bio-aerosol that lowers the reproduction number of flu-like viruses. Therefore, we hypothesize that pollen may explain the seasonality of flu-like epidemics, including COVID-19, in combination with meteorological variables. We have tested the Pollen-Flu Seasonality Theory for 2016-2020 flu-like seasons, including COVID-19, in the Netherlands, with its 17.4 million inhabitants. We combined changes in flu-like incidence per 100 K/Dutch residents (code: ILI) with pollen concentrations and meteorological data. Finally, a predictive model was tested using pollen and meteorological threshold values, inversely correlated to flu-like incidence. We found a highly significant inverse correlation of r(224) = -0.41 (p < 0.001) between pollen and changes in flu-like incidence, corrected for the incubation period. The correlation was stronger after taking into account the incubation time. We found that our predictive model has the highest inverse correlation with changes in flu-like incidence of r(222) = -0.48 (p < 0.001) when average thresholds of 610 total pollen grains/m(3), 120 allergenic pollen grains/m(3), and a solar radiation of 510 J/cm(2) are passed. The passing of at least the pollen thresholds, preludes the beginning and end of flu-like seasons. Solar radiation is a co-inhibitor of flu-like incidence, while temperature makes no difference. However, higher relative humidity increases with flu-like incidence. We conclude that pollen is a predictor of the inverse seasonality of flu-like epidemics, including COVID-19, and that solar radiation is a co-inhibitor, in the Netherlands.
What is already known on this topic? The health risk caused by high-temperatures depends on the interaction between high temperature exposure and the sensitivity and adaptability of the affected populations. What is added by this report? A comprehensive assessment model was established by principal component analysis using the data of 19 cities, 15 provincial-level administrative divisions and used to identify regional characteristics and major influencing factors of health vulnerability to extreme heat in China. What are the implications for public health practice? The results of the health vulnerability assessment could effectively identify the regions highly vulnerable to extreme heat in China and provide scientific evidence for the development of adaptive measures and resource allocation plans.
People with chronic obstructive pulmonary disease, cardiovascular disease, or hypertension have a high risk of developing severe coronavirus disease 2019 (COVID-19) and of COVID-19 mortality. However, the association between long-term exposure to air pollutants, which increases cardiopulmonary damage, and vulnerability to COVID-19 has not yet been fully established. We collected data of confirmed COVID-19 cases during the first wave of the epidemic in mainland China. We fitted a generalized linear model using city-level COVID-19 cases and severe cases as the outcome, and long-term average air pollutant levels as the exposure. Our analysis was adjusted using several variables, including a mobile phone dataset, covering human movement from Wuhan before the travel ban and movements within each city during the period of the emergency response. Other variables included smoking prevalence, climate data, socioeconomic data, education level, and number of hospital beds for 324 cities in China. After adjusting for human mobility and socioeconomic factors, we found an increase of 37.8% (95% confidence interval [CI]: 23.8%-52.0%), 32.3% (95% CI: 22.5%-42.4%), and 14.2% (7.9%-20.5%) in the number of COVID-19 cases for every 10-?g/m(3) increase in long-term exposure to NO(2), PM(2.5), and PM(10), respectively. However, when stratifying the data according to population size, the association became non-significant. The present results are derived from a large, newly compiled and geocoded repository of population and epidemiological data relevant to COVID-19. The findings suggested that air pollution may be related to population vulnerability to COVID-19 infection, although the extent to which this relationship is confounded by city population density needs further exploration.
In the present study, we aim to evaluate the delayed and cumulative effect of ozone (O(3)) exposure on mumps in a megacity with high population density and high humidity. We took Chongqing, a megacity in Southwest China, as the research area and 2013-2017 as the research period. A total of 49,258 confirmed mumps cases were collected from 122 hospitals of Chongqing. We employed the distributed lag nonlinear models with quasi-Poisson link to investigate the relationship between prevalence of mumps and O(3) exposure after adjusting for the effects of meteorological conditions. The results show that the effect of O(3) exposure on mumps was mainly manifested in the lag of 0-7 days. The ?single-day ;lag effect was the most obvious on the 4th day, with the relative risk (RR) of mumps occurs of 1.006 (95% CI: 1.003-1.007) per 10 ?g/m(3) in the O(3) exposure. The cumulative RR within 7 days was 1.025 (95% CI: 1.013-1.038). Our results suggest that O(3) exposure can increase the risk of mumps infection, which fills the gap of relevant research in mountainous areas with high population density and high humidity.
Evidence of the impact of ambient temperatures on emergency ambulance calls (EACs) in developing countries contributes to the improvement and complete understanding of the acute health effects of temperatures. This study aimed to examine the impacts and burden of heat on EACs in China, quantify the contributions of regional modifiers, and identify the vulnerable populations. A semi-parametric generalized additive model with a Poisson distribution was used to analyze the city-specific impacts of the daily maximum temperature (T-ma(x)) on EACs in June-August in 2014-2017. Stratified analyses by sex and age were performed to identify the vulnerable sub-populations. Meta-analysis was undertaken to illustrate the pooled associations. Further subgroup analysis, stratified by climate, latitude, and per capita disposable income (PCDI), and meta-regression analysis were conducted to explore the regional heterogeneity and quantify the contributions of possible modifiers. The city- and region-specific attributable fractions of EACs attributable to heat were calculated. Strong associations were observed between the daily T-max and total EACs in all cities. A total of 11.7% (95% confidence interval (CI): 11.2%-12.3%) of EACs were attributed to high temperatures in ten Chinese cities, and the central region with a low level of PCDI had the highest attributable fraction of 17.8% (95% CI: 17.2%-18.4%). People living in the central region with lower PCDI, and those aged 18-44 and 0-6 years were more vulnerable to heat than the others. The combined effects of PCDI, temperature, and latitude contributed 88.6% of the regional heterogeneity. The results complemented the understanding of the burden of EACs attributable to heat in developing countries and the quantitative contribution of regional modifiers.
BACKGROUND: Ozone pollution keeps deteriorating in the context of climate change. Maternal ozone exposure may be associated with low birth weight (LBW), but the results are still inconsistent. The identification of the critical exposure windows, a specific period of particular susceptibility during pregnancy, remains unresolved. We aimed to evaluate whether ozone exposure was associated with term LBW and further identify the susceptible exposure windows. METHODS: A retrospective cohort study was conducted in Guangzhou, a megacity in the most populous and economically developed city clusters in China. We included 444,096 singleton live births between January 2015 and July 2017. From 11 fixed stations, we collected daily 1-h maximum and 8-h maximum moving average ozone level (O(3)-1 h and O(3)-8 h) and calculated exposures for each participant based on their district of residence during pregnancy. We used traditional Logistic regression to estimate the trimester-specific association between ozone exposure and term LBW, and further estimated monthly- and weekly association by distributed lag models (DLMs) with Logistic regression. Odds ratios (ORs) and 95% confidence intervals (CIs) of term LBW were calculated for an interquartile range (IQR) increase in ozone exposure. Stratified analyses and heterogeneity tests were conducted by maternal age and infant sex. RESULTS: The incidence of term LBW was 1.9%. During the study period, the mean O(3)-1 h and O(3)-8 h levels were 112.6 µg/m(3) and 84.5 µg/m(3), respectively. Increased O(3)-1 h (IQR: 90 µg/m(3)) and O(3)-8 h (73 µg/m(3)) exposure during the second trimester were associated with increased risk of term LBW. At a monthly level, the term LBW risk was associated with O(3)-1 h exposure during the 4th-6th month and O(3)-8 h exposure during the 6th month. By estimating the weekly-specific association, we observed that critical exposure windows were the 15th- 26th gestational weeks for O(3)-1 h, and the 20th-26th weeks for O(3)-8 h, respectively. Estimated ORs and 95% CIs ranged from 1.012 (1.000, 1.024) to 1.023 (1.007, 1.039). When examined by subgroups, the effects were present among women ? 35 years or < 25 years old and those with female babies. CONCLUSIONS: This study provides compelling evidence that exposure to O(3) was associated with increased risk of term LBW, and gestational weeks 15th- 26th was found to be particularly susceptible. These findings provide a research basis for further mechanism examination, public health interventions, and targeted environmental policy-making.
IMPORTANCE Air pollution is a worldwide public health issue that has been exacerbated by recent wildfires, but the relationship between wildfire-associated air pollution and inflammatory skin diseases is unknown. OBJECTIVE To assess the associations between wildfire-associated air pollution and clinic visits for atopic dermatitis (AD) or itch and prescribed medications for AD management. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional time-series study assessed the associations of air pollution resulting from the California Camp Fire in November 2018 and 8049 dermatology clinic visits (4147 patients) at an academic tertiary care hospital system in San Francisco, 175 miles from the wildfire source. Participants included pediatric and adult patients with AD or itch from before, during, and after the time of the fire (October 2018 through February 2019), compared with those with visits in the same time frame of 2015 and 2016, when no large wildfires were near San Francisco. Data analysis was conducted from November 1, 2019, to May 30, 2020. EXPOSURES Wildfire-associated air pollution was characterized using 3 metrics: fire status, concentration of particulate matter less than 2.5 mu m in diameter (PM2.5), and satellite-based smoke plume density scores. MAIN OUTCOMES AND MEASURES Weekly clinic visit counts for AD or itch were the primary outcomes. Secondary outcomes were weekly numbers of topical and systemic medications prescribed for AD in adults. RESULTS Visits corresponding to a total of 4147 patients (mean [SD] age, 44.6 [21.1] years; 2322 [56%] female) were analyzed. The rates of visits for AD during the Camp Fire for pediatric patients were 1.49 (95% CI, 1.07-2.07) and for adult patients were 1.15 (95% CI, 1.02-1.30) times the rate for nonfire weeks at lag 0, adjusted for temperature, relative humidity, patient age, and total patient volume at the clinics for pediatric patients. The adjusted rate ratios for itch clinic visits during the wildfire weeks were 1.82 (95% CI, 1.20-2.78) for the pediatric patients and 1.29 (95% CI, 0.96-1.75) for adult patients. A 10-mu g/m(3) increase in weekly mean PM2.5 concentration was associated with a 7.7% (95% CI, 1.9%-13.7%) increase in weekly pediatric itch clinic visits. The adjusted rate ratio for prescribed systemic medications in adults during the Camp Fire at lag 0 was 1.45 (95% CI, 1.03-2.05). CONCLUSIONS AND RELEVANCE This cross-sectional study found that short-term exposure to air pollution due to the wildfire was associated with increased health care use for patients with AD and itch. These results may provide a better understanding of the association between poor air quality and skin health and guide health care professionals’ counseling of patients with skin disease and public health practice.
Prevalence of allergic diseases has been increasing due to multiple factors, among which climate change has had the most impact. Climate factors increase production of pollen, which also exhibits increased allergenicity. Also, as a result of climate change, there has been a shift in flowering phenology and pollen initiation causing prolonged pollen exposure. Various numerical models have been developed to understand the effect of climate change on pollen emission and transport and the impact on allergic airway diseases.
Previous studies have demonstrated that plants are a very good indicator of global environmental variations. The responses of many plant species to climate change are confirmed by aerobiological research. This paper presents an analysis of many parameters of pollen seasons in the Amaranthaceae family based on measurements of pollen concentrations in atmospheric air. Pollen samples were collected with the volumetric method at a sampling site in Lublin (Poland) in 2001-2019. The obtained data were verified using statistical analyses. Moreover, the presence of pollenkitt on the pollen grain surface was examined in fresh anthers using scanning electron and light microscopes, since there are some difficulties in identification of Amaranthaceae pollen grains deposited on microscopic slides in aerobiological analysis. The pollen season in Amaranthaceae began on average on June 23 and ended on October 5, i.e. it lasted 105 days. The peak value and annual pollen sum were characterized by the highest variability in the study years in comparison with other season characteristics. The annual pollen sum was in the range from 183 to 725. Maximum concentrations were most often recorded in the second half of August, which is associated with the greatest risk of development of pollen allergy symptoms in sensitive subjects during this period. The results obtained in the 19-year study revealed that the pollen seasons began 14 days earlier. Similarly, the end of the season was accelerated by 24 days. The response of these plants to climate change also include the reduced pollen production by representatives of this family, which was manifested by a decrease in the annual sum of daily airborne pollen concentrations, on average by 35%, and a reduction in the maximum pollen concentration, on average by more than 60%. We found that temperature in May and June had an effect on pollen release, and relative air humidity in May influenced pollen concentrations. We noted significant similarities in the pollen release rate during the last 8 years of the study. The scanning electron microscopy examinations showed that the pollen grain surface in the representative of this family was covered completely or partially with pollenkitt. Hence, the apertures characteristic for pollen in this family were poorly visible. The presence of pollenkitt on the surface of these polyaperturate pollen grains may play an important role in preventing water loss during pollen migration in the air. Our research has demonstrated the response of plants flowering in summer to climate change. The results not only have practical importance for public health in the aspect of allergy risk but can also help to assess environmental changes.
Most studies of short-term exposure to ambient air pollution and cerebrovascular diseases focused on specific stroke-related outcomes, and results were inconsistent due to data unavailability and limited sample size. It is unclear yet how ambient air pollution contributes to the total cardiovascular mortality in central China. Daily deaths from cerebrovascular diseases were obtained from the Disease Surveillance Point System (DSPs) of Wuhan Center for Disease Control and Prevention during the period from 2013 to 2019. Air pollution data were obtained from Wuhan Ecology and Environment Institute from 10 national air quality monitoring stations, including average daily PM(2.5), PM(10), SO(2), NO(2), and O(3). Average daily temperature and relative humidity were obtained from Wuhan Meteorological Bureau. We performed a Poisson regression in generalized additive models (GAM) to examine the association between ambient air pollution and cerebrovascular disease mortality. We observed a total of 84,811 deaths from cerebrovascular diseases from 1 January 2013 to 31 December 2019 in Wuhan. Short-term exposure to PM(2.5), PM(10), SO(2), and NO(2) was positively associated with daily deaths from cerebrovascular diseases, and no significant association was found for O(3). The largest effect on cerebrovascular disease mortality was found at lag0 for PM(2.5) (ERR: 0.927, 95% CI: 0.749-1.105 per 10 ?g/m3) and lag1 for PM(10) (ERR: 0.627, 95% CI: 0.493-0.761 per 10 ?g/m(3)), SO(2) (ERR: 2.518, 95% CI: 1.914, 3.122 per 10 ?g/m(3)), and NO(2) (ERR: 1.090, 95% CI: 0.822-1.358 per 10 ?g/m(3)). The trends across lags were statistically significant. The stratified analysis demonstrated that females were more susceptible to SO(2) and NO(2), while elder individuals aged above 65 years old, compared with younger people, suffered more from air pollution, especially from SO(2). Short-term exposure to PM(2.5), PM(10), SO(2), and NO(2) were significantly associated with a higher risk of cerebrovascular disease mortality, and elder females seemed to suffer more from air pollution. Further research is required to reveal the underlying mechanisms.
Air pollution is considered as an important concern all over the world. It disturbs the whole environment and produces more harmful effects to human’s healthy life. Relevant statistical reports from World Health Organization notify that air pollution play a major role in cause of diseases like asthma, lung cancer, stroke, early death and premature birth. Apart from diseases pollution also influence dangerous climate, weather conditions and may cause acid rain, global warming, ozone layer depletion, rainfall declines, etc. Therefore, it is essential to take necessary and preventive measures against air pollution. A comprehensive study is required to assess quality of ambient (outdoor) air, based on the observations of the major pollutants concentration drawn from different monitoring stations. Aiming at this problem, we proposed an ensemble based model to assess the air quality of United States from the period 2000 to 2016. In this article, we resolved the issues related to preprocessing of imbalanced dataset and improved the performance of the entire system through ensemble methods. We compared the recommended model with the existing ones. The experimental results show that the suggested model is superior to other systems and yield high accuracy, low error rate.
Admissions of newborn infants into Neonatal Intensive Care Units (NICU) has increased in the US over the last decade yet the role of environmental exposures as a risk factor for NICU admissions is under studied. Our study aims to determine the ecologic association between acute and intermediate ambient PM2.5 exposure durations and rates of NICU admissions, and to explore whether this association differs by area-level social stressors and meteorological factors. We conducted an ecologic time-series analysis of singleton neonates (N = 1,027,797) born in Florida hospitals between December 26, 2011 to April 30, 2019. We used electronic medical records (EMRs) in the OneFlorida Data Trust and included infants with a ZIP code in a Metropolitan Statistical Areas (MSA) and excluded extreme preterm births (<24wks gestation). The study outcome is the number of daily NICU admission at 28 days old or younger for each ZIP code in the study area. The exposures of interest are average same day, 1- and 2-day lags, and 1-3 weeks ambient PM2.5 concentration at the ZIP code-level estimated using inverse distance weighting (IDW) for each day of the study period. We used a zero-inflated Poisson regression mixed effects models to estimate adjusted associations between acute and intermediate PM2.5 exposure durations and NICU admissions rates. NICU admissions rates increased over time during the study period. Ambient 7-day average PM2.5 concentrations was significantly associated with incidence of NICU admissions, with an interquartile range (IQR = 2.37 ?g/m(3)) increase associated with a 1.4% (95% CI: 0.4%, 2.4%) higher adjusted incidence of daily NICU admissions. No other exposure duration metrics showed a significant association with daily NICU admission rates. The magnitude of the association between PM2.5 7-day average concentrations with NICU admissions was significantly (p < 0.05) higher among ZIP codes with higher proportions of non-Hispanic Blacks, ZIP codes with household incomes in the lowest quartile, and on days with higher relative humidity. Our data shows a positive relationship between acute (7-day average) PM2.5 concentrations and daily NICU admissions in Metropolitan Statistical Areas of Florida. The observed associations were stronger in socioeconomically disadvantaged areas, areas with higher proportions with non-Hispanic Blacks, and on days with higher relative humidity. Further research is warranted to study other air pollutants and multipollutant effects and identify health conditions that are driving these associations with NICU admissions.
Ambient air pollutants have been linked to adverse health outcomes, but evidence is still relatively rare in college students. Upper respiratory tract infection (URTI) is a common disease of respiratory system among college students. In this study, we assess the acute effect of air pollution on clinic visits of college students for URTI in Wuhan, China. Data on clinic visits due to URTI were collected from Wuhan University Hospital, meteorological factors (including daily temperature and relative humidity) provided by Wuhan Meteorological Bureau, and air pollutants by Wuhan Environmental Protection Bureau. In the present study, generalized additive model with a quasi-Poisson distribution link function was used to examine the association between ambient air pollutants (fine particulate matter (PM(2.5)), particulate matter (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), and ozone (O(3))) and the daily number of clinic visits of college students for URTI at Wuhan University Hospital in Wuhan, China. In the meantime, the model was adjusted for the confounding effects of long-term trends, seasonality, day of the week, public holidays, vacation, and meteorological factors. The best degrees of free in model were selected based on AIC (Akaike Information Criteria). The effect modification by gender was also examined. A total of 44,499 cases with principal diagnosis of URTI were included from January 1, 2016, to December 31, 2018. In single-pollutant models, the largest increment of URTI visits were found at lag 0 day in single-day lags, and the effect values in cumulative lags were greater than those in single-day lags. PM(2.5) (0.74% (95%CI: 0.05, 1.44)) at lag 0 day, PM(10) (0.61% (95%CI: 0.12, 1.11)) and O(3) (1.01% (95%CI: 0.24, 1.79)) at lag 0-1 days, and SO(2) (9.18% (95%CI: 3.27, 15.42)) and NO(2) (3.40% (95% CI:1.64, 5.19)) at lag 0-3 days were observed to be strongly and significantly associated with clinic visits for URTI. PM(10) and NO(2) were almost still significantly associated with URTI after controlling for the other pollutants in our two-pollutant models, where the effect value of SO(2) after inclusion of O(3) appeared to be the largest and the effects of NO(2) were also obvious compared with the other pollutants. Subgroups analysis demonstrated that males were more vulnerable to PM(10) and O(3), while females seemed more vulnerable to exposure to SO(2) and NO(2). This study implied that short-term exposure to ambient air pollution was associated with increased risk of URTI among college students at Wuhan University Hospital in Wuhan, China. And gaseous pollutants had more negative health impact than solid pollutants. SO(2) and NO(2) were the major air pollutants affecting the daily number of clinic visits on URTI, to which females seemed more vulnerable than males.
Conjunctivitis is one of the most common eye-related health problems and significantly influences patients’ quality of life. Whether air pollution increased the risks of conjunctivitis is still unclear. Daily counts of outpatient visits for conjunctivitis, air pollution, and meteorological data during January 1, 2015-December 31, 2019 were collected from Tai’an, China. Generalized additive model with Poisson distribution was used to estimate the relationship between air pollution and visits for conjunctivitis, after controlling for the long-term and seasonal trends, weather variables, and day of the week. The effect of air pollution on visits for conjunctivitis was generally acute and significant at the current day and disappeared after 2 days. The relative risk of conjunctivitis visits associated with per 10 ?g/m(3) increases in PM(2.5), PM(10), SO(2), and NO(2) at lag 0-2 days was 1.006 (95% CI: 1.001-1.011), 1.003 (95% CI: 1.000-1.0107), 1.023 (95% CI: 1.009-1.037), and 1.025 (95% CI: 1.010-1.040), respectively. The impact of air pollution on visits for conjunctivitis varied greatly by individual characteristics. The impact of NO(2) was higher in males than in females, with the opposite trend for SO(2) and PM(2.5). Effect estimates of air pollutants were higher among return visits for conjunctivitis, the elderly, and white-collar workers. Our study highlights that the vulnerable subpopulations should pay more attention to protect themselves from air pollution.
Air pollution has become a threat to human health in urban settlements, ultimately leading to negative impacts on overall economic system as well. Already developed nations and still developing countries both are at the risk of air pollution globally. In this scenario, this work aims to investigate the associations of asthma (AS) and acute upper respiratory infection (ARI) patients with satellite-based aerosol optical depth (AOD) and meteorological factors, i.e., relative humidity (RH), temperature (TEMP), and wind speed (WS). We applied second-generation unit root tests to provide empirical evidence. Two sets of unit root tests confirmed mix order of integration, and the other Westerlund co-integration test further showed strong linkages between estimated variables. Fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) tests were applied, only to explore that TEMP and WS lower the number of AS and ARI patients, but RH and AOD increase the number of patients. Therefore, in accordance with these findings, our study provides some important policy instruments to improve the health status in megacities of Pakistan.
Heatwaves-excessively hot ambient conditions that are considered a serious threat to human health-are often associated with poor air quality. The aim of this study was to examine the impact of an early heatwave episode in an industrialized plain in the eastern Mediterranean region (Thriasio, Greece) on human thermal discomfort and urban air quality. The heatwave occurred in mid (15-20) May 2020, shortly after some of the restrictions that were improsed to halt the spread of coronavirus disease 2019 (COVID-19) in Greece were lifted (on 4 May). The discomfort index (DI) and the daily air quality index (DAQI) were calculated on an hourly basis throughout spring 2020 (March, April, May) using data from two stations that measure meteorological parameters and air pollutant concentrations in the Thriasio Plain. The analysis showed that the air temperature increased during 7-17 May to levels that were more than 10 °C above the monthly average value (25.8 °C). The maximum measured air temperature was 38 °C (on 17 May). The results showed a high level of thermal discomfort. The DI exceeded the threshold of 24 °C for several hours during 13-20 May. Increased air pollution levels were also identified. The average DAQI was estimated as 0.83?±?0.1 and 1.14?±?0.2 at two monitoring stations in the region of interest during the heatwave. Particulate matter (diameter < 10 ?m) appeared to contribute significantly to the poor air quality. Significant correlations between the air temperature, DI, and AQSI were also identified.
OBJECTIVE: The wildfire allied environmental pollution is highly toxic and can cause significant wide-ranging damage to the regional environment, weather conditions, and it can facilitate the transmission of microorganisms and diseases. The present study aims to investigate the effect of wildfire allied pollutants, particulate matter (PM-2.5 ?m), and carbon monoxide (CO) on the dynamics of daily cases and deaths due to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in San Francisco, USA. MATERIALS AND METHODS: For this study, we selected San Francisco, one of the regions affected by the wildfires allied pollution in California, USA. The data on the COVID-19 pandemic in San Francisco, including daily new cases and new deaths were recorded from Worldometer Web. The daily environmental pollutants particulate matter (PM-2.5 ?m) and carbon monoxide (CO) were recorded from the metrological web “BAAQMD”. The daily cases, deaths, particulate matter (PM-2.5 ?m) and carbon monoxide were documented from the date of the occurrence of the first case of (SARS-CoV-2) in San Francisco, CA, USA, from March 20, 2020 to Sept 16, 2020. RESULTS: The results revealed a significant positive correlation between the environmental pollutants particulate matter (PM2.5 ?m) and the number of daily cases (r=0.203, p=0.007), cumulative cases (r=0.567, p<0.001) and cumulative deaths (r=0.562, p<0.001); whereas the PM2.5 ?m and daily deaths had no relationship (r=-0.015, p=0.842). In addition, CO was also positively correlated with cumulative cases (r=0.423, p<0.001) and cumulative deaths (r=0.315, p<0.001), however, CO had no correlation with the number of daily cases (r=0.134, p=0.075) and daily deaths (r=0.030, p=0.693). In San Francisco, one micrometer (?g/m3) increase in PM2.5 caused an increase in the daily cases, cumulative cases and cumulative deaths of SARS-COV-2 by 0.5%, 0.9% and 0.6%, respectively. Moreover, with a 1 part per million (ppm) increase in carbon monoxide level, the daily number of cases, cumulative cases and cumulative deaths increased by 5%, 9.3% and 5.3%, respectively. On the other hand, CO and daily deaths had no significant relationship. CONCLUSIONS: The wildfire allied pollutants, particulate matter PM-2.5?m and CO have a positive association with an increased number of SARS-COV-2 daily cases, cumulative cases and cumulative deaths in San Francisco. The metrological, disaster management and health officials must implement the necessary policies and assist in planning to minimize the wildfire incidences, environmental pollution and COVID-19 pandemic both at regional and international levels.
We estimate the effects of wildfire smoke exposure on infant health. Exposure to wildfire smoke is determined using the latitude and longitude coordinates corresponding to each infant’s home address and a fine-scaled spatial dataset of wildfire smoke plumes constructed in GIS from satellite images of the landscape. Using a difference-in-differences estimation strategy, model estimates show that exposure to wildfire smoke leads to a .034 increase in the probability of low birthweight.
Objective: The study examines how wildfire smoke exposure may impact health and safety in the agricultural workplace. Methods: Semi-structured interviews were conducted with agricultural employers and focus group discussions were held with farmworkers in three regions of California. Results: Agricultural employers had varying knowledge about and experience responding to poor air quality due to wildfire smoke. Respirators or masks were not mentioned as a potential protective measure when describing their safety practices. Farmworkers reported experiencing poor air quality due to wildfire smoke, although knowledge of safety precautions varied. Farmworkers reported employer and supervisors’ attitudes toward safety as having the greatest impact on the implementation of workplace safety measures. Conclusion: Adapting health promotion and workplace safety strategies to meet the multiple vulnerabilities and diverse needs of farmworkers is critical to successful implementation of workplace protection and safety measures. Given limited familiarity with the topic, wildfire smoke exposure resources are needed to assist employers and supervisors in their compliance with a new wildfire smoke safety regulation in California. To the best of our knowledge, this is the first study to explore agricultural employer and farmworker perceptions of the health and safety impacts of wildfire smoke and workplace exposure.
The air quality and human health impacts of wildfires depend on fire, meteorology, and demography. These properties vary substantially from one region to another in China. This study compared smoke from more than a dozen wildfires in Northeast, North, and Southwest China to understand the regional differences in smoke transport and the air quality and human health impacts. Smoke was simulated using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) with fire emissions obtained from the Global Fire Emission Database (GFED). Although the simulated PM2.5 concentrations reached unhealthy or more severe levels at regional scale for some largest fires in Northeast China, smoke from only one fire was transported to densely populated areas (population density greater than 100 people/km(2)). In comparison, the PM2.5 concentrations reached unhealthy level in local densely populated areas for a few fires in North and Southwest China, though they were very low at regional scale. Thus, individual fires with very large sizes in Northeast China had a large amount of emissions but with a small chance to affect air quality in densely populated areas, while those in North and Southwest China had a small amount of emissions but with a certain chance to affect local densely populated areas. The results suggest that the fire and air quality management should focus on the regional air quality and human health impacts of very large fires under southward/southeastward winds toward densely populated areas in Northeast China and local air pollution near fire sites in North and Southwest China.
Future climate change may worsen air quality in many regions. However, evaluations of this ‘climate penalty’ on air quality have typically not assessed the radiative effects of changes in short-lived aerosols. Additionally, China’s clean air goals will decrease pollutant emissions and aerosol loadings, with concomitant weakening of aerosol feedbacks. Here we assess how such weakened aerosol direct effects alter the estimates of air pollution and premature mortality in China attributable to mid-century climate change under Representative Concentration Pathway 4.5. We found that weakening aerosol direct effects cause boundary layer changes that facilitate diffusion. This reduces air-pollution exposure (similar to 4% in fine particulate matter) and deaths (13,800 people per year), which largely offset the additional deaths caused by greenhouse gas-dominated warming. These results highlight the benefits of reduced pollutant emissions through weakening aerosol direct effects and underline the potential of pollution control measures to mitigate climate penalties locked in by greenhouse gas emissions.
Environmental factors have been suspected to have effects on the development of Kawasaki disease. However, the associations have been conflicting. The aim of this study was to investigate the effects of air pollution, weather conditions, and epidemic infections on the risks for Kawasaki disease in Japan. The concentrations of air pollutants (nitric oxide, nitrogen dioxide, and sulfur dioxide); ambient weather conditions (temperature, atmospheric pressure, relative air humidity, precipitation, sunshine duration, and wind velocity); and the epidemic conditions of 14 infectious diseases in hospitalized patients with Kawasaki disease were monitored from 2011 to 2018 in Beppu, Japan. The overdispersed generalized additive model was used to evaluate the effects, and a combination model with a distributed lag nonlinear model was used to estimate the cumulative effects. The incidence of Kawasaki disease had positive associations with preceding hot temperature and increased concentrations of nitric oxide and sulfur dioxide and a negative association with epidemic herpangina. The cumulative relative risk of Kawasaki disease at 5 lagged days of increased temperature was 1.76 (95% confidence interval: 1.01-3.07). This city-level observational study suggested that the incidence of Kawasaki disease was associated with air pollution and increased temperature and may be indirectly influenced by epidemic herpangina.
Nitrogen dioxide (NO(2)) is an air pollutant discharged from combustion of human activities. Nitrous acid (HONO), measured as NO(2), is thought to impact respiratory function more than NO(2). HONO and NO(2) have an equilibrium relationship, and their reaction is affected by climate conditions. This study was conducted to discuss the extent of HONO contained in NO(2), depending on the level of urbanization. Whether climate conditions that promote HONO production enhanced the level of NO(2) measured was investigated using time series analysis. Climate and outdoor air pollution data measured in April 2009-March 2017 in urban (Tokyo, Osaka, and Aichi) and rural (Yamanashi) areas in Japan were used for the analysis. Air temperature had a trend of negative associations with NO(2), which might indicate the decomposition of HONO in the equilibrium between HONO and NO(2). The associations of relative humidity with NO(2) did not have consistent trends by prefecture: humidity only in Yamanashi was positively associated with NO(2). In high relative humidity conditions, the equilibrium goes towards HONO production, which was observed in Yamanashi, suggesting the proportion of HONO in NO(2) might be low/high in urban/rural areas.
BACKGROUND: We assessed the association between multiple meteorological factors and air pollutants and the number of acute myocardial infarction (AMI) cases using a multi-step process. METHODS: Daily AMI hospitalizations matched with 16 meteorological factors and air pollutants in 7 metropolitan provinces of the Republic of Korea from 2002 to 2017 were analyzed. We chose the best fit model after conducting the Granger causality (GC) test and examined the daily lag time effect on the orthogonalized impulse response functions. To define dose-response relationships, we performed a time series analysis using multiple generalized additive lag models based on seasons. RESULTS: A total of 196,762 cases of AMI in patients older than 20 years admitted for hospitalization were identified. The distribution of meteorological factors and air pollutants showed characteristics of a temperate climate. The GC test revealed a complex interaction between meteorological factors, including air pollutants, and AMI. The final selected factors were NO(2) and temperature; these increased the incidence of AMI on lag day 4 during summer (NO(2): population-attributable fraction [PAF], 3.9%; 95% confidence interval [CI], 3.6-4.0; mean temperature: PAF, 3.3%; 95% CI, 2.7-3.9). CONCLUSIONS: This multi-step time series analysis found that average temperature and NO(2) are the most important factors impacting AMI hospitalizations, specifically during summer. Based on the model, we were able to visualize the effect-time association of meteorological factors and air pollutants and AMI.
To curb the staggering health burden attributed to air pollution, the sustainable solution for India would be to reduce emissions in future. Here we project ambient fine particulate matter (PM2.5) exposure in India for the year 2030 under two contrasting air pollution emission pathways for two different climate scenarios based on Representative Concentration Pathways (RCP4.5 and RCP8.5). All-India average PM2.5 is expected to increase from 41.4 +/- 26.5 mu g m(-3) in 2010 to 61.1 +/- 40.8 and 58.2 +/- 37.5 mu g m(-3) in 2030 under RCP8.5 and RCP4.5 scenarios, respectively if India follows the current legislation (baseline) emission pathway. In contrast, ambient PM2.5 in 2030 would be 40.2 +/- 27.5 (for RCP8.5) and 39.2 +/- 25.4 (for RCP4.5) mu g m(-3) following the short-lived climate pollutant (SLCP) mitigation emission pathway. We find that the lower PM2.5 in the mitigation pathway (34.2% and 32.6%, respectively for RCP8.5 and RCP4.5 relative to the baseline emission pathway) would come at a cost of 0.3-0.5 degrees C additional warming due to the direct impact of aerosols. The premature mortality burden attributable to ambient PM2.5 exposure is expected to rise from 2010 to 2030, but 381,790 (5-95% confidence interval, CI 275,620-514,600) deaths can be averted following the mitigation emission pathway relative to the baseline emission pathway. Therefore, we conclude that given the expected large health benefit, the mitigation emission pathway is a reasonable tradeoff for India despite the meteorological response. However, India needs to act more aggressively as the World Health Organization (WHO) annual air quality guideline (10 mu g m(-3)) would remain far off.
The aim of the paper is to describe the spread forest fire event occurred in the Italian Alps in 2017 under extremely drought conditions. In the study the root causes of wildfires and their direct relapses to the air quality of the Western Po valley and the urban centre of Torino have been assessed by means of air pollution measurements (focused to particulate matter with reference samplers and optical particle counters OPCs), meteorological indicators and additional public data. Results show a good correlation among different urban sites and instrument technologies. Concentration data, compared with environmental conditions and historical values describe the clear impact of fires on both local and regional air quality. Indeed, the deferred impact of wildfires on the local wood biomass energy supply chain is briefly outlined. (C) 2019 Published by Elsevier Ltd.
PURPOSE: Global warming and air pollution are among the most important problems all over the world. Considering the key role of traffic officers who saliently deal with traffic management and are in full, constant and direct exposure to thermal stress and air pollution index, this study aims to investigate the simultaneous effects of these factors on the body temperature of traffic officers in the main squares of Tehran. METHODS: This study was conducted among 119 traffic officers who were working in 29 squares of Tehran, located near the active pollutant’s stations during 2017. Samples were selected by the census method. Environmental parameters such as air temperature (dry and wet), radiation temperature, the level of air pollution in the main squares and characteristics of officers such as body temperature and the Wet-Bulb-Globe-Temperature (WBGT) index were evaluated. Data were analyzed through independent samples t-test and factorial ANOVA with a p value of p???0.05 in SPSS software. RESULTS: There was no significant relationship between air pollution and ear temperature, but there was a statistically significant difference between the wet-bulb temperature and the ear temperature (t?=?26.4, P?
The interactive effects between particulate matter (PM) and heat waves on circulatory mortality are under-researched in the context of global climate change. We aimed to investigate the interaction between heat waves and PM on circulatory mortality in Fuzhou, a city characterized by a humid subtropical climate and low level of air pollution in China. We collected data on deaths, pollutants, and meteorology in Fuzhou between January 2016 and December 2019. Generalized additive models were used to examine the effect of PM on circulatory mortality during the heat waves, and to explore the interaction between different PM levels and heat waves on the circulatory mortality. During heat waves, circulatory mortality was estimated to increase by 8.21% (95% confidence intervals (CI): 0.32-16.72) and 3.84% (95% CI: 0.28-7.54) per 10 ?g/m(3) increase of PM(2.5) and PM(10), respectively, compared to non-heat waves. Compared with low-level PM(2.5) concentration on non-heat waves layer, the high level of PM(2.5) concentration on heat waves layer has a significant effect on the cardiovascular mortality, and the effect value was 48.35% (95% CI: 6.37-106.89). Overall, we found some evidence to suggest that heat waves can significantly enhance the impact of PM on circulatory mortality.
Climate change is a global threat that poses significant risks to pregnant women and to their developing fetus and newborn. Educating pregnant women about the risks to their pregnancy may improve maternal and child health outcomes. Prior research suggests that presenting health information in narrative format can be more effective than a didactic format. Hence, the purpose of this study was to test the effectiveness of two brief educational interventions in a diverse group of pregnant women (n = 151). Specifically, using a post-test only randomized experiment, we compared the effectiveness of brief information presented in a narrative format versus a didactic format; both information formats were also compared to a no information control group. Outcome measures included pregnant women’s actual and perceived knowledge, risk perception, affective assessment, self-efficacy, intention to take protective behaviors, and subsequent information seeking behavior. As hypothesized, for all outcome measures, the narrative format was more effective than the didactic format. These results suggest the benefits of a narrative approach (versus a didactic approach) to educating pregnant women about the maternal and child health threats posed by climate change. This study adds to a growing literature on the effectiveness of narrative-based approaches to health communication.
The coal-dominated electricity system poses major challenges for India to tackle air pollution and climate change. Although the government has issued a series of clean air policies and low-carbon energy targets, a key barrier remains enforcement. Here, we quantify the importance of policy implementation in India’s electricity sector using an integrated assessment method based on emissions scenarios, air quality simulations, and health impact assessments. We find that limited enforcement of air pollution control policies leads to worse future air quality and health damages (e.g., 14?200 to 59?000 more PM(2.5)-related deaths in 2040) than when energy policies are not fully enforced (5900 to 8700 more PM(2.5)-related deaths in 2040), since coal power plants with end-of-pipe controls already emit little air pollution. However, substantially more carbon dioxide will be emitted if low-carbon and clean coal policies are not successfully implemented (e.g., 400 to 800 million tons more CO(2) in 2040). Thus, our results underscore the important role of effectively implementing existing air pollution and energy policy to simultaneously achieve air pollution, health, and carbon mitigation goals in India.
Particularly in rural settings, there has been little research regarding the health impacts of fine particulate matter (PM2.5) during the wildfire season smoke exposure period on respiratory diseases, such as influenza, and their associated outbreaks months later. We examined the delayed effects of PM2.5 concentrations for the short-lag (1-4 weeks prior) and the long-lag (during the prior wildfire season months) on the following winter influenza season in Montana, a mountainous state in the western United States. We created gridded maps of surface PM2.5 for the state of Montana from 2009 to 2018 using spatial regression models fit with station observations and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness data. We used a seasonal quasi-Poisson model with generalized estimating equations to estimate weekly, county-specific, influenza counts for Montana, associated with delayed PM2.5 concentration periods (short-lag and long-lag effects), adjusted for temperature and seasonal trend. We did not detect an acute, short-lag PM2.5 effect nor short-lag temperature effect on influenza in Montana. Higher daily average PM2.5 concentrations during the wildfire season was po- sitively associated with increased influenza in the following winter influenza season (expected 16% or 22% increase in influenza rate per 1 mu g/m(3) increase in average daily summer PM2.5 based on two analyses, p = 0.04 or 0.008). This is one of the first observations of a relationship between PM2.5 during wildfire season and influenza months later.
BACKGROUND: Suicidal ideation is subject to serious underestimation among existing public health studies. While numerous factors have been recognized in affecting suicidal thoughts and behaviors (STB), the associated environmental risks have been poorly understood. Foremost among the various environment risks were air pollution, in particular, the PM2.5. The present study attempted to examine the relationship between PM(2.5) level and local weekly index of suicidal ideation (ISI). METHODS: Using Internet search query volumes in Baidu (2017), the largest internet search engine in China, we constructed a prefectural panel data (278 prefectures, 52?weeks) and employed dynamic panel GMM system estimation to analyze the relationship between weekly concentration of PM2.5 (Mean?=?87??g·m(-?3)) and the index of suicidal ideation (Mean?=?49.9). RESULTS: The results indicate that in the spring and winter, a 10??g·m(-?3) increase in the prior week’s PM(2.5) in a Chinese city is significantly associated with 0.020 increase in ISI in spring and a 0.007 increase in ISI in winter, after taking account other co-pollutants and meteorological conditions. CONCLUSION: We innovatively proposed the measure of suicidal ideation and provided suggestive evidence of a positive association between suicidal ideation and PM(2.5) level.
BACKGROUND: Few epidemiological investigations have focused on the influence of environmental temperature on human sperm quality. Here, we evaluated the potential association between ambient temperature and human sperm quality in Wuhan, China, and examined the interactive effect of particulate matter (PM(2.5)) and temperature. METHODS: 1780 males who had been living in Wuhan for no less than three months and received semen analysis at the Department of Reproductive Medicine in Renmin Hospital of Wuhan University between April 8, 2013 and June 30, 2015 were recruited. Daily mean meteorological data and air pollution data (PM(2.5), O(3) and NO(2)) in Wuhan between 2013 and 2015 were collected. A generalized linear model was used to explore the associations between ambient temperature and sperm quality (including sperm concentration, percentage of normal sperm morphology, and progressive motility) at 0-9, 10-14, 15-69, 70-90, and 0-90?days before semen examination, and the interaction between temperature and PM(2.5). RESULTS: The associations between ambient temperature and sperm quality were an inverted U-shape at five exposure windows, except for a lag of 0-9?days for sperm concentration. A 1?°C increase in ambient temperature above the thresholds was associated with a 2.038 (1.292?~?2.783), 1.814 (1.217?~?2.411), 1.458 (1.138?~?1.777), 0.934(0.617?~?1.251) and 1.604 (1.258?~?1.951) decrease in the percentage of normal sperm morphology at lag 0-9, lag 10-14, lag 15-69, lag 70-90, and lag 0-90?days, respectively. The interaction p-values of PM(2.5) and temperature were mostly less than 0.05 at five exposure windows. When ambient temperature exposure levels were above the thresholds, a 0.979 (0.659-1.299) and 3.559 (0.251?~?6.867) decrease in percentage of normal sperm morphology per 1?°C increase in temperature at lag 0-90?days was observed in the PM(2.5)???P(50) group and PM(2.5)?>?P(50) group, respectively. CONCLUSIONS: Our results indicate that exposure to ambient temperature has a threshold effect on sperm quality, and PM(2.5) enhances the effect of temperature on sperm quality when temperatures are above the threshold.
BACKGROUND AND OBJECTIVES: The number of pediatric patients diagnosed with influenza types A and B is increasing annually, especially in temperate regions such as Shanghai (China). The onset of pandemic influenza viruses might be attributed to various ambient meteorological factors including temperature, relative humidity (Rh), and PM(1) concentrations, etc. The study aims to explore the correlation between the seasonality of pandemic influenza and these factors. METHODS: We recruited pediatric patients aged from 0 to 18?years who were diagnosed with influenza A or B from July 1st, 2017 to June 30th, 2019 in Shanghai Children’s Medical Centre (SCMC). Ambient meteorological data were collected from the Shanghai Meteorological Service (SMS) over the same period. The correlation of influenza outbreak and meteorological factors were analyzed through preliminary Pearson’s r correlation test and subsequent time-series Poisson regression analysis using the distributed lag non-linear model (DLNM). RESULTS: Pearson’s r test showed a statistically significant correlation between the weekly number of influenza A outpatients and ambient meteorological factors including weekly mean, maximum, minimum temperature and barometric pressure (P?
Wildfire smoke (WFS) increases the risk of respiratory hospitalizations. We evaluated the association between WFS and asthma healthcare utilization (AHCU) during the 2013 wildfire season in Oregon. WFS particulate matter <= 2.5 mu m in diameter (PM2.5) was estimated using a blended model of in situ monitoring, chemical transport models, and satellite-based data. Asthma claims and place of service were identified from Oregon All Payer All Claims data from 1 May 2013 to 30 September 2013. The association with WFS PM2.5 was evaluated using time-stratified case-crossover designs. The maximum WFS PM2.5 concentration during the study period was 172 mu g/m(3). A 10 mu g/m(3) increase in WFS increased risk in asthma diagnosis at emergency departments (odds ratio [OR]: 1.089, 95% confidence interval [CI]: 1.043-1.136), office visit (OR: 1.050, 95% CI: 1.038-1.063), and outpatient visits (OR: 1.065, 95% CI: 1.029-1.103); an association was observed with asthma rescue inhaler medication fills (OR: 1.077, 95% CI: 1.065-1.088). WFS increased the risk for asthma morbidity during the 2013 wildfire season in Oregon. Communities impacted by WFS could see increases in AHCU for tertiary, secondary, and primary care.
OBJECTIVES: to evaluate the effect of air pollution (ozone – O3 and particulate matter <=10 ?m and <=2.5 ?m - PM10 and PM2.5) on the severity of Raynaud's phenomenon (RP) secondary to systemic sclerosis (SSc). DESIGN: cross-sectional, observational, and single centre study. SETTING AND PARTICIPANTS: all consecutive SSc patients residing in Lombardy (Northern Italy) were enrolled. PM10, PM2.5, and O3 concentrations were calculated for each patient at municipality resolution in the week before the evaluation. Similar considerations were made for meteorological variables (temperature and humidity). MAIN OUTCOME MEASURES: patients were asked to assess RP severity during the week before the evaluation according to a visual analogue scale (VAS). Ordinal logistic regression models were fitted to evaluate the short-term effect of temperature and air pollution with respect to RP. A univariate linear regression model was created to consider the association between temperature and pollutants. RESULTS: in this study, 87 SSc patients were enrolled. Temperature was confirmed to strongly influence RP severity. PM10 and PM.5 were found to significantly worsen RP severity for the first four days before the evaluation, including the day of the visit, and as mean up to six days before the evaluation. O3 seemed to exert a protective effect on RP severity that was significant for the first four days before the evaluation, including the day of the visit, and as mean up to seven days before the evaluation. CONCLUSIONS: since the overwhelming effect of temperature on RP, final conclusions about the exact contribution of pollutants on RP severity cannot be drawn because of the strong inter-correlation between air pollution and temperature.
In this study, the spatial pattern and temporal evolution of PM(2.5) over North China Plain (NCP) and Northeast China (NEC) during 2014-2018 was investigated. The annual mean PM(2.5) shows clear decreasing trends over time, but the seasonal mean PM(2.5) as well as the seasonal total duration and frequency of haze days shows large inter-annual fluctuation. Based on the atmospheric stagnation index (ASI), this study examined the correlation between ASI and haze events over NCP and NEC. Detailed analysis indicates that location dependency exists of ASI in the capability of capturing the haze events, and the ability is limited in NCP. Therefore, we first propose two alternative methods in defining the ASI to either account for the lag effect or enlarge the threshold value of wind speed at 500 hPa. The new methods can improve the ability of ASI to explain the haze events over NEC, though marginal improvement was achieved in NCP. Furthermore, this study constructed the equation based on the boundary layer height and wind speed at 10-meter, apparently improving the ability in haze capture rate (HCR), a ratio of haze days during the stagnation to the total haze days. Based on a multi-model ensemble analyses under Representative Concentration Pathway (RCP) 8.5, we found that by the end of this century, climate change may lead to increases in both the duration and frequency of wintertime stagnation events over NCP. In contrast, the models predict a decrease in stagnant events and the total duration of stagnation in winter over NEC.
Hot weather episodes are globally associated with excess mortality rates. Elevated ozone concentrations occurring simultaneously also contribute to excess mortality rates during these episodes. However, the relative importance of both stressors for excess mortality rates is not yet known and assumed to vary from region to region. This study analyzes time series of daily observational data of air temperature and ozone concentrations for eight of the largest German cities during the years 2000 and 2017 with respect to the relative importance of both stressors for excess mortality rates in each city. By using an event-based risk approach, various thresholds for air temperature were explored for each city to detect hot weather episodes that are statistically associated with excess mortality rates. Multiple linear regressions were then calculated to investigate the relative contribution of variations in air temperature and ozone concentrations to the explained variance in mortality rates during these episodes, including the interaction of both predictors. In all cities hot weather episodes were detected that are related to excess mortality rates. Across the cities, a strong increase of this relation was observed around the 95th percentile of each city-specific air temperature distribution. Elevated ozone concentrations during hot weather episodes are also related to excess mortality rates in all cities. In general, the relative contribution of elevated ozone concentrations on mortality rates declines with increasing air temperature thresholds and occurs mainly as a statistically inseparable part of the air temperature impact. The specific strength of the impact of both stressors varies across the investigated cities. City-specific drivers such as background climate and vulnerability of the city population might lead to these differences and could be the subject of further research. These results underline strong regional differences in the importance of both stressors during hot weather episodes and could thus help in the development of city-specific heat- ozone-health warning systems to account for city-specific features.
Previous studies have revealed associations of meteorological factors with tuberculosis (TB) cases. However, few studies have examined their lag effects on TB cases. This study was aimed to analyse nonlinear lag effects of meteorological factors on the number of TB notifications in Hong Kong. Using a 22-year consecutive surveillance data in Hong Kong, we examined the association of monthly average temperature and relative humidity with temporal dynamics of the monthly number of TB notifications using a distributed lag nonlinear models combined with a Poisson regression. The relative risks (RRs) of TB notifications were >1.15 as monthly average temperatures were between 16.3 and 17.3 °C at lagged 13-15 months, reaching the peak risk of 1.18 (95% confidence interval (CI) 1.02-1.35) when it was 16.8 °C at lagged 14 months. The RRs of TB notifications were >1.05 as relative humidities of 60.0-63.6% at lagged 9-11 months expanded to 68.0-71.0% at lagged 12-17 months, reaching the highest risk of 1.06 (95% CI 1.01-1.11) when it was 69.0% at lagged 13 months. The nonlinear and delayed effects of average temperature and relative humidity on TB epidemic were identified, which may provide a practical reference for improving the TB warning system.
Climate change and air pollution are two independent risk factors to cardiovascular diseases (CVD). Few studies investigated their interaction and potential effect modification of one another in developing countries. Individual level CVD hospital admission (ICD10: I00-I99) data for 1 January 2011 to 31 October 2016 were obtained from seven private hospitals in Cape Town. NO(2), SO(2), PM(10), temperature and relative humidity data were obtained from the South African Weather Services and the City of Cape Town. A case-crossover epidemiological study design and conditional logistic regression model were applied. Various cut-off values were applied to classify cold and warm days. In total, 54,818 CVD hospital admissions were included in the study. In general, on warm and cold days the 15-64 years old group was more at risk for CVD hospitalization with increasing air pollution levels compared to all ages combined or the ??65 years old group. Females appeared to be more at risk than males with increasing PM(10) levels. In contrast, males were more vulnerable to the effects of NO(2) and SO(2) than females. The study showed the modification effect of temperature on air pollution associated with CVD hospital admissions. The consideration of such interaction will help in policy making and public health interventions dealing with climate change-related health risks.
Exposure to particulate matter of smaller than 2.5 ?m in diameter (PM(2.5)) is linked to increased human mortality, and could be further complicated by concurrent ambient air temperatures. Published reports indicate that the association between ambient temperatures and mortality due to PM(2.5) exposure is dissimilar across different geographic areas. Thus, it is unclear how ambient temperatures at different geographic locations can together modulate the influence of PM(2.5) on mortality. In this paper, we examined how temperature modulated the association between mortality and PM(2.5) exposure in 15 Chinese cities during 2014-2016. For analysis, First, Poisson generalized additive models under different temperature stratifications (<10th, 10-90th, and >90th temperature percentiles) was used to estimate PM(2.5) associations to mortality, which were specific to different cities. Second, we used a meta-analysis to combine the effects at each temperature stratum and region (southern and northern China). Results revealed that high temperatures (daily mean temperature >90th percentile) robustly amplified observed associations of mortality and PM(2.5) exposure, and the modifications were heterogeneous geographically. In the northern regions, a 10 ?g/m(3) increment in PM(2.5) was associated with 0.18%, 0.28%, and 1.54% increase in non-accidental mortalities and 0.33%, 0.39%, and 1.32% increase in cardiovascular mortalities at low, moderate, and high temperature levels, respectively. In the southern regions, a 10 ?g/m(3) increment in PM(2.5) was associated with 0.52%, 0.62%, and 1.90% increase in non-accidental mortalities and 0.55%, 0.98%, and 2.25% increase in cardiovascular mortalities at low, moderate, and high temperature levels, respectively. It is concluded that temperature altered PM(2.5)-mortality associations in southern and northern China synergistically, but the effect was more pronounced in the south. Therefore, geography and temperature need to be considered when studying how PM(2.5) affects health.
To investigate the correlation between environmental-meteorological factors and daily visits for acute otitis media (AOM) in Lanzhou, China. METHODS: Data were collected in 2014-2016 by the Departments of Otolaryngology-Head and Neck Surgery at two hospitals in Lanzhou. Relevant information, including age, sex and visiting time, was collected. Environmental data included air quality index, PM10, PM2.5, O(3), CO, NO(2) and SO(2), and meteorological data included daily average temperature (T, °C), daily mean atmospheric pressure (AP, hPa), daily average relative humidity (RH, %) and daily mean wind speed (W, m/s). The SPSS22.0 software was used to generate Spearman correlation coefficients in descriptive statistical analysis, and the R3.5.0 software was used to calculate relative risk (RR) and to obtain exposure-response curves. The relationship between meteorological-environmental parameters and daily AOM visits was summarized. RESULTS: Correlations were identified between daily AOM visits and CO, O(3), SO(2), CO, NO(2), PM2.5 and PM10 levels. NO(2), SO(2), CO, AP, RH and T levels significantly correlated with daily AOM visits with a lag exposure-response pattern. The effects of CO, NO(2), SO(2) and AP on daily AOM visits were significantly stronger compared to other factors (P < 0.01). O(3), W, T and RH were negatively correlated with daily AOM visits. The highest RR lagged by 3-4 days. CONCLUSIONS: The number of daily AOM visits appeared to be correlated with short-term exposure to mixed air pollutants and meteorological factors from 2014 through 2016 in Lanzhou.
A thunderstorm is a risk factor for severe respiratory allergy or asthma attacks in patients suffering from pollen/spore allergy. This study aimed to investigate the changes in the spectrum and quantity of pollen and fungal spores in the air of Bratislava during summer storms as well as the impact of selected environmental parameters on these changes. Pollen/spore samples were collected using a Burkard volumetric aerospore trap during summer 2016. To identify those types of pollen/spores that may harm human health during the storm episodes, we analysed how the concentration of individual bioparticles in the air changed during pre-storm/storm/post-storm periods. The effect of environmental variables on the concentration of selected pollen/spore types was evaluated through Spearman’s correlation analysis. The results of our study suggest that thunderstorm-related respiratory allergy symptoms in the study area may be caused by (1) spores of Myxomycetes, the airborne concentration of which increases due to an increase in wind speed during the pre-storm period; (2) ruptured pollen and Diatripaceae spores, the concentration of which increases due to increase in precipitation and relative air humidity, respectively, during the storm period; and (3) spores of Fusarium and Leptosphaeria, the concentration of which increases due to increase in precipitation and air temperature, respectively, during the post-storm period.
Extreme wildfire events are becoming more common and while the immediate risks of particulate exposures to susceptible populations (i.e., elderly, asthmatics) are appreciated, the long-term health effects are not known. In 2017, the Seeley Lake (SL), MT area experienced unprecedented levels of wildfire smoke from July 31 to September 18, with a daily average of 220.9 mu g/m(3). The aim of this study was to conduct health assessments in the community and evaluate potential adverse health effects. The study resulted in the recruitment of a cohort (n= 95, average age: 63 years), for a rapid response screening activity following the wildland fire event, and two follow-up visits in 2018 and 2019. Analysis of spirometry data found a significant decrease in lung function (FEV1/FVC ratio: forced expiratory volume in first second/forced vital capacity) and a more than doubling of participants that fell below the lower limit of normal (10.2% in 2017 to 45.9% in 2018) one year following the wildfire event, and remained decreased two years (33.9%) post exposure. In addition, observed FEV(1)was significantly lower than predicted values. These findings suggest that wildfire smoke can have long-lasting effects on human health. As wildfires continue to increase both here and globally, understanding the health implications is vital to understanding the respiratory impacts of these events as well as developing public health strategies to mitigate the effects.
OBJECTIVE: The study aimed to determine if and how environmental factors correlated with asthma admission rates in geographically different parts of Guangxi province in China. SETTING: Guangxi, China. PARTICIPANTS: This study was done among 7804 asthma patients. PRIMARY AND SECONDARY OUTCOME MEASURES: Spearman correlation coefficient was used to estimate correlation between environmental factors and asthma hospitalisation rates in multiple regions. Generalised additive model (GAM) with Poisson regression was used to estimate effects of environmental factors on asthma hospitalisation rates in 14 regions of Guangxi. RESULTS: The strongest effect of carbon monoxide (CO) was found on lag1 in Hechi, and every 10?µg/m(3) increase of CO caused an increase of 25.6% in asthma hospitalisation rate (RR 1.26, 95%?CI 1.02 to 1.55). According to the correlation analysis, asthma hospitalisations were related to the daily temperature, daily range of temperature, CO, nitrogen dioxide (NO(2)) and particulate matter (PM(2.5)) in multiple regions. According to the result of GAM, the adjusted R(2) was high in Beihai and Nanning, with values of 0.29 and 0.21, which means that environmental factors are powerful in explaining changes of asthma hospitalisation rates in Beihai and Nanning. CONCLUSION: Asthma hospitalisation rate was significantly and more strongly associated with CO than with NO(2), SO(2) or PM(2.5) in Guangxi. The risk factors of asthma exacerbations were not consistent in different regions, indicating that targeted measures should differ between regions.
OBJECTIVE: To assess short term mortality risks and excess mortality associated with exposure to ozone in several cities worldwide. DESIGN: Two stage time series analysis. SETTING: 406 cities in 20 countries, with overlapping periods between 1985 and 2015, collected from the database of Multi-City Multi-Country Collaborative Research Network. POPULATION: Deaths for all causes or for external causes only registered in each city within the study period. MAIN OUTCOME MEASURES: Daily total mortality (all or non-external causes only). RESULTS: A total of 45?165?171 deaths were analysed in the 406 cities. On average, a 10 µg/m(3) increase in ozone during the current and previous day was associated with an overall relative risk of mortality of 1.0018 (95% confidence interval 1.0012 to 1.0024). Some heterogeneity was found across countries, with estimates ranging from greater than 1.0020 in the United Kingdom, South Africa, Estonia, and Canada to less than 1.0008 in Mexico and Spain. Short term excess mortality in association with exposure to ozone higher than maximum background levels (70 µg/m(3)) was 0.26% (95% confidence interval 0.24% to 0.28%), corresponding to 8203 annual excess deaths (95% confidence interval 3525 to 12?840) across the 406 cities studied. The excess remained at 0.20% (0.18% to 0.22%) when restricting to days above the WHO guideline (100 µg/m(3)), corresponding to 6262 annual excess deaths (1413 to 11?065). Above more lenient thresholds for air quality standards in Europe, America, and China, excess mortality was 0.14%, 0.09%, and 0.05%, respectively. CONCLUSIONS: Results suggest that ozone related mortality could be potentially reduced under stricter air quality standards. These findings have relevance for the implementation of efficient clean air interventions and mitigation strategies designed within national and international climate policies.
The objective of this study is to analyze the short-term effects of atmospheric pollutant concentrations (PM(10), NO(2) and O(3)) and heat and cold waves on the number of pre-term births and cases of low birth weight related to Saharan dust advection and biomass combustion. The dependent variables used in this analysis were the total number of births, births with low weight (>2.500?g) and pre-term births (<37?weeks), that occurred at the province level. Data provided by the NSI included: days with Saharan dust intrusion or biomass advection classified in terms of information provided by MITECO for each of the nine regions in Spain. A representative city was selected for reach region in which the registered average daily concentrations of PM(10), NO(2) and O(3) (?g/m(3)) were used. These were also provided by MITECO. The daily maximum and daily minimum temperature (°C) used was those registered by the meteorological observatory station located in each province capital, provided by AEMET. Using Poisson log linear regression models, the associated relative risks (RR) were measured as well as the population attributable risk (PAR) corresponding to the variables that resulted statistically significant at p?
BACKGROUND: Evidence on the acute effect of short-term exposure to nitrogen dioxide (NO(2)) on years of life lost (YLL) is rare, especially in multicity setting. METHODS: We conducted a time series study among 48 major Chinese cities covering more than 403 million people from 2013 to 2017. The relative percentage changes of NO(2)-YLL were estimated by generalized additive models in each city, then were pooled to generate average effects using random-effect models. In addition, stratified analyses by individual demographic factors and temperature as well as meta-regression analyses incorporating city-specific air pollutant concentrations, meteorological conditions, and socioeconomic indicators were performed to explore potential effect modification. RESULTS: A 10 ?g/m(3) increase in two-day moving average (lag01) NO(2) concentration was associated with 0.64% (95% CI: 0.47%, 0.81%), 0.47% (95% CI: 0.27%, 0.68%), and 0.68% (95% CI: 0.34%, 1.02%) relative increments in YLL due to nonaccidental causes, cardiovascular diseases (CVD), and respiratory diseases (RD), respectively. These associations were generally robust to the adjustment of co-pollutants, except for NO(2)-CVD that might be confounded by fine particulate matter. The increased YLL induced by NO(2) were more pronounced in elderly people, hotter days, and cities characterized by less severe air pollution or higher temperature. CONCLUSIONS: Our results demonstrated robust evidence on the associations between NO(2) exposure and YLL due to nonaccidental causes, CVD, and RD, which provided novel evidence to better understand the disease burden related to NO(2) pollution and to facilitate allocation of health resources targeting high-risk subpopulation.
Short-term effects of air pollution on the health of residents in the Metropolitan Area of Monterrey, Mexico were assessed from 2012-2015 using a time-series approach. Guadalupe had the highest mean concentrations for SO(2), CO and O(3); whereas Santa Catarina showed the highest NO(2) concentrations. Escobedo and Garcia registered the highest levels for PM(10). Only PM(10) and O(3) exceeded the maximum permissible values established in the Mexican official standards. Most of pollutants and municipalities showed a great number of associations between an increase of 10% in their current concentrations and mortality, especially for people >60 years. Different scenarios resulting from climatic change were built (increases of 5-25% in daily mean temperature), but only the increase of 25% (5 °C) showed a significant association with air pollutant concentrations and mortality. All pollutants and municipalities showed significant increases in relative risk indexes (RRI) resulting from an increase of 5 °C when people >60 years was considered. Results were comparable to those reported by other authors around the world. The RRI were low but significant, and thus are of public concern. This study demonstrated that the elderly is strongly threatened not only by atmospheric pollution but also by climatic change scenarios in warm and semiarid places.
Particulate matter from natural sources such as desert dust causes harmful effects for health. Asian dust (AD) increases the risk of acute myocardial infarction (AMI). However, little is known about the risk of myocardial infarction with nonobstructive coronary arteries (MINOCA), compared to myocardial infarction with coronary artery disease (MI-CAD). Using a time-stratified case-crossover design and conditional logistic regression models, the association between short-term exposure to AD whereby decreased visibility (
BACKGROUND: PM(2·5) is an important but modifiable environmental risk factor, not only for pulmonary diseases and cancers, but for cardiovascular health. However, the evidence regarding the association between air pollution and acute cardiac events, such as out-of-hospital cardiac arrest (OHCA), is inconsistent, especially at concentrations lower than the WHO daily guideline (25 ?g/m(3)). This study aimed to determine the associations between exposure to ambient air pollution and the incidence of OHCA. METHODS: In this nationwide case-crossover study, we linked prospectively collected population-based registry data for OHCA in Japan from Jan 1, 2014, to Dec 31, 2015, with daily PM(2·5), carbon monoxide (CO), nitrogen dioxide (NO(2)), photochemical oxidants (O(x)), and sulphur dioxide (SO(2)) exposure on the day of the arrest (lag 0) or 1-3 days before the arrest (lags 1-3), as well as the moving average across days 0-1 and days 0-3. Daily exposure was calculated by averaging the measurements from all PM(2·5) monitoring stations in the same prefecture. The effect of PM(2·5) on risk of all-cause or cardiac OHCA was estimated using a time-stratified case-crossover design coupled with conditional logistic regression analysis, adjusted for daily temperature and relative humidity. Single-pollutant models were also investigated for the individual gaseous pollutants (CO, NO(2), O(x), and SO(2)), as well as two-pollutant models for PM(2·5) with these gaseous pollutants. Subgroup analyses were done by sex and age. FINDINGS: Over the 2 years, 249?372 OHCAs were identified, with 149?838 (60·1%) presumed of cardiac origin. The median daily PM(2·5) was 11·98 ?g/m(3) (IQR 8·13-17·44). Each 10 ?g/m(3) increase in PM(2·5) was associated with increased risk of all-cause OHCA on the same day (odds ratio [OR] 1·016, 95% CI 1·009-1·023) and at lags of up to 3 days, ranging from OR 1·015 (1·008-1·022) at lag 1 to 1·033 (1·023-1·043) at lag 0-3. Results for cardiac OHCA were similar (ORs ranging from 1·016 [1·007-1·025] at lags 1 and 2 to 1·034 [1·021-1·047] at lag 0-3). Patients older than 65 years were more susceptible to PM(2·5) exposure than younger age groups but no sex differences were identified. CO, O(x), and SO(2) were also positively associated with OHCA while NO(2) was not. However, in two-pollutant models of PM(2·5) and gaseous pollutants, only PM(2·5) (positive association) and NO(2) (negative association) were independently associated with increased risk of OHCA. INTERPRETATION: Short-term exposure to PM(2·5) was associated with an increased risk of OHCA even at relatively low concentrations. Regulatory standards and targets need to incorporate the potential health gains from continual air quality improvement even in locations already meeting WHO standards. FUNDING: None.
BACKGROUND: Research investigating the effect of air pollution on diabetes incidence is mostly conducted in Europe and the United States and often produces conflicting results. The link between meteorological factors and diabetes incidence remains to be explored. We aimed to explore associations between air pollution and diabetes incidence and to estimate the nonlinear and lag effects of meteorological factors on diabetes incidence. METHODS: Our study included 19,000 people aged ?60 years from the Binhai New District without diabetes at baseline. The generalized additive model (GAM) and the distributed lag nonlinear model (DLNM) were used to explore the effect of air pollutants and meteorological factors on the incidence of diabetes. In the model combining the GAM and DLNM, the impact of each factor (delayed by 30 days) was first observed separately to select statistically significant factors, which were then incorporated into the final multivariate model. The association between air pollution and the incidence of diabetes was assessed in subgroups based on age, sex, and body mass index (BMI). RESULTS: We found that cumulative RRs for diabetes incidence were 1.026 (1.011-1.040), 1.019 (1.012-1.026), and 1.051 (1.019-1.083) per 10??g/m(3) increase in PM(2.5), PM(10), and NO(2), respectively, as well as 1.156 (1.058-1.264) per 1?mg/m(3) increase in CO in a single-pollutant model. Increased temperature, excessive humidity or dryness, and shortened sunshine duration were positively correlated with the incidence of diabetes in single-factor models. After adjusting for temperature, humidity, and sunshine, the risk of diabetes increased by 9.2% (95% confidence interval (CI):2.1%-16.8%) per 10??g/m(3) increase in PM(2.5). We also found that women, the elderly (?75 years), and obese subjects were more susceptible to the effect of PM(2.5). CONCLUSION: Our data suggest that PM(2.5) is positively correlated with the incidence of diabetes in the elderly, and the relationship between various meteorological factors and diabetes in the elderly is nonlinear.
BACKGROUND: Extreme ambient temperatures and air quality have been directly associated with various human diseases from several studies around the world. However, few analyses involving the association of these environmental circumstances with mental and behavioral disorders (MBD) have been carried out, especially in developing countries such as Brazil. METHODS: A time series study was carried out to explore the associations between daily air pollutants (SO(2), NO(2), O(3), and PM(10)) concentrations and meteorological variables (temperature and relative humidity) on hospital admissions for mental and behavioral disorders for Curitiba, Brazil. Daily hospital admissions from 2010 to 2016 were analyzed by a semi-parametric generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM). RESULTS: Significant associations between environmental conditions (10??g/m(3) increase in air pollutants and temperature °C) and hospitalizations by MBD were found. Air temperature was the environmental variable with the highest relative risk (RR) at 0-day lag for all ages and sexes analyzed, with RR values of 1.0182 (95% CI: 1.0009-1.0357) for men, and 1.0407 (95% CI: 1.0230-1.0587) for women. Ozone exposure was a risk for all women groups, being higher for the young group, with a RR of 1.0319 (95% CI: 1.0165-1.0483). Elderly from both sexes were more susceptible to temperature variability, with a RR of 1.0651 (95% CI: 1.0213-1.1117) for women, and 1.0215 (95% CI: 1.0195-1.0716) for men. CONCLUSIONS: This study suggests that temperatures above and below the thermal comfort threshold, in addition to high concentrations of air pollutants, present significant risks on hospitalizations by MBD; besides, there are physiological and age differences resulting from the effect of this exposure.
OBJECTIVE: The objective of this study was to identify frequency, severity, and risk factors associated with bronchiolitis in Puerto Rican children. METHODS: A cross-sectional was study performed at 4 emergency departments of Puerto Rico’s metropolitan area, between June 2014 and May 2015. We included children younger than 24 months, with a clinical diagnosis of bronchiolitis, who were born and living in Puerto Rico at the time of recruitment. A physician-administered questionnaire inquiring about the patient’s medical, family, and social history and a bronchiolitis severity assessment were performed. Daily weather conditions were monitored, and aeroallergens were collected with an air sample and precision weather station within the metropolitan area to evaluate environmental factors. RESULTS: We included 600 patients for 12 months. More than 50% of the recruited patients had a previous episode of bronchiolitis, of which 40% had been hospitalized. Older age (odds ratio [OR], 18.3; 95% confidence interval [CI], 9.2-36.5), male sex (OR, 1.6; 95% CI, 1.1-2.4), history of asthma (OR, 8.9; 95% CI, 3.6-22), allergic rhinitis (OR, 3.6; 95% CI, 1.8-7.4), and smoke exposure by a caretaker (OR, 2.3; 95% CI, 1.2-4.4) were predictors of bronchiolitis episodes. Bronchiolitis episodes were associated with higher severity score (P = 0.040), increased number of atopic factors (P < 0.001), and higher number of hospitalizations (P < 0.001). CONCLUSIONS: This study identifies Puerto Rican children who may present a severe clinical course of disease without traditional risk factors. Atopy-related factors are associated with frequency and severity of bronchiolitis. Puerto Rican children present risk factors related to atopy earlier in life, some of which may be modified to prevent the subsequent development of asthma.
Fine particulate matter (PM2.5) raises human health concerns since it can deeply penetrate the respiratory system and enter the bloodstream, thus potentially impacting vital organs. Strong winds transport and disperse PM2.5, which can travel over long distances. Smoke from wildfires is a major episodic and seasonal hazard in Southern California (SoCal), where the onset of Santa Ana winds (SAWs) in early fall before the first rains of winter is associated with the region’s most damaging wildfires. However, SAWs also tend to improve visibility as they sweep haze particles from highly polluted areas far out to sea. Previous studies characterizing PM2.5 in the region are limited in time span and spatial extent, and have either addressed only a single event in time or short time series at a limited set of sites. Here we study the space-time relationship between daily levels of PM2.5 in SoCal and SAWs spanning 1999-2012 and also further identify the impact of wildfire smoke on this relationship. We used a rolling correlation approach to characterize the spatial-temporal variability of daily SAW and PM2.5. SAWs tend to lower PM2.5 levels, particularly along the coast and in urban areas, in the absence of wildfires upwind. On the other hand, SAWs markedly increase PM2.5 in zip codes downwind of wildfires. These empirical relationships can be used to identify windows of vulnerability for public health and orient preventive measures.
Over the last decades, energy and pollution control policies combined with structural changes in the economy decoupled emission trends from economic growth, increasingly also in the developing world. It is found that effective implementation of the presently decided national pollution control regulations should allow further economic growth without major deterioration of ambient air quality, but will not be enough to reduce pollution levels in many world regions. A combination of ambitious policies focusing on pollution controls, energy and climate, agricultural production systems and addressing human consumption habits could drastically improve air quality throughout the world. By 2040, mean population exposure to PM2.5 from anthropogenic sources could be reduced by about 75% relative to 2015 and brought well below the WHO guideline in large areas of the world. While the implementation of the proposed technical measures is likely to be technically feasible in the future, the transformative changes of current practices will require strong political will, supported by a full appreciation of the multiple benefits. Improved air quality would avoid a large share of the current 3-9 million cases of premature deaths annually. At the same time, the measures that deliver clean air would also significantly reduce emissions of greenhouse gases and contribute to multiple UN sustainable development goals. This article is part of a discussion meeting issue ‘Air quality, past present and future’.
Pollen is an important component of bioaerosol and the distribution of pollen and its relationship with meteorological parameters can be analyzed to better prevent hay fever. Pollen assemblages can also provide basic data for analyzing the relationship between bioaerosol and PM. We collected 82 samples of airborne pollen using a TSP large flow pollen collector from June 1, 2015 to June 1, 2016, from central Zhanjiang city in South China. We also conducted a survey of the nearby vegetation at the same time, in order to characterize the major plant types and their flowering times. We then used data on daily temperature, relative humidity, precipitation, vapor pressure and wind speed from a meteorological station in the center of Zhanjiang City to assess the relationship between the distribution of airborne pollen and meteorological parameters. Our main findings and conclusions are as follows: (1) We identified 15 major pollen types, including Pinus, Castanopsis, Myrica, Euphorbiaceae, Compositae, Gramineae, Microlepia and Polypodiaceae. From the vegetation survey, we found that the pollen from these taxa represented more than 75% of local pollen, while the pollen of Podocarpus, Dacrydium and other regional pollen types represented less than 25%. (2) The pollen concentrations varied significantly in different seasons. The pollen concentrations were at a maximum in spring, consisting mainly of tree pollen; the pollen concentrations were at an intermediate level in autumn and winter, consisting mainly of herb pollen and fern spores; and the pollen concentrations in summer were the lowest, consisting mainly of fern spores. (3) Analysis of the relationship between airborne pollen concentrations and meteorological parameters showed that variations in the pollen concentrations were mainly affected by temperature and relative humidity. In addition, there were substantial differences in these relationships in different seasons. In spring, pollen concentrations were mainly affected by temperature; in summer, they were mainly affected by the direction of the maximum wind speed; in autumn, they were mainly affected by relative humidity and temperature; and in winter, they were mainly affected by relative humidity and wind speed. Temperature and relative humidity promote plant growth and flowering. Notably, the variable wind direction in summer and the increased wind speed in winter and spring are conductive to pollen transmission. (4) Of the 15 major pollen types, Moraceae, Artemisia and Gramineae are the main allergenic pollen types, with peaks in concentration during April-May, August-September, and October-December, respectively. (5) Atypical weather conditions have substantial effects on pollen dispersal. In South China, the pollen concentrations in the sunny day were usually significantly higher than that of the rainy day. The pollen concentrations increased in short rainy days, which usually came from the Herb and Fern pollen. The pollen concentrations decreased in continuous rainy days especially for the Tree and Shrub pollen. the pollen concentrations in the sunny days were usually significantly higher than that in the rainy days. The pollen concentrations increased in short and strong rainfall.
The incidence of asthma exacerbation depends on atmospheric conditions, including such meteorological factors as the ambient temperature, relative air humidity or concentration of atmospheric aerosols. An assessment of relations between the frequency of asthma exacerbation and environmental conditions was made according to the meteorological components, the biometeorological index UTCI (Universal Thermal Climate Index), as well as selected air quality parameters, including concentrations of PM(10) and PM(2.5). The study was conducted on the basis of a retrospective analysis of medical data collected at the Independent Public Hospital of Tuberculosis and Pulmonary Diseases in Olsztyn (Poland). Our analysis of patient data (from 1 January 2013 until 31 December 2017) showed a significant correlation between the number of asthma exacerbation and the UTCI value. More frequent asthma exacerbations are observed in patients aged over 65 years when air humidity increases. The UTCI values contained within class 5, describing thermoneutral conditions, correspond to an average frequency of asthma exacerbation. A decline in the UTCI value leads to a reduced number of asthma exacerbation, while a rise makes the cases of asthma exacerbations increase.
BACKGROUND: Gastroesophageal reflux disease (GERD) is a highly prevalent disease of the upper gastrointestinal tract, and it is associated with environmental and lifestyle habits. Due to an increasing interest in the environment, several groups are studying the effects of meteorological factors and air pollutants (MFAPs) on disease development. AIM: To identify MFAPs effect on GERD-related medical utilization. METHODS: Data on GERD-related medical utilization from 2002 to 2017 were obtained from the National Health Insurance Service of Korea, while those on MFAPs were obtained from eight metropolitan areas and merged. In total, 20071900 instances of GERD-related medical utilizations were identified, and 200000 MFAPs were randomly selected from the eight metropolitan areas. Data were analyzed using a multivariable generalized additive Poisson regression model to control for time trends, seasonality, and day of the week. RESULTS: Five MFAPs were selected for the prediction model. GERD-related medical utilization increased with the levels of particulate matter with a diameter ? 2.5 ?m (PM(2.5)) and carbon monoxide (CO). S-shaped and inverted U-shaped changes were observed in average temperature and air pollutants, respectively. The time lag of each variable was significant around nine days after exposure. CONCLUSION: Using five MFAPs, the final model significantly predicted GERD-related medical utilization. In particular, PM(2.5) and CO were identified as risk or aggravating factors for GERD.
The relationship between the fires occurrences and diseases is an essential issue for making public health policy and environment protecting strategy. Thanks to the Internet, today, we have a huge amount of health data and fire occurrence reports at our disposal. The challenge, therefore, is how to deal with 4 Vs (volume, variety, velocity and veracity) associated with these data. To overcome this problem, in this paper, we propose a method that combines techniques based on Data Mining and Knowledge Discovery from Databases (KDD) to discover spatial and temporal association between diseases and the fire occurrences. Here, the case study was addressed to Malaria, Leishmaniasis and respiratory diseases in Brazil. Instead of losing a lot of time verifying the consistency of the database, the proposed method uses Decision Tree, a machine learning-based supervised classification, to perform a fast management and extract only relevant and strategic information, with the knowledge of how reliable the database is. Namely, States, Biomes and period of the year (months) with the highest rate of fires could be identified with great success rates and in few seconds. Then, the K-means, an unsupervised learning algorithms that solves the well-known clustering problem, is employed to identify the groups of cities where the fire occurrences is more expressive. Finally, the steps associated with KDD is perfomed to extract useful information from mined data. In that case, Spearman’s rank correlation coefficient, a nonparametric measure of rank correlation, is computed to infer the statistical dependence between fire occurrences and those diseases. Moreover, maps are also generated to represent the distribution of the mined data. From the results, it was possible to identify that each region showed a susceptible behaviour to some disease as well as some degree of correlation with fire outbreak, mainly in the drought period.
This time-series study collects data on stroke-related mortality, years of life lost (YLL), air pollution, and meteorological conditions in 96 Chinese cities from 2013 to 2016 and proposes a three-stage strategy to generate the national and regional estimations of avoidable YLL, gains in life expectancy and stroke-related population attributable fraction by postulating that the daily fine particulate matter (PM(2.5)) has been kept under certain standards. A total of 1 318 911 stroke deaths are analyzed. Each 10 µg m(-3) increment in PM(2.5) at lag(03) is associated with a city-mean increase of 0.31 (95% CI: 0.19, 0.44) years of life lost from stroke. A number of 914.11 (95% CI: 538.28, 1288.94) years of city-mean life lost from stoke could be avoided by attaining the WHO’s Air Quality Guidelines (AQG) (25 µg m(-3)). Moreover, by applying the AQG standard, 0.11 (0.08, 0.15) years of life lost might be prevented for each death, and about 0.91% (95% CI: 0.62%, 1.19%) of the total years of life lost from stroke might be explained by the daily excess PM(2.5) exposure. This study indicates that stroke patients can have a longer life expectancy if stricter PM(2.5) standards are put in place, especially ischemic stroke patients.
Here, we develop a dry eye syndrome (DES) incidence rate prediction model using air pollutants (PM10, NO2, SO2, O-3, and CO), meteorological factors (temperature, humidity, and wind speed), population rate, and clinical data for South Korea. The prediction model is well fitted to the incidence rate (R-2= 0.9443 and 0.9388,p< 2.2 x 10(-16)). To analyze regional deviations, we classify outpatient data, air pollutant, and meteorological factors in 16 administrative districts (seven metropolitan areas and nine states). Our results confirm NO(2)and relative humidity are the factors impacting regional deviations in the prediction model.
There is a lack of evidence on causal effects of air pollution on gestational age (GA) at delivery. METHODS: Inverse probability weighting (IPW) quantile regression was applied to derive causal marginal population-level GA reduction for GA percentiles associated with increased ambient particulate matter with diameter <2.5 ?m (PM(2.5)) levels at maternal residential address for each trimester and the month preceding delivery using Massachusetts birth registry 2001 to 2015. Stratified analyses were conducted for neonatal sex, maternal age/race/education, and extreme ambient temperature conditions. RESULTS: For neonates at 2.5th, 10th, 25th, 50th, 75th, and 97.5th percentiles of GA at delivery, we estimated an adjusted GA reduction of 4.2 days (95% confidence interval [CI] = 3.4, 5.0), 1.9 days (1.6, 2.1), 1.2 days (1.0, 1.4), 0.82 days (0.72, 0.92), 0.74 days (0.54, 0.94), and 0.54 days (0.15, 0.93) for each 5 ?g/m3 increment in third trimester average PM(2.5) levels. Final gestational month average exposure yielded a similar effect with greater magnitude. Male neonates and neonates of younger (younger than 35 years) and African American mothers as well as with high/low extreme temperature exposure in third trimester were more affected. Estimates were consistently higher at lower GA percentiles, indicating preterm/early-term births being more affected. Low-exposure analyses yielded similar results, restricting to areas with PM(2.5) levels under US ambient annual standard of 12 ?g/m(3). CONCLUSIONS: Prenatal exposure to PM(2.5) in late pregnancy reduced GA at delivery among Massachusetts neonates, especially among preterm/early-term births, male neonates, and neonates of younger and African American mothers. Exposure to extremely high/low temperature amplifies the effect of PM(2.5) on GA.
This is the first study to look at future temporal urban heath island (UHI) trends of Athens (Greece) under different UHI intensity regimes. Historical changes in the Athens UHI, spanning 1971-2016, were assessed by contrasting two air temperature records from stable meteorological stations in contrasting urban and rural settings. Subsequently, we used a five-member regional climate model (RCM) sub-ensemble from EURO-CORDEX with a horizontal resolution of 0.11 degrees (similar to 12 x 12 km) to simulate air temperature data, spanning the period 1976-2100, for the two station sites. Three future emissions scenarios (RCP2.6, RCP4.5, and RCP8.5) were implanted in the simulations after 2005 covering the period 2006-2100. Two 20-year historical reference periods (1976-1995 and 1996-2015) were selected with contrasting UHI regimes; the second period had a stronger intensity. The daily maximum and minimum air temperature data (T(max)and T-min) for the two reference periods were perturbed to two future periods, 2046-2065 and 2076-2095, under the three RCPs, by applying the empirical quantile mapping (eqm) bias-adjusting method. This novel approach allows us to assess future temperature developments in Athens under two UHI intensity regimes that are mainly forced by differences in air pollution and heat input. We found that the future frequency of days with T-max> 37 degrees C in Athens was only different from rural background values under the intense UHI regime. Thus, the impact of heatwaves on the urban environment of Athens is dependent on UHI intensity. There is a large increase in the future frequency of nights with T-min> 26 degrees C in Athens under all UHI regimes and climate scenarios; these events remain comparatively rare at the rural site. This large urban amplification of the frequency of extremely hot nights is likely caused by air pollution. Consequently, local mitigation policies aimed at decreasing urban atmospheric pollution are expected to be highly effective in reducing urban temperatures and extreme heat events in Athens under future climate change scenarios. Such policies directly have multiple benefits, including reduced electricity (energy) needs, improved living quality and strong health advantages (heat- and pollution-related illness/deaths).
In October 2017, hundreds of wildfires ravaged the forests of the north and centre of Portugal. The fires were fanned by strong winds as tropical storm Ophelia swept the Iberian coast, dragging up smoke (together with Saharan dust from north-western Africa) into higher western European latitudes. Here we analyse the long-range transport of particulate matter (PM(10)) and study associations between PM(10) and short-term mortality in the Portuguese population exposed to PM(10) due to the October 2017 wildfires, the worst fire sequence in the country over the last decades. We analysed space- and ground-level observations to track the smoke plume and dust trajectory over Portugal and Europe, and to access PM(10) concentrations during the wildfires. The effects of PM(10) on mortality were evaluated using satellite data for exposure and Poisson regression models. The smoke plume covered most western European countries (including Spain, France, Belgium and the Netherlands), and reached the United Kingdom, where the population was exposed in average to an additional PM(10) level of 11.7 µg/m(3) during seven smoky days (three with dust) in relation to the reference days (days without smoke or dust), revealing the impact of the wildfires on distant populations. In Portugal, the population was exposed in average to additional PM(10) levels that varied from 16.2 to 120.6 µg/m(3) in smoky days with dust and from 6.1 to 20.9 µg/m(3) in dust-free smoky days. Results suggest that PM(10) had a significant effect on the same day natural and cardiorespiratory mortalities during the month of October 2017. For every additional 10 µg/m(3) of PM(10), there was a 0.89% (95% confidence interval, CI, 0-1.77%) increase in the number of natural deaths and a 2.34% (95% CI, 0.99-3.66%) increase in the number of cardiorespiratory-related deaths. With rising temperatures and a higher frequency of storms due to climate change, PM from Iberian wildfires together with NW African dust will tend to be more often transported into Northern European countries, which may carry health threats to areas far from the ignition sites.
Mycotoxin-producing Aspergilli (Circumdati, Flavi, and Nigri), usually associated with contaminated food, may also cause respiratory disorders and are insufficiently studied in water-damaged indoor environments. Airborne (N = 71) and dust borne (N = 76) Aspergilli collected at post-flood and control locations in Croatia resulted in eleven different species based on their calmodulin marker: A. ochraceus, A. ostianus, A. pallidofulvus, A. sclerotiorum, and A. westerdijkiae (Circumdati); A. flavus (Flavi); and A. tubingensis, A. welwitschiae, A. niger, A. piperis, and A. uvarum (Nigri). Most of the airborne (73%) and dust borne (54%) isolates were found at post-flood locations, and the highest concentrations measured in indoor air (5720 colony-forming units (CFU)/m(3)) and dust (2.5 × 10(5) CFU/g) were up to twenty times higher than in the control locations. A. flavus dominated among airborne isolates (25%) at the unrepaired locations, while 56% of the dust borne Aspergilli were identified as A. tubingensis and A. welwitschiae. The ability of identified isolates to produce mycotoxins aflatoxin B(1) (AFB(1)), fumonisin B(2) (FB(2)), and ochratoxin A were assessed by LC-MS analysis. All ochratoxin A (OTA)-producing Circumdati belonged to A. westerdijkiae (13.7 ± 15.81 µg/mL); in the section, FlaviA. flavus produced AFB(1) (2.51 ± 5.31 µg/mL), while A. welwitschiae and A. niger (section Nigri) produced FB(2) (6.76 ± 13.51 µg/mL and 11.24 ± 18.30 µg/mL, respectively). Water damage dominantly supported the occurrence of aflatoxigenic A. flavus in indoor environments. Yet unresolved, the causal relationship of exposure to indoor Aspergilli and adverse health effects may support the significance of this research.
As climate change progresses, understanding the impact on human health associated with the temperature and air pollutants has been paramount. However, the predicted effect on temperature associated with particulate matter (PM(10)) is not well understood due to the difficulty in predicting the local and regional PM(10). We compared temperature-attributable mortality for the baseline (2003-2012), 2030s (2026-2035), 2050s (2046-2055), and 2080s (2076-2085) based on a distributed lag non-linear model by simultaneously considering assumed levels of PM(10) on historical and projected temperatures under representative concentration pathway (RCP) scenarios. The considered projected PM(10) concentrations of 35, 50, 65, 80, and 95 ?g/m(3) were based on historical concentration quantiles. Our findings confirmed greater temperature-attributable risks at PM(10) concentrations above 65 ?g/m(3) due to the modification effect of the pollutants on temperature. In addition, this association between temperature and PM(10) was higher under RCP8.5 than RCP4.5. We also confirmed regional heterogeneity in temperature-attributable deaths by considering PM(10) concentrations in South Korea with higher risks in heavily populated areas. These results demonstrated that the modification association of air pollutants on health burdens attributable to increasing temperatures should be considered by researchers and policy makers.
Particulate matter (PM), a major component of air pollution, is an important carrier medium of various chemical and microbial compounds. Air pollution due to PM could increase the level of bacteria and associated adverse health effects. Staphylococci as important opportunistic pathogens that cause hospital- and community-acquired infections may transmit through air. This study aimed to obtain knowledge about the concentration of airborne bacteria as well as staphylococci associated with particulate matter with a diameter of less than 2.5 micrometers (PM(2.5)) in ambient air. The impact of meteorological factors including ultraviolet (UV) index, wind speed, temperature, and moisture on microbial concentrations was also investigated. Quartz filters were used to collect PM(2.5) and associated bacteria in ambient air of a semiarid area. Airborne bacteria were quantified by culture method and Staphylococcus species identified by molecular methods. The mean (SD) concentration of PM(2.5) and airborne bacteria was 64.83 (24.87) µg/m(3) and 38 (36) colony forming unit (CFU)/m(3), respectively. The results showed no significant correlation between the levels of PM(2.5) and concentrations of bacteria (p?<?0.05). Staphylococcus species were detected in 8 of 37 (22%) samples in a concentration from 3 to 213 CFU/m(3). S. epidermidis was detected with the highest frequency followed by S. gallinarum and S. hominis, but S. aureus and methicillin-resistant Staphylococcus aureus (MRSA) were not detected. No significant correlation between the concentrations of bacteria with meteorological parameters was observed (p?<?0.05). Our finding showed that, although the study area is sometimes subject to air pollution from PM(2.5), the concentration of PM(2.5)- associated bacteria is relatively low. According to the results, PM(2.5) may not be a source of community-associated staphylococcal infections.
OBJECTIVE: To test the hypothesis that particulate matter with an aerodynamic diameter of less than 10 ?m (PM(10)) and temperature are associated with an increased risk of adverse clinical outcomes in patients with atrial fibrillation (AF) taking vitamin K antagonists (VKAs). PATIENTS AND METHODS: We included patients with AF whose condition was stable while taking VKAs (international normalized ratio, 2.0 to 3.0) for 6 months seen in a tertiary hospital (recruitment from May 1, 2007, to December 1, 2007). During a median follow-up of 6.5 years (interquartile range, 4.3 to 7.9 years), ischemic strokes, major bleeding, adverse cardiovascular events, and mortality were recorded. From 2007 to 2016, data on average temperature and PM(10) were compared with clinical outcomes. RESULTS: The study group included 1361 patients (663 [48.7%] male; median age, 76 years [interquartile range, 71 to 81 years]). High PM(10) and low temperatures were associated with higher risk of major bleeding (adjusted hazard ratio [aHR], 1.44; 95% CI, 1.22 to 1.70 and aHR, 1.03; 95% CI, 1.01 to 1.05, respectively) and mortality (aHR, 1.50; 95% CI, 1.34 to 1.69 and aHR, 1.04; 95% CI, 1.02 to 1.06, respectively); PM(10) was also associated with ischemic stroke and temperature with cardiovascular events. The relative risk (RR) for cardiovascular events and mortality increased in months in the lower quartile of temperature (RR, 1.12; 95% CI, 1.04 to 1.21 and RR, 1.41; 95% CI, 1.15 to 1.74, respectively). Comparing seasons, there were higher risks of cardiovascular events in spring, autumn, and winter than in summer, whereas the risk of mortality increased only in winter. CONCLUSION: In patients with AF taking VKAs, high PM(10) and low temperature were associated with increased risk of ischemic stroke and cardiovascular events, respectively. Both factors increased major bleeding and mortality risks, which were higher during colder months and seasons.
A probe of a patient, seeking help in an emergency ward of a French hospital in late December 2019 because of Influenza like symptoms, was retrospectively tested positive to COVID-19. Despite the early appearance of the virus in Europe, the prevalence and virulence appeared to be low for several weeks, before the spread and severity of symptoms increased exponentially, yet with marked spatial and temporal differences. Here, we compare the possible linkages between peaks of fine particulate matter (PM2.5) and the sudden, explosive increase of hospitalizations and mortality rates in the Swiss Canton of Ticino, and the Greater Paris and London regions. We argue that these peaks of fine particulate matter are primarily occurring during thermal inversion of the boundary layer of the atmosphere. We also discuss the influence of Saharan dust intrusions on the COVID-19 outbreak observed in early 2020 on the Canary Islands. We deem it both reasonable and plausible that high PM2.5 concentrations-favored by air temperature inversions or Saharan dust intrusions-are not only modulating but even more so boosting severe outbreaks of COVID-19. Moreover, desert dust events-besides enhancing PM2.5 concentrations-can be a vector for fungal diseases, thereby exacerbating COVID-19 morbidity and mortality. We conclude that the overburdening of the health services and hospitals as well as the high over-mortality observed in various regions of Europe in spring 2020 may be linked to peaks of PM2.5 and likely particular weather situations that have favored the spread and enhanced the virulence of the virus. In the future, we recommended to monitor not only the prevalence of the virus, but also to consider the occurrence of weather situations that can lead to sudden, very explosive COVID-19 outbreaks.
Organophosphate esters (OPEs) in atmospheric fine particles (PM(2.5)) were comprehensively investigated in the Beijing-Tianjin-Hebei (BTH) region from April 2016 to March 2017. The concentrations of ?(8)OPEs in all the five sampling sites ranged from 90 to 8291 pg/m(3) (mean 1148 ± 1239 pg/m(3); median 756 pg/m(3)). The highest level (median 1067 pg/m(3)) was found at one of the urban sites in Beijing, followed by Tianjin (746 pg/m(3)) and Shijiazhuang (724 pg/m(3)). Tris(2-chloroethyl) phosphate (TCEP) and tri[(2R)-1-chloro-2-propyl] phosphate (TCPP) were the dominant compounds across the five sampling locations. Generally, the concentrations of chlorinated OPEs were relatively higher in summer than in winter (p < 0.05), but no significant seasonal difference was discovered for non-chlorinated individual OPEs. The concentrations of tri-n-butyl phosphate (TBP), TCEP, TCPP and triphenyl phosphate (TPP) were positively correlated with the meteorological parameters (i.e. temperature and relative humidity) (p < 0.05), indicating an evident influence of meteorological condition on OPE distribution. We observed a negative correlation (p < 0.05) between octanol-air partition coefficients (logK(oa)) and the ratio of PM(2.5)-bound OPE concentrations to total suspended particulates-bound OPE concentrations, suggesting that physicochemical properties affect the particle-size distribution of OPEs. Furthermore, the median value of cancer hazard quotients (HQs) of TCEP was higher than TBP and tris(2-ethylhexyl) phosphate (TEHP). The health risk assessment showed that HQ values for children were ~1.6 times higher than those for adults. Relatively higher health risk induced by PM(2.5)-bound OPEs via inhalation was found during severe hazy days than in clear days.
Fine particulate matter (PM(2.5), aerodynamic diameter ?2.5?µm) impacts the climate, reduces visibility and severely influences human health. The Indo-Gangetic Plain (IGP), home to about one-seventh of the world’s total population and a hotspot of aerosol loading, observes strong enhancements in the PM(2.5) concentrations towards winter. We performed high-resolution (12?km × 12?km) atmospheric chemical transport modeling (WRF-Chem) for the post-monsoon to winter transition to unravel the underlying dynamics and influences of regional emissions over the region. Model, capturing the observed variations to an extent, reveals that the spatial distribution of PM(2.5) having patches of enhanced concentrations (?100 µgm(-3)) during post-monsoon, evolves dramatically into a widespread enhancement across the IGP region during winter. A sensitivity simulation, supported by satellite observations of fires, shows that biomass-burning emissions over the northwest IGP play a crucial role during post-monsoon. Whereas, in contrast, towards winter, a large-scale decline in the air temperature, significantly shallower atmospheric boundary layer, and weaker winds lead to stagnant conditions (ventilation coefficient lower by a factor of ~4) thereby confining the anthropogenic influences closer to the surface. Such changes in the controlling processes from post-monsoon to winter transition profoundly affect the composition of the fine aerosols over the IGP region. The study highlights the need to critically consider the distinct meteorological processes of west-to-east IGP and changes in dominant sources from post-monsoon to winter in the formulation of future pollution mitigation policies.
Background The natural cycle of large-scale wildfires is accelerating, increasingly exposing both rural and populous urban areas to wildfire emissions. While respiratory health effects associated with wildfire smoke are well established, cardiovascular effects have been less clear. Methods and Results We examined the association between out-of-hospital cardiac arrest and wildfire smoke density (light, medium, heavy smoke) from the National Oceanic Atmospheric Association’s Hazard Mapping System. Out-of-hospital cardiac arrest data were provided by the Cardiac Arrest Registry to Enhance Survival for 14 California counties, 2015-2017 (N=5336). We applied conditional logistic regression in a case-crossover design using control days from 1, 2, 3, and 4 weeks before case date, at lag days 0 to 3. We stratified by pathogenesis, sex, age (19-34, 35-64, and >= 65 years), and socioeconomic status (census tract percent below poverty). Out-of-hospital cardiac arrest risk increased in association with heavy smoke across multiple lag days, strongest on lag day 2 (odds ratio, 1.70; 95% CI, 1.18-2.13). Risk in the lower socioeconomic status strata was elevated on medium and heavy days, although not statistically significant. Higher socioeconomic status strata had elevated odds ratios with heavy smoke but null results with light and medium smoke. Both sexes and age groups 35 years and older were impacted on days with heavy smoke. Conclusions Out-of-hospital cardiac arrests increased with wildfire smoke exposure, and lower socioeconomic status appeared to increase the risk. The future trajectory of wildfire, along with increasing vulnerability of the aging population, underscores the importance of formulating public health and clinical strategies to protect those most vulnerable.
Ozone exposure is associated with higher risk of asthma-related emergency department visits. The meteorological conditions that govern ozone concentration are projected to be more favorable to ozone formation over much of the United States due to continued climate change, even as emissions of anthropogenic ozone precursors are expected to decrease by 2050. Our goal is to quantify the health benefits of a climate change mitigation scenario versus a “business-as-usual” scenario, defined by the United Nations Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) 4.5 and 8.5, respectively, using the health impact analytical program Benefits Mapping and Analysis Program – Community Edition (BenMAP – CE) to project the number of asthma ED visits in 2045-2055. We project an annual average of 3100 averted ozone-related asthma ED visits during the 2045-2055 period under RCP4.5 versus RCP8.5, with all other factors held constant, which translates to USD $1.7 million in averted costs annually. We identify counties with tens to hundreds of avoided ozone-related asthma ED visits under RCP4.5 versus RCP8.5. Overall, we project a heterogeneous distribution of ozone-related asthma ED visits at different spatial resolutions, specifically national, regional, and county levels, and a substantial net health and economic benefit of climate change mitigation.
Background Wildfire events are increasing in prevalence in the western United States. Research has found mixed results on the degree to which exposure to wildfire smoke is associated with an increased risk of mortality. Methods We tested for an association between exposure to wildfire smoke and non-traumatic mortality in Washington State, USA. We characterized wildfire smoke days as binary for grid cells based on daily average PM2.5 concentrations, from June 1 through September 30, 2006-2017. Wildfire smoke days were defined as all days with assigned monitor concentration above a PM2.5 value of 20.4 mu g/m(3), with an additional set of criteria applied to days between 9 and 20.4 mu g/m(3). We employed a case-crossover study design using conditional logistic regression and time-stratified referent sampling, controlling for humidex. Results The odds of all-ages non-traumatic mortality with same-day exposure was 1.0% (95% CI: – 1.0 – 4.0%) greater on wildfire smoke days compared to non-wildfire smoke days, and the previous day’s exposure was associated with a 2.0% (95% CI: 0.0-5.0%) increase. When stratified by cause of mortality, odds of same-day respiratory mortality increased by 9.0% (95% CI: 0.0-18.0%), while the odds of same-day COPD mortality increased by 14.0% (95% CI: 2.0-26.0%). In subgroup analyses, we observed a 35.0% (95% CI: 9.0-67.0%) increase in the odds of same-day respiratory mortality for adults ages 45-64. Conclusions This study suggests increased odds of mortality in the first few days following wildfire smoke exposure. It is the first to examine this relationship in Washington State and will help inform local and state risk communication efforts and decision-making during future wildfire smoke events.
Background Wildfires are increasingly a significant source of fine particulate matter (PM2.5), which has been linked to adverse health effects and increased mortality. ESKD patients are potentially susceptible to this environmental stressor. Methods We conducted a retrospective time-series analysis of the association between daily exposure to wildfire PM2.5 and mortality in 253 counties near a major wildfire between 2008 and 2012. Using quasi-Poisson regression models, we estimated rate ratios (RRs) for all-cause mortality on the day of exposure and up to 30 days following exposure, adjusted for background PM2.5, day of week, seasonality, and heat. We stratified the analysis by causes of death (cardiac, vascular, infectious, or other) and place of death (clinical or nonclinical setting) for differential PM2.5 exposure and outcome classification. Results We found 48,454 deaths matched to the 253 counties. A 10-mu g/m(3) increase in wildfire PM2.5 associated with a 4% increase in all-cause mortality on the same day (RR, 1.04; 95% confidence interval [95% CI], 1.01 to 1.07) and 7% increase cumulatively over 30 days following exposure (RR, 1.07; 95% CI, 1.01 to 1.12). Risk was elevated following exposure for deaths occurring in nonclinical settings (RR, 1.07; 95% CI, 1.02 to 1.12), suggesting modification of exposure by place of death. “Other” deaths (those not attributed to cardiac, vascular, or infectious causes) accounted for the largest portion of deaths and had a strong same-day effect (RR, 1.08; 95% CI, 1.03 to 1.12) and cumulative effect over the 30-day period. On days with a wildfire PM2.5 contribution >10 mu g/m(3), exposure accounted for 8.4% of mortality. Conclusions Wildfire smoke exposure was positively associated with all-cause mortality among patients receiving in-center hemodialysis.
Air pollution and heat are significant threats to public health, especially in urban areas with intensive human activities under the trend of climate change. However, the mediation effects of urban form on health via air pollution and heat have been overlooked in previous investigations. This study explored the potential impacts and pathways of urban form on cardiovascular mortality through air pollutants and heat by using partial least squares model with data from Taiwan. The measurable characteristics of urban form include city size, urban sprawl, and mixed land use. Other factors that influence cardiovascular mortality, such as urban industrial level, economic status, aging population, and medical resource, were also considered in the model. Results revealed that maximizing mixed land use and minimizing city size and urban sprawl can help reduce cardiovascular mortality, and the minimizing city size was the most important one. Urban industrial level, economic status, aging population, and medical resource were also influential factors. This is the first study to consider the pathways and impacts of urban form on cardiovascular mortality, and our results indicate that proper urban planning and policy could reduce cardiovascular mortality.
Both ozone exposure and extreme temperatures are found to be significantly associated with mortality; however, inconsistent results have been obtained on the modification effects of temperature on the ozone-mortality association. In the present study, we conducted a nationwide time-series analysis in 128 counties from 2013-2018 to examine whether temperature modifies the association between short-term ozone exposure with nonaccidental and cause-specific mortality in China. First, we analyzed the effects of ozone exposure on mortality at different temperature levels. Then, we calculated the pooled effects through a meta-analysis across China. We found that high-temperature conditions (>75th percentile in each county) significantly enhanced the effects of ozone on nonaccidental, cardiovascular, and respiratory mortality, with increases of 0.44% (95% confidence interval (CI): 0.36 and 0.51%), 0.42% (95% CI: 0.32 and 0.51%) and 0.50% (95% CI: 0.31 and 0.68%), respectively, for a 10 ?g/m(3) increase in ozone at high temperatures. Stronger effects on nonaccidental and cardiovascular mortality were observed at high temperatures among elderly individuals aged 65 years and older compared with the younger people. Our findings provide evidence that health damage because of ozone may be influenced by the impacts of increasing temperatures, which point to the importance of mitigating ozone exposure in China under the context of climate change to further reduce the public health burden.
OBJECTIVES: This study investigated the modification of temperature effects on cardiovascular and respiratory mortality by air pollutants (particulate matter less than 2.5 and 10 µm in diameter [respectively], ozone, nitrogen dioxide, carbon monoxide, and sulfur dioxide). METHODS: Poisson additive models with a penalized distributed lag non-linear model were used to assess the association of air temperature with the daily number of deaths from cardiovascular and respiratory diseases in Ahvaz, Iran from March 21, 2014 to March 20, 2018, controlling for day of the week, holidays, relative humidity, wind speed, air pollutants, and seasonal and long-term trends. Subgroup analyses were conducted to evaluate the effect modification for sex and age group. To assess the modification of air pollutants on temperature effects, the level of each pollutant was categorized as either greater than the median value or less than/equal to the median value. RESULTS: We found no significant associations between temperature and cardiovascular and respiratory mortality. In the subgroup analyses, however, high temperatures were significantly associated with an increased risk of cardiovascular mortality among those 75 years old and older, with the strongest effect observed on day 0 relative to exposure. The results revealed a lack of interactive effects between temperature and air pollutants on cardiovascular and respiratory mortality. CONCLUSIONS: A weak but significant association was found between high temperature and cardiovascular mortality, but only in elderly people. Air pollution did not significantly modify the effect of ambient temperature on cardiovascular and respiratory mortality.
Exposure to air pollution is one of the primary global health risk factors, yet individuals lack the knowledge to engage in individual risk mitigation and the skills to mobilize for the change necessary to reduce such risks. News media is an important tool for influencing individual actions and support for public policies to reduce environmental threats; thus, a lack of news coverage of such issues may exacerbate knowledge deficits. This study examines the reporting of health risks and precautionary measures regarding air pollution in national and regional print news. We conducted a content analysis of two national and two local newspapers covering the USA’s most polluted region during a 5-year period. Coders identified information on threat, self-efficacy, protective measures and information sources. Nearly 40% of air pollution news articles mentioned human health risks. Fewer than 10% of news stories about air pollution provided information on the precautionary measures necessary for individuals to take action to mitigate their risk. Local newspapers did not report more threat (X-2= 1.931,p= 0.165) and efficacy (X-2= 1.118,p= 0.209) information. Although air pollution levels are high and continue to rise at alarming rates, our findings suggest that news media reporting is not conducive to raising environmental health literacy.
OBJECTIVE: The aim of this study was to investigate the status of Vitamin D deficiency and the effect of environmental factors on Vitamin D levels so as to provide theoretical support for public health promotion in this region. METHODS: A total of 22,387 subjects who underwent a physical examination at the center in the West China Hospital, Sichuan University, between April, 2018 and May, 2020 were enrolled in this study. Their data on gender, age, inspection date, serum 25 hydroxyvitamin D (25-(OH) D), parathyroid hormone (PTH), and total calcium were retrospectively reviewed. Next, the percentage of Vitamin D status was compared in different sex and age groups, and the fluctuation of Vitamin D level was described in relation to the change of environment. Finally, the univariable and multivariable linear regression analyses were performed to explore the risk and protective factors of Vitamin D deficiency. RESULTS: The proportion of Vitamin D deficiency in this area was 42.17%, and it was significantly higher among women and young people. The fluctuation trend of 25-(OH) D levels are consistent with temperature and solar radiation, and opposite to air quality, in the whole year. There was a positive relationship between 25-(OH) D levels with temperature and solar radiation; however, parathyroid hormone, female and AQI were negatively correlated with Vitamin D levels. CONCLUSION: Vitamin D deficiency is common in subtropic areas, such as Sichuan Basin, which is related to solar radiation and air pollution.
Short-lived climate pollutants (SLCPs) including black carbon (BC), methane (CH4), and tropospheric ozone (O-3) are major climate forcers after carbon dioxide (CO2). These SLCPs also have detrimental impacts on human health and agriculture. Studies show that the Hindu Kush Himalayan (HKH) region, which includes Nepal, has been experiencing the impacts of these pollutants in addition to greenhouse gases. In this study, we derive a national-level emission inventory for SLCPs, CO2, and air pollutants for Nepal and project their impacts under reference (REF) and mitigation policy (POL) scenarios. The impacts on human health, agriculture, and climate were then estimated by applying the following: (1) adjoint coefficients from the Goddard Earth Observing System (GEOS)-chemical transport model that quantify the sensitivity of fine particulate matter (PM2.5) and surface O-3 concentrations in Nepal, and radiative forcing in four latitudinal bands, to emissions in 2 x 2.5 degrees grids, and (2) concentration-response functions to estimate health and crop loss impacts in Nepal. With the mitigating measures undertaken, emission reductions of about 78% each of BC and CH4 and 87% of PM2.5 could be achieved in 2050 compared with the REF scenario. This would lead to an estimated avoidance of 29,000 lives lost and 1.7 million tonnes of crop loss while bringing an economic benefit in present value of 2.7 times more than the total cost incurred in its implementation during the whole period 2010-2050. The results provide useful policy insights and pathways for evidence-based decision-making in the design and effective implementation of SLCP mitigation measures in Nepal.
It is often difficult to define the relationship and the influence of climate on the occurrence and distribution of disease. To examine this issue, the effects of climate indices on the distributions of malaria and meningitis in Nigeria were assessed over space and time. The main purpose of the study was to evaluate the relationships between climatic variables and the prevalence of malaria and meningitis, and develop an early warning system for predicting the prevalence of malaria and meningitis as the climate varies. An early warning system was developed to predetermine the months in a year that people are vulnerable to malaria and meningitis. The results revealed a significant positive relationship between rainfall and malaria, especially during the wet season with correlation coefficient R-2 >= 60.0 in almost all the ecological zones. In the Sahel, Sudan and Guinea, there appears to be a strong relationship between temperature and meningitis with R-2 > 60.0. In all, the results further reveal that temperatures and aerosols have a strong relationship with meningitis. The assessment of these initial data seems to support the finding that the occurrence of meningitis is higher in the northern region, especially the Sahel and Sudan. In contrast, malaria occurrence is higher in the southern part of the study area. We suggest that a thorough investigation of climate parameters is critical for the reallocation of clinical resources and infrastructures in economically underprivileged regions.
The effects of atmospheric black carbon (BC) on climate and public health have been well established, but large uncertainties remain regarding the extent of the impacts of BC at different temporal and spatial scales. These uncertainties are largely due to the heterogeneous nature of BC in terms of its spatiotemporal distribution, mixing state, and coating composition. Here, we seek to further understand the size and mixing state of BC emitted from various sources and aged over different timescales using field measurements in the Los Angeles region. We measured refractory black carbon (rBC) with a single-particle soot photometer (SP2) on Catalina Island, California (similar to 70 km southwest of downtown Los Angeles) during three different time periods. During the first campaign (September 2017), westerly winds were dominant and measured air masses were representative of wellaged background over the Pacific Ocean. In the second and third campaigns (December 2017 and November 2018, respectively), atypical Santa Ana wind conditions allowed us to measure biomass burning rBC (BCbb) from air masses dominated by large biomass burning events in California and fossil fuel rBC (BCff) from the Los Angeles Basin. We observed that the emissions source type heavily influenced both the size distribution of the rBC cores and the rBC mixing state. BCbb had thicker coatings and larger core diameters than BBff. We observed a mean coating thickness (CTBc) of similar to 40-70 nm and a count mean diameter (CMD) of similar to 120 nm for BCbb. For BCff, we observed a CTBc of similar to 5-15 nm and a CMD of similar to 100 nm. Our observations also provided evidence that aging led to an increased CTBc for both BCbb and BCff . Aging timescales < similar to 1 d were insufficient to thickly coat freshly emitted BCff. However, CTBc for aged B-ff within aged background plumes was similar to 35 nm thicker than CTBc for fresh BCff. Likewise, we found that CTBc for aged BCbb was similar to 18 nm thicker than CTBc for fresh BCbb. The results presented in this study highlight the wide variability in the BC mixing state and provide additional evidence that the emissions source type and aging influence rBC microphysical properties.
Central to public health risk communication is understanding the perspectives and shared values among individuals who need the information. Using the responses from a Smoke Sense citizen science project, we examined perspectives on the issue of wildfire smoke as a health risk in relation to an individual’s preparedness to adopt recommended health behaviors. The Smoke Sense smartphone application provides wildfire-related health risk resources and invites participants to record their perspectives on the issue of wildfire smoke. Within the app, participants can explore current and forecasted daily air quality, maps of fire locations, satellite images of smoke plumes, and learn about health consequences of wildfire smoke. We used cluster analysis to identify perspective trait-clusters based on health status, experience with fire smoke, risk perception, self-efficacy, access to exposure-reducing resources, health information needs, and openness to health risk messaging. Differences between traits were examined based on demographics, health status, activity level and engagement with the app. We mapped these traits to the Precaution Adoption Process Model (PAPM) to indicate where each trait lies in adopting recommended health behaviors. Finally, we suggest messaging strategies that may be suitable for each trait. We determined five distinct perspective traits which included individuals who were Protectors and have decided to engage on the issue by adopting new behaviors to protect their health; Cautious, Proactive, and Susceptible individuals who were at a Deciding stage but differed based on risk perceptions and information needs; and the Unengaged who did not perceive smoke as a health issue and were unlikely to change behavior in response to messaging. Across all five traits, the level of engagement and information needs differed substantially, but were not defined by demographics. Individuals in the Susceptible trait had the highest level of engagement and the highest information needs. Messaging that emphasizes self-efficacy and benefits of reducing exposure may be effective in motivating individuals from the deciding stage to taking health protective action. Shared perspectives define an individual’s propensity for acting on recommended health behaviors, therefore, health risk message content should be tailored based on these perspectives.
Environmental hazards increase the health morbidity and mortality burden. This study compared the knowledge and perceptions about the health effects of environmental hazards among medical and engineering students of Hamdard University Karachi. A total of 263 (44.1%) engineering students, and 333 (55.9%) medical students participated in the study. Cumulatively, the three most commonly identified environmental hazards included tobacco smoking 561 (94.1%), global climate change 518 (86.9%), and solar ultraviolet radiation 511 (85.7%). The study results suggest the need for better quantifying the magnitude of understanding environmental hazards, and for health education and promotion programmes at the graduate level for medical and engineering students in Karachi.
Several studies have reported that air pollution and climatic factors are major contributors to human morbidity and mortality globally. However, the combined interactive effects of air pollution and climatic factors on human health remain largely unexplored. This study aims to investigate the interactive effects of air pollution and climatic factors on circulatory and respiratory mortality in Xi’an, China. Time-series analysis and the distributed lag non-linear model (DLNM) were employed as the study design and core statistical method. The interaction relative risk (IRR) and relative excess risk due to interaction (RERI) for temperature and Air Quality Index (AQI) interaction on circulatory mortality were 0.973(0.969, 0.977) and -0.055(-0.059, -0.048), respectively; while for relative humidity and AQI interaction, 1.098(1.011, 1.072) and 0.088(0.081, 0.107) respectively, were estimated. Additionally, the IRR and RERI for temperature and AQI interaction on respiratory mortality were 0.805(0.722, 0.896) and -0.235(-0.269, -0.163) respectively, while 1.008(0.965, 1.051) and -0.031(-0.088, 0.025) respectively were estimated for relative humidity and AQI interaction. The interaction effects of climatic factors and AQI were synergistic and antagonistic in relation to circulatory and respiratory mortality, respectively. Interaction between climatic factors and air pollution contributes significantly to circulatory and respiratory mortality.
BACKGROUND: Daily air quality index (AQI) forecast can provide early warning information, and it is not clear whether it is appropriate for childhood asthma hospitalizations (CAHs). Furthermore, little is known about the effects of AQI on CAHs, as well as the interactions between temperature, humidity and AQI. METHODS: We collected 32,238 cases in Hefei from 2013 to 2016 and estimated the association between daily CAHs and AQI by combining the Poisson Generalized Linear Models (PGLMs) with the Distributed Lag Nonlinear Models (DLNMs). The interaction between AQI and temperature was tested by stratifying AQI and temperature, as well as humidity. RESULTS: AQI was associated with an increased risk of hospitalizations for childhood asthma. The adverse effect first appeared on the 3rd day, with the RR of 1.011 (95%CI: 1.000-1.023) and continued until the 19th day of lag (RR = 1.010, 95%CI: 1.001-1.020). In the subgroup analysis, the male and pre-school children were more sensitive to AQI, and there are seasonal differences in the effects of AQI on CAHs. Besides, in a stratified analysis with an AQI of 150, we found synergies between temperature, humidity and AQI. The interaction relative risk (IRR) and relative excess risk due to interaction (RERI) for the interaction between temperature and AQI were 1.157 (95%CI: 1.029-1.306) and 0.122 (95%CI: 0.022-0.223) respectively. For the humidity, the IRR and RERI were 1.090 (95%CI: 1.056-1.206) and 0.083 (95%CI: 0.083-0.143) respectively. Exploring different subgroups in the interaction analyses, it was worth noting that female and pre-school children were more sensitive to the interaction between AQI and temperature, while school-age children were more sensitive to the interaction between AQI and humidity. CONCLUSIONS: The study found that not only AQI can significantly increase the risk of CAHs, but also that under the context of climate change, temperature and humidity have a synergistic effect on AQI, suggesting that considering only the warning information of air pollution is not enough to strengthen the prevention of childhood asthma hospitalization.
BACKGROUND: Both extreme heat and air pollution exposure during pregnancy have been associated with preterm birth; however, their combined effects are unclear. OBJECTIVES: Our goal was to estimate the independent and joint effects of heatwaves and fine particulate matter [PM < 2.5 ?m in aerodynamic diameter (PM2.5)], exposure during the final gestational week on preterm birth. METHODS: Using birth registry data from Guangzhou, China, we included 215,059 singleton live births in the warm season (1 May-31 October) between January 2015 and July 2017. Daily meteorological variables from 5 monitoring stations and PM2.5 concentrations from 11 sites were used to estimate district-specific exposures. A series of cut off temperature thresholds and durations (2, 3, and 4 consecutive d) were used to define 15 different heatwaves. Cox proportional hazard models were used to estimate the effects of heatwaves and PM2.5 exposures during the final week on preterm birth, and departures from additive joint effects were assessed using the relative excess risk due to interaction (RERI). RESULTS: Numbers of preterm births increased in association with heatwave exposures during the final gestational week. Depending on the heatwave definition used, hazard ratios (HRs) ranged from 1.10 (95% CI: 1.01, 1.20) to 1.92 (1.39, 2.64). Associations were stronger for more intense heatwaves. Combined effects of PM2.5 exposures and heatwaves appeared to be synergistic (RERIs > 0) for less extreme heatwaves (i.e., shorter or with relatively low temperature thresholds) but were less than additive (RERIs < 0) for more intense heatwaves. CONCLUSIONS: Our research strengthens the evidence that exposure to heatwaves during the final gestational week can independently trigger preterm birth. Moderate heatwaves may also act synergistically with PM2.5 exposure to increase risk of preterm birth, which adds new evidence to the current understanding of combined effects of air pollution and meteorological variables on adverse birth outcomes. https://doi.org/10.1289/EHP5117.
BACKGROUND: Due to variations in climatic conditions, the effects of meteorological factors and PM(2.5) on influenza activity, particularly in subtropical regions, vary in existing literature. In this study, we examined the relationship between influenza activity, meteorological parameters, and PM(2.5) . METHODS: A total of 20 165 laboratory-confirmed influenza cases in Hangzhou, Zhejiang province, were documented in our dataset and aggregated into weekly counts for downstream analysis. We employed a combination of the quasi-Poisson-generalized additive model and the distributed lag non-linear model to examine the relationship of interest, controlling for long-term trends, seasonal trends, and holidays. RESULTS: A hockey-stick association was found between absolute humidity and the risk of influenza infections. The overall cumulative adjusted relative risk (ARR) was statistically significant when weekly mean absolute humidity was low (<10 µg/m(3) ) and high (>17.5 µg/m(3) ). A slightly higher ARR was observed when weekly mean temperature reached over 30.5°C. A statistically significantly higher ARR was observed when weekly mean relative humidity dropped below 67%. ARR increased statistically significantly with increasing rainfall. For PM(2.5) , the ARR was marginally statistically insignificant. In brief, high temperature, wet and dry conditions, and heavy rainfall were the major risk factors associated with a higher risk of influenza infections. CONCLUSIONS: The present study contributes additional knowledge to the understanding of the effects of various environmental factors on influenza activities. Our findings shall be useful and important for the development of influenza surveillance and early warning systems.
The sensitivities of meteorological and chemical predictions to urban effects over four major North American cities are investigated using the high-resolution (2.5-km) Environment and Climate Change Canada’s air quality model with the Town Energy Balance (TEB) scheme. Comparisons between the model simulation results with and without the TEB effect show that urbanization has great impacts on surface heat fluxes, vertical diffusivity, air temperature, humidity, atmospheric boundary layer height, land-lake circulation, air pollutants concentrations and Air Quality Health Index. The impacts have strong diurnal variabilities, and are very different in summer and winter. While the diurnal variations of the impacts share some similarities over each city, the magnitudes can be very different. The underlying mechanisms of the impacts are investigated. The TEB impacts on the predictions of meteorological and air pollutants over Toronto are evaluated against ground-based observations. The results show that the TEB scheme leads to a great improvement in biases and root-mean-square deviations in temperature and humidity predictions in downtown, uptown and suburban areas in the early morning and nighttime. The scheme also leads to a big improvement of predictions of NOx, PM2.5 and ground-level ozone in the downtown, uptown and industrial areas in the early morning and nighttime.
Urbanization and climate change have been rapidly occurring globally. Evidence-based healthy city development is required to improve living quality and mitigate the adverse impact of the outdoor neighborhood environment on public health. Taking Guangzhou as an example to explore the association of neighborhood environment and public health and preferably to offer some implications for better future city development, we measured ten environmental factors (temperature (T), wind-chill index (WCI), thermal stress index (HSI), relative humidity (RH), average wind speed (AWS), negative oxygen ions (NOI), PM2.5, luminous flux (LF), and illuminance (I)) in four seasons in four typical neighborhoods, and the SF-36 health scale was employed to assess the physical and mental health of neighborhood residents in nine subscales (health transition(HT), physiological functions (PF), general health status (GH), physical pain (BP), physiological functions (RP), energy vitality (VT), mental health (MH), social function (SF), and emotional functions (RE)). The linear mixed model was used in an analysis of variance. We ranked the different environmental factors in relation to aspects of health and weighted them accordingly. Generally, the thermal environment had the greatest impact on both physical and mental health and the atmospheric environment and wind environment had the least impact on physical health and mental health, respectively. In addition, the physical health of the resident was more greatly affected by the environment than mental health. According to the results, we make a number of strategic suggestions for the renewal of the outdoor neighborhood environment in subtropical monsoon climate high-density cities and provide a theoretical basis for improving public health through landscape architecture at the neighborhood scale.
Rationale: There is significant evidence of increased healthcare utilization from cardiopulmonary causes in adults from exposure to wildfire smoke, but evidence in pediatric age groups is limited.Objectives: To quantify and examine the healthcare utilization effects of the December 2017 Lilac Fire in San Diego County among pediatric patients at the Rady Children’s Hospital (RCH) emergency department and urgent care (UC) clinics.Methods: Using data from 2011 to 2017, including data on daily particulate matter <2.5 ?m (PM(2.5)) in an inverse-distance interpolation model and RCH electronic medical records, we retrospectively analyzed pediatric respiratory visits at the RCH emergency department and UC clinics during the Santa Ana wind (SAW)-driven Lilac Fire from December 7 to 16, 2017. An interrupted time series study design was applied as our primary analysis to compare the observed pediatric respiratory visits from December 7 to 16, 2017 to what would have occurred in a counterfactual situation, namely, if the Lilac Fire had not occurred. A complementary descriptive spatial analysis was also used to evaluate the geographic distribution of respiratory visits in relationship to satellite imaging of the Lilac Fire and the associated wind pattern.Results: The Lilac Fire was associated with 16.0 (95% confidence interval [CI], 11.2-20.9) excess respiratory visits per day at the RCH emergency department across all pediatric age groups. Children aged 0 to 5 years had the highest absolute excess respiratory visits per day with 7.3 (95% CI, 3.0-11.7), whereas those aged 6 to 12 years had the highest relative increase in visits, with 3.4 (95% CI, 2.3-4.6). RCH UC clinics had similar results. The top five ZIP codes in San Diego County with the highest standard deviations of age-adjusted respiratory visits were all located generally downwind of the fire perimeter, as expected for the SAW pattern.Conclusions: We have demonstrated an increase in pediatric respiratory visits during the SAW-driven Lilac Fire in San Diego County in a patterned geographic distribution that is attributable to an increase in PM(2.5) exposure. Younger children were particularly affected. Climate change is expected to result in more frequent and extensive wildfires in the region and will require greater preparedness and adaptation efforts to protect vulnerable populations, such as young children.
Background: Air pollution is a global problem and also linked to respiratory diseases. Wildfire smog is a major cause of air pollution in the upper northern area of Thailand. Thus, in the current study, we examined whether long-term exposure to wildfire smog induces lung function changes in a population from the upper northern area of Thailand. Methods: The lung function of 115 participants with long-term exposure smog was determined using peak flow meter. Results: Long-term smoke exposure participants decreased FEV1 (forced expiratory volume in 1 second)/FVC (forced vital capacity) ratio (56.49 +/- 23.88 in males and 56.29 +/- 28.23 in females) compared with general Thai population. Moreover, the reduction of FVC, FEV1, and peak expiratory flow rate (PEFR) values also showed in both male and female subjects. These results suggest that long-term smoke exposure induces obstructive lung abnormality. Moreover, itchy/watery nose, cough, phlegm, and chest pain also reported in these subjects. Conclusion: Wildfire smog could be induced respiratory pathway inflammation and easily collapsible respiratory airways.
Sand and dust storms in arid and semiarid regions deteriorate regional air quality and threaten public health security. To quantify the negative effects of river dust on regional air quality, this study selected the estuary areas located in central Taiwan as a case study and proposed an integrated framework to measure the fugitive emission of dust from riverbeds with the aid of satellite remote sensing and wind tunnel test, together with the concentrations of particulate matter with a diameter of <10 ?m (PM(10)) around the river system by using The Air Pollution Model. Additionally, the effects of 25 types of meteorological conditions on the health risk due to exposure to dust were evaluated near the estuary areas. The results reveal landscape changes in the downstream areas of Da'an and Dajia rivers, with an increase of 370,820 m(2) and 1,554,850 m(2) of bare land areas in the dry season compared with the wet season in Da'an and Dajia rivers, respectively. On the basis of the maximum emission of river dust, PM(10) concentration increases considerably during both wet and dry seasons near the two rivers. Among 25 different types of weather conditions, frontal surface transit, outer-region circulation from tropical depression system, weak northeast monsoons, and anticyclonic outflow have considerable influence on PM(10) diffusion. In particular, weak northeast monsoons cause the highest health risk in the areas between Da'an and Dajia rivers, which is the densely populated Taichung City. Future studies should attempt to elucidate the environmental impact of dust in different weather conditions and understand the spatial risks to human health due to PM(10) concentration. Facing the increasing threat of climate and landscape changes, governments are strongly encouraged to begin multimedia assessments in environmental management and propose a long-term and systematic framework in resources planning.
Relationships of larger scale meteorological predictors with ground-level daily maximum ozone (O-3max) and daily maximum air temperature (T-max) for stations in Bavaria were analysed. O-3max and T-max as well as threshold exceedances of these variables were assessed under the constraints of ongoing climate change until the end of the twenty-first century. Under RCP8.5 scenario conditions, a substantial increase of T-max in the months from April to September arose, with a mean value of 5 K in the period 2081-2100 compared with the historical period 1986-2005. Statistical downscaling projections pointed to a mean O-3max rise of 17 mu g/m(3). The frequency of threshold exceedances showed also large changes. Hot days may occur in the future at about 30% of all days. Exceedances of O-3max > 100 mu g/m(3) were projected to increase to about 40% of all days at urban traffic sites and up to about 70% in the rural regional background. Days with O-3max > 120 mu g/m(3) occurred still at about 20% of all days at urban traffic sites and at about 45% in rural regional background locations. With respect to combined T-max > 30 degrees C and O-3max > 100 mu g/m(3) events in the future, an occurrence of such events at about 27-29% of all days in the summer months from April to September was assessed. The increases were mainly associated with the strong temperature rise until the end of the century. In summary, the projected T-max and O-3max changes point to a considerable increased health burden in Bavaria until the end of the century, resulting from strong changes of both variables and their associated individual and combined impact on human health.
Air pollution and hot temperatures present two major health risks, especially for vulnerable groups such as children, the elderly, and people with pre-existing conditions. Episodes of high ozone concentrations and heat waves have been registered throughout Europe and are expected to continue to grow due to climate change. Here, several different heat and ozone wave definitions were applied to characterize the wave-type extremes for two climatically different regions, i.e., Portugal (South Europe) and Bavaria (Central Europe), and their impacts were evaluated considering each type of hazard independently but also when they occur simultaneously. Heat and ozone waves were analyzed with respect to the underlying atmospheric circulation patterns and in terms of their association with human mortality. Heat waves were identified as the most frequent wave type and, despite different climate settings, a comparable exposure to heat and ozone waves was found in Central and South Europe. Waves were associated with in-situ built-up as well as with advection of air masses. However, in Bavaria waves showed the strongest connection with autochthonous weather conditions, while for Portugal, the strongest relationship appeared for eastern and north-eastern inflow. The most severe events, as measured by excess mortality, were always associated to compound heat-ozone waves.
BACKGROUND: Summer temperatures are expected to increase and heat waves will occur more frequently, be longer, and be more intense as a result of global warming. A growing body of evidence indicates that increasing temperature and heatwaves are associated with excess mortality and therefore global heating may become a major public health threat. However, the heat-mortality relationship has been shown to be location-specific and differences could largely be explained by the most frequent temperature. So far, in Belgium there is little known regarding the heat-mortality relationship in the different urban areas. OBJECTIVES: The objective of this study is to assess the heat-mortality relationship in the two largest urban areas in Belgium, i.e. Antwerp and Brussels for the warm seasons from 2002 until 2011 taking into account the effect of air pollution. METHODS: The threshold in temperature above which mortality increases was determined using segmented regressions for both urban areas. The relationship between daily temperature and mortality above the threshold was investigated using a generalized estimated equation with Poisson distribution to finally determine the percentage of deaths attributable to the effect of heat. RESULTS: Although only 50 km apart, the heat-mortality curves for the two urban areas are different. More specifically, an increase in mortality occurs above a maximum temperature of 25.2 °C in Antwerp and 22.8 °C in Brussels. We estimated that above these thresholds, there is an increase in mortality of 4.9% per 1 °C in Antwerp and of 3.1% in Brussels. During the study period, 1.5% of the deaths in Antwerp and 3.5% of the deaths in Brussels can be attributed to the effect of heat. The thresholds differed considerably from the most frequent temperature, particularly in Antwerp. Adjustment for air pollution attenuated the effect of temperature on mortality and this attenuation was more pronounced when adjusting for ambient ozone. CONCLUSION: Our results show a significant effect of temperature on mortality above a city-specific threshold, both in Antwerp and in Brussels. These findings are important given the ongoing global warming. Recurrent, intense and longer episodes of high temperature and expected changes in air pollutant levels will have an important impact on health in urban areas.
Wildfires have a significant adverse impact on air quality in the United States (US). To understand the potential health impacts of wildfire smoke, many epidemiology studies rely on concentrations of fine particulate matter (PM) as a smoke tracer. However, there are many gas-phase hazardous air pollutants (HAPs) identified by the Environmental Protection Agency (EPA) that are also present in wildfire smoke plumes. Using observations from the Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE-CAN), a 2018 aircraft-based field campaign that measured HAPs and PM in western US wildfire smoke plumes, we identify the relationships between HAPs and associated health risks, PM, and smoke age. We find the ratios between acute, chronic noncancer, and chronic cancer HAPs health risk and PM in smoke decrease as a function of smoke age by up to 72% from fresh (<1 day of aging) to old (>3 days of aging) smoke. We show that acrolein, formaldehyde, benzene, and hydrogen cyanide are the dominant contributors to gas-phase HAPs risk in smoke plumes. Finally, we use ratios of HAPs to PM along with annual average smoke-specific PM to estimate current and potential future smoke HAPs risks.
Smoke from wildfires contains many air pollutants of concern and epidemiological studies have identified associations between exposure to wildfire smoke PM(2.5) and mortality and respiratory morbidity, and a possible association with cardiovascular morbidity. For this study, a retrospective analysis of air quality modelling was performed to quantify the exposure to wildfire-PM(2.5) across the Canadian population. The model included wildfire emissions from across North America for a 5-month period from May to September (i.e. wildfire season), between 2013 and 2015 and 2017-2018. Large variations in wildfire-PM(2.5) were noted year-to-year, geospatially, and within fire season. The model results were then used to estimate the national population health impacts attributable to wildfire-PM(2.5) and the associated economic valuation. The analysis estimated annual premature mortalities ranging from 54-240 premature mortalities attributable to short-term exposure and 570-2500 premature mortalities attributable to long-term exposure, as well as many non-fatal cardiorespiratory health outcomes. The economic valuation of the population health impacts was estimated per year at $410M-$1.8B for acute health impacts and $4.3B-$19B for chronic health impacts for the study period. The health impacts were greatest in the provinces with populations in close proximity to wildfire activity, though health impacts were also noted across many provinces indicating the long-range transport of wildfire-PM(2.5). Understanding the population health impacts of wildfire smoke is important as climate change is anticipated to increase wildfire activity in Canada and abroad.
OBJECTIVES: To identify key predictors of general practitioner (GP) consultations for allergic rhinitis (AR) using meteorological and environmental data. DESIGN: A retrospective, time series analysis of GP consultations for AR. SETTING: A large GP surveillance network of GP practices in the London area. PARTICIPANTS: The study population was all persons who presented to general practices in London that report to the Public Health England GP in-hours syndromic surveillance system during the study period (3 April 2012 to 11 August 2014). PRIMARY MEASURE: Consultations for AR (numbers of consultations). RESULTS: During the study period there were 186?401 GP consultations for AR. High grass and nettle pollen counts (combined) were associated with the highest increases in consultations (for the category 216-270 grains/m(3), relative risk (RR) 3.33, 95%?CI 2.69 to 4.12) followed by high tree (oak, birch and plane combined) pollen counts (for the category 260-325 grains/m(3), RR 1.69, 95%?CI 1.32 to 2.15) and average daily temperatures between 15°C and 20°C (RR 1.47, 95%?CI 1.20 to 1.81). Higher levels of nitrogen dioxide (NO(2)) appeared to be associated with increased consultations (for the category 70-85?µg/m(3), RR 1.33, 95%?CI 1.03 to 1.71), but a significant effect was not found with ozone. Higher daily rainfall was associated with fewer consultations (15-20?mm/day; RR 0.812, 95% CI 0.674 to 0.980). CONCLUSIONS: Changes in grass, nettle or tree pollen counts, temperatures between 15°C and 20°C, and (to a lesser extent) NO(2) concentrations were found to be associated with increased consultations for AR. Rainfall has a negative effect. In the context of climate change and continued exposures to environmental air pollution, intelligent use of these data will aid targeting public health messages and plan healthcare demand.
Climate policies can bring local air quality and health co-benefits, which may partially or entirely offset the costs of implementing these policies. In this study, we introduce an integrated health co-benefits assessment model, the Regional Emissions-Air quality-Climate-Health (REACH) Modeling Framework, which is capable of evaluating the impact of policies on air pollution-related mortality and morbidity in the whole economic system overtime at the provincial level for China. We first provide a detailed description of the modeling framework and conduct a case study to estimate the health benefits of different climate policy scenarios. We show that a scenario consistent with the 2 degrees C target that peaks China’s emissions before 2025 could avoid around 190 thousand premature deaths in 2030. The health benefits could partially or fully cover the policy costs under different assumptions of the value of a statistical life (VSL). Our framework also illustrates that estimated costs and health benefits distribute unevenly across regions in China.
The flow of the Earth’s atmosphere not only largely determines its temperature status, but also profoundly affects aerosol concentrations. Therefore, exploring how to evaluate the synthetical effects of temperature and aerosol pollution on human health is an important topic. Regarding the atmosphere as a whole, we quantified the mortality burden attributable to short-term exposure to abnormal temperatures and PM2.5 in Beijing from the perspective of atmospheric flow. We first divided the atmospheric stability into three levels (including disturbed, normal, and stable conditions) according to the variations in meteorological conditions and PM2.5 concentrations across the stable weather index levels. We then applied a generalized additive model to separately evaluate the short-term effects of temperature and PM2.5 on mortality under each level of atmospheric stability. We further estimate the associated mortality burden using two indicators, namely attributable fraction and attributable number of deaths. Abnormal temperatures were responsible for most of the mortality burden. Cold temperatures accounted for a substantially higher mortality burden than hot temperatures. The synthetical mortality effects of temperature and PM2.5 varied for different atmospheric stabilities. A stable atmosphere poses the strongest synthetical effects of temperature and PM2.5, while a normal atmosphere provides comparatively beneficial conditions for human health. Our results indicated that the synthetical health impacts of temperature and PM2.5 driven by atmospheric flow need to be considered in the further promulgation of public health policies and air pollution abatement strategies, particularly in the context of climate change.
Background.Exposure to high air temperature in late pregnancy is increasingly recognized as a risk factor for preterm birth (PTB). However, the combined effects of heatwaves with air pollution and green space are still unexplored. In the context of climate change, investigating the interaction between environmental factors and identifying communities at higher risk is important to better understand the etiological mechanisms and design targeted interventions towards certain women during pregnancy.Objectives.To examine the combined effects of heatwaves, air pollution and green space exposure on the risk of PTB.Methods.California birth certificate records for singleton births (2005-2013) were obtained. Residential zip code-specific daily temperature during the last week of gestation was used to create 12 definitions of heatwave with varying temperature thresholds and durations. We fit multi-level Cox proportional hazard models with time to PTB as the outcome and gestational week as the temporal unit. Relative risk due to interaction (RERI) was applied to estimate the additive interactive effect of air pollution and green space on the effect of heatwaves on PTB.Results.In total, 1 967 300 births were included in this study. For PM2.5, PM(10)and O-3, we found positive additive interactions (RERIs >0) between heatwaves and higher air pollution levels. Combined effects of heatwaves and green space indicated negative interactions (RERIs <0) for less intense heatwaves (i.e. shorter duration or relatively low temperature), whereas there were potential positive interactions (RERIs >0) for more intense heatwaves.Conclusion.This study found synergistic harmful effects for heatwaves with air pollution, and potential positive interactions with lack of green space on PTB. Implementing interventions, such as heat warning systems and behavioral changes, targeted toward pregnant women at risk for high air pollution and low green space exposures may optimize the benefits of reducing acute exposure to extreme heat before delivery.
An energy supply dominated by the use of fossil fuels causes both climate change and air pollution, which have negative impacts on human capital via both health and productivity. In addition, different people are affected differently because of factors such as age, gender and education level. To enhance the understanding of the benefits of low carbon transition from the labor supply perspective and help to identify strategies of collaborative control for CO2 and local air pollutants in China, an integrated assessment model linking the air quality module and the health impact module with a disaggregated labor sector computable general equilibrium (CGE) economic system is developed and applied in this study. Results show some key findings. First, renewable energy development and carbon capture and storage (CCS) technologies will contribute significantly to GDP in terms of their impact on air quality improvement by 0.99% and 0.54%, respectively, in 2050. Second, due to differences in labor composition, air pollution has, and will continue to have, the greatest impact on sectors with a higher proportion of male and lower-educated workers – such as the coal sector, and it will have the least impact on sectors with a higher proportion of female and higher-educated workers – such as the public administration sector. Third, the different impacts of sector output will increase economic inequality.
Air pollution regulation requires knowing major sources on any given zone, setting specific controls, and assessing how health risks evolve in response to those controls. Receptor models (RM) can identify major sources: transport, industry, residential, etc. However, RM results are typically available for short term periods, and there is a paucity of RM results for developing countries. We propose to combine a cluster analysis (CA) of air pollution and meteorological measurements with a short-term RM analysis to estimate a long-term, hourly source apportionment of ambient PM(2.5) and PM(10). We have developed a proof of the concept for this proposed methodology in three case studies: a large metropolitan zone, a city with dominant residential wood burning (RWB) emissions, and a city in the middle of a desert region. We have found it feasible to identify the major sources in the CA results and obtain hourly time series of their contributions, effectively extending short-term RM results to the whole ambient monitoring period. This methodology adds value to existing ambient data. The hourly time series results would allow researchers to apportion health benefits associated with specific air pollution regulations, estimate source-specific trends, improve emission inventories, and conduct environmental justice studies, among several potential applications.
Because of fast-paced industrialization, urbanization, and population growth in Indonesia, there are serious health issues in the country resulting from air pollution. This study uses geospatial modelling technologies, namely land-use regression (LUR), geographically weighted regression (GWR), and geographic and temporal weighted regression (GTWR) models, to assess variations in particulate matter (PM(10)) and nitrogen dioxide (NO(2)) concentrations in Surabaya City, Indonesia. This is the first study to implement spatiotemporal variability of air pollution concentrations in Surabaya City, Indonesia. To develop the prediction models, air pollution data collected from seven monitoring stations from 2010 to 2018 were used as dependent variables, while land-use/land cover allocations within a 250 m to 5000 m circular buffer range surrounding the monitoring stations were collected as independent variables. A supervised stepwise variable selection procedure was applied to identify the important predictor variables for developing the LUR, GWR, and GTWR models. The developed models of LUR, GWR, and GTWR accounted for 49%, 50%, and 51% of PM(10) variations and 46%, 47%, and 48% of NO(2) variations, respectively. The GTWR model performed better (R(2) = 0.51 for PM(10) and 0.48 for NO(2)) than the other two models (R(2) = 0.49-0.50 for PM(10) and 0.46-0.47 for NO(2)), LUR and GWR. In the PM(10) model four predictor variables, public facility, industry and warehousing, paddy field, and normalized difference vegetation index (NDVI), were selected during the variable selection procedure. Meanwhile, paddy field, residential area, rainfall, and temperature played important roles in explaining NO(2) variations. Because of biomass burning issues in South Asia, the paddy field, which has a positive correlation with PM(10) and NO(2), was selected as a predictor. By using long-term monitoring data to establish prediction models, this model may better depict PM(10) and NO(2) concentration variations within areas across Asia.
We investigated the geographical character of the COVID-19 infection in China and correlated it with satellite- and ground-based measurements of air quality. Controlling for population density, we found more viral infections in those prefectures (U.S. county equivalent) afflicted by high Carbon Monoxide, Formaldehyde, PM 2.5, and Nitrogen Dioxide values. Higher mortality was also correlated with relatively poor air quality. When summarizing the results at a greater administrative level, we found that the 10 provinces (U.S. state equivalent) with the highest rate of mortality by COVID-19, were often the most polluted but not the most densely populated. Air pollution appears to be a risk factor for the incidence of this disease, despite the conventionally apprehended influence of human mobility on disease dynamics from the site of first appearance, Wuhan. The raw correlations reported here should be interpreted in a broader context, accounting for the growing evidence reported by several other studies. These findings warn communities and policymakers on the implications of long-term air pollution exposure as an ecological, multi-scale public health issue.
OBJECTIVES: There are still controversies about the impact of climatic and environmental factors on thyroid function parameters in healthy populations. We investigated the relationships between climate, air pollution exposure, and thyroid function fluctuations. METHODS: We retrospectively reviewed 327,913 individuals attending routine health checks from December 2013 to December 2018. We analyzed the associations between thyroid function and climatic factors using Spearman’s correlation analysis. We explored the relationships between thyroid function and air pollution exposure using multiple linear regression analysis, after adjusting for age, sex, season, and outdoor temperature. We also performed subgroup analyses by age and sex and sensitivity analyses of different anti-thyroid peroxidase antibody status. RESULTS: Thyroid-stimulating hormone (TSH) and free triiodothyronine (FT3) were negatively associated with outdoor temperature (r?=?-?0.66, P?<?0.001; r?=?-?0.55, P?<?0.001), while free thyroxine (FT4) and FT4/FT3 were positively associated with temperature (r?=?0.35, P?<?0.001; r?=?0.79, P?<?0.001). An increase of 10 ?g/m(3) in fine particulate matter???2.5 ?m (PM2.5) was associated with a decrease of 0.12 pmol/L in FT4 and an increase of 0.07 pmol/L in FT3 (both P?<?0.01). FT4/FT3 was significantly negatively associated with PM2.5 (coefficient: -?0.06, P?<?0.01). These results remained robust in hierarchical analyses and sensitivity analyses. CONCLUSIONS: Thyroid function parameters are associated with climate and air pollution exposure. These factors may influence variations in thyroid function. Our results also highlight the importance of public health interventions to reduce air pollution.
The shift towards the new paradigm, that is, the “ecological and humanistic” paradigm, introduced by the United Nations in the Agenda 2030, and the current period of health emergency due to COVID-19 place the human dimension at the centre of the development strategies for our cities. The humanistic dimension, in particular, is related to human wellbeing, health and living conditions. The health and wellbeing of citizens depend on factors and actions that go beyond the health sector. In particular, here, the attention is focused on the negative impacts produced by pollution and climate change, issues that concern (and that are closely related to) most urban agglomerations in the world. The pandemic due to COVID-19 has highlighted the close relationship existing among social, natural and economic systems. Each system is interdependent on the other. Thus, the pandemic has boosted the necessity to accelerate efforts to address climate change. Therefore, in this framework, new urban development models are required. The circular economy model is proposed as a model able to reduce the negative impacts of urban transformations. The attention is then focused on implementation tools for improving decision-making processes and, in particular, on the evaluation tools for assessing the multidimensional impacts of urbanisation on human health.
Human actions intensify the greenhouse effect, aggravating climate changes in the Amazon and elsewhere in the world. The Intergovernmental Panel on Climate Change (IPCC) foresees a global increase of up to 4.5 °C and 850 ppm CO(2) (above current levels) by 2100. This will impact the biology of the Aedes aegypti mosquito, vector of Dengue, Zika, urban Yellow Fever and Chikungunya. Heat shock proteins are associated with adaptations to anthropic environments and the interaction of some viruses with the vector. The transcription of the hsp26, hsp83 and hsc70 genes of an A. aegypti population, maintained for more than forty-eight generations, in the Current, Intermediate and Extreme climatic scenario predicted by the IPCC was evaluated with qPCR. In females, highest levels of hsp26, hsp83 and hsc70 expression occurred in the Intermediate scenario, while in males, levels were high only for hsp26 gene in Current and Extreme scenarios. Expression of hsp83 and hsc70 genes in males was low under all climatic scenarios, while in the Extreme scenario females had lower expression than in the Current scenario. The data suggest compensatory or adaptive processes acting on heat shock proteins, which can lead to changes in the mosquito’s biology, altering vectorial competence.
Air pollution and the urban heat island effect are consistently linked to numerous respiratory and heat-related illnesses. Additionally, these stressors disproportionately impact low-income and historically marginalized communities due to their proximity to emissions sources, lack of access to green space, and exposure to other adverse environmental conditions. Here, we use relatively low-cost stationary sensors to analyze PM2.5 and temperature data throughout the city of Richmond, Virginia, on the ten hottest days of 2019. For both hourly means within the ten hottest days of 2019 and daily means for the entire record for the year, the temperature was found to exhibit a positive correlation with PM2.5. Analysis of hourly means on the ten hottest days yielded a diurnal pattern in which PM2.5 levels peaked in the early morning and reached their minima in the mid-afternoon. Spatially, sites exhibiting higher temperatures consistently had higher PM2.5 readings, with vulnerable communities in the east end and more intensely developed parts of the city experiencing significantly higher temperatures and PM2.5 concentrations than the suburban neighborhoods in the west end. These findings suggest an uneven distribution of air pollution in Richmond during extreme heat events that are similar in pattern but less pronounced than the temperature differences during these events, although further investigation is required to verify the extent of this relationship. As other studies have found both of these environmental stressors to correlate with the distribution of green space and other land-use factors in cities, innovative and sustainable planning decisions are crucial to the mitigation of these issues of inequity going forward.
Objectives: Inconsistent results have been found between pneumonia and meteorological factors. We aimed to identify principal meteorological factors associated with pneumonia, and to estimate the effect size and lag time. Methods: This was nationwide population-based study used a healthcare claims database merged with a weather database in eight metropolitan cities in Korea. We applied a stepwise approach using the Granger causality test and generalized additive model to elucidate the association between weekly pneumonia incidence (WPI) and meteorological factors/air pollutants (MFAP). Impulse response function was used to examine the time lag. Results: In total, 2 011 424 cases of pneumonia were identified from 2007 to 2017. Among MFAP, diurnal temperature range (DTR), humidity and particulate matter <= 2.5 mm in diameter (PM2.5) showed statistically significant associations with WPI (p < 0.001 for all 3 MFAPs). The association of DTR and WPI showed an inverted U pattern for bacterial and unspecified pneumonia, whereas for viral pneumonia, WPI increased gradually in a more linear manner with DTR and no substantial decline. Humidity showed a consistent pattern in all three pneumonia categories. WPI steeply increased up to 10 to 20 mu g/m(3) of PM2.5 but did not show a further increase in higher concentrations. On the basis of the result, we examined the effect of MFAP in different lag times up to 3 weeks. Conclusions: DTR, humidity and PM2.5 were identified as MFAP most closely associated with WPI. With the model, we were able to visualize the effectetime association of MFAP and WPI. (C) 2020 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.
Objective: Given the lack of studies examining the associations between daily weather and air pollution with nightly objective sleep over multiple weeks, we quantified these associations in a prospective cohort of healthy participants with episodic migraine. Methods: Ninety-eight participants completed daily electronic diaries and wore an actigraph for an average of 45 ds, and a total 4406 nights of data were collected. Nightly sleep characteristics including duration, wake after sleep onset (WASO), and efficiency were assessed using wrist actigraphy. Daily weather parameters and air pollution levels were collected from local weather station and ground-level air quality monitors. We used linear fixed effects models adjusting for participant, day of the week, and day of the year (for weather analysis), and additionally adjusted for temperature and relative humidity (for air pollution analysis). Results: The participants were 35 +/- 12 yrs old and 86 were women. A 10 degrees F higher daily average temper-ature was associated with 0.88 (95% CI: 0.06, 1.70) minutes longer WASO and 0.14% (95% CI:-0.01%, 0.30%) lower sleep efficiency on that night. A 14 parts per billion (ppb) (interquartile range) higher daily maximum eight-h ozone was associated with 7.51 (95% CI: 3.23, 11.79) minutes longer sleep duration on that night. Associations did not differ between cold (October-March) and warm (April-September) seasons. Conclusions: Higher daily ozone was associated with longer sleep duration and modest associations were observed between higher temperature and lower WASO and lower efficiency. (c) 2020 Elsevier B.V. All rights reserved.
BACKGROUND: Despite the substantial role indoor exposure has played in heat wave-related mortality, few epidemiological studies have examined the health effects of exposure to indoor heat. As a result, knowledge gaps regarding indoor heat-health thresholds, vulnerability, and adaptive capacity persist. OBJECTIVE: We evaluated the role of indoor heat exposure on mortality and morbidity among the elderly ( ? 65?years of age) in Houston, Texas. METHODS: Mortality and emergency hospital admission data were obtained through the Texas Department of State Health Services. Summer indoor heat exposure was modeled at the U.S. Census block group (CBG) level using building energy models, outdoor weather data, and building characteristic data. Indoor heat-health associations were examined using time-stratified case-crossover models, controlling for temporal trends and meteorology, and matching on CBG of residence, year, month, and weekday of the adverse health event. Separate models were fitted for three indoor exposure metrics, for individual lag days 0-6, and for 3-d moving averages (lag 0-2). Effect measure modification was explored via stratification on individual- and area-level vulnerability factors. RESULTS: We estimated positive associations between short-term changes in indoor heat exposure and cause-specific mortality and morbidity [e.g., circulatory deaths, odds ratio per?5°C?increase = 1.16 (95% CI: 1.03, 1.30)]. Associations were generally positive for earlier lag periods and weaker across later lag periods. Stratified analyses suggest stronger associations between indoor heat and emergency hospital admissions among African Americans compared with Whites. DISCUSSION: Findings suggest excess mortality among certain elderly populations in Houston who are likely exposed to high indoor heat. We developed a novel methodology to estimate indoor heat exposure that can be adapted to other U.S. LOCATIONS: In locations with high air conditioning prevalence, simplified modeling approaches may adequately account for indoor heat exposure in vulnerable neighborhoods. Accounting for indoor heat exposure may improve the estimation of the total impact of heat on health. https://doi.org/10.1289/EHP6340.
Background: A growing number of cities, including Greater London, have set ambitious targets, including detailed policies and implementation plans, to reach global goals on sustainability, health, and climate change. Here we present a tool for a rapid assessment of the magnitude of impact of specific policy initiatives to reach these targets. The decision-support tool simultaneously quantifies the environmental and health impacts of specified selected policies. Methods: The ‘Cities Rapid Assessment Framework for Transformation (CRAFT)’ tool was applied to Greater London. CRAFT quantifies the effects of ten environmental policies on changes in (1) greenhouse gas (GHG) emissions, (2) exposures to environmental hazards, (3) travel-related physical activity, and (4) mortality (the number of attributable deaths avoided in one typical year). Publicly available data and epidemiological evidence were used to make rapid quantitative estimates of these effects based on proportional reductions in GHG emissions and environmental exposures from current baseline levels and to compute the mortality impacts. Results: The CRAFT tool estimates that, of roughly 50,000 annual deaths in Greater London, the modelled hazards (PM (2.5) (from indoor and outdoor sources), outdoor NO (2), indoor radon, cold, overheating) and low travel-related physical activity are responsible for approximately 10,000 premature environment-related deaths. Implementing the selected polices could reduce the annual mortality number by about 20% (~1,900 deaths) by 2050. The majority of these deaths (1,700) may be avoided through increased uptake in active travel. Thus, out of ten environmental policies, the ‘active travel’ policy provides the greatest health benefit. Also, implementing the ten policies results in a GHG reduction of around 90%. Conclusions: The CRAFT tool quantifies the effects of city policies on reducing GHG emissions, decreasing environmental health hazards, and improving public health. The tool has potential value for policy makers through providing quantitative estimates of health impacts to support and prioritise policy options.
China’s gains in food production over the past four decades have been associated with substantial agricultural nitrogen losses, which contribute to air and water pollution, greenhouse gas emissions and damage to human health. Here, we explore the potential to improve agricultural production practices that simultaneously increase yields while addressing these environmental challenges. We link agronomic research with air quality modelling for an integrated assessment of four improved nitrogen management strategies: improved farm management practices with nitrogen use reductions; machine deep placement of fertilizer; enhanced-efficiency fertilizer use; and improved manure management. We find that simultaneous implementation of the four strategies provides the largest benefits, which include: reductions in PM2.5 concentrations and associated premature deaths; increases in grain yields and grain nitrogen use efficiency; reductions in NO3- leaching and runoff and greenhouse gas emissions. Total benefits of US$30 billion per year exceed the US$18 billion per year in costs. Our findings indicate that policies that improve farmers’ agricultural nitrogen management in China will improve both food security and public health while addressing multiple environmental challenges. Similar increases in attention on agricultural policy around the world are likely to provide large benefits in food security, environmental integrity and public health.
