An accurate fine-resolution surface of the chemical composition of fine particulate matter (PM2.5) would offer valuable information for epidemiological studies and health impact assessments. We ...develop geoscience-derived estimates of PM2.5 composition from a chemical transport model (GEOS-Chem) and satellite observations of aerosol optical depth, and statistically fuse these estimates with ground-based observations using a geographically weighted regression over North America to produce a spatially complete representation of sulfate, nitrate, ammonium, black carbon, organic matter, mineral dust, and sea-salt over 2000–2016. Significant long-term agreement is found with cross-validation sites over North America (R2 = 0.570.96), with the strongest agreement for sulfate (R2 = 0.96), nitrate (R2 = 0.90), and ammonium (R2 = 0.86). We find that North American decreases in population-weighted fine particulate matter (PM2.5) concentrations since 2000 have been most heavily influenced by regional changes in sulfate and organic matter. Regionally, the relative importance of several chemical components are found to change with PM2.5 concentration, such as higher PM2.5 concentrations having a larger proportion of nitrate and a smaller proportion of sulfate. This data set offers information for research into the health effects of PM2.5 chemical components.
Millions of people die every year from diseases caused by exposure to outdoor air pollution. Some studies have estimated premature mortality related to local sources of air pollution, but local air ...quality can also be affected by atmospheric transport of pollution from distant sources. International trade is contributing to the globalization of emission and pollution as a result of the production of goods (and their associated emissions) in one region for consumption in another region. The effects of international trade on air pollutant emissions, air quality and health have been investigated regionally, but a combined, global assessment of the health impacts related to international trade and the transport of atmospheric air pollution is lacking. Here we combine four global models to estimate premature mortality caused by fine particulate matter (PM
) pollution as a result of atmospheric transport and the production and consumption of goods and services in different world regions. We find that, of the 3.45 million premature deaths related to PM
pollution in 2007 worldwide, about 12 per cent (411,100 deaths) were related to air pollutants emitted in a region of the world other than that in which the death occurred, and about 22 per cent (762,400 deaths) were associated with goods and services produced in one region for consumption in another. For example, PM
pollution produced in China in 2007 is linked to more than 64,800 premature deaths in regions other than China, including more than 3,100 premature deaths in western Europe and the USA; on the other hand, consumption in western Europe and the USA is linked to more than 108,600 premature deaths in China. Our results reveal that the transboundary health impacts of PM
pollution associated with international trade are greater than those associated with long-distance atmospheric pollutant transport.
Summary Background Emerging evidence suggests that living near major roads might adversely affect cognition. However, little is known about its relationship with the incidence of dementia, ...Parkinson's disease, and multiple sclerosis. We aimed to investigate the association between residential proximity to major roadways and the incidence of these three neurological diseases in Ontario, Canada. Methods In this population-based cohort study, we assembled two population-based cohorts including all adults aged 20–50 years (about 4·4 million; multiple sclerosis cohort) and all adults aged 55–85 years (about 2·2 million; dementia or Parkinson's disease cohort) who resided in Ontario, Canada on April 1, 2001. Eligible patients were free of these neurological diseases, Ontario residents for 5 years or longer, and Canadian-born. We ascertained the individual's proximity to major roadways based on their residential postal-code address in 1996, 5 years before cohort inception. Incident diagnoses of dementia, Parkinson's disease, and multiple sclerosis were ascertained from provincial health administrative databases with validated algorithms. We assessed the associations between traffic proximity and incident dementia, Parkinson's disease, and multiple sclerosis using Cox proportional hazards models, adjusting for individual and contextual factors such as diabetes, brain injury, and neighbourhood income. We did various sensitivity analyses, such as adjusting for access to neurologists and exposure to selected air pollutants, and restricting to never movers and urban dwellers. Findings Between 2001, and 2012, we identified 243 611 incident cases of dementia, 31 577 cases of Parkinson's disease, and 9247 cases of multiple sclerosis. The adjusted hazard ratio (HR) of incident dementia was 1·07 for people living less than 50 m from a major traffic road (95% CI 1·06–1·08), 1·04 (1·02–1·05) for 50–100 m, 1·02 (1·01–1·03) for 101–200 m, and 1·00 (0·99–1·01) for 201–300 m versus further than 300 m ( p for trend=0·0349). The associations were robust to sensitivity analyses and seemed stronger among urban residents, especially those who lived in major cities (HR 1·12, 95% CI 1·10–1·14 for people living <50 m from a major traffic road), and who never moved (1·12, 1·10–1·14 for people living <50 m from a major traffic road). No association was found with Parkinson's disease or multiple sclerosis. Interpretation In this large population-based cohort, living close to heavy traffic was associated with a higher incidence of dementia, but not with Parkinson's disease or multiple sclerosis. Funding Health Canada (MOA-4500314182).
Abstract
Ambient fine particulate matter (PM
2.5
) is the world’s leading environmental health risk factor. Reducing the PM
2.5
disease burden requires specific strategies that target dominant ...sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM
2.5
exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74–1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM
2.5
burden), with coal contributing to over half. Other dominant global sources included residential (0.74 0.52–0.95 million deaths; 19.2%), industrial (0.45 0.32–0.58 million deaths; 11.7%), and energy (0.39 0.28–0.51 million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources.
•This is a retrospective cohort study based on a national multi-center survey. 54,517 pregnant women from 55 hospitals in 24 provinces were included in the final analysis;•A combined ...geoscience-statistical model was applied to estimate the exposure concentration of PM2.5 and its components;•We used a generalized mixed model to estimate the associations, and identified several components with higher risks.•We conducted the model analysis across different exposure windows and found that the second trimester is a relatively sensitive window.
Ambient air pollution has been linked to the development of gestational diabetes mellitus (GDM). However, previous studies provided inconsistent findings and no study has examined the effects of complex chemical constituents of the particular matter on GDM, especially in developing countries. Therefore, we aim to investigate the associations of exposure to PM2.5 (particular matter ≤ 2.5 μm) and its constituents with GDM, and to identify susceptible exposure window in a large survey in China.
The China Labor and Delivery Survey was a cross-sectional investigation conducted in 24 provinces in China between 2015 and 2016. A random sample of all deliveries in each participating hospital was selected and detailed obstetric and newborn information was extracted from medical records. Average concentrations of PM2.5 and six constituents (organic matter, black carbon, sulfate, nitrate, ammonium and soil dust) were estimated (1 km × 1 km) using a combined geoscience-statistical model. GDM was diagnosed based on an oral glucose tolerance test (OGTT) between 24 to 28 weeks of gestation and according to IADPSG criteria. Generalized linear mixed models were used to adjust for potential confounders.
A total of 54,517 subjects from 55 hospitals were included. The incidence of GDM was 10.8%. An interquartile range (IQR) increase in PM2.5 exposure in the 2nd trimester of pregnancy was associated with an increased GDM risk in the single pollutant model, adjusted odds ratio (aOR) = 1.11 and 95% confidence interval (CI): 1.01–1.22. Exposure to organic matter (aOR = 1.14; 95%CI: 1.05–1.23), black carbon (aOR = 1.15; 95%CI: 1.07–1.25) and nitrate (aOR = 1.13; 95%CI: 1.02–1.24) during 2nd trimester were associated with increased risks of GDM. Associations between constituents and GDM were robust after controlling for total PM2.5 mass and accounting for multi-collinearity.
Exposure to PM2.5 in 2nd trimester of pregnancy was associated with an increased risk of GDM. Organic matter, black carbon and nitrate may be the main culprits for the association.
Air pollution is a major risk factor for global health, with 3 million deaths annually being attributed to fine particulate matter ambient pollution (PM2.5).The primary source of information for ...estimating population exposures to air pollution has been measurements from ground monitoring networks but, although coverage is increasing, regions remain in which monitoring is limited. The data integration model for air quality supplements ground monitoring data with information from other sources, such as satellite retrievals of aerosol optical depth and chemical transport models. Set within a Bayesian hierarchical modelling framework, the model allows spatially varying relationships between ground measurements and other factors that estimate air quality. The model is used to estimate exposures, together with associated measures of uncertainty, on a high resolution grid covering the entire world from which it is estimated that 92% of the world's population reside in areas exceeding the World Health Organization's air quality guidelines.
Ambient air pollution is associated with numerous adverse health impacts. Previous assessments of global attributable disease burden have been limited to urban areas or by coarse spatial resolution ...of concentration estimates. Recent developments in remote sensing, global chemical-transport models, and improvements in coverage of surface measurements facilitate virtually complete spatially resolved global air pollutant concentration estimates. We combined these data to generate global estimates of long-term average ambient concentrations of fine particles (PM2.5) and ozone at 0.1° × 0.1° spatial resolution for 1990 and 2005. In 2005, 89% of the world’s population lived in areas where the World Health Organization Air Quality Guideline of 10 μg/m3 PM2.5 (annual average) was exceeded. Globally, 32% of the population lived in areas exceeding the WHO Level 1 Interim Target of 35 μg/m3, driven by high proportions in East (76%) and South (26%) Asia. The highest seasonal ozone levels were found in North and Latin America, Europe, South and East Asia, and parts of Africa. Between 1990 and 2005 a 6% increase in global population-weighted PM2.5 and a 1% decrease in global population-weighted ozone concentrations was apparent, highlighted by increased concentrations in East, South, and Southeast Asia and decreases in North America and Europe. Combined with spatially resolved population distributions, these estimates expand the evaluation of the global health burden associated with outdoor air pollution.
Experimental evidence and studies of children and adolescents suggest that ambient fine particulate matter particulate matter
in aerodynamic diameter (
) air pollution may be obesogenic, but the ...relationship between
and the risk of body weight gain and obesity in adults is uncertain.
Our goal was to characterize the association between
and the risks of weight gain and obesity.
We followed 3,902,440 U.S. Veterans from 2010 to 2018 (median 8.1 y, interquartile range: 7.3-8.4) and assigned time-updated
exposures by linking geocoded residential street addresses with satellite-based estimates of surface-level
mass (at
resolution). Associations with
were estimated using Cox proportional hazards models for incident obesity body mass index (
and a
increase in weight relative to baseline and linear mixed models for associations with intra-individual changes in BMI and weight.
A
higher average annual
concentration was associated with risk of incident obesity
;
(95% CI: 1.06, 1.11) and the risk of a
(
) increase in weight
(95% CI: 1.06, 1.08) and with higher intra-individual changes in BMI
(95% CI: 0.139, 0.142) and weight
(95% CI: 0.955, 0.981). Nonlinear exposure-response models indicated associations at
concentrations below the national standard of
. As expected, a negative exposure control (ambient air sodium) was not associated with obesity or weight gain. Associations were consistent in direction and magnitude across sensitivity analyses that included alternative outcomes and exposures assigned at different spatial resolutions.
air pollution was associated with the risk of obesity and weight gain in a large predominantly male cohort of U.S. Veterans. Discussions about health effects of
should include its association with obesity, and deliberations about the epidemiology of obesity should consider its association with
. Investigation in other cohorts will deepen our understanding of the relationship between
and weight gain and obesity. https://doi.org/10.1289/EHP7944.
The rapid increase of aerosols over the Indian Subcontinent over the last decade has the potential for severe health implications. However, the lack of a dense network to measure PM2.5 (particles ...with aerodynamic diameter<2.5μm) hinders health risk assessments at regional scale. Here, we utilize Multiangle Imaging SpectroRadiometer (MISR)-retrieved columnar aerosol optical depths to estimate surface PM2.5 based on recently published conversion factors that account for the composition and vertical distribution of aerosols. We examine the space–time variability of bias-corrected (utilizing coincident in-situ observations) PM2.5 over the Indian Subcontinent for the period Mar 2000–Feb 2010. We show that 51% of the subcontinent's 1.4 billion people are exposed to pollution that exceed the World Health Organization's highest annual air quality threshold of 35μgm−3, while another 13% and 18% are exposed in the ranges 25–35 and 15–25μgm−3 respectively. Of the remaining population who breathe clean air, only 25% live in urban areas. In many regions, the high-levels of pollution are persistent rather than episodic. PM2.5 concentrations in the rural areas of the Indo-Gangetic Basin are higher than many urban centers in peninsular India. Five hotspots (where PM2.5 increases by >15μgm−3 over the ten-year period) are identified, which cover parts of the eleven Indian states and Bangladesh affecting ~23% of the population. Our results highlight the urgent need to carry out local cohort studies at these hotspots to better understand the health impacts under local conditions.
► Variability of fine particulates over India from ten years (Mar 2000–Feb 2010) data for the first time ► Exposure analysis based on World Health Organization air quality standards ► Estimation of changes in PM2.5 during the ten-year period ► Robust statistics of PM2.5 (urban vs. rural) for further studies ► The method complements the data gap in India for studying health effects of aerosols
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