[Show abstract][Hide abstract] ABSTRACT: Backround:
Fine particulate air pollution (PM2.5) is known to contribute to cardiorespiratory mortality but it is not clear how PM2.5 oxidative burden (i.e. the ability of PM2.5 to cause oxidative stress) may influence long-term mortality risk.
We examined the relationship between PM2.5 oxidative burden and cause-specific mortality in Ontario, Canada. Integrated PM2.5 samples were collected from 30 provincial monitoring sites between 2012 and 2013. The oxidative potential (% depletion/µg) of regional PM2.5 was measured as the ability of filter extracts to deplete antioxidants (glutathione and ascorbate) in a synthetic respiratory tract lining fluid. PM2.5oxidative burden was calculated as the product of PM2.5 mass concentrations and regional estimates of oxidative potential. In total, this study included 193,300 people who completed the Canadian long-form census in 1991 and who lived within 5km of a site where oxidative potential was measured. Deaths occurring between 1991 and 2009 were identified through record linkages and Cox proportional hazard models were used to estimate hazard ratios (and 95% confidence intervals) for interquartile changes in exposure adjusting for individual-level covariates and indirect-adjustment for smoking and obesity.
Glutathione-related oxidative burden was associated with cause-specific mortality. For lung cancer specifically, this metric was associated with a 12% (95% CI: 5.0-19) increased risk of mortality whereas a 5.0% (95% CI: 0.1, 10) increase was observed for PM2.5. Indirect adjustment for smoking and obesity decreased the lung cancer hazard ratio for glutathione-related oxidative burden but it remained significantly elevated (HR=1.07, 95% CI: 1.005, 1.146). Ascorbate-related oxidative burden was not associated with mortality.
Our findings suggest that glutathione-related oxidative burden may be more strongly associated with lung cancer mortality than PM2.5 mass concentrations.
Full-text · Article · Apr 2016 · Environmental Research
[Show abstract][Hide abstract] ABSTRACT: Objective:
To estimate the degree to which fine particulate (PM2.5) air pollution is associated with systemic autoimmune rheumatic diseases (SARDs).
We used population-based administrative data from Alberta (1993-2007) and Quebec (1989-2011). SARD algorithms included ≥2 physician billing codes, or ≥1 rheumatology billing code, or ≥1 hospitalization diagnostic code (for systemic lupus, Sjogren's Syndrome, scleroderma, polymyositis, dermatomyositis, or undifferentiated connective tissue disease). Bayesian hierarchical latent class regression models estimated the probability that any given resident was a SARD case, based on the algorithms. Mean 2001-2006 residential ambient PM2.5 levels were assigned using satellite-derived data for dissemination area regions in Alberta and CLSC regions in Quebec. The sum of individual level probabilities provided the estimated total cases per region in each province, according to age, sex, urban-versus-rural residence, income, and PM2.5 levels. In Alberta, we ran separate models for First-Nations (FN) and non-First Nations subgroups. Bayesian logistic regression modeling generated odds ratio (OR) estimates for being a SARD case, accounting concurrently for demographics, as well as an interaction term between age and sex.
Our data suggested that the probability of being a SARD case was higher among females versus males and for residents aged >45 versus younger, with the highest ORs for older females. Independently, the odds of being a SARDs case increased with PM2.5 levels in both provinces.
Our data suggest that PM2.5 exposure may be associated with an increased risk of SARDs.
No preview · Article · Apr 2016 · Environmental Research
[Show abstract][Hide abstract] ABSTRACT: Most studies on the association between exposure to fine particulate matter (PM2.5) and mortality have considered only total concentration of PM2.5 or individual components of PM2.5, and not the combined effects of concentration and particulate composition. We sought to develop a method to estimate the risk of death from long-term exposure to PM2.5 and the distribution of its components, namely: sulphate, nitrate, ammonium, organic mass, black carbon, and mineral dust. We decomposed PM2.5 exposure into the sum of total concentration and the proportion of each component. We estimated the risk of death due to exposure using a cohort of ∼2.4 million Canadians who were followed for vital status over 16 years. Modelling the concentration of PM2.5 with the distribution of the proportions of components together was a superior predictor for mortality than either total PM2.5 concentration alone, or all component concentrations modelled together. Our new approach has the advantage of characterizing the toxicity of the atmosphere in its entirety. This is required to fully understand the health benefits associated with strategies to improve air quality that may result in complex changes not only in PM2.5 concentration, but also in the distribution of particle components.
[Show abstract][Hide abstract] ABSTRACT: There are few multi-decadal observations of atmospheric aerosols worldwide. This study applies global hourly visibility (Vis) observations at more than 3000 stations to investigate historical trends in atmospheric haze over 1945–1996 for the US, and over 1973–2013 for Europe and Eastern Asia. A comprehensive data screening and processing framework is developed and applied to minimize uncertainties and construct monthly statistics of inverse visibility (1/Vis). This data processing includes removal of relatively clean cases with high uncertainty, and change point detection to identify and separate methodological discontinuities such as the introduction of instrumentation. Although the relation between 1/Vis and bext varies across different stations, spatially coherent trends of the screened 1/Vis exhibit consistency with the temporal evolution of collocated aerosol measurements, including the atmospheric extinction coefficient (bext) trend of −2.4 % yr−1 (95 % CI: −3.7, −1.1 % yr−1) vs. 1/Vis trend of −1.6 % yr−1 (95 % CI: −2.4, −0.8 % yr−1) over the US for 1989–1996, and the fine aerosol mass (PM2.5) trend of −5.8 % yr−1 (95 % CI: −7.8, −4.2 % yr−1) vs. 1/Vis trend of −3.4 % yr−1 (95 % CI: −4.4, −2.4 % yr−1) over Europe for 2006–2013. Regional 1/Vis and EDGAR sulfur dioxide (SO2) emissions are significantly correlated over the eastern US for 1970–1995 (r=0.73), over Europe for 1973–2008 (r ~ 0.9) and over China for 1973–2008 (r ~ 0.9). Consistent "reversal points" from increasing to decreasing in SO2 emission data are also captured by the regional 1/Vis time series (e.g. late 1970s for the eastern US, early 1980s for Western Europe, late 1980s for Eastern Europe, and mid 2000s for China). The consistency of inferred 1/Vis trends with other in situ measurements and emission data demonstrates promise in applying these reconstructed 1/Vis data for historical air quality studies.
No preview · Article · Dec 2015 · Atmospheric Chemistry and Physics
[Show abstract][Hide abstract] ABSTRACT: We determine and interpret fine particulate matter (PM2.5) concentrations in eastern China for January to December 2013 at a horizontal resolution of 6 km from aerosol optical depth (AOD) retrieved from the Korean geostationary ocean color imager (GOCI) satellite instrument. We implement a set of filters to minimize cloud contamination in GOCI AOD. Evaluation of filtered GOCI AOD with AOD from the Aerosol Robotic Network (AERONET) indicates significant agreement with mean fractional bias (MFB) in Beijing of 6.7 % and northern Taiwan of −1.2 %. We use a global chemical transport model (GEOS-Chem) to relate the total column AOD to the near-surface PM2.5. The simulated PM2.5 / AOD ratio exhibits high consistency with ground-based measurements in Taiwan (MFB = −0.52 %) and Beijing (MFB = −8.0 %). We evaluate the satellite-derived PM2.5 versus the ground-level PM2.5 in 2013 measured by the China Environmental Monitoring Center. Significant agreement is found between GOCI-derived PM2.5 and in situ observations in both annual averages (r2 = 0.66, N = 494) and monthly averages (relative RMSE = 18.3 %), indicating GOCI provides valuable data for air quality studies in Northeast Asia. The GEOS-Chem simulated chemical composition of GOCI-derived PM2.5 reveals that secondary inorganics (SO42-, NO3-, NH4+) and organic matter are the most significant components. Biofuel emissions in northern China for heating increase the concentration of organic matter in winter. The population-weighted GOCI-derived PM2.5 over eastern China for 2013 is 53.8 μg m−3, with 400 million residents in regions that exceed the Interim Target-1 of the World Health Organization.
Full-text · Article · Nov 2015 · Atmospheric Chemistry and Physics
[Show abstract][Hide abstract] ABSTRACT: Exposure to ambient air pollution is a major risk factor for global disease. Assessment of the impacts of air pollution on population health and the evaluation of trends relative to other major risk factors requires regularly updated, accurate, spatially resolved exposure estimates. We combined satellite-based estimates, chemical transport model simulations and ground measurements from 79 different countries to produce new global estimates of annual average fine particle (PM2.5) and ozone concentrations at 0.1° × 0.1° spatial resolution for five-year intervals from 1990-2010 and the year 2013. These estimates were then applied to assess population-weighted mean concentrations for 1990 – 2013 for each of 188 countries. In 2013, 87% of the world’s population lived in areas exceeding the World Health Organization (WHO) Air Quality Guideline of 10 μg/m3 PM2.5 (annual average). Between 1990 and 2013, decreases in population-weighted mean concentrations of PM2.5 were evident in most high income countries, in contrast to increases estimated in South Asia, throughout much of Southeast Asia, and in China. Population-weighted mean concentrations of ozone increased in most countries from 1990 - 2013, with modest decreases in North America, parts of Europe, and several countries in Southeast Asia.
Full-text · Article · Nov 2015 · Environmental Science and Technology
[Show abstract][Hide abstract] ABSTRACT: Background:
Few studies examining the associations between long-term exposure to ambient air pollution and mortality have considered multiple pollutants when assessing changes in exposure due to residential mobility during follow-up.
We investigated associations between cause-specific mortality and ambient concentrations of fine particulate matter (≤2.5μm; PM2.5), ozone (O3), and nitrogen dioxide (NO2) in anational cohort of about 2.5 million Canadians.
We assigned estimates of annual concentrations of these pollutants to the residential postal codes of subjects for each year during 16 years of follow-up. Historical tax data allowed us to track subjects’ residential postal code annually. We estimated hazard ratios (HRs) for each pollutant separately and adjusted for the other pollutants. We also estimated the product of the three HRs as a measure of the cumulative association with mortality for several causes of death for an increment of the mean minus the 5th percentile of each pollutant: 5.0 μg/m 3 for PM2.5, 9.5ppb for O3, and 8.1ppb for NO2.
PM2.5 , O3, and NO2 were associated with nonaccidental and cause-specific mortality in single-pollutant models. Exposure to PM2.5 alone was not sufficient to fully characterize the toxicity of the atmospheric mix or to fully explain the risk of mortality associated with exposure to ambient pollution. Assuming additiveassociations, the estimated HR for nonaccidental mortality corresponding to a change in exposure from the mean to the 5th percentile for all three pollutants together was 1.075 (95%CI: 1.067,1.084). Accounting for residential mobility had only a limited impact on the association between mortality and PM
2.5 and O3, but increased associations with NO2
In this large, national-level cohort, we found positive associations between several common causes of death and exposure to PM2.5, O3, and NO2
[Show abstract][Hide abstract] ABSTRACT: Satellite observations of the Ultraviolet Aerosol Index (UVAI) are sensitive to absorption of solar radiation by aerosols; this absorption affects photolysis frequencies and radiative forcing. We develop a global simulation of the UVAI using the 3-D chemical transport model GEOS-Chem coupled with the Vector Linearized Discrete Ordinate Radiative Transfer model (VLIDORT). The simulation is applied to interpret UVAI observations from the Ozone Monitoring Instrument (OMI) for the year 2007. Simulated and observed values are highly consistent in regions where mineral dust dominates the UVAI, but a large negative bias (−0.32 to −0.97) exists between simulated and observed values in biomass burning regions. We determine effective optical properties for absorbing organic aerosol, known as brown carbon (BrC), and implement them into GEOS-Chem to better represent observed UVAI values over biomass burning regions. The addition of absorbing BrC decreases the mean bias between simulated and OMI UVAI values from −0.57 to −0.09 over West Africa in January, from −0.32 to +0.0002 over South Asia in April, from −0.97 to −0.22 over southern Africa in July, and from −0.50 to +0.33 over South America in September. The spectral dependence of absorption after adding BrC to the model is broadly consistent with reported observations for biomass burning aerosol, with Absorbing Angstrom Exponent (AAE) values ranging from 2.9 in the ultraviolet (UV) to 1.3 across the UV-Near IR spectrum. We assess the effect of the additional UV absorption by BrC on atmospheric photochemistry by examining tropospheric hydroxyl radical (OH) concentrations in GEOS-Chem. The inclusion of BrC decreases OH by up to 35 % over South America in September, up to 25 % over southern Africa in July, and up to 20 % over other biomass burning regions. Global annual mean OH concentrations in GEOS-Chem decrease due to the presence of absorbing BrC, increasing the methyl chloroform lifetime from 5.62 to 5.68 years, thus reducing the bias against observed values. We calculate the direct radiative effect (DRE) of BrC using GEOS-Chem coupled with the radiative transfer model RRTMG (GC-RT). Treating organic aerosol as containing absorbing BrC rather than as primarily scattering changes global annual mean all-sky top of atmosphere (TOA) DRE by +0.05 W m-2 and all-sky surface DRE by −0.06 W m-2. Regional changes of up to +0.5 W m-2 at TOA and down to −1 W m-2 at the surface are found over major biomass burning regions.
No preview · Article · Oct 2015 · Atmospheric Chemistry and Physics
[Show abstract][Hide abstract] ABSTRACT: We used a Geographically Weighted Regression (GWR) statistical model to represent bias of fine particulate matter concentrations (PM2.5) derived from a 1 km Optimal Estimate (OE) Aerosol Optical Depth (AOD) satellite retrieval that used AOD to PM2.5 relationships from a Chemical Transport Model (CTM) for 2004 to 2008 over North America. This hybrid approach combined the geophysical understanding and global applicability intrinsic to the CTM relationships with the knowledge provided by observational constraints. Adjusting the OE PM2.5 estimates according to the GWR-predicted bias yielded significant improvement compared to unadjusted long-term mean values (R2=0.82 versus R2=0.62) even when a large fraction (70%) of sites were withheld for cross-validation (R2=0.78), and developed seasonal skill (R2=0.62 - 0.89). The effect of individual GWR predictors on OE PM2.5 estimates additionally provided insight into the sources of uncertainty for global satellite-derived PM2.5 estimates. These predictor-driven effects imply that local variability in surface elevation and urban emissions are important sources of uncertainty in geophysical calculations of the AOD to PM2.5 relationship used in satellite-derived PM2.5 estimates over North America, and potentially worldwide.
No preview · Article · Aug 2015 · Environmental Science & Technology
[Show abstract][Hide abstract] ABSTRACT: Air pollution is associated with morbidity and premature mortality. Satellite remote sensing provides globally consistent decadal-scale observations of ambient NO2 pollution.
We determined global population-weighted annual mean NO2 concentrations from 1996 through 2012.
We used observations of NO2 tropospheric column densities from three satellite instruments in combination with chemical transport modeling to produce a global 17-year record of ground-level NO2 at 0.1° x 0.1° resolution. We calculated linear trends in population-weighted annual mean NO2 (PWMNO2) concentrations in different regions around the world as defined by the Global Burden of Disease Study.
We found that PWMNO2 in High-Income North America (Canada and the U.S.) decreased more steeply than in any other region, having declined by -4.7% yr(-1) (95% confidence interval (CI): -5.3, -4.1). PWMNO2 decreased in Western Europe at a rate of -2.5% yr(-1) (95% CI: -3.0, -2.1). The highest PWMNO2 occurred in High-Income Asia Pacific (predominantly Japan and South Korea) in 1996, with a subsequent decrease of -2.1% yr(-1) (95% CI: -2.7, -1.5). In contrast, PWMNO2 almost tripled in East Asia (China, North Korea, and Taiwan), at a rate of 6.7% yr(-1) (95% CI: 6.0, 7.3). The satellite-derived estimates of trends in ground-level NO2 were consistent with regional trends inferred with ground-station monitoring networks in North America (within 0.7% yr(-1)) and Europe (within 0.3% yr(-1)). Our rankings of regional average NO2 and long-term trends differed from the satellite-derived estimates of fine particulate matter reported elsewhere, demonstrating the utility of both indicators to describe changing pollutant mixtures.
Long-term trends in satellite-derived ambient NO2 provide new information about changing global exposure to ambient air pollution. Our estimates are publicly available at http://fizz.phys.dal.ca/~atmos/martin/?page_id=232.
No preview · Article · Aug 2015 · Environmental Health Perspectives
[Show abstract][Hide abstract] ABSTRACT: Numerous studies have examined associations between air pollution and pregnancy outcomes but most have been restricted to urban populations living near monitors.
To examine the association between pregnancy outcomes and fine particulate matter in a large national study including urban and rural areas.
Analyses were based on approximately 3 million singleton live births in Canada between 1999 and 2008. Exposures to PM2.5 (particles of median aerodynamic diameter < 2.5 µm) were assigned by mapping the mother's postal code to a monthly surface based on a national land use regression model that incorporated observations from fixed-site monitoring stations and satellite-derived estimates of PM2.5. Generalized estimating equations were used to examine the association between PM2.5 and preterm birth (gestational age < 37 weeks), term low birth weight (<2500 g), small for gestational age (SGA, <10th percentile of birth weight for gestational age), and term birth weight, adjusting for individual covariates and neighbourhood socioeconomic status (SES).
In fully adjusted models, a 10 µg/m(3) increase in PM2.5 over the entire pregnancy was associated with SGA (OR = 1.04, 95% CI 1.01, 1.07) and reduced term birth weight (-20.5 g, 95% CI -24.7, -16.4). Associations varied across subgroups based on maternal place of birth and period (1999-2003 vs. 2004-2008).
This study based on approximately 3 million births across Canada and employing PM2.5 estimates from a national spatiotemporal model provides further evidence linking PM2.5 and pregnancy outcomes.
Full-text · Article · Jun 2015 · Environmental Health Perspectives
[Show abstract][Hide abstract] ABSTRACT: Epidemiological and health impact studies of fine particulate matter (PM2.5) have been limited in China because of the lack of spatially and temporally continuous PM2.5 monitoring data. Satellite remote sensing of aerosol optical depth (AOD) is widely used in estimating ground-level PM2.5 concentrations. We improved the method for estimating long-term surface PM2.5 concentrations using satellite remote sensing and a chemical transport model, and derived PM2.5 concentrations over China for 2006-2012. We generated a map of surface PM2.5 concentrations at 0.1° × 0.1° over China using the nested-grid GEOS-Chem model, most recent bottom-up emission inventory, and satellite observations from the MODIS and MISR instruments. Aerosol vertical profiles from the space-based CALIOP lidar were used to adjust the climatological drivers of the bias in the simulated results, and corrections were made for incomplete sampling. We found significant spatial agreement between the satellite-derived PM2.5 concentrations and the ground-level PM2.5 measurements collected from literatures (r = 0.74, slope = 0.77, intercept = 11.21 μg/m3). The population-weighted mean of PM2.5 concentrations in China is 71 μg/m3 and more than one billion people live in locations where PM2.5 concentrations exceed the World Health Organization Air Quality Interim Target-1 of 35 μg/m3. The results from our work are substantially higher than previous work, especially in heavily polluted regions. The overall population-weighted mean uncertainty over China is 17.2 μg/m3, as estimated using ground-level AOD measurements and vertical profiles observed from CALIOP.
Full-text · Article · Jun 2015 · Remote Sensing of Environment
[Show abstract][Hide abstract] ABSTRACT: Background:
Long-term exposure to fine particulate matter (PM2.5) has been associated with increased mortality, especially from cardiovascular disease. There are, however, uncertainties about the nature of the exposure-response relation at lower concentrations. In Canada, where ambient air pollution levels are substantially lower than in most other countries, there have been few attempts to study associations between long-term exposure to PM2.5 and mortality.
We present a prospective cohort analysis of 89,248 women who enrolled in the Canadian National Breast Screening Study between 1980 and 1985, and for whom residential measures of PM2.5 could be assigned. We derived individual-level estimates of long-term exposure to PM2.5 from satellite observations. We linked cohort records to national mortality data to ascertain mortality between 1980 and 2005. We used Cox proportional hazards models to characterize associations between PM2.5 and several causes of death. The hazard ratios (HRs) and 95% confidence intervals (CIs) computed from these models were adjusted for several individual and neighborhood-level characteristics.
The cohort was composed predominantly of Canadian-born (82%) and married (80%) women. The median residential concentration of PM2.5 was 9.1 μg/m(3) (standard deviation = 3.4). In fully adjusted models, a 10 μg/m(3) increase in PM2.5 exposure was associated with elevated risks of nonaccidental (HR: 1.12; 95% CI = 1.04, 1.19), and ischemic heart disease mortality (HR: 1.34; 95% CI = 1.09, 1.66).
The findings from this study provide additional support for the hypothesis that exposure to very low levels of ambient PM2.5 increases the risk of cardiovascular mortality.
[Show abstract][Hide abstract] ABSTRACT: Recent Global Burden of Disease (GBD) assessments estimated that outdoor fine-particulate matter (PM2.5) is a causal factor in over 5% of global premature deaths. PM2.5 is produced by a variety of direct and indirect, natural and anthropogenic processes that complicate PM2.5 management. This study develops a proof-of-concept method to quantify the effects on global premature mortality of changes to PM2.5 precursor emissions. Using the adjoint of the GEOS-Chem chemical transport model, we calculated sensitivities of global PM2.5-related premature mortality to emissions of precursor gases (SO2, NOx, NH3) and carbonaceous aerosols. We used a satellite-derived ground-level PM2.5 dataset at approximately 10 km x 10 km resolution to better align the exposure with population density. We used exposure-response functions from the GBD project to relate mortality to exposure in the adjoint calculation. The response of global mortality to changes in local anthropogenic emissions varied spatially by several orders of magnitude. The largest reductions in mortality for a 1 kg km 2 yr 1 decrease in emissions were for ammonia and carbonaceous aerosols in Eastern Europe. The greatest reductions in mortality for a 10% decrease in emissions were found for secondary inorganic sources in East Asia. In general a 10% decrease in SO2 emissions was the most effective source to control, but regional exceptions were found.
No preview · Article · Mar 2015 · Environmental Science and Technology
[Show abstract][Hide abstract] ABSTRACT: Background: More than a decade of satellite observations offers global information about the trend and magnitude of human exposure to fine particulate matter (PM2.5).
Objective: In this study, we developed improved global exposure estimates of ambient PM2.5 mass and trend using PM2.5 concentrations inferred from multiple satellite instruments.
Methods: We combined three satellite-derived PM2.5 sources to produce global PM2.5 estimates at about 10 km × 10 km from 1998 through 2012. For each source, we related total column retrievals of aerosol optical depth to near-ground PM2.5 using the GEOS–Chem chemical transport model to represent local aerosol optical properties and vertical profiles. We collected 210 global ground-based PM2.5 observations from the literature to evaluate our satellite-based estimates with values measured in areas other than North America and Europe.
Results: We estimated that global population-weighted ambient PM2.5 concentrations increased 0.55 μg/m3/year (95% CI: 0.43, 0.67) (2.1%/year; 95% CI: 1.6, 2.6) from 1998 through 2012. Increasing PM2.5 in some developing regions drove this global change, despite decreasing PM2.5 in some developed regions. The estimated proportion of the population of East Asia living above the World Health Organization (WHO) Interim Target-1 of 35 μg/m3 increased from 51% in 1998–2000 to 70% in 2010–2012. In contrast, the North American proportion above the WHO Air Quality Guideline of 10 μg/m3 fell from 62% in 1998–2000 to 19% in 2010–2012. We found significant agreement between satellite-derived estimates and ground-based measurements outside North America and Europe (r = 0.81; n = 210; slope = 0.68). The low bias in satellite-derived estimates suggests that true global concentrations could be even greater.
Conclusions: Satellite observations provide insight into global long-term changes in ambient PM2.5 concentrations. Satellite-derived estimates and ground-based PM2.5 observations from this study are available for public use.
Citation: van Donkelaar A, Martin RV, Brauer M, Boys BL. 2015. Use of satellite observations for long-term exposure assessment of global concentrations of fine particulate matter. Environ Health Perspect 123:135–143; http://dx.doi.org/10.1289/ehp.1408646
Full-text · Article · Oct 2014 · Environmental Health Perspectives
[Show abstract][Hide abstract] ABSTRACT: Epidemiologic and health impact studies are inhibited by the paucity of global, long-term measurements of the chemical composition of fine particulate matter. We inferred PM2.5 chemical composition at 0.1o x 0.1o spatial resolution for 2004-2008 by combining aerosol optical depth retrieved from the MODIS and MISR satellite instruments, with coincident profile and composition information from the GEOS-Chem global chemical transport model. Evaluation of the satellite-model PM2.5 composition dataset with North American in situ measurements indicated significant spatial agreement for secondary inorganic aerosol, particulate organic mass, black carbon, mineral dust and sea salt. We found that global population-weighted PM2.5 concentrations were dominated by particulate organic mass (11.9 ± 7.3 g/m3), secondary inorganic aerosol (11.1 ± 5.0 g/m3), and mineral dust (11.1 ± 7.9 g/m3). Secondary inorganic PM2.5 concentrations exceeded 30 g/m3 over East China. Sensitivity simulations suggested that population-weighted ambient PM2.5 from biofuel burning (11 g/m3) could be almost as large as from fossil fuel combustion sources (17 g/m3). These estimates offer information about global population exposure to the chemical components and sources of PM2.5.
Full-text · Article · Oct 2014 · Environmental Science and Technology
[Show abstract][Hide abstract] ABSTRACT: For many regions around the world ground-based observations of fine particulate matter (PM2.5) have insufficient spatial coverage to assess long-term health impacts. Although satellites offer a promising avenue to enhance spatial coverage, there are limitations and outstanding questions about the accuracy and precision with which ground-level aerosol mass concentrations can be inferred from satellite remote sensing. We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates in health effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) is an emerging global federation of ground-level monitoring stations that provide hourly PM2.5 estimates in highly populated regions. Each station is collocated with an existing ground-based sun photometer to measure aerosol optical depth (AOD). SPARTAN filters are analyzed for total PM2.5 mass, black carbon, water-soluble ions and metals. A three-city pilot study has shown good agreement between SPARTAN air filters and the nephelometer. The network has now expanded to stations spread over four continents. Participating groups include those in Bangladesh, Brazil, Canada, China, India, Indonesia, Israel, Philippines, Nigeria, Vietnam, and the United States. This presentation will describe our recent aerosol and chemical speciation results and the implications for global PM2.5 concentrations.
[Show abstract][Hide abstract] ABSTRACT: Horizontal visibility measured at ground meteorological stations provides an under-exploited source of information for studying the interdecadal variation of aerosols and their climatic impacts. Here we propose to use a 3-hourly visibility dataset to infer aerosol optical depth (AOD) over East China, using the nested GEOS-Chem chemical transport model to interpret the spatiotemporally varying relations between columnar and near-surface aerosols. Our analysis is focused in 2006 under cloud-free conditions. We evaluate the visibility-inferred AOD using MODIS/Terra and MODIS/Aqua AOD datasets, after validating MODIS data against three ground AOD measurement networks (AERONET, CARSNET and CSHNET). We find that the two MODIS datasets agree with ground-based AOD measurements, with negative mean biases of 0.05–0.08 and Reduced Major Axis regression slopes around unity. Visibility-inferred AOD roughly capture the general spatiotemporal patterns of the two MODIS datasets with negligible mean differences. The inferred AOD reproduce the seasonal variability (correlation exceeds 0.9) and the slight AOD growth from the late morning to early afternoon shown in the MODIS datasets, suggesting the validity of our AOD inference method. Future research will extend the visibility-based AOD inference to study the long-term variability of AOD.
Full-text · Article · Oct 2014 · Atmospheric Environment