scholarly journals Supplementary material to "Long-term Particulate Matter Modeling for Health Effects Studies in California – Part II: Concentrations and Sources of Ultrafine Organic Aerosols"

2016 ◽  
Author(s):  
Jianlin Hu ◽  
Shantanu Jathar ◽  
Hongliang Zhang ◽  
Qi Ying ◽  
Shu-Hua Chen ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Health Effects ◽  
Organic Aerosols ◽  
Supplementary Material

scholarly journals Long-term Particulate Matter Modeling for Health Effects Studies in California – Part II: Concentrations and Sources of Ultrafine Organic Aerosols

2016 ◽  
Author(s):  
Jianlin Hu ◽  
Shantanu Jathar ◽  
Hongliang Zhang ◽  
Qi Ying ◽  
Shu-Hua Chen ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Health Effects ◽  
Waste Disposal ◽  
Size Fraction ◽  
Organic Aerosols ◽  
Epidemiological Studies ◽  
Anthropogenic Sources ◽  
Major Constituent ◽  
Spatial Distributions ◽  
Mobile Emissions

Abstract. Organic aerosol (OA) is a major constituent of ultrafine particulate matter (PM0.1). Recent epidemiological studies have identified associations between PM0.1 OA and premature mortality and low birth weight. In this study, the source-oriented UCD/CIT model was used to simulate the concentrations and sources of primary organic aerosols (POA) and secondary organic aerosols (SOA) in PM0.1 in California for a 9-year (2000–2008) modeling period with 4 km horizontal resolution to provide more insights about PM0.1 OA for health effects studies. As a related quality control, predicted monthly average concentrations of fine particulate matter (PM2.5) total organic carbon at six major urban sites had mean fractional bias of −0.31 to 0.19 and mean fractional errors of 0.4 to 0.59. The predicted ratio of PM2.5 SOA/OA was lower than estimates derived from chemical mass balance (CMB) calculations by a factor of 2 ~ 3, which suggests the potential effects of processes such as POA volatility, additional SOA formation mechanism, and missing sources. OA in PM0.1, the focus size fraction of this study, is dominated by POA. Wood smoke is found to be the single biggest source of PM0.1 OA in winter in California, while meat cooking, mobile emissions (gasoline and diesel engines), and other anthropogenic sources (mainly solvent usage and waste disposal) are the most important sources in summer. Biogenic emissions are predicted to be the largest PM0.1 SOA source, followed by mobile sources and other anthropogenic sources, but these rankings are sensitive to the SOA model used in the calculation. Air pollution control programs aiming to reduce the PM0.1 OA concentrations should consider controlling solvent usage, waste disposal, and mobile emissions in California, but these findings should be revisited after the latest science is incorporated into the SOA exposure calculations. The spatial distributions of SOA associated with different sources are not sensitive to the choice of SOA model, although the absolute amount of SOA can change significantly. Therefore, the spatial distributions of PM0.1 POA and SOA over the 9-year study period provide useful information for epidemiological studies to further investigate the associations with health outcomes.

scholarly journals Association of Cardiovascular Disease and Long-Term Exposure to Fine Particulate Matter (PM2.5) in the Southeastern United States

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 947
Author(s):  
R. Burciaga Valdez ◽  
Mohammad Z. Al-Hamdan ◽  
Mohammad Tabatabai ◽  
Darryl B. Hood ◽  
Wansoo Im ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Particulate Matter ◽  
Health Effects ◽  
Fine Particulate Matter ◽  
Clinical Risk Factors ◽  
Clinical Risk ◽  
Fine Particulate ◽  
Ambient Levels

There is a well-documented association between ambient fine particulate matter air pollution (PM2.5) and cardiovascular disease (CVD) morbidity and mortality. Exposure to PM2.5 can cause premature death and harmful and chronic health effects such as heart attack, diabetes, and stroke. The Environmental Protection Agency sets annual PM2.5 standards to reduce these negative health effects. Currently above an annual average level of 12.0 µg/m is considered unhealthy. Methods. We examined the association of long-term exposure to PM2.5 and CVD in a cohort of 44,610 individuals who resided in 12 states recruited into the Southern Community Cohort Study (SCCS). The SCCS was designed to recruit Black and White participants who received care from Federally Qualified Health Centers; hence, they represent vulnerable individuals from low-income families across this vast region. This study tests whether SCCS participants who lived in locations exposed to elevated ambient levels of PM2.5 concentrations were more likely to report a history of CVD at enrollment (2002–2009). Remotely sensed satellite data integrated with ground monitoring data provide an assessment of the average annual PM2.5 in urban and rural locations where the SCCS participants resided. We used multilevel logistic regression to estimate the associations between self-reported CVD and exposure to elevated ambient levels of PM2.5. Results. We found a 13.4 percent increase in the odds of reported CVD with exposure to unhealthy levels of PM2.5 exposure at enrollment. The SCCS participants with medical histories of hypertension, hypercholesterolemia, and smoking had, overall, 385 percent higher odds of reported CVD than those without these clinical risk factors. Additionally, Black participants were more likely to live in locations with higher ambient PM2.5 concentrations and report high levels of clinical risk factors, thus, they may be at a greater future risk of CVD. Conclusions: In the SCCS participants, we found a strong relation between exposures to high ambient levels of PM2.5 and self-reported CVD at enrollment.

scholarly journals SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications

2015 ◽  
Vol 8 (1) ◽  
pp. 505-521 ◽  
Author(s):  
G. Snider ◽  
C. L. Weagle ◽  
R. V. Martin ◽  
A. van Donkelaar ◽  
K. Conrad ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Particulate Matter ◽  
Health Effects ◽  
Satellite Remote Sensing ◽  
Fine Particulate Matter ◽  
Ground Level ◽  
Water Soluble ◽  
Global Network ◽  
Spatial Coverage

Abstract. Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2.5) at the global scale. Satellite remote sensing offers a promising approach to provide information on both short- and long-term exposure to PM2.5 at local-to-global scales, but 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 alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD). We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health-effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) includes a global federation of ground-level monitors of hourly PM2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of regions around the world, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. Mean PM2.5 concentrations across sites vary by more than 1 order of magnitude. Our initial measurements indicate that the ratio of AOD to ground-level PM2.5 is driven temporally and spatially by the vertical profile in aerosol scattering. Spatially this ratio is also strongly influenced by the mass scattering efficiency.

scholarly journals SPARTAN: a global network to evaluate and enhance satellite-based estimates of ground-level particulate matter for global health applications

2014 ◽  
Vol 7 (7) ◽  
pp. 7569-7611 ◽  
Author(s):  
G. Snider ◽  
C. L. Weagle ◽  
R. V. Martin ◽  
A. van Donkelaar ◽  
K. Conrad ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Particulate Matter ◽  
Health Effects ◽  
Satellite Remote Sensing ◽  
Vertical Profile ◽  
Ground Level ◽  
Water Soluble ◽  
Global Network ◽  
Aerosol Scattering

Abstract. Ground-based observations have insufficient spatial coverage to assess long-term human exposure to fine particulate matter (PM2.5) at the global scale. Satellite remote sensing offers a promising approach to provide information on both short- and long-term exposure to PM2.5 at local-to-global scales, but 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 alone. A key source of uncertainty is the global distribution of the relationship between annual average PM2.5 and discontinuous satellite observations of columnar aerosol optical depth (AOD). We have initiated a global network of ground-level monitoring stations designed to evaluate and enhance satellite remote sensing estimates for application in health effects research and risk assessment. This Surface PARTiculate mAtter Network (SPARTAN) includes a global federation of ground-level monitors of hourly PM2.5 situated primarily in highly populated regions and collocated with existing ground-based sun photometers that measure AOD. The instruments, a three-wavelength nephelometer and impaction filter sampler for both PM2.5 and PM10, are highly autonomous. Hourly PM2.5 concentrations are inferred from the combination of weighed filters and nephelometer data. Data from existing networks were used to develop and evaluate network sampling characteristics. SPARTAN filters are analyzed for mass, black carbon, water-soluble ions, and metals. These measurements provide, in a variety of global regions, the key data required to evaluate and enhance satellite-based PM2.5 estimates used for assessing the health effects of aerosols. Mean PM2.5 concentrations across sites vary by an order of magnitude. Initial measurements indicate that the AOD column to PM2.5 ratio is driven temporally primarily by the vertical profile of aerosol scattering; and spatially by a~ more complex interaction of the aerosol scattering vertical profile and by the mass scattering efficiency.

Sign in / Sign up

Export Citation Format

Share Document