Coal generates almost 40% of the world's electricity with 80 countries throughout the world using coal power. An inherent part of this generation is the rail transport of coal in uncovered cars, often up to a mile long. Existing studies document the subsequent increments of PM2.5 to the near-rail populations, which typically include a large number of economically disadvantaged residents and/or people of color. However, to date there is no assessment of the health implications of this stage in the use of coal. The present study quantifies such impacts on a region in the San Francisco Bay Area. The analysis shows important effects on mortality, hospitalization for cardiovascular and respiratory disease, asthma exacerbation, work loss, and days of restricted activity. Several of these outcomes exhibited a one to six percent increase over baseline. As such, it delineates the implications for the global effects of the transport of coal.

Exposure to fine particulate matter (PM2.5) is associated with adverse health effects, including mortality, even at low concentrations. Rail conveyance of coal, accounting for one-third of American rail freight tonnage, is a source of PM2.5. However, there are limited studies of its contribution to PM2.5, especially in urban settings where residents experience higher exposure and vulnerability to air pollution. We developed a novel artificial intelligence-driven monitoring system to quantify average and maximum PM2.5 concentrations of full and empty (unloaded) coal trains compared to freight and passenger trains. The monitor was close to the train tracks in Richmond, California, a city with a racially diverse population of 115,000 and high rates of asthma and heart disease. We used multiple linear regression models controlling for diurnal patterns and meteorology. The results indicate coal trains add on average 8.32 µg/m3 (95% CI = 6.37, 10.28; p < 0.01) to ambient PM2.5, while sensitivity analysis produced midpoints ranging from 5 to 12 µg/m3. Coal trains contributed 2 to 3 µg/m3 more of PM2.5 than freight trains, and 7 µg/m3 more under calm wind conditions, suggesting our study underestimates emissions and subsequent concentrations of coal train dust. Empty coal cars tended to add 2 µg/m3. Regarding peak concentrations of PM2.5, our models suggest an increase of 17.4 µg/m3 (95% CI = 6.2, 28.5; p < 0.01) from coal trains, about 3 µg/m3 more than freight trains. Given rail shipment of coal occurs globally, including in populous areas, it is likely to have adverse effects on health and environmental justice.

Indonesian peatlands have been drained for agricultural development for several decades. This development has made a major contribution to economic development. At the same time, peatland drainage is causing significant air pollution resulting from peatland fires. Peatland fires occur every year, even though their extent is much larger in dry (El Niño) years. We examine the health effects of long-term exposure to fine particles (PM2.5) from all types of peatland fires (including the burning of above and below ground biomass) in Sumatra and Kalimantan, where most peatland fires in Indonesia take place. We derive PM2.5 concentrations from satellite imagery calibrated and validated with Indonesian Government data on air pollution, and link increases in these concentrations to peatland fires, as observed in satellite imagery. Subsequently, we apply available epidemiological studies to relate PM2.5 exposure to a range of health outcomes. The model utilizes the age distribution and disease prevalence of the impacted population. We find that PM2.5 air pollution from peatland fires, causes, on average, around 33,100 adults and 2900 infants to die prematurely each year from air pollution. In addition, peatland fires cause on average around 4390 additional hospitalizations related to respiratory diseases, 635,000 severe cases of asthma in children, and 8.9 million lost workdays. The majority of these impacts occur in Sumatra because of its much higher population density compared to Kalimantan. A main source of uncertainty is in the Concentration Response Functions (CRFs) that we use, with different CRFs leading to annual premature adult mortality ranging from 19,900 to 64,800 deaths. Currently, the population of both regions is relatively young. With aging of the population over time, vulnerabilities to air pollution and health effects from peatland fires will increase. Peatland fire health impacts provide a further argument to combat fires in peatlands, and gradually transition to peatland management models that do not require drainage and are therefore not prone to fire risks.

Author(s): Ostro, B; Nandam, K; Way, D; Malone, M; Emerson, G; Li-Sauerwine, S; Khandelwal, S; King, A

Air pollution health-effect studies commonly use central monitor concentrations (CMCs) of airborne fine particulate matter (PM2.5) to represent population exposure near the monitoring sites. The spatial distribution of PM2.5 constituents is presumed to be the same and is well-represented by the CMC. Here we apply chemical transport models in California and show that the population-weighted concentrations (PWCs) of secondary PM2.5 constituents within the 12 km buffer zone are within +/- 20% of the respective CMC values, but the PWCs of primary PM2.5 constituents differ from the CMC values by -40 to +60%. The appropriate CMC representative distance varies significantly in different cities due to the unique combination of population distribution, emissions patterns, and meteorology at each location. We conclude that exposure misclassification can be significant if the same representative distance is assumed for multiple CMC PM2.5 constituents across all sites in a single air pollution epidemiology study that has a large spatial and temporal range. This misclassification will increase the variance around the effect estimate and therefore reduce the likelihood of finding a statistically significant effect.

Inhalation of airborne particulate matter (PM) is associated with a variety of adverse health outcomes. However, the relative toxicity of specific PM types-mixtures of particles of varying sizes, shapes, and chemical compositions-is not well understood. A major impediment has been the sparse distribution of surface sensors, especially those measuring speciated PM. Aerosol remote sensing from Earth orbit offers the opportunity to improve our understanding of the health risks associated with different particle types and sources. The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard NASA's Terra satellite has demonstrated the value of near-simultaneous observations of backscattered sunlight from multiple view angles for remote sensing of aerosol abundances and particle properties over land. The Multi-Angle Imager for Aerosols (MAIA) instrument, currently in development, improves on MISR's sensitivity to airborne particle composition by incorporating polarimetry and expanded spectral range. Spatiotemporal regression relationships generated using collocated surface monitor and chemical transport model data will be used to convert fractional aerosol optical depths retrieved from MAIA observations to near-surface PM10, PM2.5, and speciated PM2.5. Health scientists on the MAIA team will use the resulting exposure estimates over globally distributed target areas to investigate the association of particle species with population health effects. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Airborne particulate matter (PM) is a well-known cause of cardiovascular disease and mortality and has also been associated with respiratory disease, low birth weight, lung cancer, and other adverse health outcomes. However, our understanding of the relative toxicity of specific PM types-mixtures with different proportions of particles of various sizes, shapes, and compositions-is less well understood. Observations from space, in conjunction with data from surface monitors and chemical transport models, offer a practical means of generating frequent, high spatial resolution maps of PM concentrations in major population centers around the world. The Multi-Angle Imager for Aerosols (MAIA) investigation, currently in development, is motivated by the scientific and societal benefits of linking PM types with adverse health outcomes and the value of satellite observations for addressing this objective.

Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.

Background: Exposure to ambient fine particulate matter (PM2.5) has been linked with premature mortality, but sources of PM2.5 have been less studied. Methods: We evaluated associations between source-specific PM2.5 exposures and cause-specific short-term mortality in eight California locations from 2002 to 2011. Speciated PM2.5 measurements were source-apportioned using Positive Matrix Factorization into eight sources and combined with death certificate data. We used time-stratified case-crossover analysis with conditional logistic regression by location and meta-analysis to calculate pooled estimates. Results: Biomass burning was associated with all-cause mortality lagged 2 days after exposure (lag2) (% change(lag2) in odds per interquartile range width increase in biomass burning PM2.5 = 0.8, 95% confidence interval [CI] = 0.2, 1.4), cardiovascular (% change(lag2) = 1.3, 95% CI = 0.3, 2.4), and ischemic heart disease (% change(lag2) = 2.0, 95% CI = 0.6, 3.5). Vehicular emissions were associated with increases in cardiovascular mortality (% change(lag0) = 1.4, 95% CI = 0.0, 2.9). Several other sources exhibited positive associations as well. Many findings persisted during the cool season. Warm season biomass burning was associated with respiratory/thoracic cancer mortality (% change(lag1) = 5.9, 95% CI = 0.7, 11.3), and warm season traffic was associated with all-cause (% change(lag0) = 1.9, 95% CI = 0.1, 3.6) and cardiovascular (% change(lag0) = 2.9, 95% CI = 0.1, 5.7) mortality. Conclusions: Our results suggest that acute exposures to biomass burning and vehicular emissions are linked with cardiovascular mortality, with additional sources (i.e., soil, secondary nitrate, secondary sulfate, aged sea salt, and chlorine sources) showing associations with other specific mortality types.

The Global Burden of Disease (GBD) is a comparative assessment of the health impact of the major and well-established risk factors, including ambient air pollution (AAP) assessed by concentrations of PM2.5 (particles less than 2.5 µm) and ozone. Over the last two decades, major improvements have emerged for two important inputs in the methodology for estimating the impacts of PM2.5: the assessment of global exposure to PM2.5 and the development of integrated exposure risk models (IERs) that relate the entire range of global exposures of PM2.5 to cause-specific mortality. As a result, the estimated annual mortality attributed to AAP increased from less than 1 million in 2000 to roughly 3 million for GBD in years 2010 and 2013, to 4.2 million for GBD 2015. However, the magnitude of the recent change and uncertainty regarding its rationale have resulted, in some cases, in skepticism and reduced confidence in the overall estimates. To understand the underlying reasons for the change in mortality, we examined the estimates for the years 2013 and 2015 to determine the quantitative implications of alternative model input assumptions. We calculated that the year 2013 estimates increased by 8% after applying the updated exposure data used in GBD 2015, and increased by 23% with the application of the updated IERs from GBD 2015. The application of both upgraded methodologies together increased the GBD 2013 estimates by 35%, or about one million deaths. We also quantified the impact of the changes in demographics and the assumed threshold level. Since the global estimates of air pollution-related deaths will continue to change over time, a clear documentation of the modifications in the methodology and their impacts is necessary. In addition, there is need for additional monitoring and epidemiological studies to reduce uncertainties in the estimates for low- and medium-income countries, which contribute to about one-half of the mortality.

Background: Studies have reported associations between long-term air pollution exposures and cardiovascular mortality. The biological mechanisms connecting them remain uncertain. Methods: We examined associations of fine particles (PM2.5) and ozone with serum markers of cardiovascular disease risk in a cohort of midlife women. We obtained information from women enrolled at six sites in the multi-ethnic, longitudinal Study of Women’s Health Across the Nation, including repeated measurements of high-sensitivity C-reactive protein, fibrinogen, tissue-type plasminogen activator antigen, plasminogen activator inhibitor type 1, and factor VIIc (factor VII coagulant activity). We obtained residence-proximate PM2.5 and ozone monitoring data for a maximum five annual visits, calculating prior year, 6-month, 1-month, and 1-day exposures and their relations to serum markers using longitudinal mixed models. Results: For the 2,086 women studied from 1999 to 2004, PM2.5 exposures were associated with all blood markers except factor VIIc after adjusting for age, race/ethnicity, education, site, body mass index, smoking, and recent alcohol use. Adjusted associations were strongest for prior year exposures for high-sensitivity C-reactive protein (21% increase per 10 &mgr;g/m3 PM2.5, 95% confidence interval [CI]: 6.6, 37), tissue-type plasminogen activator antigen (8.6%, 95% CI: 1.8, 16), and plasminogen activator inhibitor (35%, 95% CI: 19, 53). An association was also observed between year prior ozone exposure and factor VIIc (5.7% increase per 10 ppb ozone, 95% CI: 2.9, 8.5). Conclusions: Our findings suggest that prior year exposures to PM2.5 and ozone are associated with adverse effects on inflammatory and hemostatic pathways for cardiovascular outcomes in midlife women.

While many studies have investigated the health effects associated with acute exposure to fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5)), very few have considered the risks of specific sources of PM2.5 We used city-specific source apportionment in 8 major metropolitan areas in California from 2005-2009 to examine the associations of source-specific PM2.5 exposures from vehicular emissions, biomass burning, soil, and secondary nitrate and sulfate sources with emergency department visits (EDVs) for cardiovascular and respiratory diseases, including 7 subclasses. Using a case-crossover analysis, we observed associations of vehicular emissions with all cardiovascular EDVs (excess risk = 1.6%, 95% confidence interval: 0.9, 2.4 for an interquartile-range increment of 2.8 µg/m(3)) and with several subclasses of disease. In addition, vehicular emissions, biomass burning, and soil sources were associated with all respiratory EDVs and with EDVs for asthma. The soil source, which includes resuspended road dust, generated the highest risk estimate for asthma (excess risk = 4.5%, 95% confidence interval: 1.1, 8.0). Overall, our results provide additional evidence of the public health consequences of exposure to specific sources of PM2.5 and indicate that some sources of PM2.5 may pose higher risks than the overall PM2.5 mass.

Introduction: In a previous study associations between C-Reactive protein (CRP), a marker of cardiovascular inflammation, and long-term exposure to fine particles (PM2.5) were reported using data from the SWAN cohort of approximately middle-aged 2,000 women. However, little is known about the specific sources and species of PM2.5 that may be responsible. In addition, there are few studies of the impacts of long-term exposure to ultrafine particles (PM0.1), especially regarding its impacts on inflammatory biomarkers. Methods: We investigated the inflammatory impacts of long-term exposure to certain sources and species of both PM2.5 and PM0.1 in California using the SWAN data with up to five annual repeated measures of CRP. Exposure data at the residential level were provided by a chemical transport model that generated estimates of PM2.5 and PM0.1 mass, 11 species and 8 sources of primary particles at a 4 km grid resolution. Linear mixed models accounting for repeated measures within an individual were used to estimate the effects of prior-year exposure on CRP. Results: We found strong associations between CRP and PM2.5 mass and several species including secondary organic aerosols and metals such as iron and copper. Larger risks were observed for those above the median age of 47. Two-pollutant models and inclusion of ozone and nitrogen dioxide, confirmed these associations. Regarding sources, associations with CRP were observed for both PM2.5 and PM0.1 for a combined category that included natural gas combustion, road dust, brake and tire dust and cement production. Conclusions: In this study, we observed significant associations between CRP and long-term exposure to several species and sources of PM2.5 and PM0.1. The results suggest an important risk from exposure tor motor vehicles and other combustion sources. This suggests a plausible pathway by which exposure to particulate matter may be associated with increased risk of cardiovascular disease and mortality.

This conclusion presents some closing thoughts on corporate crime discussed in the various chapters of this book. It talks about the shifting dynamics of state-corporate relations, the meaning of a vulnerable corporation, and what it means to be pragmatic and utopian. The book seeks to demonstrate that the corporation cannot be effectively reformed, not through corporate social responsibility (CSR), not through regulation, not through tinkering with structures and functions such as is the stuff of corporate governance. It is emphasized that harm and crime are not marginal but central to corporate activity, generated through corporate personhood, and the techniques and mindsets of 'externalities', the corporation's dehumanising structure of irresponsibility, and its necessarily a-moral, calculative rationality. The book also clarifies how the corporate drive for profits kills, maims and steals from people as a matter of course …

Background: Studies have explored ozone’s connection to asthma and total respiratory emergency department visits (EDVs) but have neglected other specific respiratory diagnoses despite hypotheses relating ozone to respiratory infections and allergic responses. Objective: We examined relationships between ozone and EDVs for respiratory visits, including specifically acute respiratory infections (ARI), asthma, pneumonia, chronic obstructive pulmonary disease (COPD), and upper respiratory tract inflammation (URTI). Methods: We conducted a multi-site time-stratified case-crossover study of ozone exposures for approximately 3.7 million respiratory EDVs from 2005 through 2008 among California residents living within 20 km of an ozone monitor. Conditional logistic regression was used to estimate associations by climate zone. Random effects meta-analysis was then applied to estimate pooled excess risks (ER). Effect modification by season, distance from the monitor and individual demographic characteristics (i.e., age, race/ethnicity, sex, and payment method), and confounding by other gaseous air pollutants were also investigated. Meta-regression was utilized to explore how climate zone–level meteorological, demographic, and regional differences influenced estimates. Results: We observed ozone-associated increases in all respiratory, asthma, and ARI visits, which were slightly larger in the warm season [asthma ER per 10-ppb increase in mean of same and previous 3 days ozone exposure (lag03) = 2.7%, 95% CI: 1.5, 3.9; ARI ERlag03 = 1.4%, 95% CI: 0.8, 1.9]. EDVs for pneumonia, COPD, and URTI were also significantly associated with ozone exposure over the whole year, but typically more consistently so during the warm season. Conclusions: Short-term ozone exposures among California residents living near an ozone monitor were positively associated with EDVs for asthma, ARI, pneumonia, COPD, and URTI from 2005 through 2008. Those associations were typically larger and more consistent during the warm season. Our findings suggest that these outcomes should be considered when evaluating the potential health benefits of reducing ozone concentrations. Citation: Malig BJ, Pearson DL, Chang YB, Broadwin R, Basu R, Green RS, Ostro B. 2016. A time-stratified case-crossover study of ambient ozone exposure and emergency department visits for specific respiratory diagnoses in California (2005–2008). Environ Health Perspect 124:745–753; http://dx.doi.org/10.1289/ehp.1409495

BACKGROUND:Although several cohort studies report associations between chronic exposure to fine particles (PM2.5) and mortality, few have studied the effects of chronic exposure to ultrafine (UF) particles. In addition, few studies have estimated the effects of the constituents of either PM2.5 or UF particles.METHODS:We used a statewide cohort of > 100,000 women from the California Teachers Study who were followed from 2001 through 2007. Exposure data at the residential level were provided by a chemical transport model that computed pollutant concentrations from > 900 sources in California. Besides particle mass, monthly concentrations of 11 species and 8 sources or primary particles were generated at 4-km grids. We used a Cox proportional hazards model to estimate the association between the pollutants and all-cause, cardiovascular, ischemic heart disease (IHD), and respiratory mortality.RESULTS:We observed statistically significant (p < 0.05) associations of IHD with PM2.5 mass, nitrate, elemental carbon (EC), copper (Cu), and secondary organics and the sources gas- and diesel-fueled vehicles, meat cooking, and high-sulfur fuel combustion. The hazard ratio estimate of 1.19 (95% CI: 1.08, 1.31) for IHD in association with a 10-μg/m3 increase in PM2.5 is consistent with findings from the American Cancer Society cohort. We also observed significant positive associations between IHD and several UF components including EC, Cu, metals, and mobile sources.CONCLUSIONS:Using an emissions-based model with a 4-km spatial scale, we observed significant positive associations between IHD mortality and both fine and ultrafine particle species and sources. Our results suggest that the exposure model effectively measured local exposures and facilitated the examination of the relative toxicity of particle species.