Faculty Bibliography

Background: Which components of ambient air particulate matter (PM) are most associated with adverse health effects is less well known. In addition, current Chemical Speciation Network (CSN) data, with every 3rd/6th day sampling schedule, do not allow an examination of multi-day effects of chemical components. Objectives: To determine the associations between daily PM2.5 (PM < 2.5 mum in aerodynamic diameter) components and hospitalizations in Seattle and Detroit using time-series analyses. Methods: We obtained daily PM2.5 Teflon filters for the years of 2002-2004 and analyzed trace elements using X-ray fluorescence, and black carbon (BC) using light reflectance as a surrogate measure of elemental carbon (EC). We used Poisson regression and distributed-lag models to estimate cumulative effects (lags of 0 through 2 days) for cardiovascular and respiratory diseases, with adjustments for time-varying covariates. We computed the excess risks for interquartile range (IQR) increases of each pollutant component for both warm and cold seasons. Results: The PM2.5 components and gaseous pollutants most closely associated with cardiovascular and respiratory hospitalization in Detroit were secondary aerosols, traffic markers, and biomass combustion; while in Seattle, those for cold season traffic emissions and residual oil burning. Conclusions: The effects of PM2.5 on daily hospitalizations vary with source, season, and locale, consistent with the hypothesis that PM2.5 composition has an appreciable influence on the health effects attributable to PM2.5. The multi-day risk estimates were generally bigger than individual day effects, suggesting that risk assessments using a single day lag model are likely to underestimate the health impacts

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 (PM(2.5)) and ozone at 0.1 degrees x 0.1 degrees 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 mug/m(3) PM(2.5) (annual average) was exceeded. Globally, 32% of the population lived in areas exceeding the WHO Level 1 Interim Target of 35 mug/m(3), 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 PM(2.5) 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.

Using daily fine particulate matter (PM2.5) composition data from the 2000-2005 U.S. EPA Chemical Speciation Network (CSN) for over 200 sites, we applied multivariate methods to identify and quantify the major fine particulate matter (PM2.5) source components in the U.S. Novel aspects of this work were: (1) the application of factor analysis (FA) to multi-city daily data, drawing upon both spatial and temporal variations of chemical species; and, (2) the exclusion of secondary components (sulfates, nitrates and organic carbon) from the source identification FA to more clearly discern and apportion the PM2.5 mass to primary emission source categories. For the quantification of source-related mass, we considered two approaches based upon the FA results: 1) using single key tracers for sources identified by FA in a mass regression; and, 2) applying Absolute Principal Component Analysis (APCA). In each case, we followed a two-stage mass regression approach, in which secondary components were first apportioned among the identified sources, and then mass was apportioned to the sources and to other secondary mass not explained by the individual sources. The major U.S. PM2.5 source categories identified via FA (and their key elements) were: Metals Industry (Pb, Zn); Crustal/Soil Particles (Ca, Si); Motor Vehicle Traffic (EC, NO2); Steel Industry (Fe, Mn); Coal Combustion (As, Se); Oil Combustion (V, Ni); Salt Particles (Na, Cl) and Biomass Burning (K). Nationwide spatial plots of the source-related PM2.5 impacts were confirmatory of the factor interpretations: ubiquitous sources, such as Traffic and Soil, were found to be spread across the nation, more unique sources (such as Steel and Metals Processing) being highest in select industrialized cities, Biomass Burning was highest in the U.S. Northwest, while Residual Oil combustion was highest in cities in the Northeastern U.S. and in cities with major seaports. The sum of these source contributions and the secondary PM2.5 components agreed well with the U.S. PM2.5 observed during the study period (mean=14.3 ug/m3; R2= 0.91). Apportionment regression analyses using single-element tracers for each source category gave results consistent with the APCA estimates. Comparisons of nearby sites indicated that the PM2.5 mass and the secondary aerosols were most homogenous spatially, while traffic PM2.5 and its tracer, EC, were among the most spatially representative of the source-related components. Comparison of apportionment results to a previous analysis of the 1979-1982 IP Network revealed similar and correlated major U.S. source category factors, albeit at lower levels than in the earlier period, suggesting a consistency in the U.S. spatial patterns of these source-related exposures over time, as well. These results indicate that applying source apportionment methods to the nationwide CSN can be an informative avenue for identifying and quantifying source components for the subsequent estimation of source-specific health effects, potentially contributing to more efficient regulation of PM2.5.

Background: Past time-series studies of the health effects of fine particulate matter [aerodynamic diameter </= 2.5 microm (PM2.5)] have used chemically nonspecific PM2.5 mass. However, PM2.5 is known to vary in chemical composition with source, and health impacts may vary accordingly.Objective: We tested the association between source-specific daily PM2.5 mass and hospital admissions in a time-series investigation that considered both single-lag and distributed-lag models.Methods: Daily PM2.5 speciation measurements collected in midtown Manhattan were analyzed via positive matrix factorization source apportionment. Daily and distributed-lag generalized linear models of Medicare respiratory and cardiovascular hospital admissions during 2001-2002 considered PM2.5 mass and PM2.5 from five sources: transported sulfate, residual oil, traffic, steel metal works, and soil.Results: Source-related PM2.5 (specifically steel and traffic) was significantly associated with hospital admissions but not with total PM2.5 mass. Steel metal works-related PM2.5 was associated with respiratory admissions for multiple-lag days, especially during the cleanup efforts at the World Trade Center. Traffic-related PM2.5 was consistently associated with same-day cardiovascular admissions across disease-specific subcategories. PM2.5 constituents associated with each source (e.g., elemental carbon with traffic) were likewise associated with admissions in a consistent manner. Mean effects of distributed-lag models were significantly greater than were maximum single-day effect models for both steel- and traffic-related PM2.5.Conclusions: Past analyses that have considered only PM2.5 mass or only maximum single-day lag effects have likely underestimated PM2.5 health effects by not considering source-specific and distributed-lag effects. Differing lag structures and disease specificity observed for steel-related versus traffic-related PM2.5 raise the possibility of distinct mechanistic pathways of health effects for particles of differing chemical composition

Background: Previous studies have reported relationships between adverse respiratory health outcomes and residential proximity to traffic pollution, but have not previously shown this at a personal exposure level. Objective: To compare, among inner-city children with asthma, the associations of adverse asthma outcome incidences with increased personal exposure to fine particle (PM2.5) mass air pollution vs. with the diesel-related carbonaceous fraction of PM2.5. Methods: Daily 24-hr personal samples of PM2.5, including the elemental carbon (EC) fraction, were collected for forty fifth-grade children with asthma at four South Bronx schools (10 children per school) during approximately one month each. Spirometry and symptom scores were recorded several times daily during weekdays. Results: Significantly elevated same-day relative risks of cough (1.23 (95% CI -1.0, 1.545), wheeze 1.45 (95% CI 1.03, 10.4), shortness of breath 1.41 (95% CI 1.0, 1.99%) and total symptoms 1.30 (95% CI 4.0, 1.62) were found with an increase in personal EC, but not with personal PM2.5 mass. Increased risk of cough and total symptoms was found with increased one-day lag and two-day average school-site EC. No significant associations were found with school-site PM2.5 mass or sulfur. The EC effect estimate was robust to addition of gaseous pollutants. Conclusion: Adverse health associations were strongest with personal measures of EC exposure, suggesting that the diesel 'soot' fraction of PM2.5 is most responsible for pollution-related asthma exacerbations among children living proximal to roadways. Studies that rely on exposure to particulate mass may underestimate PM health impacts

Background: Recent time-series studies have indicated that both cardiovascular disease (CVD)mortality and hospitalizations are associated with particulate matter (PM). However, seasonal patterns of PM associations with these outcomes are not consistent, and PM components responsible for these associations have not been determined. We investigated this issue in New York City (NYC), where PM originates from regional and local combustion sources.Objective: In this study, we examined the role of particulate matter with aerodynamic diameter </= 2.5 microm (PM2.5) and its key chemical components on both CVD hospitalizations and on mortality in NYC.Methods: We analyzed daily deaths and emergency hospitalizations for CVDs among persons >/= 40 years of age for associations with PM2.5, its chemical components, nitrogen dioxide (NO2), carbon monoxide, and sulfur dioxide for the years 2000-2006 using a Poisson time-series model adjusting for temporal and seasonal trends, temperature effects, and day of the week. We estimated excess risks per interquartile-range increases at lags 0 through 3 days for warm (April through September) and cold (October through March) seasons.Results: The CVD mortality series exhibit strong seasonal trends, whereas the CVD hospitalization series show a strong day-of-week pattern. These outcome series were not correlated with each other but were individually associated with a number of PM2.5 chemical components from regional and local sources, each with different seasonal patterns and lags. Coal-combustion-related components (e.g., selenium) were associated with CVD mortality in summer and CVD hospitalizations in winter, whereas elemental carbon and NO2 showed associations with these outcomes in both seasons.Conclusion: Local combustion sources, including traffic and residual oil burning, may play a year-round role in the associations between air pollution and CVD outcomes, but transported aerosols may explain the seasonal variation in associations shown by PM2.5 mass

BACKGROUND: Recent toxicological and epidemiological studies have shown associations between particulate matter (PM) and adverse health effects, but which PM components are most influential is less well known. OBJECTIVES: In this study, we used time-series analyses to determine the associations between daily fine PM [PM </= 2.5 microm in aerodynamic diameter (PM2.5)] concentrations and daily mortality in two U.S. cities-Seattle, Washington, and Detroit, Michigan. METHODS: We obtained daily PM2.5 filters for the years of 2002-2004 and analyzed trace elements using X-ray fluorescence and black carbon using light reflectance as a surrogate measure of elemental carbon. We used Poisson regression and distributed lag models to estimate excess deaths for all causes and for cardiovascular and respiratory diseases adjusting for time-varying covariates. We computed the excess risks for interquartile range increases of each pollutant at lags of 0 through 3 days for both warm and cold seasons. RESULTS: The cardiovascular and respiratory mortality series exhibited different source and seasonal patterns in each city. The PM2.5 components and gaseous pollutants associated with mortality in Detroit were most associated with warm season secondary aerosols and traffic markers. In Seattle, the component species most closely associated with mortality included those for cold season traffic and other combustion sources, such as residual oil and wood burning. CONCLUSIONS: The effects of PM2.5 on daily mortality vary with source, season, and locale, consistent with the hypothesis that PM composition has an appreciable influence on the health effects attributable to PM

In this report we review the health effects of three short-lived greenhouse pollutants-black carbon, ozone, and sulphates. We undertook new meta-analyses of existing time-series studies and an analysis of a cohort of 352,000 people in 66 US cities during 18 years of follow-up. This cohort study provides estimates of mortality effects from long-term exposure to elemental carbon, an indicator of black carbon mass, and evidence that ozone exerts an independent risk of mortality. Associations among these pollutants make drawing conclusions about their individual health effects difficult at present, but sulphate seems to have the most robust effects in multiple-pollutant models. Generally, the toxicology of the pure compounds and their epidemiology diverge because atmospheric black carbon, ozone, and sulphate are associated and could interact with related toxic species. Although sulphate is a cooling agent, black carbon and ozone could together exert nearly half as much global warming as carbon dioxide. The complexity of these health and climate effects needs to be recognised in mitigation policies.