SPATIAL AND TEMPORAL VARIATION IN PM2.5 CHEMICAL COMPOSITION IN THE UNITED STATES FOR HEALTH EFFECTS STUDIES

Michelle L. Bell, Yale University, School of Forestry and Environmental Studies
Francesca Dominici, Johns Hopins Bloomberg School of Public Health, Department of Biostatistics
Keita Ebisu, Yale University, School of Public Health
Scott L. Zeger, The Johns Hopkins Bloomberg School of Public Health, Department of Biostatistics
Jonathan M. Samet, Johns Hopkins Bloomberg School of Public Health, Department of Epidemiology

Abstract

While numerous studies have demonstrated links between particulate matter and adverse health effects, the chemical component(s) of the PM mixture that cause injury are unknown. This work characterizes spatial and temporal variability of PM2.5 components in the U.S. with the objective of identifying components for assessment in epidemiological studies. We constructed a database of 52 PM2.5 component concentrations for 203 U.S. counties for 2000 to 2005. First, we described the challenges inherent to analysis of a national PM2.5 chemical composition database. Second, we identified components that substantially contribute to and/or co-vary with PM2.5 total mass. Third, we characterized the seasonal and regional variability of targeted components. We identified strong seasonal and geographical variation in PM2.5 chemical composition. Only seven of the 52 components contributed 1% or more to total mass for yearly or seasonal averages (NH4+, elemental carbon, organic carbon, NO3-, Si, Na+, and SO4=). Strongest correlations with PM2.5 total mass were with NH4+ (yearly and each season), organic carbon (winter and autumn), NO3- (winter), and SO4= (yearly, spring, and summer), with particularly strong correlations for NH4+ and SO4= in summer. Components that co-varied with PM2.5 total mass, based on daily detrended data, were NH4+, organic carbon, elemental carbon, NO3-, SO4=, and bromine. We identified a subset of PM2.5 components that should be further investigated to determine whether: 1) their daily variation is associated with daily variation of health indicators; and 2) their seasonal and regional patterns can explain the regional and seasonal heterogeneity in PM10 and PM2.5 health risks.