Grantee Research Project Results

Spatial and temporal variation in PM2.5 chemical composition in the United States for health effects studies.

Citation:

Bell ML, Dominici F, Ebisu K, Zeger SL, Samet JM. Spatial and temporal variation in PM2.5 chemical composition in the United States for health effects studies. Environmental Health Perspectives 2007;115(7):989-995.

Abstract:

BACKGROUND: Although numerous studies have demonstrated links between particulate matter (PM) and adverse health effects, the chemical components of the PM mixture that cause injury are unknown. OBJECTIVES: This work characterizes spatial and temporal variability of PM2.5 (PM with aerodynamic diameter < 2.5 µm) components in the United States; our objective is to identify components for assessment in epidemiologic studies. METHODS: We constructed a database of 52 PM2.5 component concentrations for 187 U.S. counties for 2000-2005. First, we describe the challenges inherent to analysis of a national PM2.5 chemical composition database. Second, we identify components that contribute substantially to and/or co-vary with PM2.5 total mass. Third, we characterize the seasonal and regional variability of targeted components. RESULTS: Strong seasonal and geographic variations in PM2.5 chemical composition are identified. Only seven of the 52 components contributed ≥ 1% to total mass for yearly or seasonal averages [ammonium (NH4+), elemental carbon (EC), organic carbon matter (OCM), nitrate (NO4–), silicon, sodium (Na+), and sulfate (SO42-)]. Strongest correlations with PM2.5 total mass were with NH4+ (yearly), OCM (especially winter), NO3- (winter), and SO42– (yearly, spring, autumn, and summer), with pparticularly strong correlations for NH4+ and SO42- in summer. Components that co-varied with PM2.5 total mass, based on daily detrended data, were NH4+, SO42-, OCM, NO3-, bromine, and EC. CONCLUSIONS: The subset of identified PM2.5 components should be investigated further to determine whether their daily variation is associated with daily variation of health indicators, and whether their seasonal and regional patterns can explain the seasonal and regional heterogeneity in PM10 (PM with aerodynamic diameter < 10 µm) and PM2.5 health risks.