Using Fused Chemical Transport Models to Estimate Spatially and Temporally Resolved Ambient Air Pollution in Georgia and North Carolina

摘要

A number of adverse health impacts, including acute cardiovascular disease-related events, have been associated with exposure to fine particulate matter (e.g., PM2.5). Given the prevalence of data for PM2.5 mass concentrations, most of these studies are based upon total PM2.5 mass, not on individual species. However, a number of studies have found differing associations of disease outcomes with PM2.5 components (or species), and PM properties (e.g., size and oxidative potential: OP). Data assimilation using chemical transport modelling (CMAQ) and observations is used to develop concentration fields of major PM2.5 components for two areas: Georgia and North Carolina. As part of a cohort study of birthweight, speciated PM2.5 and gaseous pollutant fields were constructed over Georgia for 2002-2006. Increases in air pollutant concentrations were associated with decreases in mean birth weight. In this study, speciated PM fields are also constructed over North Carolina for 2002-2009 studying patients who had undergone a cardiac catheterization in North Carolina. As part of a comparison of approaches, the model-observation fusing approach used here for PM2.5, performance was similar to using a method including satellite data as well as more coarse resolution modellind and provided speciated PM2.5 fields as well as gaseous pollutants that are not as readily observed using remote sensing methods, or where such observations are temporally constrained. Speciated spatiotemporal fields developed here include elemental and organic carbon (EC/OC), sulfate, nitrate, ammonium, and crustal material. The CMAQ approach also provides NOx, O3 and CO fields, and can also estimate additional properties such as aerosol pH and oxidative potential. While this works was funded, in part, by the US EPA, this abstract does not necessarily reflect EPA policy.