Advancements in Modeling the Regional Patterns and Dynamics of Ambient Aerosols and Associated Potential Population Exposures
V.M. Vyas, Q. Sun, P.G. Georgopoulos (EOHSI, UMDNJ - R.W. Johnson Medical School and Rutgers University)
The characterization of potential population exposures to fine (outdoor) airborne particulate matter requires as inputs the spatial and temporal regional variation patterns of ambient aerosols, in addition to demographic and human activities information. Two complementary approaches are used here in the framework of MENTOR-OPERAS to determine these patterns: (1) Spatio-Temporal Random Field (STRF) theory-based analysis of observed PM10 and PM2.5 mass concentration data, and (2) Mechanistic regional aerosol models which provide numerical solutions of the General Dynamic Equation that describes the complex evolution of the mass and number concentrations, as well as of the size and chemical composition distributions of atmospheric aerosol, starting from detailed information on meteorology and emissions of primary particles and precursor gases. The STRF method combines spatial and temporal information to provide more accurate estimates of interpolated concentrations than those resulting from purely spatial or purely temporal methods, thus reducing uncertainty associated with the estimates. Regional aerosol modeling performed for the case studies presented here utilizes novel comprehensive aerosol and cloud modules incorporated into urban/regional Air Quality Simulation Platforms. Results from investigations of PM pollution episodes across the Eastern United States include comparisons of model prediction with available data from monitor networks and field studies. The spatiotemporal PM distributions obtained from the two approaches above are coupled with demographic data through an exposure assessment module based on GIS (Geographic Information System), that has been developed to estimate potential outdoor population exposures in MENTOR-OPERAS; they can also be used in conjunction with other MENTOR components in order to develop estimates of actual (i.e. affected by microenvironmental parameters) exposures The integrated system presented here is useful in evaluating the efficiency of emission reduction measures with respect to both ambient PM levels and the corresponding number of people potentially exposed to these levels.