Regional Modeling of Atmospheric Aerosols for Exposure Analysis: an Application to the Eastern United States
Q. Sun, V. Purushothaman, P.G. Georgopoulos (EOHSI, UMDNJ - R.W. Johnson Medical School and Rutgers University)
The viability of regional aerosol models for performing analysis of potential population exposure to PM is evaluated in this work through assessment of relevant model input databases and case studies focusing on model sensitivity. The objective of this work is to produce and test/evaluate components for the Modeling ENvironment for TOtal Risk Studies (MENTOR) currently being developed at EOHSI. These components would offer various alternatives for calculating and evaluating estimates of spatiotemporal fields of ambient airborne particulate matter (Vyas et al., PM 2000). The case studies presented utilize an aerosol model incorporated into MCNC's Multiscale Air Quality SImulation Platform (MAQSIP) to investigate the particulate pollution in eastern United States during the July 9-13, 1995 episode. A cloud model is modified for the sectional representation of the aerosol size distribution to account for sulfate production in clouds. The effects of an assumed primary PM emission size profile on the ambient PM2.5 and PM10 mass are examined. Then the efficiency of SO2 emission reduction in reducing the inorganic PM mass is investigated.
The PM distributions obtained from this model are coupled with demographic data through a GIS (Geographic Information System) based exposure assessment tool that has been developed to estimate potential outdoor population exposures. This GIS-based tool is a component of MENTOR and can be used in conjunction with other components to estimate individual exposures within different microenvironments (Isukapalli et al., PM 2000). The exposure assessment tool 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 exposed.