Comparative assessment of regional population exposures to ozone and PM during a summer episode using alternative photochemical air quality simulation models
Q. Sun, A. Chandrasekar, P.G. Georgopoulos (EOHSI, UMDNJ - R.W. Johnson Medical School and Rutgers University)
The objective of this work is to evaluate the performances of alternative Photochemical Air Quality Simulation Models (PAQSMs) in predicting ambient ozone and PM concentrations and to demonstrate and compare their utility in the assessment of potential population exposures in the Eastern U.S.
The two regional PAQSMs used are US EPA's Community Multiscale Air Quality (CMAQ) model, a component of the Models-3 system, and MCNC's Multiscale Air Quality Simulation Platform (MAQSIP). The emissions data were processed from the National Emissions Trends (NET) inventory using MCNC's Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system, and the meteorological inputs were developed through MM5 simulations. Fourteen vertical layers and three levels of nested domains are used, with grid resolution of 36km for the outmost domain, 12km for the intermediate domain and 4km for the innermost domain. The outmost domain encompass the eastern United States (OTAG region) while the inner domains are centered around the State of New Jersey and the metropolitan Philadelphia area. The simulations were carried out for two weeks starting July 11, 1999. Two different aerosol dynamics formulations are employed for PM predictions: a modal aerosol model is included as part of the current release of CMAQ; a dynamic sectional aerosol model based on a formulation developed at the University of Delaware (UDAERO) is incorporated in the version of MAQSIP used here. The results from these different simulations are analyzed and compared with data from US EPA's Aerometric Information Retrieval System (AIRS) to assess the models' performances in air quality prediction.
The PM and ozone distributions obtained from both models are coupled with demographic data to estimate potential outdoor population exposures through a GIS (Geographic Information System)-based exposure assessment tool that has been developed as part of the MENTOR (Modeling Environment for Total Risk) system. The exposure predictions corresponding to the two PAQSMs are compared to each other and their differences are discussed in the context of modeling uncertainties for emission control strategy development and for health data interpretation.