Effects of Grid Resolution on the Simulation of Urban Air Quality: Application of Models-3/CMAQ to the Philadelphia Metropolitan Area at 12, 4, and 1.3 KM Resolutions

Comprehensive Eulerian modeling systems have been used to study air quality problems and their impact on human exposure. Last year, U.S. EPA has released the Models-3/Community Multi-scale Air Quality (CMAQ) modeling system to the public. The modeling system includes most of the critical science processes such as atmospheric transport, deposition, cloud mixing, emissions, gas- and aqueous-phase chemical transformation processes, and aerosol dynamics and chemistry. To provide an integral view of meteorological and air quality modeling, a robust and fully compressible governing set of equations has been introduced with CMAQ. It allows linkage of the chemistry-transport model to a variety of meteorological models that represent dynamics at different spatial and temporal scales.

To explore the multiscale nature of the CMAQ, we have been testing CMAQ with various horizontal grid resolutions such as 200, 80, 50, 36, 12, and 4 km to simulate air quality at regional and urban scales linked with different meteorological models. The present study focuses on the establishment of air quality modeling paradigm at the urban scale. Air quality simulation at urban scale is strongly influenced by the pollutant influx at boundaries as well as the model grid size used. To account for the pollutant fluxes at boundaries accurately, it is common to apply the multilevel nesting simulations from regional to urban scale. To meet demands for higher resolution air quality simulations to study such environmental issues as human exposure to air pollution, effects of grid resolutions on the urban air quality simulation must be investigated. In this paper, we explore application of CMAQ at 1 km resolution to the Philadelphia Metropolitan Area. Ozone and PM2.5 concentrations will be compared with the runs at 12- and 4-km resolutions. Also, we will assess spatial and temporal variability of these runs. We will discuss several computational issues and data requirements such as emissions and environmental data to establish CMAQ's capability for simulating urban air quality at fine resolutions.