The effects of atmospheric water cycle on air quality modeling in the southeast region of the United States

The accuracy of air quality modeling depends strongly on the inputs of meteorological fields which not only determine pollution transport, but also affect the stratification of pollutants. This study investigates the effects of atmospheric water cycle on air quality modeling by comparing the modeled fine particle (PM2.5) distributions driven by two distinct sets of meteorological fields.

In the first (control) experiment, standard meteorological fields from MM5 will be used as input for the EPA air quality model (CMAQ) to simulate the PM2.5 distribution in southeast region of US. In the second (sensitivity) experiment, observed precipitation at rain gage stations is assimilated into MM5, to provide a more accurate set of meteorological fields, including wind, temperature, pressure, humidity, and precipitation. The improved meteorological fields are then provided as input to drive CMAQ. Two cases in 2001, one under fair weather condition, and the other included significant precipitation processes, are studied. The effect of improved meteorological fields on the PM2.5 simulation is analyzed by comparing the results from the control experiment to the sensitivity experiment. The results indicate that during rainy days, accurate simulation of precipitation is important for air quality modeling, not only through the effects of precipitation on wet deposition, but also through dynamic and thermodynamic adjustments of other meteorological fields to precipitation correction.