Frank Gronwald^1,, Shoou-Yuh Chang¹

Determining the level of air pollution is a modern day necessity for government regulators and industrialized sources. Air dispersion models are often used to determine the concentration of a pollutant. However changing conditions and several assumptions made by the models limit their accuracy at various times. The objectives of this research are the evaluation of four different air dispersion models (Gaussian Plume, Variable K Theory, Box, and AFTOX) as well as developing a more efficient method of evaluating air dispersion models. In the process of determining their performance, the change in accuracy was measured through RMSE calculations and the change in precision was measured through calculating the Brier Score. It was found that in the prediction of NO₂ Variable K Theory and Gaussian Plume both models produced average reduction of 21.2% of mean RMSE from the other models. The Variable K model also proved to be most precise with a 8.9% lower Brier Score than the next best model.

air dispersion modeling, brier score, gaussian plume, AFTOX, Variable K Theory