The AERMOD model performance was evaluated for 1-hour averaging period using emission inventory and air monitoring data for sulphur dioxide (SO2) of Lucas County, Ohio for the years 1991 and 1992. The air monitoring data were used from the two monitoring stations in the area. The concentration data were classified into stable, unstable and neutral groups based on inverse of Monin-Obukhov length, a stability parameter and further subdivided into three categories depending upon high, moderate and low wind speeds.
Model evaluation was carried out for two different situations: 1) in predicting the concentration for a given point and time for general applications, and 2) in predicting highest concentration values for regulatory use. Uncertainties associated with the model predictions for general applications were estimated using the iv statistical measure and the bootstrap resampling method. Robust and seductive confidence limits are calculated for normalized mean square error, fractional bias and coefficient of correlation to find whether the model overpredicts or underpredicts. For regulatory applications the model was tested using robust highest concentrations (RHC) statistic and Q-Q plots.
AERMOD did not yield good performance in predicting concentrations for general applications for 1-hr averaging period for an urban area. However, the model showed reasonable performance under neutral and stable cases with low wind speed for obtaining regulatory concentrations (RHC) for 1-hr averaging period. Most of the RHC values are within a factor of two for neutral and stable atmosphere.