A Comparative Validation of the RAM and Modified SAI Models for Short Term SO2 Concentrations in Detroit

The RAM model provided by the U.S. EPA has been applied to the metropolitan Detroit area for SO₂ concentrations and is compared to concentrations predicted by a numerical model and to field data obtained by the 14 station air sampling network maintained by the Wayne County Air Pollution Control Division. Great care was taken to develop the emission inventory. Based upon examination of the temporal and spatial correspondence of the respective model predictions and observed concentrations, the correlation coefficients for the 24-hour averaged data, the correlation coefficients for over 700 3-hour averaged observations, and the cumulative frequency distributions of the model output and observations, it is concluded that the numerical model provides a superior predictive tool to evaluate cause and effect relations, but that the RAM model, at far lower cost, predicts the correct magnitude of the worst events. Hence RAM might well be used in the Detroit Area for statistically based regulatory decisions.