An Evaluation of Some Commonly Used Highway Dispersion Models

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Abstract
This paper presents an evaluation of four gaussian (GM, HIWAY, AIRPOL-4, CALINE-2), and three numerical (DANARD, MROAD 2, ROADS) models with the tracer gas data collected in the General Motors experiment. Various statistical techniques are employed to quantify the predictive capability of each of the above models. In general, the three numerical models performed rather poorly compared to the gaussian models. For this data set, the model with the best performance in accurately predicting the measured concentrations was the GM model followed in order by AIRPOL-4, HIWAY, CALINE-2, DANARD, MR0AD2, and ROADS. Although the GM model provides by far a better simulation than any of the models tested here, it is skewed toward underprediction. As a screening tool for regulatory purposes, however, HIWAY model would be useful since this model has the highest percentage in the category of overprediction if the concentration data in the range of 50th percentile through 100th percentile are included in the analysis. The present version of the HIWAY model for stable and parallel wind-road conditions warrants modifications to improve its predictive capability. Current studies indicate that the modified HIWAY model can be used with greater confidence by the regulatory agencies.

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