Inter-comparison of AERMOD and ISC3 modeling results to the Alaska tracer field experiment

Abstract

AERMOD is an advanced plume model that incorporates updated treatments of the boundary layer theory, understanding of turbulence and dispersion, and includes handling of terrain interactions as well as the PRIME downwash algorithm. It was reported that the US EPA approved AERMOD for short-range dispersion modeling. It was the high time that AERMOD would replace ISC3. ISC3 is a traditional Gaussian plume model regarded as the regulatory model of US EPA with the capacity of building downwash similar to that of AERMOD. In this paper, the authors describe the advantages of AERMOD over the regulatory model of ISC3 by comparing their predicted ground level concentrations (GLC) along downwind distance to the Alaska tracer field data. The field experiment features buoyant release of effluent at elevated height over a flat terrain and local flows influenced by building downwash. Three measures to compare the observed and simulated concentration data, such as linear regression, quantile-quantile (QQ) and residual box are utilized. To sum up, AERMOD shows significantly better space-time correlation and probability distribution than the ISC3, which frequently overestimates the GLC for effluent released with significant plume rise under stable atmospheric conditions. The performance of AERMOD is greatly enhanced by introducing the state-of-the-art knowledge of boundary layer meteorology as well as the turbulence parameterization method. In particular, AERMOD takes into account the meander effect on coherent plume in stable condition with current state-of-the-art Planetary Boundary Layer (PBL) parameterizations, while ISC3 is not capable of producing such important effect. Generally speaking, 1.17 is the overall predicted-to-observed ratio for short-term averages using AERMOD. 1.94 is the overall predicted-to-observed ratio for short-term averages using ISC3.