Abstract
This paper reviews the influence of computational fluid dynamics in the improvement of atmospheric dispersion models. Some of the factors that led to the widespread use of this computational approach include the availability of affordable high-performance workstations, the sharing of data via the information superhighway and the advances in the development of computational algorithms. While the traditional role of computational fluid dynamics has been to provide wind fields for dispersion models, recent new applications have emerged wherein prognostic forecast models were used to provide responses to weather-related emergencies on both local as well as regional scales.
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