Air quality dispersion models are useful tools for determining potential concentration impacts from proposed as well as existing sources. The models can be categorized into four general classes: Gaussian, numerical, statistical (empirical), and physical. The first three models are computer based, with numerical and Gaussian models dominating the field. This section focuses on Gaussian-based models since they are the most widely applied. This wide application is almost entirely due to their ease of application and the conservative estimates they provide, despite any of their shortcomings in precisely describing a plume's diffusion in the atmosphere.
Gaussian-based models generally require three types of input data: source emission data, receptor data, and meteorological data, though the latter two can be assumed in some cases. Source emission data provide the characteristics of the pollutant released to the atmosphere. Receptor data provide the location where a predicted concentration is desired. Meteorological data provide the conditions for the model to determine how the emissions are transported from the source to the receptor.
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