TAPM was also able to model all annual datasets well without assimilating any local wind observations.Īir quality traffic - related measures have been implemented worldwide to control the pollution levels of urban areas. There were no dispersion processes represented by these datasets that TAPM was unable to model. TAPM performed either well (Kincaid, Indianapolis, Lovett, Anglesea and Kwinana), or acceptably (Bowline and Westvaco), with good prediction of extreme concentrations and small error (relative to the other models). The only process that AERMOD was unable to simulate was shoreline fumigation (Kwinana). In contrast to the AUSPLUME results, AERMOD did not perform poorly for any of the datasets, although marginally acceptable results for Kincaid, Westvaco, Anglesea, and Kwinana datasets are of some concern. AERMOD performed well for Indianapolis and Lovett, and acceptably for Bowline. However, a number of processes could not adequately be modelled by AUSPLUME, including dispersion for sources with stack heights less than 100m and urban dispersion (Indianapolis), dispersion affected by building downwash (Bowline), dispersion in complex terrain such as plume impact on hills (Lovett, and to some extent Westvaco), and shoreline fumigation in coastal environments (Kwinana). AUSPLUME performed well for Kincaid and acceptably for Anglesea. The studies include important processes of air pollution dispersion for all stabilities, in flat terrain, in flat terrain with building downwash, in complex terrain, and in coastal terrain. The performance of AUSPLUME, AERMOD and TAPM in predicting extreme (high) concentrations has been inter-compared and evaluated for seven high quality field datasets of pollutant dispersion from point sources.
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