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Authors: Kaswan, Vijay Pratap
Issue Date: 2012
Abstract: Air pollution modeling is a numerical tool used to describe the causal relationship between emissions, meteorology, atmospheric concentrations, deposition, and other factors. Air pollution measurements give important, quantitative information about ambient concentrations and deposition, but they can only describe air quality at specific locations and times, without giving clear guidance on the identification of the causes of the air quality problem. Dispersion models are used to estimate or to predict the downwind concentration of air pollutants or toxins emitted from sources such as industrial plants, vehicular traffic or accidental chemical releases. These models are employed to determine whether existing or proposed new industrial facilities are or will be in compliance with the National Ambient Air Quality Standards (NAAQS) of the corresponding country. AERMOD is also such type of models and a regulatory model of Environmental Protection Agency (EPA) of the United States of America. It is important that the predictions made by an air quality model are reliable. The idea is to find out the quality and reliability of the predictions made by a model when compared to real life data. AERMOd is also comprehensively evaluated with the available datasets on American experimental sites. A common observation from all these evaluation is that the model has a tendency towards under-prediction as compared to observed values. This study was an attempt to evaluate the model with Copenhagen data set, which is a European Experimental site. Its shows same tendency towards under-prediction as compared to observed values.
Other Identifiers: M.Tech
Appears in Collections:MASTERS' DISSERTATIONS (Civil Engg)

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