Mining and modeling for a metropolitan Atlanta ozone pollution decision-making framework

In this paper, we present a Decision-Making Framework (DMF) for reducing ozone pollution in the metropolitan Atlanta region. High ground-level concentrations of ozone continue to be a serious problem in several US cities, and Atlanta is one of the most serious of these cases. In contrast to the &quo...

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Bibliographic Details
Published inIIE transactions Vol. 39; no. 6; pp. 607 - 615
Main Authors Yang, Zehua, Chen, Victoria C. P., Chang, Michael E., Murphy, Terrence E., Tsai, Julia C. C.
Format Journal Article
LanguageEnglish
Published Norcross Taylor & Francis Group 01.06.2007
Taylor & Francis Ltd
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Summary:In this paper, we present a Decision-Making Framework (DMF) for reducing ozone pollution in the metropolitan Atlanta region. High ground-level concentrations of ozone continue to be a serious problem in several US cities, and Atlanta is one of the most serious of these cases. In contrast to the "trial and error" approach utilized by state government decision-makers, our DMF searches for dynamic and focused control strategies that require a lower total reduction of emissions than current control strategies. Our DMF utilizes a rigorous stochastic dynamic programming formulation and includes an Atmospheric Chemistry Module to represent how ozone concentrations change over time. This paper focuses on the procedures within the Atmospheric Chemistry Module. Using the US EPA's Urban Airshed Model for Atlanta, we use mining and metamodeling tools to develop a computationally efficient representation of the relevant ozone air chemistry. The proposed approach is able to effectively model changes in ozone concentrations over a 24-hour period.
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ISSN:0740-817X
2472-5854
1545-8830
2472-5862
DOI:10.1080/07408170600899508