Abstract
Abstract Geographic allocation of chemical plants significantly affects industrial business sustainability as well as regional environmental sustainability. According to site selection rules, the air quality impact to surrounding communities for a newly constructed chemical plant must be taken into account. To address this issue, regional background air-quality information, new plant emissions, and local statistical meteorological conditions have to be simultaneously considered. Based on that, the potential air-quality impacts from candidate sites of a new chemical plant can be thoroughly evaluated and the final site determination can be optimized to minimize air-quality impacts based on the likelihood of local meteorological conditions. In this paper, a systematic methodology for this purpose has been developed. It includes the modeling and optimization work to apply Monte Carlo optimization for optimal site selection of new chemical plants with their given emission data. This study can not only determine the potential impact for the distribution of new chemical plants with respect to regional statistical meteorological conditions, but also identify an optimal site for each new chemical plant with the minimal environment impact to surrounding communities. Case studies are employed to demonstrate the efficacy of the developed methodology.
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