Risk Assessment for Environmentally Sustainable Business Planning and Optimization Based on the Identification of Regional Meteorology Pattern

Currently, more and more attention has been paid to the environmentally sustainability of the surrounding community by the whole society. However, during the manufacturing operation of industrial plants, there are inevitable pollutant emission dispersion into the atmosphere from the plume or flare combustion. The impact scope and seriousness level of the emission events to the surrounding community will be affected by not only the emission amount but also the regional meteorological situation. The spatial and temporal distribution pattern of the climate will play a very important role in the performance of the regional air quality. Furthermore, the environmental sustainability is of great significance to the result of whether the industrial business venture will be successful or not. Therefore the potential impact of climate pattern in the regional air quality performance should be evaluated during the risk assessment so as to timely and effectively support diagnostic and prognostic decisions. In this research, a systematic methodology for such applications has been developed. It includes two stages of modeling and simulation work: i) Pattern identification for the climate distribution change scenarios from the historical meteorological data and ii) Monte Carlo based simulation of regional air quality performance from normal emission of current multiple emission sources. Different scenarios of climate distribution pattern will be assumed to prediction the comprehensive air quality results in order to disclose their relationships. For the risk assessment, the peak pollutant concentration and the standard deviation at the air quality concerned region should be evaluated. This study can not only help to determine the potential impact for the distribution of multiple plants responsible for the characteristics of regional climate, but also provide the technical support for the future industrial expansion with minimal environment impact to the surrounding community.