A gaussian-box modeling approach for urban air quality management in a Northern Chinese City—II. pollutant emission abatement

Abstract

A modeling framework by linking air quality simulation with system optimization was presented in this paper to develop cost-effective urban air quality management strategies in Fengnan district of China. The relation between the total allowable emission and wind speed as well as the relation between the total allowable emission and air-quality-guideline satisfaction were quantified based on the simulation results of the Gaussian-box modeling system. The area-source emission reduction objective in each functional zone of the study city during the heating and non-heating seasons was calculated based on such relations. A linear programming model was then developed to optimize the emission abatement which was subject to a number of dust and SO2 control measures. The economic objective of the air quality management strategy was to minimize the total emission control system cost while the environmental objective can still be satisfied. The environmental objective was reflected by the emission reduction objective of TSP, PM10 and SO2 corresponding to an air-quality-guideline satisfaction percentage of 80%. Consequently, the modeling system comprehensively took into account the information of emission reduction objectives, emission abatement alternatives, emission reduction cost, and related resources constraints. An optimal emission abatement strategy and the related cost were obtained for various pollution control measures. The results would provide sound bases for decision makers in terms of effective urban air quality management and ensuring healthy economic development in the study city.