A new statistical modeling and optimization framework for establishing high-resolution PM_(10) emission inventory - Ⅱ. Integrated air quality simulation and optimization for performance improvement

摘要

An integrated air quality simulation and optimization approach was proposed to improve the accuracy of the high-resolution PM_(10) emission inventories developed through regression models. A case study of Tangshan region in northern China was presented as an example. A linear programming optimization model was developed to minimize the mean error between simulated and monitored PM_(10) concentrations in different counties. A transfer coefficient matrix was used to represent source-receptor relationships and was developed through running a MM5-CMAQ air quality model. The results revealed that the proposed simulation-optimization approach could decrease the error of the PM_(10) emission inventory from 17.0 to 7.9% at the regional level, and from 31.44 to 14.17% at the county level. Accuracy improvement ranged from 0.39 to 61.44% for the study counties in Tangshan. The correlation coefficient between the estimated PM_(10) emissions and the monitored PM_(10) concentration in various counties was also increased from 0.82 to 0.91. Together with the regression models, the simulation-optimization method provides a promising and effective framework for developing high-accuracy and high-resolution air pollutant emission inventories.