Improvement And Application Of A Multi-Region Air Control And Response Modeling System

With increasingly rigorous combined air pollution and growing stringent air quality regulation, how to develop a scientific and high-effective real-time air quality response to emission reductions, is the key to make a system of integrated and optimal air pollution control strategy by comparing the effectiveness of various control strategies. The Response Surface Model(RSM) based on a high-dimensional Kriging interpolation algorithm can capture the nonlinear response of emission changes under various control scenarios, but has a limited capacity to capture the linear response of fine particles(PM2.5) to primary particulate matter(PM) emission changes. In China, there is a significant portion of PM2.5 resulting from primary PM emission. Therefore, it is practical and necessary to develop an innovative system for capturing the response of China’s PM2.5 to its emission changes through the improvements of Response Surface Model.In this dissertation, the PM2.5 emissions are divided into two parts, the nonlinear response gaseous precursors and the linear response primary PM. The first parts are used to create a nonlinear Response Surface Model with the high-dimensional Kriging interpolation algorithm. On the basis of the nonlinear response surface model, this dissertation employs a linear fitting method to capture the linear response to primary PM emission changes, and then set up a new PM2.5 response surface model with RSM-Linear coupled fitting method. This new RSM has the ability of capturing the response of PM2.5 to emission changes from both gaseous precursor and primary PM, and will be validated by cross validation and out of sample validation. Besides, a module for outputting gridded model data to the Software for Model Attainment Test-Community Edition(SMAT-CE) in the RSM system is developed. With the rapid real-time response ability of RSM, the newly developed module establishes a data link between RSM system and SMAT-CE, and has the ability to provide streamlined model responses to emission control scenario for SMAT-CE using a simple interface. Finally, the performance and application of this system in decision-making is demonstrated through two case studies of Yangtze River Delta(YRD) in China.Results show that this system is capable of reproducing the Community Multi-Scale Air Quality(CMAQ) model simulation results with the maximum Normalized Mean Error <5%. It is also demonstrated that the system is capable of real-time evaluating the response of PM2.5 to both gaseous precursors and primary PM. This system has the ability to identify the contributions of major emission sources to ambient PM2.5 and provide streamline air quality data for SMAT-CE to perform attainment assessments, which can provide assistance for decision-making in developing and optimizing air pollution control strategy in China.