ALasso-regression based modeling method of urban PM2.5 diffusion measurement

Urbanization in China has led to increasingly serious environmental pollution. To solve the problem of PM2.5 pollution diffusion caused by urbanization, a modeling method of urban PM2.5 diffusion based on the Lasso regression algorithm is proposed. According to the geographical characteristics of the urban area and the distribution characteristics of PM2.5 pollution sources, a polar coordinate system-based non-point source Gaussian plume model is proposed. Considering the lack of monitoring data about PM2.5 concentration, a parameter identification algorithm based on Lasso regression is proposed to calculate PM2.5 emission rate of pollution sources. The experimental results of a city show that the urban PM2.5 diffusion modeling method based on the Lasso regression algorithm can effectively calculate PM2.5 emission rate, accurately simulate the diffusion of PM2.5, and provide a model basis for the follow-up urban PM2.5 diffusion research.