Abstract
A detailed test plan was developed by analyzing the factors affecting PM2.5 diffusion in the urban street traffic microenvironment. After field investigation, several test streets within the third Ring Road of Harbin city were selected to investigate and test the hourly traffic flow of the streets, and the geometric structure of the block (road width, building height) was measured. The research carried out tests on the PM2.5 concentration, wind speed, temperature and relative humidity of actual street test points. Based on the actual test data, BP artificial neural network and the improved LMBP neural network were used to carry out simulation research on MATLAB platform respectively. A PM2.5 concentration prediction model was established to compare and analyze the reliability of the model. Scientific and reasonable prediction of PM2.5 pollution in the traffic microenvironment in a specific area.
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