Quantitative association analysis between PM(2.5) concentration and factors on industry, energy, agriculture, and transportation

Rapid urbanization is causing serious PM(2.5) (particulate matter ≤2.5 μm) pollution in China. However, the impacts of human activities (including industrial production, energy production, agriculture, and transportation) on PM(2.5) concentrations have not been thoroughly studied. In this study, we obtained a regression formula for PM(2.5) concentration based on more than 1 million PM(2.5) recorded values and data from meteorology, industrial production, energy production, agriculture, and transportation for 31 provinces of mainland China between January 2013 and May 2017. We used stepwise regression to process 49 factors that influence PM(2.5) concentration, and obtained the 10 primary influencing factors. Data of PM(2.5) concentration and 10 factors from June to December, 2017 was used to verify the robustness of the model. Excluding meteorological factors, production of natural gas, industrial boilers, and ore production have the highest association with PM(2.5) concentration, while nuclear power generation is the most positive factor in decreasing PM(2.5) concentration. Tianjin, Beijing, and Hebei provinces are the most vulnerable to high PM(2.5) concentrations caused by industrial production, energy production, agriculture, and transportation (IEAT).