Relationship between PM2.5 pollution and firms’ emissions in Shaanxi Province, China - Zhao, Jie; Yuan, Linjiang; Jia, Ce; Guan, Panbo (Frontiers in Earth Science, 2023)
The relationship between the high-frequency time series of PM 2.5 in the atmosphere and the air pollutants emitted by industrial firms is not yet fully understood. This study aimed to identify independent PM 2.5 clustering regions in Shaanxi Province and to evaluate the spatio-temporal correlations of PM 2.5 concentrations and pollutant emissions from industrial firms in these regions.To accomplish this, daily data on PM 2.5 concentrations and air pollutants emitted by industrial firms were analyzed using the K-means spatial clustering method and cross-wavelet transformation. The results show that: (1) PM 2.5 concentrations in Shaanxi Province can be divided into three independent clustering regions. (2) The lagged impact of industrial emissions on PM 2.5 concentrations were about 1/4-1/2 period. (3) PM 2.5 was mainly influenced by particulate matter (PM) emissions from industrial plants during the period of 16-32 days, while nitrogen oxides (NO x ) significantly affected PM 2.5 concentrations during the period of 32-64 days. (4) Emissions of PM, NO x , and sulfur dioxide (SO 2 ) more significantly affect PM 2.5 concentrations in northern and central Shaanxi, and pollutants emitted by firms in the thermal power generation, utility, and steel industries had more significant effects on PM 2.5 concentrations than those emitted by the cement manufacturing and electric power industries. During the COVID-19 shutdown, the emissions of 2 firms cannot significantly affect PM 2.5 concentrations. These findings suggest that emission reduction initiatives should consider industrial, regional, and periodic differences to reduce PM 2.5 pollution during winter.