Influence factors and spillover effect of PM2.5concentration on Fen-wei Plain
HUANG Xiao-gang1,2,3, SHAO Tian-jie1, ZHAO Jing-bo1,2, CAO Jun-ji2, SONG Yong-yong1
1. School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China; 2. Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; 3. College of Geographical Sciences, Shanxi Normal University, Linfen 041004, China
Abstract：Based on data collected by real-time monitoring and remote sensing retrieval from 2015 to 2017, the paper probed into the spatial and temporal change of PM2.5 concentration and its influence factors on Fen-wei Plain via spatial autocorrelation analysis and spatial regression analysis. The results showed that:1) The growing trend of the concentration during these three years was a result of a rapid increase during the heating period (from November to next March), while there was no significant inter-annual variation during the non-heating period (from April to October). 2) The average monthly change of PM2.5 concentration was in a U shape, with a much higher concentration during the heating period. And days with PM2.5 non-attainment during the heating period to the total yearly PM2.5 polluted days increased from the 75.0% in 2015 to the 83.4% in 2017. 3)Cities on the Plain were all in an increasing trend except Tongchuan and Sanmenxia, among which plains from Xianyang to Yuncheng and Luoyang Basin were experiencing the worst PM2.5 pollution with a subtle rural-urban difference, and, thus, formed a highly polluted area. Then it followed by Linfen and plains along side the upper reach of Fen River, which were also in a bad condition but with an evident urban-rural difference. 4) Based on spatial regression analysis, there was a significant spatial spillover effect for the PM2.5concentration on the Plain. Driving factors including annual average temperature, urbanization rate, and energy consumption positively effected the PM2.5 concentration, and additionally, they drove the PM2.5 pollution of neighboring areas into a worse situation. On the contrary, annual precipitation and relief amplitude were not only negatively correlated with the concentration of PM2.5, they also helped for a lower PM2.5 concentration in neighboring areas. Moreover, the transmission effect by wind facilitated the PM2.5 pollution, while vegetation coverage discourage PM2.5 concentration, but neither of their indirect effect was significant.
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