RESOURCES AND ENVIRONMENT IN THE YANGTZE BASIN >> 2020, Vol. 29 >> Issue (7): 1497-1506.doi: 10.11870/cjlyzyyhj202007003

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TemporalSpatial Evolution of PM 2.5 and Driving Factors in Yangtze River Delta Urban Agglomeration

WANG Zhao 1 ,YAN Xiao-bing 2   

  1. (1.Public Administration of Hohai University,Nanjing 211100,China;2. Qu QiuBai School of Government of Changzhou University,Changzhou 213159,China)
  • Online:2020-07-20 Published:2020-08-28

Abstract: Scientific identification of PM 2.5 space differentiation and its driving factors is the key to regional air pollution control. Taking the daily average PM 2.5 concentration of national measure points as the data source, the spatiotemporal evolution and influencing factors of PM 2.5 concentration in Yangtze River Delta Urban Agglomerations were studied based on various spatial analysis methods. The results showed that: (1) From 2013 to 2017, the annual average concentration of PM 2.5 in the Yangtze River Delta Urban Agglomerations was on a declining trend; the differences among cities showed a gradually decreasing trend. (2) The concentration of PM 2.5 was highest in December and lowest in August. From January to December, the concentration of PM 2.5 decreased first and then increased. (3) In 2013, the high concentration area of PM 2.5 was mainly distributed in Jiangsu Province; in 2017, the high concentration area of PM 2.5 was mainly distributed in Anhui Province. In the past five years, the spatial barycenter of PM 2.5 concentration shifted 72 km to Anhui Province. (4) There was obvious spatial autocorrelation of PM 2.5 concentration in Yangtze River Delta Urban Agglomerations. In addition, there was a phenomenon of "flock together " for highhigh value area and lowlow value area of PM 2.5 concentration, and the agglomeration degree had an increasing trend. (5) The influencing factors of PM 2.5 concentration include natural factors and social factors. Natural factors found that rainfall is now related to PM2.5concentration. Social factors mainly come from industrial emissions, traffic emissions and energy consumption. Among them, the impact of energy consumption was the largest, followed by industrial emissions, traffic emissions ranked last.

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