GEOGRAPHICAL RESEARCH ›› 2019, Vol. 38 ›› Issue (7): 1777-1790.doi: 10.11821/dlyj020181135

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Spatial evolution and influencing factors of urban environmental pollution supervision level in China

Bo YU1(), Xu YANG1,2(), Xiangli WU1, Yuanhe CAO3, Ying CAI1, Xuewei WANG1, Cheng ZHAO1   

  1. 1. College of Geographical Science/Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Harbin Normal University, Harbin 150025, China
    2. Antai College of Economics and Management, Shanghai Jiaotong University, Shanghai 200030, China
    3. Northeast Agricultural University, International Culture Education College, Harbin 150030, China
  • Received:2018-11-16 Revised:2019-04-24 Online:2019-07-20 Published:2019-07-12


Based on the data on China's 2010-2016 prefecture-level city pollution supervision level, The Rank-Size rule is used to analyze the scale distribution of urban environmental pollution supervision level in China. Using spatial autocorrelation, spatial econometric model and other geoscience research methods, we adopt the quantitative analysis to examine the regional differences, spatial and temporal distribution patterns, influencing factors and spatial spillover effects of urban pollution regulation in China. Four conclusions are listed below: (1) From 2010 to 2016, China's pollution supervision level showed an overall upward trend, and its regional agglomeration was obvious. There was a significant spatial autocorrelation in the pollution supervision level. Among them, the Yangtze River Delta and the Pearl River Delta were relatively stable high-value gathering areas of pollution control, and in recent years extended to the eastern Shandong Peninsula urban agglomeration, while the central and western regions were stable low-value gathering areas, indicating that the pollution supervision level had obvious regional aggregation. (2) The level of urban pollution regulation in China presents a sub-type distribution. The cities with high pollution supervision level are mainly distributed in the eastern and central regions. The scale of pollution supervision between high-order cities is gradually narrowing, and the distribution among cities is relatively well distributed. The dispersion trend is more obvious than the concentration trend. (3) Considering the complexity of the influencing factors, the spatial measurement model is used to analyze the influencing factors in the selection of many research methods. The urban population density, economic development level and proportion of secondary industry output value have a significant positive impact on urban pollution supervision level, whereas urban scale has a negative impact on pollution supervision level. (4) Urban economic development, population density, openness, and industrial structure have a significant direct effect on the spillover effect of urban pollution supervision level, while the ratio of the output value of the secondary industry and sulphur dioxide emissions have a significant indirect effect on the pollution supervision level, that is, the promotion of the secondary industry in the region is conducive to that of pollution supervision in neighboring cities

Key words: pollution supervision level, spatial autocorrelation, rank-size rule, spatial spillover effect