SCIENTIA GEOGRAPHICA SINICA ›› 2018, Vol. 38 ›› Issue (11): 1799-1808.doi: 10.13249/j.cnki.sgs.2018.11.007

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Spatial-temporal Pattern and Driving Factors of Public Participation in Environmental Regulation: Taking the Yangtze River Economic Belt as An Example

Yong Ma1(), Yun Tong1(), Jie Ren2, Jun Liu1   

  1. 1. Academy of Green Department, School of Business, Hubei University, Wuhan 430062, Hubei, China
    2. Business School, University of Queensland, Brisbane 4072, Queensland, Australia
  • Received:2017-11-22 Revised:2018-02-06 Online:2018-11-20 Published:2018-11-20
  • Supported by:
    Youth Program of National Social Science Foundation (17CJY051), Major Project of Hubei Provincial Government Procurement of Intellectual Achievements (HBZD201705), Major Project of Hubei Province’s Social Science Fund (2015190)

Abstract:

The public participation in environmental regulation based on the 12369 environmental complaint data of the Yangtze River economic belt is taken as the research object. Taking the city as the research scale, the spatial analysis method is used to reveal the spatial and temporal pattern of public participation in environmental regulation. The dominant driving factors of public participation in environmental regulation are screened by Geodetector. Using GWR(geographically weighted regression)model to reveal the spatial heterogeneity of each dominant driving factors, such as economic level, industrial structure, human land pressure, emission intensity, informatization level, and environmental risk. The results show that: 1) The public participation in environmental regulation in the Yangtze River Economic Belt has significant spatial positive correlation, and the spatial agglomeration degree has decreased significantly in 2015. 2) The spatial pattern of public participation in environmental regulation in Yangtze River Economic Belt is basically stable in 2013-2015. The most area of the Yangtze River Delta city group, Wuhan and Nanchang in the middle reaches of the Yangtze River City Group, and small area of Chengdu Chongqing city agglomeration are the high intensity zone of public participation in environmental regulation. 3) The factor detection results from Geodetector excluded two primary variables: fixed assets investment per square kilometer and the number of college students per tens thousands of people. 4) The OLS model fitting results show that the driving force affecting the public participation in environmental regulation intensity followed by environmental risk factors, human factors, stress intensity factor, the informatization level of emission factor, economic factor, and industrial structure factor. In addition to the industrial structure and the level of information, the other factors are positively correlated with public participation in environmental regulation. 5) Multinomial parameters show that the GWR model of public participation environmental regulation intensity in the Yangtze River Economic Belt is better than the OLS model. 6) The GWR model fitting shows the driving factors of spatial heterogeneity, and spatial heterogeneity of each driving factor has the difference, provides a theoretical basis for environmental regulation policy and public participation intensity differences for different regions to take. The GWR model fitting results show the difference from spatial heterogeneity of each driving factor, and provides a theoretical basis and targeted strategies for of environmental regulation in different regions.

Key words: public participation in environmental regulation, spatial and temporal evolution, driving factors, GeoDetector, GWR, the Yangtze River Economic Belt

CLC Number: 

  • F224