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Coupling coordination measurement of environmental governance: case of China

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Abstract

The results show that a comprehensive evaluation system consisting of natural resources, pollution response, government management, and legal involvement can systematically assess the coupling coordination degree (CCD) of environmental governance. The information entropy weight (IEW) method and technique for order preference by similarity to an ideal solution (TOPSIS) are jointly used to analyze the CCD of environmental governance in China. The combination of the IEW method and TOPSIS can provide effective references for the sustainable development of environmental governance and are helpful for effectively providing systematic and specific measures. From 2008 to 2017, the CCD of China’s environmental governance fluctuated and generally showed a benign trend. At the same time, the range of CCD among regions was more aggregated and balanced. In addition, the CCD of China’s environmental governance showed spatial relationships and formed a clear spatial cluster in which the coastal areas had higher CCD than did the inland areas.

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Funding

This research was funded by Shanghai Municipal Education Commission, Grant Number ZZSDJU19012; Shanghai CCP Committee of Education and Health Work, Grant Number TZYJ-2019-B37; and Shanghai Dianji University, Grant Number 19AR20.

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Authors and Affiliations

Authors

Contributions

Conceptualization, YG; methodology, YG; software, YT; validation, YT; formal analysis, YT; investigation, YT; resources, YT; data curation, YT; writing—original draft preparation, YT; writing—review and editing, YG; visualization, YT; supervision, YG; project administration, YG; funding acquisition, YG.

Corresponding author

Correspondence to Yuqing Geng.

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Conflicts of interest

The authors declare no conflict of interest.

Additional information

Handling Editor: Pierre Dutilleul.

Appendix

Appendix

See Table 3.

Table 3 CCD values

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Tan, Y., Geng, Y. Coupling coordination measurement of environmental governance: case of China. Environ Ecol Stat 27, 253–272 (2020). https://doi.org/10.1007/s10651-020-00444-6

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  • DOI: https://doi.org/10.1007/s10651-020-00444-6

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