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The Impact of Urbanization on Environmental Quality in Ecologically Fragile Areas: Evidence from Hengduan Mountain, Southwest China

Author

Listed:
  • Jue Wang

    (Business School, Chengdu University of Technology, Chengdu 610059, China
    Digital Hu Line Research Institute, Chengdu University of Technology, Chengdu 610059, China)

  • Rui Wang

    (Business School, Chengdu University of Technology, Chengdu 610059, China)

Abstract

The impact of urbanization on the environmental quality of ecologically fragile areas has long been ambiguous. With a focus on the human–environment interaction in 95 counties of Hengduan Mountain, an ecologically fragile region in southwestern China, in this study, we clarify the impact and mechanism of urbanization on environmental quality through the environmental regulation effect, using econometric models and county-level panel data from 2010 to 2019. The results of this study show that: (1) urbanization and environmental regulation have increased over this 10-year period within the study area and regional differences in environmental quality have decreased; (2) urbanization significantly contributes to environmental quality, with heterogenous effects on different environmental elements—increasing the proportion of wetlands and green areas per capita but suppressing vegetation coverage and production efficiency; and (3) environmental regulation is an important mechanism for urbanization to improve environmental quality; however, there are negative externalities on neighboring areas. The results of this study show that urbanization and environmental quality are not always mutually exclusive, thus providing a reference for the development of pro-environmental urbanization to improve sustainable development in ecologically fragile areas.

Suggested Citation

  • Jue Wang & Rui Wang, 2024. "The Impact of Urbanization on Environmental Quality in Ecologically Fragile Areas: Evidence from Hengduan Mountain, Southwest China," Land, MDPI, vol. 13(4), pages 1-18, April.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:4:p:503-:d:1374672
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    Cited by:

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    2. repec:bcp:journl:v:9:y:2025:i:10:p:5860-5873 is not listed on IDEAS
    3. Ozcan, Burcu & Gultekin Tarla, Esma & Simsek, Ahmed Ihsan, 2026. "The determinants of renewable energy production in China: A machine learning approach," Renewable Energy, Elsevier, vol. 256(PF).

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