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Assessing Ecological Carrying Capacity in the Guangdong-Hong Kong-Macao Greater Bay Area Based on a Three-Dimensional Ecological Footprint Model

Author

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  • Ye-Ning Wang

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Qiang Zhou

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Hao-Wei Wang

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China)

Abstract

As one of the most developed and competitive metropolitan areas in the world, the contradiction between resource depletion and sustainable development in the Guangdong-Hong Kong-Macao Greater Bay Area (GHMGBA) has become a crucial issue nowadays. This paper analyzed the natural capital utilization patterns in GHMGBA during 2009–2016 based on a three-dimensional ecological footprint model. Ecological carrying capacity intensity (EC intensity ) was calculated to optimize the accounting of ecological carrying capacity (EC). Ecological footprint depth (EF depth ) and EC intensity were quantitatively investigated and influencing factors were further explored based on a partial least squares (PLS) model. Results showed that GHMGBA had been operating in a deficit state due to the shortage of natural capital flow and accumulated stock depletion. The highest EF depth occurred in Macao (17.11~26.21) and Zhongshan registering the lowest (2.42~3.58). Cropland, fossil energy and construction land constituted the most to total ecological deficit, while woodland was continuously in a slight surplus. Natural capital utilization patterns of 11 cities were divided into four categories through hierarchical clustering analysis. Driving factors of EF depth , EC intensity and three-dimensional ecological deficit (ED 3D ) were mainly students in primary and secondary education, disposable income, consumption expenditure, R&D personnel and freight volume. Our findings could provide guidance for decision-makers to develop resource utilization portfolios in GHMGBA.

Suggested Citation

  • Ye-Ning Wang & Qiang Zhou & Hao-Wei Wang, 2020. "Assessing Ecological Carrying Capacity in the Guangdong-Hong Kong-Macao Greater Bay Area Based on a Three-Dimensional Ecological Footprint Model," Sustainability, MDPI, vol. 12(22), pages 1-18, November.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:22:p:9705-:d:448524
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