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

被引:15
|
作者
Wang, Ye-Ning [1 ,2 ]
Zhou, Qiang [1 ,2 ]
Wang, Hao-Wei [1 ]
机构
[1] Chinese Acad Sci, Inst Urban Environm, Key Lab Urban Environm & Hlth, Xiamen 361021, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
ecological footprint size; ecological footprint depth; ecological carrying capacity intensity; driving factor; GHMGBA; ENVIRONMENTAL KUZNETS CURVE; ENERGY-CONSUMPTION; SUSTAINABILITY; HYPOTHESIS; IMPACT; EMISSIONS; PATTERNS; PROVINCE; SHAANXI; REGIONS;
D O I
10.3390/su12229705
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 (ECintensity) was calculated to optimize the accounting of ecological carrying capacity (EC). Ecological footprint depth (EFdepth) and ECintensity 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 EFdepth occurred in Macao (17.11 similar to 26.21) and Zhongshan registering the lowest (2.42 similar to 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 EFdepth, ECintensity and three-dimensional ecological deficit (ED3D) 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.
引用
收藏
页码:1 / 18
页数:18
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