Abstract
The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is the most prominent urban agglomeration in China, with plans for further development. Using the regional collaboration theoretical framework for assessing urban comprehensive carrying capacity (UCC), the improved entropy method is applied to establish an index system based on a social, economic, environment, and transportation perspective to compare UCCs of the GBA’s 11 cities for 2000–2016. Results show that the social subsystem is central to the evaluation system. Cities’ performances vary significantly, with six becoming overloaded in 2016 and the other five remaining loadable. Guangzhou performed best, with a rising UCC; Shenzhen rebounded after a long period of decline; Hong Kong’s capacity rose slightly, with some fluctuation; and Macao performed worse and continues to slide, with no signs of improvement. Overall, the UCC of the urban agglomeration showed a downward trend, with only a few cities continuing to improve. The spatial distribution for UCC was high in the north and low in the south, showing scope for improvement. The study enriches regional collaboration theory and proposes policy implications for GBA development.
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This GBA region includes the special administrative regions of Hong Kong and Macao and the nine municipalities of Guangzhou, Shenzhen, Zhuhai, Foshan, Huizhou, Dongguan, Zhongshan, Jiangmen, and Zhaoqing in Guangdong Province.
For example, the document “Decisions on major issues concerning upholding and improving the system of socialism with Chinese characteristics and promoting the modernization of China’s governance system and capacity” contains a requirement to improve the capacity of central cities and urban agglomerations to comprehensively support and optimize the allocation of resources. Please refer to http://www.gov.cn/zhengce/2019-11/05/content_5449023.htm
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With respect to grading standards, “poor value” denotes the lowest value of a given indicator while “excellent value” denotes the highest value of a given indicator. This is because some indicators show negative attributes, such as industrial solid waste produced, where a higher value equates to greater harm to the environment, so the highest value is denoted as “poor value.”
Please refer to: https://www.dsec.gov.mo/home_zhcn.aspx
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Acknowledgments
Thanks are due to the anonymous reviewers for their constructive comments.
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This work was supported by the National Nature Science Foundation (71903131) and the China Postdoctoral Science Foundation (2019M653047).
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Highlights
• Carrying capacity of the bay area has been explored using improved entropy method;
• Capacity levels of Hong Kong/Macao are estimated in index system with other cities;
• Spatial distribution of carrying capacity is high in the north and low in the south;
• Regional collaboration theory is enriched through consideration of the bay area;
• This study is the first to comprehensively evaluate capacity levels in the bay area.
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Weng, H., Kou, J. & Shao, Q. Evaluation of urban comprehensive carrying capacity in the Guangdong–Hong Kong–Macao Greater Bay Area based on regional collaboration. Environ Sci Pollut Res 27, 20025–20036 (2020). https://doi.org/10.1007/s11356-020-08517-6
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DOI: https://doi.org/10.1007/s11356-020-08517-6