ORIGINAL RESEARCH
Study on Sustainable Development of Mining Cities by the Method of Relative Resources Carrying Capacity and GM (1, 1) Model
Keyu Bao 1  
,   Gang He 1, 2  
,   Lan Jin 1  
,   Jingwen Yang 1  
,   Qingting Zhou 1  
 
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1
College of Economy and Management, Anhui University of Science and Technology, Huainan, Anhui, 232001, China
2
State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines, Huainan, Anhui, 232001, China
CORRESPONDING AUTHOR
Gang He   

College of Economy and Management, Anhui University of Science and Technology, China
Submission date: 2019-12-19
Final revision date: 2020-03-01
Acceptance date: 2020-03-02
Online publication date: 2020-05-22
Publication date: 2020-08-05
 
Pol. J. Environ. Stud. 2020;29(6):3983–3995
 
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ABSTRACT
Mining cities in China are vital energy bases that contribute greatly to the country’s development. With the pressure of resources depletion and environmental destruction, the sustainable development of these cities is increasingly concerned by the government. This study chooses typical mining cities in Anhui Province of China as the case studies, then selects ten indicators from four dimensions of natural, economic, social, and environmental resources and improves the relative resources carrying capacity (RRCC) model. The dynamic changes of RRCC of these cities from 2007 to 2017 are analyzed. Then the predicted values in 2018-2023 were gotten based on GM (1, 1) model. The results indicate that: (1) Overall, the RRCC of these cities are overload and the overload population has slightly decreased. (2) The primary resources carrying the population are natural resources, but their carrying capacity shows a declining trend. The carrying capacities of economic, social, and environmental resources are much less than that of natural resources, although they have increased a lot in these years. (3) The RRCC and its variation tendency of each mining city are different. (4) The predicted RRCC of these cities would become stronger and the population overload would decrease in the next six years.
eISSN:2083-5906
ISSN:1230-1485