Measurement and Spatial-Temporal Evolution Characteristics of Low-Carbon Cities with High-Quality Development: The Case Study of the Yangtze River Economic Belt, China

Haonan Yang, Liang Chen (), Huan Huang and Panyu Tang
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Haonan Yang: School of Finance and Accounting, Chengdu Jincheng College, Chengdu 610097, China
Liang Chen: School of Finance and Accounting, Chengdu Jincheng College, Chengdu 610097, China
Huan Huang: College of Business, Chengdu University of Technology, Chengdu 610059, China
Panyu Tang: School of Finance and Accounting, Chengdu Jincheng College, Chengdu 610097, China

Sustainability, 2022, vol. 14, issue 15, 1-23

Abstract: Carrying out measurements of low-carbon city development levels and exploring their core driving factors are focuses of attention in the field of building sustainable low-carbon cities (LCC). Previous studies have mainly focused on the national or provincial level, ignoring the problem of heterogeneity among different cities, and the consideration of the influencing factors of low-carbon cities has not been comprehensive enough. Given this, the authors of this paper selected 107 cities in the Yangtze River Economic Belt from 2006 to 2019, constructed a general comprehensive index system for measuring the high-quality development level of low-carbon cities at the prefecture-level city level, and explored the spatial and temporal evolution trends and core drivers of the high-quality development level of low-carbon cities in the Yangtze River Economic Belt using the CRITIC–VIKOR method and an ensemble learning algorithm. The empirical results showed that most of the cities in the Yangtze River Economic Belt showed an overall upward trend in the level of high-quality development and a certain degree of “central collapse” in the spatial distribution. In addition, this paper further confirms that industrial structure is the most central driver of low-carbon urban development, the importance of urban carbon emissions and the level of science and technology innovation are gradually increasing, and a certain aggregation effect is formed in space that has led to a significant urban “siphon effect”. These results provide new evidence on the spatial and temporal evolution of the high-quality development of low-carbon cities in China and can help authorities formulate more targeted policies and strategic plans to enhance the high-quality development of low-carbon cities.

Keywords: low-carbon city; core drivers exploration; ensemble learning algorithm; spatial autocorrelation analysis; Yangtze River Economic Belt (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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