期刊
ENERGY
卷 214, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2020.118944
关键词
Carbon emission inequality; Hierarchical cluster analysis; Multi-sectoral decomposition analysis; Gini coefficient; Chinese cities
资金
- Fundamental Research Funds for the Central Universities of China [JBK2001044, JBK190961]
The study used hierarchical cluster analysis and a decomposition approach to explore multi-sectoral determinants of carbon emission inequality in 285 prefecture-level cities in China. It was found that the emission disparity in the industrial consumption sector is the main source of emission inequalities in clustering city groups, and the emission inequality of each city group decreased in the reporting period, mainly due to changes in emissions per capita. The impact of population mobility on emission inequality was not detected.
Based on the data of 285 prefecture-level cities, hierarchical cluster analysis and a decomposition approach using the Gini coefficient were used to explore multi-sectoral determinants of the carbon emission inequality in Chinese clustering cities. The results indicate that the emission disparity of the industrial consumption sector is the main source of emission inequalities in clustering city groups. Compared with the base period, the emission inequality of each clustering city group decreased in the reporting period, which was mainly attributed to changes in emissions per capita, whereas an impact of population mobility on emission inequality was not detected. Our results have important implications for Chinese city governments that are to adopt differentiated emission reduction policies. (C) 2020 Elsevier Ltd. All rights reserved.
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