Impacts of Energy Structure on Carbon Emissions in China, 1997–2019

Fengjian Ge, Jiangfeng Li, Yi Zhang, Shipeng Ye and Peng Han
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Fengjian Ge: Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, China
Jiangfeng Li: Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, China
Yi Zhang: Department of Economics and Management, China University of Geosciences, Wuhan 430074, China
Shipeng Ye: Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, China
Peng Han: Department of Land Resource Management, School of Public Administration, China University of Geosciences, Wuhan 430074, China

IJERPH, 2022, vol. 19, issue 10, 1-25

Abstract: To mitigate climate change, reducing carbon dioxide (CO 2 ) emissions is of paramount importance. China, the largest global CO 2 emitter, proposes to peak carbon emissions by 2030 and become carbon neutral by 2060; transforming the energy structure represents one of the primary means of addressing carbon emissions; thus, it is essential to investigate the impacts of alternate energy sources throughout the country. Based on energy consumption and carbon emissions data from 30 provincial-level administrative regions in China (excluding Tibet, Hong Kong, Taiwan, and Macau, due to the lack of data), the study here investigated the shares of coal, petroleum, natural gas, and non-fossil energy sources (i.e., hydropower, nuclear power, wind power, solar power, and biomass power), as they relate to total, per capita, and per unit GDP CO 2 emissions via spatial regression. The results showed that: (1) The epicenters of coal and carbon emissions have shifted from the east to the central and western regions; (2) There is a significant correlation between energy structure and carbon emissions: coal has a positive effect, petroleum’s effects are positive at first, and negative subsequently; while both natural gas and non-fossil energy sources have a negative impact; (3) Provincial-level carbon emissions are affected by energy structure, carbon emissions in neighboring regions, and other factors.

Keywords: carbon emissions; energy structure; Moran’s I; SEMLD; provincial level; China (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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