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Spatio-Temporal Evolution of Carbon Emission in China’s Tertiary Industry: A Decomposition of Influencing Factors from the Perspective of Energy-Industry-Consumption

Zhengyang Li, Yukuan Wang (wangyukuan@imde.ac.cn), Yafeng Lu and Shravan Kumar Ghimire
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Zhengyang Li: Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
Yukuan Wang: Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
Yafeng Lu: Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
Shravan Kumar Ghimire: Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China

Energies, 2023, vol. 16, issue 15, 1-18

Abstract: The development of the tertiary industry is of great significance for promoting industrial structure, optimizing and upgrading it, and achieving regional energy conservation and emission reduction goals. This study adopts a quantitative method to analyze the spatio-temporal pattern of carbon emissions from China’s tertiary industry from 2004 to 2019. In order to analyze emissions from aspects such as energy structure, energy intensity, energy carrying capacity, industrial structure, level of industrial development, income level, consumption capacity, energy consumption intensity, and population size, this study establishes a hybrid factor decomposition model called the “energy-industry-consumption” research framework. The study shows that carbon emissions from China’s tertiary industry have been increasing year by year from 2004 to 2019, with a growth rate of 353.10%. Transportation is the largest contributor to the increase in carbon emissions from China’s tertiary industry. The carbon emissions from the tertiary industry in each province show four types: high-speed growth, low-speed growth, fluctuating growth, and stable growth. During the study period, carbon emissions produce a spatial heterogeneity with the highest emissions in the south and lowest in the northwestern part of China. The spatial pattern of per capita carbon emissions is not significant. Guangdong has the highest carbon emissions, and Shanghai and Beijing have higher per capita carbon emissions. Industrial factors and consumption factors have a positive effect on carbon emissions in China’s tertiary industry, while energy factors have a negative effect. The leading factor of carbon emissions in China’s tertiary industry has gradually shifted from energy to industry.

Keywords: carbon emission; tertiary industry; factor decomposition; spatio-temporal distribution; China (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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