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Feasibility of peaking carbon emissions of the power sector in China’s eight regions: decomposition, decoupling, and prediction analysis

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Abstract

Carbon emissions in the power sector are an important part of China’s total carbon emissions and have a significant impact on whether China can achieve the 2030 carbon peak target. Based on the three perspectives of decomposition, decoupling, and prediction, this paper studies the feasibility of carbon emission peaks in eight major regional power sectors in China. First, the generalized Divisia index model (GDIM) is used to decompose the carbon emissions of the eight regional power sectors, and the driving factors and their effects on carbon emissions in the power sector of each region are compared. Then, the decoupling index based on the generalized Divisia index model (GDIM-D) is used to study the decoupling relationship between the carbon emissions of the eight regional power sectors and economic growth. Finally, the carbon emissions and decoupling indices of the power sector from 2017 to 2030 are predicted. The results show the following. First, the gross domestic product (GDP) and output scale are the main factors contributing to the carbon emissions of the eight regional power sectors. The carbon intensity of the power sector in GDP (C/G) and output carbon intensity(C/E) are the main factors that contribute to the reduction. Second, the carbon emissions of the southern coast, the middle Yellow River, and the Southwest peaked in 2013 and have been decoupled from economic growth, while those in the other regions have not peaked or decoupled. Third, if the carbon emissions of the power sector in the Northeast, northern coast, eastern coast, middle Yangtze River, and Northwest reach a peak in 2030, they will face many emission reduction pressures. This paper provides a reference for studying the carbon emissions of China’s regional power sectors and their relationship with economic growth and has important implications for peak carbon emissions at the national level.

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Funding

This paper is supported by the Youth Research Program in Humanities and Social Sciences, Ministry of Education (18YJC910013), National Social Science Fund (19CTJ008), Liaoning Province Financial Scientific Research Fund Project (18B010), the National Natural Science Foundation of China (71573034), Liaoning Social Science Fund (L17CTJ001, L17BJY042), and the Research Project of Dongbei University of Finance and Economics (DUFE2017Q16).

Author information

Yong Wang and Xuelian Su were mainly responsible for the writing of the full text. Yonghong Xu conceived and designed the study. Lin Qi and Peipei Shang built the models of the paper.

Correspondence to Yonghong Xu.

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The authors declare that they have no conflict of interest.

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Appendix

Appendix

Table 1 Division of the eight regions
Table 2 Nomenclature in this paper
Table 3 Summary of mentioned studies in this paper
Table 4 Summary of main conclusions of this paper
Fig. 7
figure7

Diagram of carbon emission forecast for the power sector of China’s five regions from 2017 to 2030 (when the average annual growth rate of GDP is 5.5%)

Fig. 8
figure8

Diagram of carbon emission forecast for the power sector of China’s five regions from 2017 to 2030 (when the average annual growth rate of GDP is 7.5%)

Fig. 9
figure9

Diagram of the comparison of carbon emissions in the power sector caused by unit GDP of China’s five regional power sector (when the average annual growth rate of GDP is 5.5%)

Fig. 10
figure10

Diagram of the comparison of carbon emissions in the power sector caused by unit GDP of China’s five regional power sector (when the average annual growth rate of GDP is 7.5%)

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Wang, Y., Su, X., Qi, L. et al. Feasibility of peaking carbon emissions of the power sector in China’s eight regions: decomposition, decoupling, and prediction analysis. Environ Sci Pollut Res 26, 29212–29233 (2019). https://doi.org/10.1007/s11356-019-05909-1

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Keywords

  • Power sector
  • Carbon emission peak
  • Factor decomposition
  • Economic decoupling
  • Predictive assessment
  • China