Prediction analysis of carbon emission in China’s electricity industry based on the dual carbon background

Ze-qun Ding, Hong-qing Zhu, Wei-ye Zhou and Zhi-gang Bai

PLOS ONE, 2024, vol. 19, issue 5, 1-17

Abstract: The electric power sector is the primary contributor to carbon emissions in China. Considering the context of dual carbon goals, this paper examines carbon emissions within China’s electricity sector. The research utilizes the LMDI approach for methodological rigor. The results show that the cumulative contribution of economies scale, power consumption factors and energy structure are 114.91%, 85.17% and 0.94%, which contribute to the increase of carbon emissions, the cumulative contribution of power generation efficiency and ratio of power dissipation to generation factor are -19.15% and -0.01%, which promotes the carbon reduction. The decomposition analysis highlights the significant influence of economic scale on carbon emissions in the electricity industry, among the seven factors investigated. Meanwhile, STIRPAT model, Logistic model and GM(1,1) model are used to predict carbon emissions, the average relative error between actual carbon emissions and the predicted values are 0.23%, 8.72% and 7.05%, which indicates that STIRPAT model is more suitable for medium- to long-term predictions. Based on these findings, the paper proposes practical suggestions to reduce carbon emissions and achieve the dual carbon goals of the power industry.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0302068

DOI: 10.1371/journal.pone.0302068

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