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. 2024 May 17;19(5):e0302068.
doi: 10.1371/journal.pone.0302068. eCollection 2024.

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

Ze-Qun Ding  1   2 , Hong-Qing Zhu  2 , Wei-Ye Zhou  1   3 , Zhi-Gang Bai  2
Affiliations

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

Ze-Qun Ding et al. PLoS One. .

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.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Variation of carbon emission and intensity from 2000 to 2020.
Fig 2
Fig 2. Carbon emission decomposition from 2000 to 2020, China.
Fig 3
Fig 3. The predicted carbon emissions and the actual from 2000 to 2020, China.
Fig 4
Fig 4. The predicted carbon emissions and the actual from 2000 to 2020, China.
Fig 5
Fig 5. The predicted carbon emissions with different model.
See this image and copyright information in PMC

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