Unraveling the Estimation Bias of Carbon Emission Efficiency in China’s Power Industry by Carbon Transfer from Inter-Provincial Power Transmission

Current evaluations of carbon emission efficiency in China’s provincial power industry often neglect the impact of carbon transfers from inter-regional power transmission, leading to biased assessments that hinder the sustainable development of the energy transition. To address this, we propose an advanced efficiency evaluation model that incorporates a multi-regional input–output (MRIO) framework, refining CO2 emission calculations and correcting parameter deviations in the slack-based measure (SBM) model. This model improves both the precision and fairness of carbon emission efficiency assessments. We apply the MRIO-SBM model to evaluate carbon emission efficiency in the power industry across 30 provinces in China for 2012, 2015, and 2017, revealing the impact of carbon transfers on efficiency. The results indicate that incorporating MRIO improves the precision of SBM evaluations. Significant regional disparities are observed: eastern coastal regions achieve higher efficiencies, while northeastern and western regions typically exhibit lower values, ranging from 0.5 to 0.7. Efficiency evaluations must account for carbon transfer dynamics, as these transfers can lead to overestimations of efficiency by up to 19% in electricity-importing regions and underestimations of approximately 10% in electricity-exporting regions. Furthermore, the findings emphasize the need to foster low-carbon cross-regional collaboration to promote sustainable development in the power industry.

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Publication Details

Journal
Sustainability
Published
2025-03-06
DOI
https://doi.org/10.3390/su17052312
Citations
1
Primary Topic
Environmental Impact and Sustainability
Type
article
Field-Weighted Citation Impact
0.80

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article

Unraveling the Estimation Bias of Carbon Emission Efficiency in China’s Power Industry by Carbon Transfer from Inter-Provincial Power Transmission

Huangwei Deng, Bin Zhou, Yue Han, Qin Ji-wei
1 citations
Sustainability
Environmental Impact and Sustainability
0.80
article

Unraveling the Estimation Bias of Carbon Emission Efficiency in China’s Power Industry by Carbon Transfer from Inter-Provincial Power Transmission

Huangwei Deng, Bin Zhou, Yue Han, Qin Ji-wei
article en
1 citations

Abstract

Current evaluations of carbon emission efficiency in China’s provincial power industry often neglect the impact of carbon transfers from inter-regional power transmission, leading to biased assessments that hinder the sustainable development of the energy transition. To address this, we propose an advanced efficiency evaluation model that incorporates a multi-regional input–output (MRIO) framework, refining CO2 emission calculations and correcting parameter deviations in the slack-based measure (SBM) model. This model improves both the precision and fairness of carbon emission efficiency assessments. We apply the MRIO-SBM model to evaluate carbon emission efficiency in the power industry across 30 provinces in China for 2012, 2015, and 2017, revealing the impact of carbon transfers on efficiency. The results indicate that incorporating MRIO improves the precision of SBM evaluations. Significant regional disparities are observed: eastern coastal regions achieve higher efficiencies, while northeastern and western regions typically exhibit lower values, ranging from 0.5 to 0.7. Efficiency evaluations must account for carbon transfer dynamics, as these transfers can lead to overestimations of efficiency by up to 19% in electricity-importing regions and underestimations of approximately 10% in electricity-exporting regions. Furthermore, the findings emphasize the need to foster low-carbon cross-regional collaboration to promote sustainable development in the power industry.

SustainabilityVol. 17(5)
Tongji University (CN), Xinjiang University (CN)
Natural Science Foundation of Xinjiang Province
Openalex Percentile: Top 32%
Environmental Impact and Sustainability
0.80
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