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Changes in carbon emission performance of energy-intensive industries in China

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Abstract

As the major energy consumers, energy-intensive industries are the key players in achieving carbon emission reduction targets. The paper builds a super slack-based model (SBM) considering this undesirable output and calculates the carbon emission efficiency. Then, the meta-frontier Malmquist–Luenberger productivity index (MF-MLPI) is constructed to dynamically analyze the growth rate changes of the carbon emission efficiency and the regional differences in energy-intensive industries. Furthermore, the carbon emission reduction potential of the energy-intensive industries in various economic regions of China is discussed, and the conclusions are as follows: there is a big difference in the carbon emission technology gap ratios (TGRs) of the energy-intensive industries in different economic regions; the growth rate of the carbon emission efficiency of energy-intensive industries shows a trend of first declining and then slowly recovering, while the carbon reduction potential generally shows a trend of decreasing and then rising; and the carbon emission reduction potential in the eastern region keeps decreasing.

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The data and materials used in the study are available from the corresponding author by request.

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Funding

The funding for this research was provided by Jiangsu Provincial Social Science Fund (Grant No:19EYB012) and the Jiangsu University Philosophy and Social Science Project (Grant No:2019SJA0187) in China. Furthermore, we are grateful to the professors that gave us a lot of advice on the paper.

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Contributions

Yao Chen, writing—original draft, methodology, formal analysis, conceptualization, supervision, project administration, and funding acquisition. Jing Wu, investigation, data curation, and formal analysis.

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Correspondence to Yao Chen.

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The authors declare no competing interests.

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Responsible Editor: Roula Inglesi-Lotz

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Chen, Y., Wu, J. Changes in carbon emission performance of energy-intensive industries in China. Environ Sci Pollut Res 29, 43913–43927 (2022). https://doi.org/10.1007/s11356-021-18354-w

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  • DOI: https://doi.org/10.1007/s11356-021-18354-w

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