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Carbon Emission Efficiency and Reduction Potential Based on Three-Stage Slacks-Based Measure with Data Envelopment Analysis and Malmquist at the City Scale in Fujian Province, China

Author

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  • Tingting Wu

    (Fujian Provincial Key Laboratory of Agroecological Processing and Safety Monitoring, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
    Fujian Provincial Key Laboratory of Environmental Engineering, Fujian Academy of Environmental Sciences, Fuzhou 350013, China)

  • Junjun Chen

    (Fujian Provincial Key Laboratory of Environmental Engineering, Fujian Academy of Environmental Sciences, Fuzhou 350013, China)

  • Chengchun Shi

    (Fujian Provincial Key Laboratory of Environmental Engineering, Fujian Academy of Environmental Sciences, Fuzhou 350013, China)

  • Guidi Yang

    (Fujian Provincial Key Laboratory of Agroecological Processing and Safety Monitoring, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

Abstract

Increased carbon emissions led to extreme weather, global warming, and other environmental problems. In order to control energy input and reduce carbon emissions, this study first combines a three-stage Slacks-Based Measure with Data Envelopment Analysis (SBM-DEA) and uses the Malmquist index to quantify energy consumption at the city scale and the related carbon emission efficiency in Fujian Province for the period 2015–2020. Second, we explore the carbon reduction potential on the city scale from the perspective of improving carbon emission efficiency. Our results demonstrate that (i) the carbon emission efficiency of the nine cities increases overall in the first stage, when technical efficiency approaches the efficiency frontier state and efficiency shortage is mainly caused by the lack of pure technical efficiency. (ii) Regression by stochastic frontier analysis in the second stage reveals that the secondary industry correlates positively at 1% significance with fossil energy consumption and power consumption, indicating that the carbon emission efficiency decreases as the secondary industry increases. (iii) Putian and Xiamen reduced their carbon emission efficiency in the third stage due to (a) the input redundancy of fossil energy and social power consumption and (b) excessive undesirable output carbon emissions. (iv) There were improvements in carbon emission efficiency peaks in 2015, with Longyan, Ningde, and Sanming improving by about 50%. This improvement then decreased up to the year 2020, when the improvement in the carbon emission efficiency of Ningde and Zhangzhou was 6.02% and 9.50%, respectively, and that of all other cities was less than 1%. Therefore, we suggest that carbon emission reduction in the future can be further improved by improving technology, optimizing industrial structure, and various other ways to further improve carbon emission efficiency.

Suggested Citation

  • Tingting Wu & Junjun Chen & Chengchun Shi & Guidi Yang, 2023. "Carbon Emission Efficiency and Reduction Potential Based on Three-Stage Slacks-Based Measure with Data Envelopment Analysis and Malmquist at the City Scale in Fujian Province, China," Sustainability, MDPI, vol. 15(16), pages 1-15, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:16:p:12363-:d:1217050
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    References listed on IDEAS

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    1. Zhou, Sheng & Xu, Zhiwei, 2022. "Energy efficiency assessment of RCEP member states: A three-stage slack based measurement DEA with undesirable outputs," Energy, Elsevier, vol. 253(C).
    2. Zhou, P. & Ang, B.W. & Han, J.Y., 2010. "Total factor carbon emission performance: A Malmquist index analysis," Energy Economics, Elsevier, vol. 32(1), pages 194-201, January.
    3. Yuxin Yan & Yubao Chen & Minghua Han & Hui Zhen, 2022. "Research on Energy Efficiency Evaluation of Provinces along the Belt and Road under Carbon Emission Constraints: Based on Super-Efficient SBM and Malmquist Index Model," Sustainability, MDPI, vol. 14(14), pages 1-14, July.
    4. Joseph Aldy, 2006. "Per Capita Carbon Dioxide Emissions: Convergence or Divergence?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 33(4), pages 533-555, April.
    5. Yun Tian & Rui Wang & Minhao Yin & Huijie Zhang, 2023. "Study on the Measurement and Influencing Factors of Rural Energy Carbon Emission Efficiency in China: Evidence Using the Provincial Panel Data," Agriculture, MDPI, vol. 13(2), pages 1-16, February.
    6. Qizhen Wang & Qian Zhang, 2022. "Foreign Direct Investment and Carbon Emission Efficiency: The Role of Direct and Indirect Channels," Sustainability, MDPI, vol. 14(20), pages 1-23, October.
    7. Joseph E. Aldy, 2007. "Divergence in State-Level Per Capita Carbon Dioxide Emissions," Land Economics, University of Wisconsin Press, vol. 83(3), pages 353-369.
    8. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    9. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    10. Yongjun Li & Wenhui Hou & Weiwei Zhu & Feng Li & Liang Liang, 2021. "Provincial carbon emission performance analysis in China based on a Malmquist data envelopment analysis approach with fixed-sum undesirable outputs," Annals of Operations Research, Springer, vol. 304(1), pages 233-261, September.
    11. Jinkai Li & Jingjing Ma & Wei Wei, 2020. "Analysis and Evaluation of the Regional Characteristics of Carbon Emission Efficiency for China," Sustainability, MDPI, vol. 12(8), pages 1-22, April.
    12. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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