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An improved approach for measuring the efficiency of low carbon city practice in China

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  • Du, Xiaoyun
  • Meng, Conghui
  • Guo, Zhenhua
  • Yan, Hang

Abstract

To meet the dual carbon goal, Chinese cities have invested a lot of human, material and financial resources in practicing low carbon city (LCC) and have made great progress. However, it seems that the efficiency of LCC performance remains unexplored. This study aims to propose an improved method for measuring LCC performance from an efficiency perspective (LCCE method). In developing this method, LCC practice is considered as a system, and the input factors of LCCE consist of labor force, capital stock, and energy consumption. Economic growth and carbon emissions are overall output factors, and four dimensional output factors, such as optimizing industrial structure are identified. Subsequently, the super-SBM model of LCCE is built up by integrating multiple inputs and outputs. A demonstration of the proposed LCCE method was conducted using data of 256 prefecture-level cities in China from 2006 to 2019. The research findings reveal that: (1) LCCE of cities in the western region performed slightly better than the other three regions; (2) LCCE of Chinese cities shows a U-shaped relationship with city size. This study proposes an improved approach for measuring LCCE and provides an essential reference for central and local governments in China to better formulate low-carbon strategies.

Suggested Citation

  • Du, Xiaoyun & Meng, Conghui & Guo, Zhenhua & Yan, Hang, 2023. "An improved approach for measuring the efficiency of low carbon city practice in China," Energy, Elsevier, vol. 268(C).
    • Handle: RePEc:eee:energy:v:268:y:2023:i:c:s0360544223000725
    DOI: 10.1016/j.energy.2023.126678
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    as
    1. Vlontzos, George & Niavis, Spyros & Manos, Basil, 2014. "A DEA approach for estimating the agricultural energy and environmental efficiency of EU countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 91-96.
    2. Shuai, Chenyang & Shen, Liyin & Jiao, Liudan & Wu, Ya & Tan, Yongtao, 2017. "Identifying key impact factors on carbon emission: Evidences from panel and time-series data of 125 countries from 1990 to 2011," Applied Energy, Elsevier, vol. 187(C), pages 310-325.
    3. Fang, Guochang & Gao, Zhengye & Tian, Lixin & Fu, Min, 2022. "What drives urban carbon emission efficiency? – Spatial analysis based on nighttime light data," Applied Energy, Elsevier, vol. 312(C).
    4. Huo, Weidong & Qi, Jie & Yang, Tong & Liu, Jialu & Liu, Miaomiao & Zhou, Ziqi, 2022. "Effects of China's pilot low-carbon city policy on carbon emission reduction: A quasi-natural experiment based on satellite data," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    5. Zhang, Fan & Deng, Xiangzheng & Phillips, Fred & Fang, Chuanglin & Wang, Chao, 2020. "Impacts of industrial structure and technical progress on carbon emission intensity: Evidence from 281 cities in China," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    6. Ferreira, Ana & Pinheiro, Manuel Duarte & de Brito, Jorge & Mateus, Ricardo, 2018. "Combined carbon and energy intensity benchmarks for sustainable retail stores," Energy, Elsevier, vol. 165(PB), pages 877-889.
    7. Zhanhang Zhou & Linjian Cao & Kuokuo Zhao & Dongliang Li & Ci Ding, 2021. "Spatio-Temporal Effects of Multi-Dimensional Urbanization on Carbon Emission Efficiency: Analysis Based on Panel Data of 283 Cities in China," IJERPH, MDPI, vol. 18(23), pages 1-20, December.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. Bai, Caiquan & Du, Kerui & Yu, Ying & Feng, Chen, 2019. "Understanding the trend of total factor carbon productivity in the world: Insights from convergence analysis," Energy Economics, Elsevier, vol. 81(C), pages 698-708.
    10. Axel Baeumler & Ede Ijjasz-Vasquez & Shomik Mehndiratta, 2012. "Sustainable Low-Carbon City Development in China," World Bank Publications - Books, The World Bank Group, number 12330, December.
    11. Emrouznejad, Ali & Yang, Guo-liang, 2016. "A framework for measuring global Malmquist–Luenberger productivity index with CO2 emissions on Chinese manufacturing industries," Energy, Elsevier, vol. 115(P1), pages 840-856.
    12. Cui, Qiang & Li, Ye, 2015. "An empirical study on the influencing factors of transportation carbon efficiency: Evidences from fifteen countries," Applied Energy, Elsevier, vol. 141(C), pages 209-217.
    13. Xie, Chunping & Bai, Mengqi & Wang, Xiaolei, 2018. "Accessing provincial energy efficiencies in China’s transport sector," Energy Policy, Elsevier, vol. 123(C), pages 525-532.
    14. Wang, Guofeng & Deng, Xiangzheng & Wang, Jingyu & Zhang, Fan & Liang, Shiqi, 2019. "Carbon emission efficiency in China: A spatial panel data analysis," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    15. Zhang, Ning & Wei, Xiao, 2015. "Dynamic total factor carbon emissions performance changes in the Chinese transportation industry," Applied Energy, Elsevier, vol. 146(C), pages 409-420.
    16. Guo, Xiaoying & Lu, Ching-Cheng & Lee, Jen-Hui & Chiu, Yung-Ho, 2017. "Applying the dynamic DEA model to evaluate the energy efficiency of OECD countries and China," Energy, Elsevier, vol. 134(C), pages 392-399.
    17. Zhang, Yue-Jun & Jiang, Lin & Shi, Wei, 2020. "Exploring the growth-adjusted energy-emission efficiency of transportation industry in China," Energy Economics, Elsevier, vol. 90(C).
    18. Chiu, Yung-ho & Huang, Chin-wei & Ma, Chun-Mei, 2011. "Assessment of China transit and economic efficiencies in a modified value-chains DEA model," European Journal of Operational Research, Elsevier, vol. 209(2), pages 95-103, March.
    19. Wang, Eric C. & Huang, Weichiao, 2007. "Relative efficiency of R&D activities: A cross-country study accounting for environmental factors in the DEA approach," Research Policy, Elsevier, vol. 36(2), pages 260-273, March.
    20. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    21. Yan, Yu & Huang, Junbing, 2022. "The role of population agglomeration played in China's carbon intensity: A city-level analysis," Energy Economics, Elsevier, vol. 114(C).
    22. Feng, Chao & Wang, Miao, 2018. "Analysis of energy efficiency in China's transportation sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 565-575.
    23. Moon, Hana & Min, Daiki, 2017. "Assessing energy efficiency and the related policy implications for energy-intensive firms in Korea: DEA approach," Energy, Elsevier, vol. 133(C), pages 23-34.
    24. Liao, Nuo & He, Yong, 2018. "Exploring the effects of influencing factors on energy efficiency in industrial sector using cluster analysis and panel regression model," Energy, Elsevier, vol. 158(C), pages 782-795.
    25. Tan, Sieting & Yang, Jin & Yan, Jinyue & Lee, Chewtin & Hashim, Haslenda & Chen, Bin, 2017. "A holistic low carbon city indicator framework for sustainable development," Applied Energy, Elsevier, vol. 185(P2), pages 1919-1930.
    26. Cheng, Zhonghua & Li, Lianshui & Liu, Jun & Zhang, Huiming, 2018. "Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 330-339.
    27. Bian, Yiwen & He, Ping & Xu, Hao, 2013. "Estimation of potential energy saving and carbon dioxide emission reduction in China based on an extended non-radial DEA approach," Energy Policy, Elsevier, vol. 63(C), pages 962-971.
    28. Tao, Xueping & Wang, Ping & Zhu, Bangzhu, 2016. "Provincial green economic efficiency of China: A non-separable input–output SBM approach," Applied Energy, Elsevier, vol. 171(C), pages 58-66.
    29. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    30. Yu, Yantuan & Zhang, Ning, 2021. "Low-carbon city pilot and carbon emission efficiency: Quasi-experimental evidence from China," Energy Economics, Elsevier, vol. 96(C).
    31. Liu, Tiantian & Wang, Qunwei & Su, Bin, 2016. "A review of carbon labeling: Standards, implementation, and impact," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 68-79.
    32. Song, Malin & Song, Yaqing & An, Qingxian & Yu, Huayin, 2013. "Review of environmental efficiency and its influencing factors in China: 1998–2009," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 8-14.
    33. Dhakal, Shobhakar, 2009. "Urban energy use and carbon emissions from cities in China and policy implications," Energy Policy, Elsevier, vol. 37(11), pages 4208-4219, November.
    34. Song, Malin & Zheng, Wanping & Wang, Zeya, 2016. "Environmental efficiency and energy consumption of highway transportation systems in China," International Journal of Production Economics, Elsevier, vol. 181(PB), pages 441-449.
    35. Song, Qijiao & Qin, Ming & Wang, Ruichen & Qi, Ye, 2020. "How does the nested structure affect policy innovation?: Empirical research on China's low carbon pilot cities," Energy Policy, Elsevier, vol. 144(C).
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