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Research of Carbon Emission Reduction Potentials in the Yellow River Basin, Based on Cluster Analysis and the Logarithmic Mean Divisia Index (LMDI) Method

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  • Jingcheng Li

    (School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
    Beijing Laboratory of National Economic Security Early-Warning Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Menggang Li

    (Beijing Laboratory of National Economic Security Early-Warning Engineering, Beijing Jiaotong University, Beijing 100044, China)

Abstract

China has implemented many green transition policies to reach its carbon peak target, some of which do not consider the actual carbon reduction pressures that localities can afford, thus lowering the living standards of residents and economic growth, which makes the green transition process unsustainable. The Yellow River Basin plays an important role in China’s energy, food, manufacturing, and ecological sectors. Thus, the design of green transition policies in the region needs to be modest and efficient. Based on the data of 100 prefecture-level cities in the Yellow River Basin from 2006 to 2017, this paper uses the K-means clustering to divide the carbon reduction potential of cities into four types. Most cities’ carbon reduction potentials are low or medium, unsuitable for adopting a rapid green transition. Based on the logarithmic mean Divisia index (LMDI) decomposition results and the carbon reduction potential, we designed different carbon-control pathways: Shandong and Henan should focus on increasing investment in green technology, especially oxy-combustion technology; Gansu, Ningxia, and Qinghai could partially offset carbon emissions through land use, land-use change and forestry (LULUCF) activities; Sichuan and Inner Mongolia should increase their energy-use efficiency; Shaanxi and Shanxi could use green finance to complete the upgrading of local industries. The above emission-reduction strategies can be actively pursued in cities with high emission reduction potential and should be implemented with caution in cities with low emission reduction potential. This paper provides a new and cost-effective perspective on carbon emission control in the Yellow River Basin.

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  • Jingcheng Li & Menggang Li, 2022. "Research of Carbon Emission Reduction Potentials in the Yellow River Basin, Based on Cluster Analysis and the Logarithmic Mean Divisia Index (LMDI) Method," Sustainability, MDPI, vol. 14(9), pages 1-16, April.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5284-:d:803660
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    1. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    2. Su, Bin & Ang, B.W., 2015. "Multiplicative decomposition of aggregate carbon intensity change using input–output analysis," Applied Energy, Elsevier, vol. 154(C), pages 13-20.
    3. Hu, Yuan & Peng, Ling & Li, Xiang & Yao, Xiaojing & Lin, Hui & Chi, Tianhe, 2018. "A novel evolution tree for analyzing the global energy consumption structure," Energy, Elsevier, vol. 147(C), pages 1177-1187.
    4. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    5. Schipper, L. & Howarth, R. & Carlassare, E., 1992. "Energy intensity, sectoral activity, and structural change in the Norwegian economy," Energy, Elsevier, vol. 17(3), pages 215-233.
    6. Shahbaz, Muhammad & Loganathan, Nanthakumar & Muzaffar, Ahmed Taneem & Ahmed, Khalid & Ali Jabran, Muhammad, 2016. "How urbanization affects CO2 emissions in Malaysia? The application of STIRPAT model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 83-93.
    7. York, Richard & Rosa, Eugene A. & Dietz, Thomas, 2003. "STIRPAT, IPAT and ImPACT: analytic tools for unpacking the driving forces of environmental impacts," Ecological Economics, Elsevier, vol. 46(3), pages 351-365, October.
    8. Jinhuang Mao & Qiong Wu & Meihong Zhu & Chengpeng Lu, 2022. "Effects of Environmental Regulation on Green Total Factor Productivity: An Evidence from the Yellow River Basin, China," Sustainability, MDPI, vol. 14(4), pages 1-21, February.
    9. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    10. De Oliveira-De Jesus, Paulo M., 2019. "Effect of generation capacity factors on carbon emission intensity of electricity of Latin America & the Caribbean, a temporal IDA-LMDI analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 516-526.
    11. Haikun Wang & Xi Lu & Yu Deng & Yaoguang Sun & Chris P. Nielsen & Yifan Liu & Ge Zhu & Maoliang Bu & Jun Bi & Michael B. McElroy, 2019. "China’s CO2 peak before 2030 implied from characteristics and growth of cities," Nature Sustainability, Nature, vol. 2(8), pages 748-754, August.
    12. Joeri Rogelj & Alexander Popp & Katherine V. Calvin & Gunnar Luderer & Johannes Emmerling & David Gernaat & Shinichiro Fujimori & Jessica Strefler & Tomoko Hasegawa & Giacomo Marangoni & Volker Krey &, 2018. "Scenarios towards limiting global mean temperature increase below 1.5 °C," Nature Climate Change, Nature, vol. 8(4), pages 325-332, April.
    13. Zhang, Youguo, 2010. "Supply-side structural effect on carbon emissions in China," Energy Economics, Elsevier, vol. 32(1), pages 186-193, January.
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    Cited by:

    1. Tian, Ying & Pang, Jun, 2023. "What causes dynamic change of green technology progress: Convergence analysis based on industrial restructuring and environmental regulation," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 189-199.
    2. Ping Zhou & Hailing Li, 2022. "Carbon Emissions from Manufacturing Sector in Jiangsu Province: Regional Differences and Decomposition of Driving Factors," Sustainability, MDPI, vol. 14(15), pages 1-17, July.

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