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Driving forces of CO2 emissions from the transport, storage and postal sectors: A pathway to achieving carbon neutrality

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  • Shang, Wen-Long
  • Ling, Yantao
  • Ochieng, Washington
  • Yang, Linchuan
  • Gao, Xing
  • Ren, Qingzhong
  • Chen, Yilin
  • Cao, Mengqiu

Abstract

In tandem with the urbanisation process, China's transport sector is currently experiencing rapid development and was ranked third out of all the industrial sectors in terms of generating CO2 emissions in 2020, which poses a huge challenge to achieving carbon neutrality. Primarily using the energy consumption data from China's transport, storage and postal sectors (TSPS) and input and output data between 2007 and 2020, this study first uses the Tapio decoupling model to evaluate the decoupling effect in the TSPS. Structural decomposition analysis is then applied to explore sectoral linkages and decompose the forces driving CO2 emissions. Additionally, we explore the main determinants of the energy structure effect and final demand in terms of energy consumption and industrial sector demand. Our results show that the target sector experienced a weak decoupling, which implies that the low-carbon transformation of this sector became increasingly apparent. Factor decomposition shows that improvements in energy intensity, energy structure and the production input and output structure have contributed significantly to reducing CO2 emissions, but these gains have been largely offset by final demand, resulting in a net reduction of 27.97 million tons from 2007 to 2020. The increased usage of low carbon forms of energy, such as natural gas, is the key driver behind the emissions reduction effect in terms of the energy structure. However, the higher final demand from the construction sector and the wholesale and retail trades are the main factors that have increased CO2 emissions. By adopting a sectoral and energy structure decomposition perspective, our study can be used to provide guidance to governments seeking to pursue carbon-reduction policies to achieve carbon peak and carbon neutrality, in the TSPS in particular.

Suggested Citation

  • Shang, Wen-Long & Ling, Yantao & Ochieng, Washington & Yang, Linchuan & Gao, Xing & Ren, Qingzhong & Chen, Yilin & Cao, Mengqiu, 2024. "Driving forces of CO2 emissions from the transport, storage and postal sectors: A pathway to achieving carbon neutrality," Applied Energy, Elsevier, vol. 365(C).
  • Handle: RePEc:eee:appene:v:365:y:2024:i:c:s0306261924006093
    DOI: 10.1016/j.apenergy.2024.123226
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    as
    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. & Li, Yingzhu, 2017. "Input-output and structural decomposition analysis of Singapore's carbon emissions," Energy Policy, Elsevier, vol. 105(C), pages 484-492.
    3. Das, Aparna & Paul, Saikat Kumar, 2014. "CO2 emissions from household consumption in India between 1993–94 and 2006–07: A decomposition analysis," Energy Economics, Elsevier, vol. 41(C), pages 90-105.
    4. Tian, Xin & Chang, Miao & Lin, Chen & Tanikawa, Hiroki, 2014. "China’s carbon footprint: A regional perspective on the effect of transitions in consumption and production patterns," Applied Energy, Elsevier, vol. 123(C), pages 19-28.
    5. He, He & Reynolds, Christian John & Li, Linyang & Boland, John, 2019. "Assessing net energy consumption of Australian economy from 2004–05 to 2014–15: Environmentally-extended input-output analysis, structural decomposition analysis, and linkage analysis," Applied Energy, Elsevier, vol. 240(C), pages 766-777.
    6. Li, Jia Shuo & Zhou, H.W. & Meng, Jing & Yang, Q. & Chen, B. & Zhang, Y.Y., 2018. "Carbon emissions and their drivers for a typical urban economy from multiple perspectives: A case analysis for Beijing city," Applied Energy, Elsevier, vol. 226(C), pages 1076-1086.
    7. Erik Dietzenbacher & Bart Los, 1998. "Structural Decomposition Techniques: Sense and Sensitivity," Economic Systems Research, Taylor & Francis Journals, vol. 10(4), pages 307-324.
    8. Smriti Mallapaty, 2020. "How China could be carbon neutral by mid-century," Nature, Nature, vol. 586(7830), pages 482-483, October.
    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. Sun, J. W., 1998. "Changes in energy consumption and energy intensity: A complete decomposition model," Energy Economics, Elsevier, vol. 20(1), pages 85-100, February.
    11. Pan, Xunzhang & Wang, Hailin & Wang, Lining & Chen, Wenying, 2018. "Decarbonization of China's transportation sector: In light of national mitigation toward the Paris Agreement goals," Energy, Elsevier, vol. 155(C), pages 853-864.
    12. Bin Su & B. W. Ang, 2012. "Structural Decomposition Analysis Applied To Energy And Emissions: Aggregation Issues," Economic Systems Research, Taylor & Francis Journals, vol. 24(3), pages 299-317, March.
    13. Rutger Hoekstra & Jeroen van den Bergh, 2002. "Structural Decomposition Analysis of Physical Flows in the Economy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(3), pages 357-378, November.
    14. Lan, Jun & Malik, Arunima & Lenzen, Manfred & McBain, Darian & Kanemoto, Keiichiro, 2016. "A structural decomposition analysis of global energy footprints," Applied Energy, Elsevier, vol. 163(C), pages 436-451.
    15. Wang, W.W. & Zhang, M. & Zhou, M., 2011. "Using LMDI method to analyze transport sector CO2 emissions in China," Energy, Elsevier, vol. 36(10), pages 5909-5915.
    16. Mi, Zhifu & Zheng, Jiali & Meng, Jing & Zheng, Heran & Li, Xian & Coffman, D'Maris & Woltjer, Johan & Wang, Shouyang & Guan, Dabo, 2019. "Carbon emissions of cities from a consumption-based perspective," Applied Energy, Elsevier, vol. 235(C), pages 509-518.
    17. Yuan, Baolong & Ren, Shenggang & Chen, Xiaohong, 2015. "The effects of urbanization, consumption ratio and consumption structure on residential indirect CO2 emissions in China: A regional comparative analysis," Applied Energy, Elsevier, vol. 140(C), pages 94-106.
    18. Liu, Zheng & Huang, Yu-Qing & Shang, Wen-Long & Zhao, Yuan-Jun & Yang, Zao-Li & Zhao, Zhao, 2022. "Precooling energy and carbon emission reduction technology investment model in a fresh food cold chain based on a differential game," Applied Energy, Elsevier, vol. 326(C).
    19. Cao, Shuyan & Xie, Gaodi & Zhen, Lin, 2010. "Total embodied energy requirements and its decomposition in China's agricultural sector," Ecological Economics, Elsevier, vol. 69(7), pages 1396-1404, May.
    20. Su, Bin & Ang, B.W., 2012. "Structural decomposition analysis applied to energy and emissions: Some methodological developments," Energy Economics, Elsevier, vol. 34(1), pages 177-188.
    21. Wang, H. & Ang, B.W., 2018. "Assessing the role of international trade in global CO2 emissions: An index decomposition analysis approach," Applied Energy, Elsevier, vol. 218(C), pages 146-158.
    22. Geng, Yong & Zhao, Hongyan & Liu, Zhu & Xue, Bing & Fujita, Tsuyoshi & Xi, Fengming, 2013. "Exploring driving factors of energy-related CO2 emissions in Chinese provinces: A case of Liaoning," Energy Policy, Elsevier, vol. 60(C), pages 820-826.
    23. Wang, Yafei & Zhao, Hongyan & Li, Liying & Liu, Zhu & Liang, Sai, 2013. "Carbon dioxide emission drivers for a typical metropolis using input–output structural decomposition analysis," Energy Policy, Elsevier, vol. 58(C), pages 312-318.
    24. Du, Huibin & Chen, Zhenni & Peng, Binbin & Southworth, Frank & Ma, Shoufeng & Wang, Yuan, 2019. "What drives CO2 emissions from the transport sector? A linkage analysis," Energy, Elsevier, vol. 175(C), pages 195-204.
    25. Xiaoping Zhu & Rongrong Li, 2017. "An Analysis of Decoupling and Influencing Factors of Carbon Emissions from the Transportation Sector in the Beijing-Tianjin-Hebei Area, China," Sustainability, MDPI, vol. 9(5), pages 1-19, April.
    26. Hong, Jingke & Li, Clyde Zhengdao & Shen, Qiping & Xue, Fan & Sun, Bingxia & Zheng, Wei, 2017. "An Overview of the driving forces behind energy demand in China's construction industry: Evidence from 1990 to 2012," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 85-94.
    27. Henrik Jacobsen, 2000. "Energy Demand, Structural Change and Trade: A Decomposition Analysis of the Danish Manufacturing Industry," Economic Systems Research, Taylor & Francis Journals, vol. 12(3), pages 319-343.
    28. Helgesen, Per Ivar & Lind, Arne & Ivanova, Olga & Tomasgard, Asgeir, 2018. "Using a hybrid hard-linked model to analyze reduced climate gas emissions from transport," Energy, Elsevier, vol. 156(C), pages 196-212.
    29. Liang, Sai & Zhang, Tianzhu, 2011. "What is driving CO2 emissions in a typical manufacturing center of South China? The case of Jiangsu Province," Energy Policy, Elsevier, vol. 39(11), pages 7078-7083.
    30. Hu, Yi & Yin, Zhifeng & Ma, Jian & Du, Wencui & Liu, Danhe & Sun, Luxi, 2017. "Determinants of GHG emissions for a municipal economy: Structural decomposition analysis of Chongqing," Applied Energy, Elsevier, vol. 196(C), pages 162-169.
    31. Munksgaard, Jesper & Pedersen, Klaus Alsted & Wien, Mette, 2000. "Impact of household consumption on CO2 emissions," Energy Economics, Elsevier, vol. 22(4), pages 423-440, August.
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