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Decomposition Analysis and Trend Prediction of CO 2 Emissions in China’s Transportation Industry

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  • Ming Meng

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, Hebei, China)

  • Manyu Li

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, Hebei, China)

Abstract

China’s transportation industry has become one of the major industries with rapid growth in CO 2 emissions, which has a significant impact in controlling the increase of CO 2 emissions. Therefore, it is extremely necessary to use a hybrid trend extrapolation model to project the future carbon dioxide emissions of China. On account of the Intergovernmental Panel on Climate Change (IPCC) inventory method of carbon accounting, this paper applied the Logarithmic Mean Divisia Index (LMDI) model to study the factors affected by CO 2 emissions. The affected factors are further subdivided into the scale of employees, per capita carrying capacity, transport intensity, average transportation distance, energy input and output structure, energy intensity and industrial structure. The results are as follows: (1) Per capita carrying capacity is the most important factor to promote the growth of CO 2 emissions, while industrial structure is the main reason to inhibit the growth of CO 2 emissions; (2) the expansion of the number of employees has played a positive role in the growth of CO 2 emissions and the organization and technology management of the transportation industry should be strengthened; (3) comprehensive transportation development strategy can make the transportation intensity effect effectively reduce CO 2 emissions; (4) the CO 2 emissions of the transportation industry will continue to increase during 2018–2025, with a cumulative value of about 336.11 million tons. The purpose of this study is to provide scientific guidance for the government’s emission reduction measures in the transportation industry. In addition, there are still some deficiencies in the study of its influencing factors in this paper and further improvements are necessary for the subsequent research expansion.

Suggested Citation

  • Ming Meng & Manyu Li, 2020. "Decomposition Analysis and Trend Prediction of CO 2 Emissions in China’s Transportation Industry," Sustainability, MDPI, vol. 12(7), pages 1-20, March.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:2596-:d:336779
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    1. Achour, Houda & Belloumi, Mounir, 2016. "Decomposing the influencing factors of energy consumption in Tunisian transportation sector using the LMDI method," Transport Policy, Elsevier, vol. 52(C), pages 64-71.
    2. Yi Liang & Dongxiao Niu & Haichao Wang & Yan Li, 2017. "Factors Affecting Transportation Sector CO 2 Emissions Growth in China: An LMDI Decomposition Analysis," Sustainability, MDPI, vol. 9(10), pages 1-20, September.
    3. Jose Luis Osorio-Tejada & Eva Llera-Sastresa & Ahmad Hariza Hashim, 2018. "Well-to-Wheels Approach for the Environmental Impact Assessment of Road Freight Services," Sustainability, MDPI, vol. 10(12), pages 1-27, November.
    4. Feng, Y.Y. & Chen, S.Q. & Zhang, L.X., 2013. "System dynamics modeling for urban energy consumption and CO2 emissions: A case study of Beijing, China," Ecological Modelling, Elsevier, vol. 252(C), pages 44-52.
    5. Hoekstra, Rutger & van den Bergh, Jeroen C. J. M., 2003. "Comparing structural decomposition analysis and index," Energy Economics, Elsevier, vol. 25(1), pages 39-64, January.
    6. Meng, Ming & Shang, Wei & Zhao, Xiaoli & Niu, Dongxiao & Li, Wei, 2015. "Decomposition and forecasting analysis of China's energy efficiency: An application of three-dimensional decomposition and small-sample hybrid models," Energy, Elsevier, vol. 89(C), pages 283-293.
    7. Decai Tang & Tingyu Ma & Zhijiang Li & Jiexin Tang & Brandon J. Bethel, 2016. "Trend Prediction and Decomposed Driving Factors of Carbon Emissions in Jiangsu Province during 2015–2020," Sustainability, MDPI, vol. 8(10), pages 1-15, October.
    8. Zhu, Bangzhu & Su, Bin & Li, Yingzhu, 2018. "Input-output and structural decomposition analysis of India’s carbon emissions and intensity, 2007/08 – 2013/14," Applied Energy, Elsevier, vol. 230(C), pages 1545-1556.
    9. Timilsina, Govinda R. & Shrestha, Ashish, 2009. "Why have CO2 emissions increased in the transport sector in Asia ? underlying factors and policy options," Policy Research Working Paper Series 5098, The World Bank.
    10. 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.
    11. Fergus Green & Nicholas Stern, 2017. "China's changing economy: implications for its carbon dioxide emissions," Climate Policy, Taylor & Francis Journals, vol. 17(4), pages 423-442, May.
    12. Suyi Kim, 2019. "Decomposition Analysis of Greenhouse Gas Emissions in Korea’s Transportation Sector," Sustainability, MDPI, vol. 11(7), pages 1-16, April.
    13. Greening, Lorna A. & Ting, Mike & Davis, William B., 1999. "Decomposition of aggregate carbon intensity for freight: trends from 10 OECD countries for the period 1971-1993," Energy Economics, Elsevier, vol. 21(4), pages 331-361, August.
    14. Timilsina, Govinda R. & Shrestha, Ashish, 2009. "Transport sector CO2 emissions growth in Asia: Underlying factors and policy options," Energy Policy, Elsevier, vol. 37(11), pages 4523-4539, November.
    15. Changzheng Zhu & Dawei Gao, 2019. "A Research on the Factors Influencing Carbon Emission of Transportation Industry in “the Belt and Road Initiative” Countries Based on Panel Data," Energies, MDPI, vol. 12(12), pages 1-17, June.
    16. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    17. Ang, B. W. & Liu, F. L. & Chew, E. P., 2003. "Perfect decomposition techniques in energy and environmental analysis," Energy Policy, Elsevier, vol. 31(14), pages 1561-1566, November.
    18. 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.
    19. 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.
    20. Bi, Jun & Zhang, Rongrong & Wang, Haikun & Liu, Miaomiao & Wu, Yi, 2011. "The benchmarks of carbon emissions and policy implications for China's cities: Case of Nanjing," Energy Policy, Elsevier, vol. 39(9), pages 4785-4794, September.
    21. Shao, Shuai & Yang, Lili & Gan, Chunhui & Cao, Jianhua & Geng, Yong & Guan, Dabo, 2016. "Using an extended LMDI model to explore techno-economic drivers of energy-related industrial CO2 emission changes: A case study for Shanghai (China)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 516-536.
    22. Ang, B.W. & Huang, H.C. & Mu, A.R., 2009. "Properties and linkages of some index decomposition analysis methods," Energy Policy, Elsevier, vol. 37(11), pages 4624-4632, November.
    23. Meng, Ming & Niu, Dongxiao & Shang, Wei, 2014. "A small-sample hybrid model for forecasting energy-related CO2 emissions," Energy, Elsevier, vol. 64(C), pages 673-677.
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