IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i7p2596-d336779.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/7/2596/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/7/2596/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    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. 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.
    3. 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.
    4. Suyi Kim, 2019. "Decomposition Analysis of Greenhouse Gas Emissions in Korea’s Transportation Sector," Sustainability, MDPI, vol. 11(7), pages 1-16, April.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liping Zhu & Zhizhong Li & Xubiao Yang & Yili Zhang & Hui Li, 2022. "Forecast of Transportation CO 2 Emissions in Shanghai under Multiple Scenarios," Sustainability, MDPI, vol. 14(20), pages 1-18, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Manel Daldoul & Ahlem Dakhlaoui, 2018. "Using the LMDI Decomposition Approach to Analyze the Influencing Factors of Carbon Emissions in Tunisian Transportation Sector," International Journal of Energy Economics and Policy, Econjournals, vol. 8(6), pages 22-28.
    2. Liang, Wei & Gan, Ting & Zhang, Wei, 2019. "Dynamic evolution of characteristics and decomposition of factors influencing industrial carbon dioxide emissions in China: 1991–2015," Structural Change and Economic Dynamics, Elsevier, vol. 49(C), pages 93-106.
    3. Isik, Mine & Sarica, Kemal & Ari, Izzet, 2020. "Driving forces of Turkey's transportation sector CO2 emissions: An LMDI approach," Transport Policy, Elsevier, vol. 97(C), pages 210-219.
    4. Xue-Ting Jiang & Jie-Fang Dong & Xing-Min Wang & Rong-Rong Li, 2016. "The Multilevel Index Decomposition of Energy-Related Carbon Emission and Its Decoupling with Economic Growth in USA," Sustainability, MDPI, vol. 8(9), pages 1-16, August.
    5. Yang Yu & Qiuyue Kong, 2017. "Analysis on the influencing factors of carbon emissions from energy consumption in China based on LMDI method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 88(3), pages 1691-1707, September.
    6. Xu, X.Y. & Ang, B.W., 2013. "Index decomposition analysis applied to CO2 emission studies," Ecological Economics, Elsevier, vol. 93(C), pages 313-329.
    7. Wang, Miao & Feng, Chao, 2018. "Using an extended logarithmic mean Divisia index approach to assess the roles of economic factors on industrial CO2 emissions of China," Energy Economics, Elsevier, vol. 76(C), pages 101-114.
    8. Jialing Zou & Zhipeng Tang & Shuang Wu, 2019. "Divergent Leading Factors in Energy-Related CO 2 Emissions Change among Subregions of the Beijing–Tianjin–Hebei Area from 2006 to 2016: An Extended LMDI Analysis," Sustainability, MDPI, vol. 11(18), pages 1-17, September.
    9. Liu, Ningyin & Zhang, Yan & Fath, Brian D., 2021. "The material metabolism characteristics and growth patterns of the central cities of China's Beijing-Tianjin-Hebei region," Ecological Modelling, Elsevier, vol. 448(C).
    10. Wang, Miao & Feng, Chao, 2021. "The consequences of industrial restructuring, regional balanced development, and market-oriented reform for China's carbon dioxide emissions: A multi-tier meta-frontier DEA-based decomposition analysi," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
    11. Huang, Fei & Zhou, Dequn & Wang, Qunwei & Hang, Ye, 2019. "Decomposition and attribution analysis of the transport sector’s carbon dioxide intensity change in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 343-358.
    12. Cahill, Caiman J. & Ó Gallachóir, Brian P., 2012. "Combining physical and economic output data to analyse energy and CO2 emissions trends in industry," Energy Policy, Elsevier, vol. 49(C), pages 422-429.
    13. Sobrino, Natalia & Monzon, Andres, 2014. "The impact of the economic crisis and policy actions on GHG emissions from road transport in Spain," Energy Policy, Elsevier, vol. 74(C), pages 486-498.
    14. Tang, Chengcai & Zhong, Linsheng & Ng, Pin, 2017. "Factors that Influence the Tourism Industry's Carbon Emissions: a Tourism Area Life Cycle Model Perspective," Energy Policy, Elsevier, vol. 109(C), pages 704-718.
    15. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    16. Suyi Kim, 2019. "Decomposition Analysis of Greenhouse Gas Emissions in Korea’s Transportation Sector," Sustainability, MDPI, vol. 11(7), pages 1-16, April.
    17. Jiang, Jingjing & Ye, Bin & Xie, Dejun & Li, Ji & Miao, Lixin & Yang, Peng, 2017. "Sector decomposition of China’s national economic carbon emissions and its policy implication for national ETS development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 855-867.
    18. Li, Tianxiang & Baležentis, Tomas & Makutėnienė, Daiva & Streimikiene, Dalia & Kriščiukaitienė, Irena, 2016. "Energy-related CO2 emission in European Union agriculture: Driving forces and possibilities for reduction," Applied Energy, Elsevier, vol. 180(C), pages 682-694.
    19. Nishijima, Daisuke, 2017. "The role of technology, product lifetime, and energy efficiency in climate mitigation: A case study of air conditioners in Japan," Energy Policy, Elsevier, vol. 104(C), pages 340-347.
    20. Shigemi Kagawa & Yuriko Goto & Sangwon Suh & Keisuke Nansai & Yuki Kudoh, 2012. "Accounting for Changes in Automobile Gasoline Consumption in Japan: 2000–2007," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 1(1), pages 1-27, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:2596-:d:336779. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.