IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i18p5742-d634013.html
   My bibliography  Save this article

Analysis of Influencing Factors of Carbon Emissions in China’s Logistics Industry: A GDIM-Based Indicator Decomposition

Author

Listed:
  • Changyou Zhang

    (School of Modern Post, Xi’an University of Posts & Telecommunications, Xi’an 710061, China)

  • Wenyu Zhang

    (School of Economics and Management, Xi’an University of Posts & Telecommunications, Xi’an 710061, China)

  • Weina Luo

    (School of Economics and Management, Xi’an University of Posts & Telecommunications, Xi’an 710061, China)

  • Xue Gao

    (School of Economics and Management, Xi’an University of Posts & Telecommunications, Xi’an 710061, China)

  • Bingchen Zhang

    (School of Economics and Management, Xi’an University of Posts & Telecommunications, Xi’an 710061, China)

Abstract

Due to increased global carbon dioxide emissions, the greenhouse effect is being aggravated, which has attracted wide attention. China is committed to promoting the low-carbon development of all industries. This paper analyzed the influencing factors of carbon emissions in the Chinese logistics industry, so as to identify the key factors that influence carbon emissions. Based on the carbon emission data of China’s logistics industry in 2000–2019, this paper applied the carbon emission coefficients issued by the Intergovernmental Panel on Climate Change. For the first time, the Generalized Divisia Index Method was used to analyze the degree of influence of the factors on carbon emissions. This method considered more variables and their relationships. The results showed that (1) the carbon emissions of the logistics industry were increased by 3.22 times from 2000 to 2018, and showed negative growth for the first time in 2019; (2) the added value of the logistics industry is the most important factor in increasing carbon emissions (with a contribution ratio of 65.45%), energy consumption and practical population size are the main factors in carbon emissions. The promotion of this industry is subjected to decreased per capita carbon emissions, which have a large impact on total carbon emissions; (3) the intensity of carbon output is the most important factor in the reduction of carbon emissions (with a contribution ratio of −29.1%), where the energy carbon intensity and per capita added value are the main influencing factors with regard to the reduction of carbon emissions, while energy intensity has a negative inhibitory effect on carbon emissions, and (4) the influencing factors have negative effects on the cumulative inhibition of carbon emissions in the logistics industry, to an extent that is far less than the integral promotion of carbon emissions. Finally, according to the research conclusions of this paper, it is feasible to make recommendations for the carbon reduction of the logistics industry.

Suggested Citation

  • Changyou Zhang & Wenyu Zhang & Weina Luo & Xue Gao & Bingchen Zhang, 2021. "Analysis of Influencing Factors of Carbon Emissions in China’s Logistics Industry: A GDIM-Based Indicator Decomposition," Energies, MDPI, vol. 14(18), pages 1-23, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5742-:d:634013
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/18/5742/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/18/5742/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Vaninsky, Alexander, 2014. "Factorial decomposition of CO2 emissions: A generalized Divisia index approach," Energy Economics, Elsevier, vol. 45(C), pages 389-400.
    2. Jianda Wang & Xiucheng Dong & Kangyin Dong, 2021. "How renewable energy reduces CO2 emissions? Decoupling and decomposition analysis for 25 countries along the Belt and Road," Applied Economics, Taylor & Francis Journals, vol. 53(40), pages 4597-4613, August.
    3. Paul Tae-Woo Lee & Oh Kyoung Kwon & Xiao Ruan, 2019. "Sustainability Challenges in Maritime Transport and Logistics Industry and Its Way Ahead," Sustainability, MDPI, vol. 11(5), pages 1-9, March.
    4. Ang, B.W., 1995. "Decomposition methodology in industrial energy demand analysis," Energy, Elsevier, vol. 20(11), pages 1081-1095.
    5. Qiucheng Li & Jiang Hu & Bolin Yu, 2021. "Spatiotemporal Patterns and Influencing Mechanism of Urban Residential Energy Consumption in China," Energies, MDPI, vol. 14(13), pages 1-17, June.
    6. Changzheng Zhu & Meng Wang & Yarong Yang, 2020. "Analysis of the Influencing Factors of Regional Carbon Emissions in the Chinese Transportation Industry," Energies, MDPI, vol. 13(5), pages 1-20, March.
    7. Shiqing Zhang & Jianwei Wang & Wenlong Zheng, 2018. "Decomposition Analysis of Energy-Related CO 2 Emissions and Decoupling Status in China’s Logistics Industry," Sustainability, MDPI, vol. 10(5), pages 1-21, April.
    8. Hatzigeorgiou, Emmanouil & Polatidis, Heracles & Haralambopoulos, Dias, 2008. "CO2 emissions in Greece for 1990–2002: A decomposition analysis and comparison of results using the Arithmetic Mean Divisia Index and Logarithmic Mean Divisia Index techniques," Energy, Elsevier, vol. 33(3), pages 492-499.
    9. Duan, Hongbo & Mo, Jianlei & Fan, Ying & Wang, Shouyang, 2018. "Achieving China's energy and climate policy targets in 2030 under multiple uncertainties," LSE Research Online Documents on Economics 86481, London School of Economics and Political Science, LSE Library.
    10. 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.
    11. Yong Wang & Yu Zhou & Lin Zhu & Fei Zhang & Yingchun Zhang, 2018. "Influencing Factors and Decoupling Elasticity of China’s Transportation Carbon Emissions," Energies, MDPI, vol. 11(5), pages 1-29, May.
    12. Lin, Boqiang & Sun, Chuanwang, 2010. "Evaluating carbon dioxide emissions in international trade of China," Energy Policy, Elsevier, vol. 38(1), pages 613-621, January.
    13. Duan, Hongbo & Mo, Jianlei & Fan, Ying & Wang, Shouyang, 2018. "Achieving China's energy and climate policy targets in 2030 under multiple uncertainties," Energy Economics, Elsevier, vol. 70(C), pages 45-60.
    14. Ang, B.W. & Zhang, F.Q., 2000. "A survey of index decomposition analysis in energy and environmental studies," Energy, Elsevier, vol. 25(12), pages 1149-1176.
    15. Zhao, Min & Tan, Lirong & Zhang, Weiguo & Ji, Minhe & Liu, Yuan & Yu, Lizhong, 2010. "Decomposing the influencing factors of industrial carbon emissions in Shanghai using the LMDI method," Energy, Elsevier, vol. 35(6), pages 2505-2510.
    16. Dong, Kangyin & Hochman, Gal & Timilsina, Govinda R., 2020. "Do drivers of CO2 emission growth alter overtime and by the stage of economic development?," Energy Policy, Elsevier, vol. 140(C).
    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. Wang, Jianda & Dong, Kangyin & Wang, Kun, 2023. "Towards green recovery: Platform economy and its impact on carbon emissions in China," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 969-987.
    2. Wei Fan & Xi Luo & Jiabei Yu & Yiyang Dai, 2021. "An Empirical Study of Carbon Emission Impact Factors Based on the Vector Autoregression Model," Energies, MDPI, vol. 14(22), pages 1-17, November.
    3. Wu, Zhonghuan & Duan, Chunlin & Cui, Yuting & Qin, Rong, 2023. "Consumers' attitudes toward low-carbon consumption based on a computational model: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    4. Yuntao Bai & Yuan Gao & Delong Li & Dehai Liu, 2022. "Coordinated Distribution or Client Introduce? Analysis of Energy Conservation and Emission Reduction in Canadian Logistics Enterprises," Sustainability, MDPI, vol. 14(24), pages 1-14, December.
    5. Shiqing Zhang & Yaping Li & Zheng Liu & Xiaofei Kou & Wenlong Zheng, 2023. "Towards a Decoupling between Economic Expansion and Carbon Dioxide Emissions of the Transport Sector in the Yellow River Basin," Sustainability, MDPI, vol. 15(5), pages 1-26, February.
    6. Yanming Sun & Shixian Liu & Lei Li, 2022. "Grey Correlation Analysis of Transportation Carbon Emissions under the Background of Carbon Peak and Carbon Neutrality," Energies, MDPI, vol. 15(9), pages 1-24, April.
    7. Caifen Xu & Yu Zhang & Yangmeina Yang & Huiying Gao, 2023. "Carbon Peak Scenario Simulation of Manufacturing Carbon Emissions in Northeast China: Perspective of Structure Optimization," Energies, MDPI, vol. 16(13), pages 1-31, July.
    8. Juan Li & Qinmei Wang, 2022. "Impact of the Digital Economy on the Carbon Emissions of China’s Logistics Industry," Sustainability, MDPI, vol. 14(14), pages 1-18, July.

    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. Fernández González, P. & Presno, M.J. & Landajo, M., 2015. "Regional and sectoral attribution to percentage changes in the European Divisia carbonization index," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1437-1452.
    2. Fernández González, P. & Landajo, M. & Presno, M.J., 2014. "Tracking European Union CO2 emissions through LMDI (logarithmic-mean Divisia index) decomposition. The activity revaluation approach," Energy, Elsevier, vol. 73(C), pages 741-750.
    3. Xu, X.Y. & Ang, B.W., 2013. "Index decomposition analysis applied to CO2 emission studies," Ecological Economics, Elsevier, vol. 93(C), pages 313-329.
    4. Fernández González, P., 2015. "Exploring energy efficiency in several European countries. An attribution analysis of the Divisia structural change index," Applied Energy, Elsevier, vol. 137(C), pages 364-374.
    5. Fernández González, P. & Landajo, M. & Presno, M.J., 2013. "The Divisia real energy intensity indices: Evolution and attribution of percent changes in 20 European countries from 1995 to 2010," Energy, Elsevier, vol. 58(C), pages 340-349.
    6. Robaina, Margarita & Neves, Ana, 2021. "Complete decomposition analysis of CO2 emissions intensity in the transport sector in Europe," Research in Transportation Economics, Elsevier, vol. 90(C).
    7. Lin, Boqiang & Ouyang, Xiaoling, 2014. "Analysis of energy-related CO2 (carbon dioxide) emissions and reduction potential in the Chinese non-metallic mineral products industry," Energy, Elsevier, vol. 68(C), pages 688-697.
    8. Zhang, Wei & Li, Ke & Zhou, Dequn & Zhang, Wenrui & Gao, Hui, 2016. "Decomposition of intensity of energy-related CO2 emission in Chinese provinces using the LMDI method," Energy Policy, Elsevier, vol. 92(C), pages 369-381.
    9. Jian Liu & Qingshan Yang & Yu Zhang & Wen Sun & Yiming Xu, 2019. "Analysis of CO 2 Emissions in China’s Manufacturing Industry Based on Extended Logarithmic Mean Division Index Decomposition," Sustainability, MDPI, vol. 11(1), pages 1-28, January.
    10. Ke Liu & Xinyue Xie & Mingxue Zhao & Qian Zhou, 2022. "Carbon Emissions in the Yellow River Basin: Analysis of Spatiotemporal Evolution Characteristics and Influencing Factors Based on a Logarithmic Mean Divisia Index (LMDI) Decomposition Method," Sustainability, MDPI, vol. 14(15), pages 1-18, August.
    11. Vaninsky, Alexander, 2014. "Factorial decomposition of CO2 emissions: A generalized Divisia index approach," Energy Economics, Elsevier, vol. 45(C), pages 389-400.
    12. Yong Wang & Yu Zhou & Lin Zhu & Fei Zhang & Yingchun Zhang, 2018. "Influencing Factors and Decoupling Elasticity of China’s Transportation Carbon Emissions," Energies, MDPI, vol. 11(5), pages 1-29, May.
    13. Linwei Ma & Chinhao Chong & Xi Zhang & Pei Liu & Weiqi Li & Zheng Li & Weidou Ni, 2018. "LMDI Decomposition of Energy-Related CO 2 Emissions Based on Energy and CO 2 Allocation Sankey Diagrams: The Method and an Application to China," Sustainability, MDPI, vol. 10(2), pages 1-37, January.
    14. Liu, Zhu & Liang, Sai & Geng, Yong & Xue, Bing & Xi, Fengming & Pan, Ying & Zhang, Tianzhu & Fujita, Tsuyoshi, 2012. "Features, trajectories and driving forces for energy-related GHG emissions from Chinese mega cites: The case of Beijing, Tianjin, Shanghai and Chongqing," Energy, Elsevier, vol. 37(1), pages 245-254.
    15. Patiño, Lourdes Isabel & Alcántara, Vicent & Padilla, Emilio, 2021. "Driving forces of CO2 emissions and energy intensity in Colombia," Energy Policy, Elsevier, vol. 151(C).
    16. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2015. "Driving factors behind carbon dioxide emissions in China: A modified production-theoretical decomposition analysis," Energy Economics, Elsevier, vol. 51(C), pages 252-260.
    17. Rina Wu & Jiquan Zhang & Yuhai Bao & Quan Lai & Siqin Tong & Youtao Song, 2016. "Decomposing the Influencing Factors of Industrial Sector Carbon Dioxide Emissions in Inner Mongolia Based on the LMDI Method," Sustainability, MDPI, vol. 8(7), pages 1-14, July.
    18. Jieting Yin & Chaowei Huang, 2022. "Analysis on Influencing Factors Decomposition and Decoupling Effect of Power Carbon Emissions in Yangtze River Economic Belt," Sustainability, MDPI, vol. 14(22), pages 1-26, November.
    19. Cheng, Shulei & Wang, Ping & Chen, Boyang & Fan, Wei, 2022. "Decoupling and decomposition analysis of CO2 emissions from government spending in China," Energy, Elsevier, vol. 243(C).
    20. Kang, Jidong & Zhao, Tao & Liu, Nan & Zhang, Xin & Xu, Xianshuo & Lin, Tao, 2014. "A multi-sectoral decomposition analysis of city-level greenhouse gas emissions: Case study of Tianjin, China," Energy, Elsevier, vol. 68(C), pages 562-571.

    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:jeners:v:14:y:2021:i:18:p:5742-:d:634013. 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.