IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i1p226-d194960.html
   My bibliography  Save this article

Analysis of CO 2 Emissions in China’s Manufacturing Industry Based on Extended Logarithmic Mean Division Index Decomposition

Author

Listed:
  • Jian Liu

    (School of Geographical Science, Northeast Normal University, Changchun 130024, China)

  • Qingshan Yang

    (School of Geographical Science, Northeast Normal University, Changchun 130024, China)

  • Yu Zhang

    (School of Geographical Science, Northeast Normal University, Changchun 130024, China)

  • Wen Sun

    (School of Geographical Science, Northeast Normal University, Changchun 130024, China)

  • Yiming Xu

    (School of Geographical Science, Northeast Normal University, Changchun 130024, China)

Abstract

China is the world’s largest emitter of CO 2 . As the largest sector of China’s fossil energy consumption and carbon emissions, manufacturing plays an important role in achieving emission reduction targets in China. Using the extended logarithmic mean division index (LMDI) decomposition model, this paper decomposed the factors that affect the CO 2 emissions of China’s manufacturing industry into eight effects. The results show the following: (1) China’s manufacturing CO 2 emissions increased from 1.91 billion tons in 1995 to 6.25 billion tons in 2015, with an average annual growth rate of 6%. Ferrous metal smelting and rolling were the largest sources of carbon dioxide emissions, followed by chemical raw materials and products and then non-metallic minerals. (2) During the research period, the industrial activity effects were the most important factor leading to increased CO 2 emissions in manufacturing and energy intensity was the most important factor in promoting the reduction of CO 2 emissions from manufacturing. The investment intensity was the second most influential factor leading to the increase in China’s manufacturing CO 2 emissions after the industrial scale and this even exceeded the industrial activity effect in some time periods (2000–2005). R&D efficiency and R&D intensity were shown to have significant roles in reducing CO 2 emissions in China’s manufacturing industry. The input of R&D innovation factors is an effective way to achieve emission reductions in China’s manufacturing industry. (3) There were differences in the driving factors of CO 2 emissions in the manufacturing industry in different periods that were closely related to the international and domestic economic development environment and the relevant policies of the Chinese government regarding energy conservation and emission reduction. (4) Sub-sector research found that the factors that affect the reduction of CO 2 emissions in various industries appear to be differentiated. This paper has important policy significance to allow the Chinese government to implement effective energy-saving and emission reduction measures and to reduce CO 2 emissions from the manufacturing industry.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:1:p:226-:d:194960
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/1/226/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/1/226/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Ang, B. W. & Pandiyan, G., 1997. "Decomposition of energy-induced CO2 emissions in manufacturing," Energy Economics, Elsevier, vol. 19(3), pages 363-374, July.
    3. Schipper, Lee & Murtishaw, Scott & Khrushch, Marta & Ting, Michael & Karbuz, Sohbet & Unander, Fridtjof, 2001. "Carbon emissions from manufacturing energy use in 13 IEA countries: long-term trends through 1995," Energy Policy, Elsevier, vol. 29(9), pages 667-688, July.
    4. Wenxiu Wang & Yaoqiu Kuang & Ningsheng Huang, 2011. "Study on the Decomposition of Factors Affecting Energy-Related Carbon Emissions in Guangdong Province, China," Energies, MDPI, vol. 4(12), pages 1-24, December.
    5. Salim, Ruhul A. & Shafiei, Sahar, 2014. "Urbanization and renewable and non-renewable energy consumption in OECD countries: An empirical analysis," Economic Modelling, Elsevier, vol. 38(C), pages 581-591.
    6. Vaninsky, Alexander, 2014. "Factorial decomposition of CO2 emissions: A generalized Divisia index approach," Energy Economics, Elsevier, vol. 45(C), pages 389-400.
    7. Cosimo Magazzino, 2014. "A Panel VAR Approach of the Relationship among Economic Growth, CO2 Emissions, and Energy Use in the ASEAN-6 Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 4(4), pages 546-553.
    8. Oludolapo A Olanrewaju, 2018. "Energy consumption in South African industry: A decomposition analysis using the LMDI approach," Energy & Environment, , vol. 29(2), pages 232-244, March.
    9. Hammond, G.P. & Norman, J.B., 2012. "Decomposition analysis of energy-related carbon emissions from UK manufacturing," Energy, Elsevier, vol. 41(1), pages 220-227.
    10. Suyi Kim, 2017. "LMDI Decomposition Analysis of Energy Consumption in the Korean Manufacturing Sector," Sustainability, MDPI, vol. 9(2), pages 1-17, February.
    11. Lin, Boqiang & Moubarak, Mohamed, 2013. "Decomposition analysis: Change of carbon dioxide emissions in the Chinese textile industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 389-396.
    12. Erik Dietzenbacher & Jesper Stage, 2006. "Mixing oil and water? Using hybrid input-output tables in a Structural decomposition analysis," Economic Systems Research, Taylor & Francis Journals, vol. 18(1), pages 85-95.
    13. 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.
    14. Liu, Lan-Cui & Fan, Ying & Wu, Gang & Wei, Yi-Ming, 2007. "Using LMDI method to analyze the change of China's industrial CO2 emissions from final fuel use: An empirical analysis," Energy Policy, Elsevier, vol. 35(11), pages 5892-5900, November.
    15. Mingxiang Deng & Wei Li & Yan Hu, 2016. "Decomposing Industrial Energy-Related CO 2 Emissions in Yunnan Province, China: Switching to Low-Carbon Economic Growth," Energies, MDPI, vol. 9(1), pages 1-19, January.
    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. Yang, Shenglang & Shi, Xunpeng, 2018. "Intangible capital and sectoral energy intensity: Evidence from 40 economies between 1995 and 2007," Energy Policy, Elsevier, vol. 122(C), pages 118-128.
    18. Xie, Xuan & Shao, Shuai & Lin, Boqiang, 2016. "Exploring the driving forces and mitigation pathways of CO2 emissions in China’s petroleum refining and coking industry: 1995–2031," Applied Energy, Elsevier, vol. 184(C), pages 1004-1015.
    19. Albrecht, Johan & Francois, Delphine & Schoors, Koen, 2002. "A Shapley decomposition of carbon emissions without residuals," Energy Policy, Elsevier, vol. 30(9), pages 727-736, July.
    20. 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.
    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. & Zhang, F.Q., 2000. "A survey of index decomposition analysis in energy and environmental studies," Energy, Elsevier, vol. 25(12), pages 1149-1176.
    23. Chung, William & Zhou, Guanghui & Yeung, Iris M.H., 2013. "A study of energy efficiency of transport sector in China from 2003 to 2009," Applied Energy, Elsevier, vol. 112(C), pages 1066-1077.
    24. Ang, B.W. & Liu, Na, 2007. "Negative-value problems of the logarithmic mean Divisia index decomposition approach," Energy Policy, Elsevier, vol. 35(1), pages 739-742, January.
    25. 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.
    26. 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.
    27. Yeongjun Yeo & Dongnyok Shim & Jeong-Dong Lee & Jörn Altmann, 2015. "Driving Forces of CO 2 Emissions in Emerging Countries: LMDI Decomposition Analysis on China and India’s Residential Sector," Sustainability, MDPI, vol. 7(12), pages 1-22, December.
    28. Shafiei, Sahar & Salim, Ruhul A., 2014. "Non-renewable and renewable energy consumption and CO2 emissions in OECD countries: A comparative analysis," Energy Policy, Elsevier, vol. 66(C), pages 547-556.
    29. 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.
    30. Fei Wang & Changjian Wang & Yongxian Su & Lixia Jin & Yang Wang & Xinlin Zhang, 2017. "Decomposition Analysis of Carbon Emission Factors from Energy Consumption in Guangdong Province from 1990 to 2014," Sustainability, MDPI, vol. 9(2), pages 1-15, February.
    31. Xu, Bin & Lin, Boqiang, 2016. "Assessing CO2 emissions in China’s iron and steel industry: A dynamic vector autoregression model," Applied Energy, Elsevier, vol. 161(C), pages 375-386.
    32. Jeong, Kyonghwa & Kim, Suyi, 2013. "LMDI decomposition analysis of greenhouse gas emissions in the Korean manufacturing sector," Energy Policy, Elsevier, vol. 62(C), pages 1245-1253.
    33. Zhe Wang & Lin Zhao & Guozhu Mao & Ben Wu, 2015. "Factor Decomposition Analysis of Energy-Related CO 2 Emissions in Tianjin, China," Sustainability, MDPI, vol. 7(8), pages 1-16, July.
    34. Yujiao Xian & Ke Wang & Xunpeng Shi & Chi Zhang & Yi-Ming Wei & Zhimin Huang, 2018. "Carbon emissions intensity reduction target for China¡¯s power industry: An efficiency and productivity perspective," CEEP-BIT Working Papers 117, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    35. 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.
    36. Jie-Fang Dong & Chun Deng & Xing-Min Wang & Xiao-Lei Zhang, 2016. "Multilevel Index Decomposition of Energy-Related Carbon Emissions and Their Decoupling from Economic Growth in Northwest China," Energies, MDPI, vol. 9(9), pages 1-17, August.
    37. Sheinbaum, Claudia & Ozawa, Leticia & Castillo, Daniel, 2010. "Using logarithmic mean Divisia index to analyze changes in energy use and carbon dioxide emissions in Mexico's iron and steel industry," Energy Economics, Elsevier, vol. 32(6), pages 1337-1344, November.
    38. Zhang, Ming & Mu, Hailin & Ning, Yadong & Song, Yongchen, 2009. "Decomposition of energy-related CO2 emission over 1991-2006 in China," Ecological Economics, Elsevier, vol. 68(7), pages 2122-2128, May.
    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. Khurshid, Adnan & Khan, Khalid & Cifuentes-Faura, Javier & Chen, Yufeng, 2024. "Asymmetric multifractality: Comparative efficiency analysis of global technological and renewable energy prices using MFDFA and A-MFDFA approaches," Energy, Elsevier, vol. 289(C).
    2. Liu, Jian & Yang, Qingshan & Ou, Suhua & Liu, Jie, 2022. "Factor decomposition and the decoupling effect of carbon emissions in China's manufacturing high-emission subsectors," Energy, Elsevier, vol. 248(C).
    3. 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.

    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. 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.
    2. 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.
    3. 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.
    4. Wang, Miao & Feng, Chao, 2018. "Decomposing the change in energy consumption in China's nonferrous metal industry: An empirical analysis based on the LMDI method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2652-2663.
    5. 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.
    6. 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.
    7. Román-Collado, Rocío & Cansino, José M. & Botia, Camilo, 2018. "How far is Colombia from decoupling? Two-level decomposition analysis of energy consumption changes," Energy, Elsevier, vol. 148(C), pages 687-700.
    8. Xu, X.Y. & Ang, B.W., 2013. "Index decomposition analysis applied to CO2 emission studies," Ecological Economics, Elsevier, vol. 93(C), pages 313-329.
    9. Rui Jiang & Rongrong Li & Qiuhong Wu, 2019. "Investigation for the Decomposition of Carbon Emissions in the USA with C-D Function and LMDI Methods," Sustainability, MDPI, vol. 11(2), pages 1-15, January.
    10. Wang, Miao & Feng, Chao, 2017. "Analysis of energy-related CO2 emissions in China’s mining industry: Evidence and policy implications," Resources Policy, Elsevier, vol. 53(C), pages 77-87.
    11. Lin, Boqiang & Tan, Ruipeng, 2017. "Sustainable development of China's energy intensive industries: From the aspect of carbon dioxide emissions reduction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 386-394.
    12. 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.
    13. Vaninsky, Alexander, 2014. "Factorial decomposition of CO2 emissions: A generalized Divisia index approach," Energy Economics, Elsevier, vol. 45(C), pages 389-400.
    14. Wen, Hong-xing & Chen, Zhe & Yang, Qian & Liu, Jin-yi & Nie, Pu-yan, 2022. "Driving forces and mitigating strategies of CO2 emissions in China: A decomposition analysis based on 38 industrial sub-sectors," Energy, Elsevier, vol. 245(C).
    15. 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.
    16. Wang, Miao & Feng, Chao, 2017. "Decomposition of energy-related CO2 emissions in China: An empirical analysis based on provincial panel data of three sectors," Applied Energy, Elsevier, vol. 190(C), pages 772-787.
    17. Jialing Zou & Weidong Liu & Zhipeng Tang, 2017. "Analysis of Factors Contributing to Changes in Energy Consumption in Tangshan City between 2007 and 2012," Sustainability, MDPI, vol. 9(3), pages 1-14, March.
    18. Jia, Hongxiang & Li, Tianjiao & Wang, Anjian & Liu, Guwang & Guo, Xiaoqian, 2021. "Decoupling analysis of economic growth and mineral resources consumption in China from 1992 to 2017: A comparison between tonnage and exergy perspective," Resources Policy, Elsevier, vol. 74(C).
    19. Lei Liu & Ke Wang & Shanshan Wang & Ruiqin Zhang & Xiaoyan Tang, 2019. "Exploring the Driving Forces and Reduction Potential of Industrial Energy-Related CO 2 Emissions during 2001–2030: A Case Study for Henan Province, China," Sustainability, MDPI, vol. 11(4), pages 1-25, February.
    20. Yu, Shiwei & Wei, Yi-Ming & Wang, Ke, 2014. "Provincial allocation of carbon emission reduction targets in China: An approach based on improved fuzzy cluster and Shapley value decomposition," Energy Policy, Elsevier, vol. 66(C), pages 630-644.

    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:11:y:2019:i:1:p:226-:d:194960. 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.