IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v8y2016i7p661-d73835.html
   My bibliography  Save this article

Decomposing the Influencing Factors of Industrial Sector Carbon Dioxide Emissions in Inner Mongolia Based on the LMDI Method

Author

Listed:
  • Rina Wu

    (College of Environment, Northeast Normal University, Changchun 130024, China)

  • Jiquan Zhang

    (College of Environment, Northeast Normal University, Changchun 130024, China)

  • Yuhai Bao

    (Inner Mongolia Key Laboratory of Remote Sensing and Geographic Information, Huhhot 010022, China
    College of Geographical Science, Inner Mongolia Normal University, Hohhot, Inner Mongolia 010020, China)

  • Quan Lai

    (College of Environment, Northeast Normal University, Changchun 130024, China
    Inner Mongolia Key Laboratory of Remote Sensing and Geographic Information, Huhhot 010022, China
    College of Geographical Science, Inner Mongolia Normal University, Hohhot, Inner Mongolia 010020, China)

  • Siqin Tong

    (College of Environment, Northeast Normal University, Changchun 130024, China)

  • Youtao Song

    (College of Environment, Liaoning University, Shenyang 110036, China)

Abstract

Understanding of the influencing factors of industrial sector carbon dioxide emissions is essential to reduce natural and anthropogenic greenhouse gas emissions. In this paper, we applied the Logarithmic Mean Divisia Index (LMDI) decomposition method based on the extended Kaya identity to analyze the changes in industrial carbon dioxide emissions resulting from 39 industrial sectors in Inner Mongolia northeast of China over the period 2003–2012. The factors were divided into five types of effects i.e., industrial growth effect, industrial structure effect, energy effect, energy intensity effect, population effect and comparative analysis of differential influences of various factors on industrial sector. Our results clearly show that (1) Industrial sector carbon dioxide emissions have increased from 134.00 million ton in 2003 to 513.46 million ton in 2012, with an annual average growth rate of 16.097%. The industrial carbon dioxide emissions intensity has decreased from 0.99 million ton/billion yuan to 0.28 million ton/billion yuan. Also, the energy structure has been dominated by coal; (2) Production and supply of electric power, steam and hot water, coal mining and dressing, smelting and pressing of ferrous metals, petroleum processing, coking and nuclear fuel processing, and raw chemical materials and chemical products account for 89.74% of total increased industrial carbon dioxide emissions; (3) The industrial growth effect and population effect are found to be a critical driving force for increasing industrial sector carbon dioxide emissions over the research period. The energy intensity effect is the crucial drivers of the decrease of carbon dioxide emissions. However, the energy structure effect and industrial structure effect have considerably varied over the study years without displaying any clear trend.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:7:p:661-:d:73835
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/8/7/661/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/8/7/661/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. R. Becker & Y. Wang, 2013. "Measuring the Chinese business cycle," Applied Economics, Taylor & Francis Journals, vol. 45(28), pages 3988-4003, October.
    3. Zhong Qin & Qiao Wang, 2013. "Tunneling and Monitoring in Chinese Share Market," Research in World Economy, Research in World Economy, Sciedu Press, vol. 4(2), pages 28-35, September.
    4. 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.
    5. Lise, Wietze, 2006. "Decomposition of CO2 emissions over 1980-2003 in Turkey," Energy Policy, Elsevier, vol. 34(14), pages 1841-1852, September.
    6. 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.
    7. Xu, X.Y. & Ang, B.W., 2013. "Index decomposition analysis applied to CO2 emission studies," Ecological Economics, Elsevier, vol. 93(C), pages 313-329.
    8. 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.
    9. 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.
    10. Zhang, Yue-Jun & Da, Ya-Bin, 2015. "The decomposition of energy-related carbon emission and its decoupling with economic growth in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1255-1266.
    11. Cellura, Maurizio & Longo, Sonia & Mistretta, Marina, 2012. "Application of the Structural Decomposition Analysis to assess the indirect energy consumption and air emission changes related to Italian households consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1135-1145.
    12. Changjian Wang & Fei Wang & Hongou Zhang & Yuyao Ye & Qitao Wu & Yongxian Su, 2014. "Carbon Emissions Decomposition and Environmental Mitigation Policy Recommendations for Sustainable Development in Shandong Province," Sustainability, MDPI, vol. 6(11), pages 1-16, November.
    13. Tijun Fan & Ruiling Luo & Haiyang Xia & Xiaopeng Li, 2015. "Using LMDI method to analyze the influencing factors of carbon emissions in China’s petrochemical industries," 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. 75(2), pages 319-332, February.
    14. Ang, B. W., 2005. "The LMDI approach to decomposition analysis: a practical guide," Energy Policy, Elsevier, vol. 33(7), pages 867-871, May.
    15. Ma, Chunbo & Stern, David I., 2008. "China's changing energy intensity trend: A decomposition analysis," Energy Economics, Elsevier, vol. 30(3), pages 1037-1053, May.
    16. 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.
    17. Fernández González, P. & Landajo, M. & Presno, M.J., 2014. "Multilevel LMDI decomposition of changes in aggregate energy consumption. A cross country analysis in the EU-27," Energy Policy, Elsevier, vol. 68(C), pages 576-584.
    18. 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.
    19. 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.
    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. 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.
    22. Fan He & Bijun Wang, 2013. "Chinese Interests in the Global Investment Regime," EABER Working Papers 23755, East Asian Bureau of Economic Research.
    23. 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.
    24. Elizabeth Xiao Wang & Joanna Tsai & Sandra Chan, 2013. "Merger Remedies with Chinese Characteristics," Antitrust Chronicle, Competition Policy International, vol. 8.
    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. 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.
    2. Zhiyuan Duan & Xian’en Wang & Xize Dong & Haiyan Duan & Junnian Song, 2020. "Peaking Industrial Energy-Related CO 2 Emissions in Typical Transformation Region: Paths and Mechanism," Sustainability, MDPI, vol. 12(3), pages 1-19, January.
    3. Shiming Liao & Dong Wang & Ting Ren & Xuemin Liu, 2022. "Heterogeneity and Decomposition Analysis of Manufacturing Carbon Dioxide Emissions in China’s Post-Industrial Innovative Megacity Shenzhen," IJERPH, MDPI, vol. 19(23), pages 1-19, November.
    4. Xiao Zhang & Meng Li & Qiao Li & Yanan Wang & Wei Chen, 2021. "Spatial Threshold Effect of Industrial Land Use Efficiency on Industrial Carbon Emissions: A Case Study in China," IJERPH, MDPI, vol. 18(17), pages 1-17, September.
    5. Teng Zhang & Yixuan Sun & Mei Guan & Jieming Kang & Baolei Zhang, 2022. "Human Activity Intensity in China under Multi-Factor Interactions: Spatiotemporal Characteristics and Influencing Factors," Sustainability, MDPI, vol. 14(5), pages 1-16, March.
    6. Chuyu Xia & Yan Li & Yanmei Ye & Zhou Shi & Jingming Liu, 2017. "Decomposed Driving Factors of Carbon Emissions and Scenario Analyses of Low-Carbon Transformation in 2020 and 2030 for Zhejiang Province," Energies, MDPI, vol. 10(11), pages 1-16, October.
    7. Huiru Zhao & Guo Huang & Ning Yan, 2018. "Forecasting Energy-Related CO 2 Emissions Employing a Novel SSA-LSSVM Model: Considering Structural Factors in China," Energies, MDPI, vol. 11(4), pages 1-21, March.
    8. 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.
    9. Zhaosu Meng & Huan Wang & Baona Wang, 2018. "Empirical Analysis of Carbon Emission Accounting and Influencing Factors of Energy Consumption in China," IJERPH, MDPI, vol. 15(11), pages 1-15, November.

    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. 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.
    2. 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.
    3. 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.
    4. 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.
    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. 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.
    7. Du, Kerui & Xie, Chunping & Ouyang, Xiaoling, 2017. "A comparison of carbon dioxide (CO2) emission trends among provinces in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 19-25.
    8. 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.
    9. 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.
    10. Duran, Elisa & Aravena, Claudia & Aguilar, Renato, 2015. "Analysis and decomposition of energy consumption in the Chilean industry," Energy Policy, Elsevier, vol. 86(C), pages 552-561.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Xinlin Zhang & Yuan Zhao & Qi Sun & Changjian Wang, 2017. "Decomposition and Attribution Analysis of Industrial Carbon Intensity Changes in Xinjiang, China," Sustainability, MDPI, vol. 9(3), pages 1-16, March.
    16. Xing Zhou & Meihua Zhou & Ming Zhang, 2016. "Contrastive analyses of the influence factors of interprovincial carbon emission induced by industry energy in China," 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. 81(3), pages 1405-1433, April.
    17. 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.
    18. 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.
    19. Edyta Sidorczuk-Pietraszko, 2020. "Spatial Differences in Carbon Intensity in Polish Households," Energies, MDPI, vol. 13(12), pages 1-21, June.
    20. Wang, H. & Ang, B.W. & Su, Bin, 2017. "Assessing drivers of economy-wide energy use and emissions: IDA versus SDA," Energy Policy, Elsevier, vol. 107(C), pages 585-599.

    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:8:y:2016:i:7:p:661-:d:73835. 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.