IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i17p6925-d404165.html
   My bibliography  Save this article

Implications of Energy Intensity Ratio for Carbon Dioxide Emissions in China

Author

Listed:
  • Jiabin Chen

    (Institute of Mineral Resources Economics, Chinese Academy of Natural Resources Economics, Beijing 101149, China
    Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources, Beijing 101149, China)

  • Shaobo Wen

    (Institute of Mineral Resources Economics, Chinese Academy of Natural Resources Economics, Beijing 101149, China
    Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources, Beijing 101149, China)

Abstract

Industrial carbon dioxide (CO 2 ) emissions are mainly derived from fossil energy use, which is composed of procedures involving extraction of energy from the natural system as well as its exchange and consumption in the social system. However, recent research on low-carbon transitions considers the cost of energy commodities from a separate perspective—a biophysical or monetary perspective. We introduce the energy intensity ratio (EIR), which is a novelty perspective combining biophysical and monetary metrics to estimate the cost of energy commodities in the low-carbon energy transitions. This combination is essential, since the feedback of energy into the biophysical system will influence the performance of energy in the economic system and vice versa. Based on the Logarithmic Mean Divisia Index (LMDI), we developed the EIR-LMDI method to explain the changes in CO 2 emissions. The changes in CO 2 emissions caused by the EIR are the net energy effect. In China, the net energy effect kept CO 2 emissions at a compound annual growth rate of 6.15% during 2007–2018. Especially after 2014, the net energy effect has been the largest driver of the increase in CO 2 emissions. During the study period, high net energy usually indicated high CO 2 emissions. Coal is the most important energy commodity and dominates the net energy effect; the least volatile component is the EIR of natural gas. The EIR affects CO 2 emissions by the price crowding-out effect and the scale expansion effect, which make the process of low-carbon transition uncertain. The results illuminate that policymakers should monitor the net energy effect to prevent it from offsetting efforts to reduce energy intensity.

Suggested Citation

  • Jiabin Chen & Shaobo Wen, 2020. "Implications of Energy Intensity Ratio for Carbon Dioxide Emissions in China," Sustainability, MDPI, vol. 12(17), pages 1-13, August.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:6925-:d:404165
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/17/6925/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/12/17/6925/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. King, Carey W., 2020. "An integrated biophysical and economic modeling framework for long-term sustainability analysis: the HARMONEY model," Ecological Economics, Elsevier, vol. 169(C).
    2. Ang, B.W., 2015. "LMDI decomposition approach: A guide for implementation," Energy Policy, Elsevier, vol. 86(C), pages 233-238.
    3. Cleveland, Cutler J. & Kaufmann, Robert K. & Stern, David I., 2000. "Aggregation and the role of energy in the economy," Ecological Economics, Elsevier, vol. 32(2), pages 301-317, February.
    4. 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.
    5. Kander, Astrid & Stern, David I., 2014. "Economic growth and the transition from traditional to modern energy in Sweden," Energy Economics, Elsevier, vol. 46(C), pages 56-65.
    6. Cleveland, Cutler J., 2005. "Net energy from the extraction of oil and gas in the United States," Energy, Elsevier, vol. 30(5), pages 769-782.
    7. Azadeh, A. & Amalnick, M.S. & Ghaderi, S.F. & Asadzadeh, S.M., 2007. "An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors," Energy Policy, Elsevier, vol. 35(7), pages 3792-3806, July.
    8. Liu, F. L. & Ang, B. W., 2003. "Eight methods for decomposing the aggregate energy-intensity of industry," Applied Energy, Elsevier, vol. 76(1-3), pages 15-23, September.
    9. Li, Guo & Zakari, Abdulrasheed & Tawiah, Vincent, 2020. "Energy resource melioration and CO2 emissions in China and Nigeria: Efficiency and trade perspectives," Resources Policy, Elsevier, vol. 68(C).
    10. Carey W. King & John P. Maxwell & Alyssa Donovan, 2015. "Comparing World Economic and Net Energy Metrics, Part 2: Total Economy Expenditure Perspective," Energies, MDPI, vol. 8(11), pages 1-22, November.
    11. Tang, Xu & Snowden, Simon & Höök, Mikael, 2013. "Analysis of energy embodied in the international trade of UK," Energy Policy, Elsevier, vol. 57(C), pages 418-428.
    12. Megan C. Guilford & Charles A.S. Hall & Peter O’Connor & Cutler J. Cleveland, 2011. "A New Long Term Assessment of Energy Return on Investment (EROI) for U.S. Oil and Gas Discovery and Production," Sustainability, MDPI, vol. 3(10), pages 1-22, October.
    13. 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.
    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. Carey W. King, 2015. "Comparing World Economic and Net Energy Metrics, Part 3: Macroeconomic Historical and Future Perspectives," Energies, MDPI, vol. 8(11), pages 1-24, November.
    16. David I. Stern and Astrid Kander, 2012. "The Role of Energy in the Industrial Revolution and Modern Economic Growth," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    17. Carey W. King & John P. Maxwell & Alyssa Donovan, 2015. "Comparing World Economic and Net Energy Metrics, Part 1: Single Technology and Commodity Perspective," Energies, MDPI, vol. 8(11), pages 1-26, November.
    18. Ang, B.W. & Xu, X.Y., 2013. "Tracking industrial energy efficiency trends using index decomposition analysis," Energy Economics, Elsevier, vol. 40(C), pages 1014-1021.
    19. Paul, Shyamal & Bhattacharya, Rabindra Nath, 2004. "CO2 emission from energy use in India: a decomposition analysis," Energy Policy, Elsevier, vol. 32(5), pages 585-593, March.
    20. 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.
    Full references (including those not matched with items on IDEAS)

    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. Carey W. King, 2015. "Comparing World Economic and Net Energy Metrics, Part 3: Macroeconomic Historical and Future Perspectives," Energies, MDPI, vol. 8(11), pages 1-24, November.
    2. Carey W. King & John P. Maxwell & Alyssa Donovan, 2015. "Comparing World Economic and Net Energy Metrics, Part 1: Single Technology and Commodity Perspective," Energies, MDPI, vol. 8(11), pages 1-26, November.
    3. Lina I. Brand-Correa & Paul E. Brockway & Claire L. Copeland & Timothy J. Foxon & Anne Owen & Peter G. Taylor, 2017. "Developing an Input-Output Based Method to Estimate a National-Level Energy Return on Investment (EROI)," Energies, MDPI, vol. 10(4), pages 1-21, April.
    4. Carey W. King, 2021. "Interdependence of Growth, Structure, Size and Resource Consumption During an Economic Growth Cycle," Papers 2106.02512, arXiv.org.
    5. 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.
    6. Xue-Ting Jiang & Min Su & Rongrong Li, 2018. "Decomposition Analysis in Electricity Sector Output from Carbon Emissions in China," Sustainability, MDPI, vol. 10(9), pages 1-18, September.
    7. Fei Wang & Changjian Wang & Jing Chen & Zeng Li & Ling Li, 2020. "Examining the determinants of energy-related carbon emissions in Central Asia: country-level LMDI and EKC analysis during different phases," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(8), pages 7743-7769, December.
    8. Court, Victor & Fizaine, Florian, 2017. "Long-Term Estimates of the Energy-Return-on-Investment (EROI) of Coal, Oil, and Gas Global Productions," Ecological Economics, Elsevier, vol. 138(C), pages 145-159.
    9. 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).
    10. 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.
    11. 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.
    12. Patiño, Lourdes Isabel & Alcántara, Vicent & Padilla, Emilio, 2021. "Driving forces of CO2 emissions and energy intensity in Colombia," Energy Policy, Elsevier, vol. 151(C).
    13. Aramendia, Emmanuel & Brockway, Paul E. & Pizzol, Massimo & Heun, Matthew K., 2021. "Moving from final to useful stage in energy-economy analysis: A critical assessment," Applied Energy, Elsevier, vol. 283(C).
    14. Boratyński, Jakub, 2021. "Decomposing structural decomposition: The role of changes in individual industry shares," Energy Economics, Elsevier, vol. 103(C).
    15. Bowen Xiao & Dongxiao Niu & Xiaodan Guo, 2016. "The Driving Forces of Changes in CO 2 Emissions in China: A Structural Decomposition Analysis," Energies, MDPI, vol. 9(4), pages 1-17, March.
    16. Yu-Kai Huang & Jyh-Yih Hsu & Lih-Chyun Sun, 2017. "A Study of Energy Efficiency and Mitigation of Carbon Emission: Implication of Decomposing Energy Intensity of Manufacturing Sector in Taiwan," International Journal of Energy Economics and Policy, Econjournals, vol. 7(2), pages 26-33.
    17. 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.
    18. Brizga, Janis & Feng, Kuishuang & Hubacek, Klaus, 2013. "Drivers of CO2 emissions in the former Soviet Union: A country level IPAT analysis from 1990 to 2010," Energy, Elsevier, vol. 59(C), pages 743-753.
    19. Haugom, Erik & Mydland, Ørjan & Pichler, Alois, 2016. "Long term oil prices," Energy Economics, Elsevier, vol. 58(C), pages 84-94.
    20. Trotta, Gianluca, 2020. "Assessing energy efficiency improvements and related energy security and climate benefits in Finland: An ex post multi-sectoral decomposition analysis," Energy Economics, Elsevier, vol. 86(C).

    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:17:p:6925-:d:404165. 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.