IDEAS home Printed from https://ideas.repec.org/a/nat/natene/v1y2016i7d10.1038_nenergy.2016.77.html
   My bibliography  Save this article

Quantifying uncertainties influencing the long-term impacts of oil prices on energy markets and carbon emissions

Author

Listed:
  • David L. McCollum

    (International Institute for Applied Systems Analysis (IIASA)
    University of Tennessee)

  • Jessica Jewell

    (International Institute for Applied Systems Analysis (IIASA))

  • Volker Krey

    (International Institute for Applied Systems Analysis (IIASA))

  • Morgan Bazilian

    (The World Bank)

  • Marianne Fay

    (The World Bank)

  • Keywan Riahi

    (International Institute for Applied Systems Analysis (IIASA)
    Graz University of Technology)

Abstract

Oil prices have fluctuated remarkably in recent years. Previous studies have analysed the impacts of future oil prices on the energy system and greenhouse gas emissions, but none have quantitatively assessed how the broader, energy-system-wide impacts of diverging oil price futures depend on a suite of critical uncertainties. Here we use the MESSAGE integrated assessment model to study several factors potentially influencing this interaction, thereby shedding light on which future unknowns hold the most importance. We find that sustained low or high oil prices could have a major impact on the global energy system over the next several decades; and depending on how the fuel substitution dynamics play out, the carbon dioxide consequences could be significant (for example, between 5 and 20% of the budget for staying below the internationally agreed 2 ∘C target). Whether or not oil and gas prices decouple going forward is found to be the biggest uncertainty.

Suggested Citation

  • David L. McCollum & Jessica Jewell & Volker Krey & Morgan Bazilian & Marianne Fay & Keywan Riahi, 2016. "Quantifying uncertainties influencing the long-term impacts of oil prices on energy markets and carbon emissions," Nature Energy, Nature, vol. 1(7), pages 1-8, July.
  • Handle: RePEc:nat:natene:v:1:y:2016:i:7:d:10.1038_nenergy.2016.77
    DOI: 10.1038/nenergy.2016.77
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/nenergy201677
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1038/nenergy.2016.77?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Bilgili, Faik & Mugaloglu, Erhan & Koçak, Emrah, 2018. "The impact of oil prices on CO2 emissions in China: A Wavelet coherence approach," MPRA Paper 90170, University Library of Munich, Germany.
    2. Shu Mo & Ting Wang, 2022. "Synergistic Effects of International Oil Price Fluctuations and Carbon Tax Policies on the Energy–Economy–Environment System in China," IJERPH, MDPI, vol. 19(21), pages 1-17, October.
    3. Millischer, Laurent & Evdokimova, Tatiana & Fernandez, Oscar, 2023. "The carrot and the stock: In search of stock-market incentives for decarbonization," Energy Economics, Elsevier, vol. 120(C).
    4. Yosuke Arino & Fuminori Sano & Keigo Akimoto, 2017. "Future Fossil Fuel Price Impacts on NDC Achievement; Estimation of GHG Emissions and Mitigation Costs," Eurasian Journal of Economics and Finance, Eurasian Publications, vol. 5(4), pages 16-35.
    5. Panos, Evangelos & Kober, Tom & Wokaun, Alexander, 2019. "Long term evaluation of electric storage technologies vs alternative flexibility options for the Swiss energy system," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    6. Peter Lopion & Peter Markewitz & Detlef Stolten & Martin Robinius, 2019. "Cost Uncertainties in Energy System Optimization Models: A Quadratic Programming Approach for Avoiding Penny Switching Effects," Energies, MDPI, vol. 12(20), pages 1-12, October.
    7. Taha Zaghdoudi, 2018. "Asymmetric responses of CO2 emissions to oil price shocks in China: a non-linear ARDL approach," Economics Bulletin, AccessEcon, vol. 38(3), pages 1485-1493.
    8. Li, Houjian & Huang, Xinya & Guo, Lili, 2023. "Extreme risk dependence and time-varying spillover between crude oil, commodity market and inflation in China," Energy Economics, Elsevier, vol. 127(PB).
    9. Mahdi Salehi & Seyed Hamed Fahimifard & Grzegorz Zimon & Andrzej Bujak & Adam Sadowski, 2022. "The Effect of CO 2 Gas Emissions on the Market Value, Price and Shares Returns," Energies, MDPI, vol. 15(23), pages 1-17, December.
    10. Katrakilidis Constantinos & Zafeiriou Eleni & Sariannidis Nikolaos & Dimitris Bantis, 2019. "Greenhouse gas emissions–crude oil prices: an empirical investigation in a nonlinear framework," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(6), pages 2835-2856, December.
    11. Middleton, Richard S. & Gupta, Rajan & Hyman, Jeffrey D. & Viswanathan, Hari S., 2017. "The shale gas revolution: Barriers, sustainability, and emerging opportunities," Applied Energy, Elsevier, vol. 199(C), pages 88-95.
    12. Hongtao Ren & Wenji Zhou & Hangzhou Wang & Bo Zhang & Tieju Ma, 2022. "An energy system optimization model accounting for the interrelations of multiple stochastic energy prices," Annals of Operations Research, Springer, vol. 316(1), pages 555-579, September.
    13. Li, Wei & Sun, Wen & Li, Guomin & Jin, Baihui & Wu, Wen & Cui, Pengfei & Zhao, Guohao, 2018. "Transmission mechanism between energy prices and carbon emissions using geographically weighted regression," Energy Policy, Elsevier, vol. 115(C), pages 434-442.
    14. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2020. "Causality between CO2 Emissions and Stock Markets," Energies, MDPI, vol. 13(11), pages 1-14, June.
    15. Wang, Keying & Wu, Meng & Sun, Yongping & Shi, Xunpeng & Sun, Ao & Zhang, Ping, 2019. "Resource abundance, industrial structure, and regional carbon emissions efficiency in China," Resources Policy, Elsevier, vol. 60(C), pages 203-214.
    16. Ritchie, Justin & Dowlatabadi, Hadi, 2017. "Why do climate change scenarios return to coal?," Energy, Elsevier, vol. 140(P1), pages 1276-1291.

    More about this item

    Statistics

    Access and download statistics

    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:nat:natene:v:1:y:2016:i:7:d:10.1038_nenergy.2016.77. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.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.