Abstract

Several major economies rely heavily on fossil fuel production and exports, yet current low-carbon technology diffusion, energy efficiency and climate policy may be substantially reducing global demand for fossil fuels1,2,3,4. This trend is inconsistent with observed investment in new fossil fuel ventures1,2, which could become stranded as a result. Here, we use an integrated global economy–environment simulation model to study the macroeconomic impact of stranded fossil fuel assets (SFFA). Our analysis suggests that part of the SFFA would occur as a result of an already ongoing technological trajectory, irrespective of whether or not new climate policies are adopted; the loss would be amplified if new climate policies to reach the 2 °C target of the Paris Agreement are adopted and/or if low-cost producers (some OPEC countries) maintain their level of production (‘sell out’) despite declining demand; the magnitude of the loss from SFFA may amount to a discounted global wealth loss of US$1–4 trillion; and there are clear distributional impacts, with winners (for example, net importers such as China or the EU) and losers (for example, Russia, the United States or Canada, which could see their fossil fuel industries nearly shut down), although the two effects would largely offset each other at the level of aggregate global GDP.

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Acknowledgements

The authors acknowledge C-EERNG and Cambridge Econometrics for support, and funding from EPSRC (J.-F.M., fellowship no. EP/K007254/1), the Newton Fund (J.-F.M., P.S., J.E.V., H.P., U.C., EPSRC grant no. EP/N002504/1 and ESRC grant no. ES/N013174/1), NERC (N.R.E., P.B.H., H.P., U.C., grant no. NE/P015093/1), CONICYT (P.S.), the Philomathia Foundation (J.E.V.), the Cambridge Humanities Research Grants Scheme (J.E.V.), Horizon 2020 (J.-F.M., F.K., Sim4Nexus project no. 689150) and the European Commission (J.-F.M., H.P., F.K., U.C., DG ENERGY contract no. ENER/A4/2015-436/SER/S12.716128). J.-F.M. acknowledges the support of L. J. Turner during extended critical medical treatment, and H. de Coninck and M. Grubb for discussions. We are grateful to N. Bauer for sharing data from his study.

Author information

Affiliations

  1. Department of Environmental Science, Radboud University, Nijmegen, The Netherlands

    • J.-F. Mercure
    •  & F. Knobloch
  2. Cambridge Centre for Environment, Energy and Natural Resource Governance (C-EENRG), University of Cambridge, Cambridge, UK

    • J.-F. Mercure
    • , H. Pollitt
    • , J. E. Viñuales
    • , N. R. Edwards
    • , P. Salas
    • , I. Sognnaes
    • , A. Lam
    •  & F. Knobloch
  3. Cambridge Econometrics Ltd, Covent Garden, Cambridge, UK

    • J.-F. Mercure
    • , H. Pollitt
    •  & U. Chewpreecha
  4. Environment, Earth and Ecosystems, The Open University, Milton Keynes, UK

    • N. R. Edwards
    •  & P. B. Holden
  5. Department of Economics, Faculty of Social Sciences, University of Macao, Taipa, Macau

    • A. Lam

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Contributions

J.-F.M. designed and coordinated the research. J.-F.M., J.E.V., N.R.E., H.P. and I.S. wrote the article. J.-F.M., H.P. and U.C. ran simulations. U.C. and H.P. managed E3ME. J.-F.M. and A.L. developed FTT:Transport. J.-F.M. and P.S. developed FTT:Power and the resource depletion model. F.K. and J.-F.M. developed FTT:Heat. P.B.H. and N.R.E. ran GENIE simulations and provided scientific support on climate change. J.E.V. contributed geopolitical expertise.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to J.-F. Mercure.

Supplementary information

  1. Supplementary Information

    Supplementary notes 1–5, Supplementary tables 1–8, Supplementary figures 1–11, Supplementary references

  2. Supplementary Data 1

    Dataset for detailed public policies assumed in model scenarios

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DOI

https://doi.org/10.1038/s41558-018-0182-1