Abstract

Burgeoning demands for mobility and private vehicle ownership undermine global efforts to reduce energy-related greenhouse gas emissions. Advanced vehicles powered by low-carbon sources of electricity or hydrogen offer an alternative to conventional fossil-fuelled technologies. Yet, despite ambitious pledges and investments by governments and automakers, it is by no means clear that these vehicles will ultimately reach mass-market consumers. Here, we develop state-of-the-art representations of consumer preferences in multiple global energy-economy models, specifically focusing on the non-financial preferences of individuals. We employ these enhanced model formulations to analyse the potential for a low-carbon vehicle revolution up to 2050. Our analysis shows that a diverse set of measures targeting vehicle buyers is necessary to drive widespread adoption of clean technologies. Carbon pricing alone is insufficient to bring low-carbon vehicles to the mass market, though it may have a supporting role in ensuring a decarbonized energy supply.

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Acknowledgements

We acknowledge funding provided by the ADVANCE project (FP7/2007–2013, grant agreement number 308329) of the European Commission. P. Kolp, D. Huppmann and M. Strubegger of IIASA provided critical assistance with MESSAGE-Transport model development. B. Girod (ETH-Zürich) helped with IMAGE model development. N. Lutsey of The International Council on Clean Transportation (ICCT) referred us to the most up-to-date information on AFV-supporting policies at the time of writing.

Author information

Affiliations

  1. International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria

    • David L. McCollum
    • , Charlie Wilson
    • , Volker Krey
    •  & Keywan Riahi
  2. Howard H. Baker Jr. Center for Public Policy, University of Tennessee, Knoxville, TN, USA

    • David L. McCollum
  3. Tyndall Centre for Climate Change Research, University of East Anglia, Norwich, United Kingdom

    • Charlie Wilson
    •  & Hazel Pettifor
  4. Climate and Sustainable Innovation (CSI) Program, Fondazione Eni Enrico Mattei (FEEM), and Economic analysis of Climate Impacts and Policy Division (ECIP), Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC), Milan, Italy

    • Michela Bevione
    • , Samuel Carrara
    •  & Johannes Emmerling
  5. Climate, Air and Energy Department, PBL Netherlands Environmental Assessment Agency, The Hague, The Netherlands

    • Oreane Y. Edelenbosch
    •  & Detlef P. van Vuuren
  6. Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands

    • Oreane Y. Edelenbosch
    •  & Detlef P. van Vuuren
  7. Ecole des Ponts, Centre International de Recherche sur l’Environnement et le Développement (CIRED), Nogent-sur-Marne, France

    • Céline Guivarch
  8. E3MLab/Institute of Communications and Computer Systems, National Technical University of Athens, Zografou, Greece

    • Panagiotis Karkatsoulis
    •  & Leonidas Paroussos
  9. UCL Energy Institute, University College London, Central House, London, United Kingdom

    • Ilkka Keppo
    •  & Baltazar Solano Rodriguez
  10. Center for Transportation Analysis, Oak Ridge National Laboratory (ORNL), Knoxville, TN, USA

    • Zhenhong Lin
  11. Department of Industrial and Systems Engineering, University of Tennessee, Knoxville, TN, USA

    • Zhenhong Lin
  12. Centre International de Recherche sur l’Environnement et le Développement (CIRED) & Société de Mathématiques Appliquées et de Sciences Humaines (SMASH), Nogent-sur-Marne, France

    • Eoin Ó Broin
  13. Institute of Transportation Studies, University of California, Davis, Davis, CA, USA

    • Kalai Ramea
  14. Institute of Thermal Engineering, Graz University of Technology, Graz, Austria

    • Keywan Riahi
  15. Payne Institute, Colorado School of Mines, Golden, CO, USA

    • Keywan Riahi
  16. Systems Analysis Group, Research Institute of Innovative Technology for the Earth (RITE), Kyoto, Japan

    • Fuminori Sano

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Contributions

D.L.M., C.W., V.K. and K. Riahi designed the research. H.P., C.W., Z.L. and K. Ramea contributed data for the modelling. D.L.M., M.B., E.ÓB., S.C., O.Y.E., J.E., C.G., P.K., I.K., V.K., L.P., K. Riahi, B.S.R. and D.P.v.V. implemented the modelling. D.L.M. wrote the manuscript, with all authors contributing.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to David L. McCollum.

Supplementary information

  1. Supplementary Information

    Supplementary Tables 1–5, Supplementary Figures 1–18, Supplementary Discussion, Supplementary Methods, Supplementary References

  2. Supplementary Data 1

    Model assumptions for annual driving distances and consumer group splits by region

  3. Supplementary Data 2

    Model assumptions for (dis)utility costs by non-financial attribute, consumer group, vehicle technology and region

  4. Supplementary Data 3

    Model assumptions for capital costs of light-duty vehicles over time in each model’s USA region in the ‘AFV Push’ scenario with US$100 per tCO2 carbon pricing

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DOI

https://doi.org/10.1038/s41560-018-0195-z