Comparing transformation pathways across major economies (original) (raw)

Abstract

This paper explores the consequences of different policy assumptions and the derivation of globally consistent, national low-carbon development pathways for the seven largest greenhouse gas (GHG)–emitting countries (EU28 as a bloc) in the world, covering approximately 70% of global CO2 emissions, in line with their contributions to limiting global average temperature increase to well below 2 °C as compared with pre-industrial levels. We introduce the methodology for developing these pathways by initially discussing the process by which global integrated assessment model (IAM) teams interacted and derived boundary conditions in the form of carbon budgets for the different countries. Carbon budgets so derived for the 2011–2050 period were then used in eleven different national energy-economy models and IAMs for producing low-carbon pathways for the seven countries in line with a well below 2 °C world up to 2050. We present a comparative assessment of the resulting pathways and of the challenges and opportunities associated with them. Our results indicate quite different mitigation pathways for the different countries, shown by the way emission reductions are split between different sectors of their economies and technological alternatives.

Access this article

Log in via an institution

Subscribe and save

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

The alternative text for this image may have been generated using AI.

Fig. 2

The alternative text for this image may have been generated using AI.

Fig. 3

The alternative text for this image may have been generated using AI.

Fig. 4

The alternative text for this image may have been generated using AI.

Fig. 5

The alternative text for this image may have been generated using AI.

Similar content being viewed by others

Notes

  1. As soon as a country ratifies the Paris Agreement, its INDC becomes a NDC.
  2. In fact, GEM-E3 is a global model, but because of its great resolution for the EU-28 region, it is being referred to, here, as if it was a national model for the EU. The same applies to the GCAM model here, which is also a global IAM but because of its right resolution for the USA, it is being used as a national model for this country.
  3. Note that more recent literature may present different carbon-budget numbers (see, for example, Rogelj et al. 2016b, Peters 2016, Millar et al. 2017), which can be largely explained by methodological differences.

References

Download references

Funding

This study benefited from the financial support of the European Commission via the Linking Climate and Development Policies-Leveraging International Networks and Knowledge Sharing (CD-LINKS) project, financed by the European Union’s Horizon 2020 research and innovation program under grant agreement no. 642147 (CD-LINKS). We thank all CD-LINKS project partners for contributing to scenario development. Results presented here are not automatically endorsed by CD-LINKS project partners. RS would like to acknowledge the financial support received from the National Council for Scientific and Technological Development (CNPq), and from the National Institute of Science and Technology for Climate Change Phase 2 under CNPq Grant 465501/2014-1 and the National Coordination for High Level Education and Training (CAPES) Grant 88887.136402/2017-00, all from Brazil. WC would like to thank the support from National Science Foundation of China (71690243) for the development and improvement of China-TIMES. SF and KO would like to acknowledge the support received from the Environment Research and Technology Development Fund (2-1702) of the Environmental Restoration and Conservation Agency, Japan.

Author information

Authors and Affiliations

  1. Centre for Energy and Enviromental Economics, Energy Planning Program, CENERGIA/PPE/COPPE/UFRJ, Centro de Tecnologia, Universidade Federal do Rio de Janeiro (COPPE/UFRJ), Bloco C, Sala C-211, Cidade Universitária, Ilha do Fundão, Rio de Janeiro, RJ, 21941-914, Brazil
    R. Schaeffer & A. Köberle
  2. Grantham Institute, Imperial College London (ICL), London, UK
    A. Köberle
  3. PBL Netherlands Environmental Assessment Agency, Hague, The Netherlands
    H. L. van Soest & D. P. van Vuuren
  4. Copernicus Institute, Utrecht University, Utrecht, The Netherlands
    H. L. van Soest & D. P. van Vuuren
  5. Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany
    C. Bertram, G. Luderer, E. Kriegler & F. Ueckerdt
  6. International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
    K. Riahi & V. Krey
  7. Kyoto University (KyotoU), Kyoto, Japan
    S. Fujimori
  8. National Institute for Environmental Studies (NIES), Tsukuba, Japan
    S. Fujimori
  9. Institute of Energy, Environment and Economy, Tsinghua University (TU), Beijing, China
    W. Chen
  10. Energy Research Institute (ERI), Beijing, China
    C. He
  11. School of Electrical and Computer Engineering, E3MLab, National Technical University of Athens, Athens, Greece
    Z. Vrontisi
  12. Indian Institute of Management-Ahmedabad (IIMA), Ahmedabad, India
    S. Vishwanathan & A. Garg
  13. The Energy and Resources Institute (TERI), New Delhi, India
    R. Mathur & S. Shekhar
  14. Mizuho Information & Research Institute (MHIR), Tokyo, Japan
    K. Oshiro
  15. Higher School of Economics (HSE), Moscow, Russia
    G. Safonov
  16. Pacific Northwest National Laboratory (PNNL), Richland, WA, USA
    G. Iyer
  17. Research Institute of Innovative Technology for the Earth (RITE), Kyoto, 619-0292, Japan
    K. Gi
  18. Russian Presidential Academy of National Economy and Public Administration (RANEPA), Moscow, Russia
    V. Potashnikov

Authors

  1. R. Schaeffer
  2. A. Köberle
  3. H. L. van Soest
  4. C. Bertram
  5. G. Luderer
  6. K. Riahi
  7. V. Krey
  8. D. P. van Vuuren
  9. E. Kriegler
  10. S. Fujimori
  11. W. Chen
  12. C. He
  13. Z. Vrontisi
  14. S. Vishwanathan
  15. A. Garg
  16. R. Mathur
  17. S. Shekhar
  18. K. Oshiro
  19. F. Ueckerdt
  20. G. Safonov
  21. G. Iyer
  22. K. Gi
  23. V. Potashnikov

Contributions

RS, AK and HvS coordinated the analyses and writing of this paper, to which all authors contributed. HvS created the figs. CB, GL, RS, KR, VK, DvV, EK, FU and HvS coordinated the national modeling study. The national model scenarios were developed by AK and RS (BLUES-Brazil), WC (China-TIMES), CH (China-IPAC), ZV (EU-GEM-E3 and EU-PRIMES), RM and SS (India-MARKAL), SSV and AG (India-AIM), KG (Japan-DNE21+), KO and SF (Japan-AIM/Enduse), GS and VP (Russia-TIMES), and GI (USA-GCAM).

Corresponding author

Correspondence toR. Schaeffer.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This article is part of a Special Issue on “National Low-Carbon Development Pathways” edited by Roberto Schaeffer, Valentina Bosetti, Elmar Kriegler, Keywan Riahi, Detlef van Vuuren, and John Weyant

Electronic supplementary material

Rights and permissions

About this article

Cite this article

Schaeffer, R., Köberle, A., van Soest, H.L. et al. Comparing transformation pathways across major economies.Climatic Change 162, 1787–1803 (2020). https://doi.org/10.1007/s10584-020-02837-9

Download citation

Keywords