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Probabilistic cost estimates for climate change mitigation

A Corrigendum to this article was published on 15 January 2014

Abstract

For more than a decade, the target of keeping global warming below 2 °C has been a key focus of the international climate debate1. In response, the scientific community has published a number of scenario studies that estimate the costs of achieving such a target2,3,4,5. Producing these estimates remains a challenge, particularly because of relatively well known, but poorly quantified, uncertainties, and owing to limited integration of scientific knowledge across disciplines6. The integrated assessment community, on the one hand, has extensively assessed the influence of technological and socio-economic uncertainties on low-carbon scenarios and associated costs2,3,4,7. The climate modelling community, on the other hand, has spent years improving its understanding of the geophysical response of the Earth system to emissions of greenhouse gases8,9,10,11,12. This geophysical response remains a key uncertainty in the cost of mitigation scenarios but has been integrated with assessments of other uncertainties in only a rudimentary manner, that is, for equilibrium conditions6,13. Here we bridge this gap between the two research communities by generating distributions of the costs associated with limiting transient global temperature increase to below specific values, taking into account uncertainties in four factors: geophysical, technological, social and political. We find that political choices that delay mitigation have the largest effect on the cost–risk distribution, followed by geophysical uncertainties, social factors influencing future energy demand and, lastly, technological uncertainties surrounding the availability of greenhouse gas mitigation options. Our information on temperature risk and mitigation costs provides crucial information for policy-making, because it clarifies the relative importance of mitigation costs, energy demand and the timing of global action in reducing the risk of exceeding a global temperature increase of 2 °C, or other limits such as 3 °C or 1.5 °C, across a wide range of scenarios.

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Figure 1: Methodology for creating cost–risk relationships for a given temperature limit.
Figure 2: Influence of mitigation technology, energy demand and political inaction on the cost–risk distributions for staying below 2 °C.
Figure 3: Cost–risk distributions for returning global temperature increase to below 1.5 °C by 2100.

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References

  1. Randalls, S. History of the 2 °C climate target. Clim. Change 1, 598–605 (2010)

    Google Scholar 

  2. Clarke, L. et al. International climate policy architectures: overview of the EMF 22 International Scenarios. Energy Econ. 31, S64–S81 (2009)

    Article  Google Scholar 

  3. Edenhofer, O. et al. The economics of low stabilization: model comparison of mitigation strategies and costs. Energy J. 31, 11–48 (2010)

    Google Scholar 

  4. UNEP. Bridging the Emissions Gap 15–20 (United Nations Environment Programme, 2011)

  5. O’Neill, B. C., Riahi, K. & Keppo, I. Mitigation implications of midcentury targets that preserve long-term climate policy options. Proc. Natl Acad. Sci. USA 107, 1011–1016 (2010)

    Article  ADS  Google Scholar 

  6. Core Writing Team, Pachauri, R. K. & Reisinger, A. (eds) Climate Change 2007: Synthesis Report (Intergovernmental Panel on Climate Change, 2007)

    Google Scholar 

  7. Riahi, K. et al. in Global Energy Assessment: Toward a Sustainable Future 1203–1306 (Cambridge Univ. Press, 2012)

    Google Scholar 

  8. Friedlingstein, P. et al. Climate–carbon cycle feedback analysis: results from the C4MIP model intercomparison. J. Clim. 19, 3337–3353 (2006)

    Article  ADS  Google Scholar 

  9. Meehl, G. A., Covey, C., McAvaney, B., Latif, M. & Stouffer, R. J. Overview of the coupled model intercomparison project. Bull. Am. Meteorol. Soc. 86, 89–93 (2005)

    Article  ADS  Google Scholar 

  10. Meehl, G. A. et al. in IPCC Fourth Assessment Report (eds S. Solomon et al.) 747–847 (Cambridge Univ. Press, 2007)

    Google Scholar 

  11. Meinshausen, M., Wigley, T. M. L. & Raper, S. C. B. Emulating atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 2: applications. Atmos. Chem. Phys. 11, 1457–1471 (2011)

    Article  ADS  CAS  Google Scholar 

  12. Archer, D. et al. Atmospheric lifetime of fossil fuel carbon dioxide. Annu. Rev. Earth Planet. Sci. 37, 117–134 (2009)

    Article  ADS  CAS  Google Scholar 

  13. Schaeffer, M., Kram, T., Meinshausen, M., van Vuuren, D. P. & Hare, W. L. Near-linear cost increase to reduce climate-change risk. Proc. Natl Acad. Sci. USA 105, 20621–20626 (2008)

    Article  ADS  Google Scholar 

  14. Rao, S. & Riahi, K. The role of non-CO2 greenhouse gases in climate change mitigation: long-term scenarios for the 21st century. Energy J. 27, 177–200 (2006)

    Google Scholar 

  15. Riahi, K., Gruebler, A. & Nakicenovic, N. Scenarios of long-term socio-economic and environmental development under climate stabilization. Technol. Forecast. Social Change 74, 887–935 (2007)

    Article  Google Scholar 

  16. Meinshausen, M., Raper, S. C. B. & Wigley, T. M. L. Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 1: Model description and calibration. Atmos. Chem. Phys. 11, 1417–1456 (2011)

    Article  ADS  CAS  Google Scholar 

  17. Rogelj, J., Meinshausen, M. & Knutti, R. Global warming under old and new scenarios using IPCC climate sensitivity range estimates. Nature Clim. Change 2, 248–253 (2012)

    Article  ADS  Google Scholar 

  18. Knutti, R. et al. A review of uncertainties in global temperature projections over the twenty-first century. J. Clim. 21, 2651–2663 (2008)

    Article  ADS  Google Scholar 

  19. Mastrandrea, M. D. et al. Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties 3 (Intergovernmental Panel on Climate Change, 2010); available at http://www.ipcc.ch/pdf/supporting-material/uncertainty-guidance-note.pdf

  20. Smith, S. M. et al. Equivalence of greenhouse-gas emissions for peak temperature limits. Nature Clim. Change 2, 535–538 (2012)

    Article  ADS  CAS  Google Scholar 

  21. UNFCCC. FCCC/CP/2010/7/Add.1 Decision 1/CP.16 3 (UN Framework Convention on Climate Change, 2010)

  22. Smith, S. J. & Edmonds, J. A. The economic implications of carbon cycle uncertainty. Tellus B 58, 586–590 (2006)

    Article  ADS  Google Scholar 

  23. Vaughan, N. & Lenton, T. &. Shepherd, J. Climate change mitigation: trade-offs between delay and strength of action required. Clim. Change 96, 29–43 (2009)

    Article  ADS  CAS  Google Scholar 

  24. den Elzen, M., van Vuuren, D. & van Vliet, J. Postponing emission reductions from 2020 to 2030 increases climate risks and long-term costs. Clim. Change 99, 313–320 (2010)

    Article  ADS  Google Scholar 

  25. Bosetti, V., Carraro, C., Sgobbi, A. & Tavoni, M. Delayed action and uncertain stabilisation targets. How much will the delay cost? Clim. Change 96, 299–312 (2009)

    Article  ADS  Google Scholar 

  26. Krey, V. & Riahi, K. Implications of delayed participation and technology failure for the feasibility, costs, and likelihood of staying below temperature targets: greenhouse gas mitigation scenarios for the 21st century. Energy Econ. 31, S94–S106 (2009)

    Article  Google Scholar 

  27. UNFCCC. FCCC/CP/2011/9/Add.1 Decision 1/CP.17 (UN Framework Convention on Climate Change, 2011)

  28. UN. World Population Prospects: The 2008 Revision Population Database (United Nations, 2009)

  29. Nakicenovic, N. & Swart, R. IPCC Special Report on Emissions Scenarios (Cambridge Univ. Press, 2000)

    Google Scholar 

  30. Meinshausen, M. et al. Greenhouse-gas emission targets for limiting global warming to 2°C. Nature 458, 1158–1162 (2009)

    Article  ADS  CAS  Google Scholar 

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Acknowledgements

We thank V. Krey, P. Kolp and M. Strubegger for their support in developing the model set-up and extracting the results, R. Knutti and R. Socolow for comments and feedback during the writing process and S. Hatfield-Dodds, whose review comments substantially contributed to improving our manuscript. J.R. was supported by the Swiss National Science Foundation (project 200021-135067) and the IIASA Peccei Award Grant.

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All authors were involved in designing the research. J.R. performed the research in collaboration with D.L.M. All authors contributed to writing the paper.

Corresponding author

Correspondence to Joeri Rogelj.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Text 1-3, which includes background information about our modelling framework, setup and results, Supplementary Tables 1–2, Supplementary Figures 1-10, Supplementary References. This file was replaced on 15 January 2014 and contains updated versions of Supplementary Figures 2, 3, 4, 5, 8, and 9, in line with the description in the Corrigendum 10.1038/nature12937. None of these changes affect our conclusions or discussion of results. (PDF 2632 kb)

Supplementary Data

This file contains a Cost-Risk Check Tool, which allows for interactive querying of our cost-risk distributions for 1.5, 2, 2.5, and 3°C. Different cost metrics can be selected for various energy supply and demand combinations. This file was replaced on 15 January 2014. (XLSX 204 kb)

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Rogelj, J., McCollum, D., Reisinger, A. et al. Probabilistic cost estimates for climate change mitigation. Nature 493, 79–83 (2013). https://doi.org/10.1038/nature11787

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