The appropriate use of reference scenarios in mitigation analysis

Abstract

Comparing emissions scenarios is an essential part of mitigation analysis, as climate targets can be met in various ways with different economic, energy system and co-benefit implications. Typically, a central ‘reference scenario’ acts as a point of comparison, and often this has been a no policy baseline with no explicit mitigative action taken. The use of such baselines is under increasing scrutiny, raising a wider question around the appropriate use of reference scenarios in mitigation analysis. In this Perspective, we assess three critical issues relevant to the use of reference scenarios, demonstrating how different policy contexts merit the use of different scenarios. We provide recommendations to the modelling community on best practice in the creation, use and communication of reference scenarios.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    Adoption of the Paris Agreement FCCC/CP/2015/L.9/Rev.1 (UNFCCC, 2015).

  2. 2.

    Weyant, J. Some contributions of integrated assessment models of global climate change. Rev. Environ. Econ. Policy 11, 115–137 (2017).

    Google Scholar 

  3. 3.

    Krey, V. Global energy-climate scenarios and models: a review. Wiley Interdiscip. Rev. Energy Environ. 3, 363–383 (2014).

    Google Scholar 

  4. 4.

    Pfenninger, S., Hawkes, A. & Keirstead, J. Energy systems modeling for twenty-first century energy challenges. Renew. Sustain. Energy Rev. 33, 74–86 (2014).

    Google Scholar 

  5. 5.

    IPCC Climate Change 2001: Mitigation (eds Metz, B. et al.) (Cambridge Univ. Press, 2001).

  6. 6.

    IPCC Climate Change 2007: Impacts, Adaptation and Vulnerability (eds Parry, M. L. et al.) (Cambridge Univ. Press, 2007).

  7. 7.

    IPCC Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) (Cambridge Univ. Press, 2014).

  8. 8.

    Rogelj, J. et al. in Special Report on Global Warming of 1.5°C (eds Masson-Delmotte, V. et al.) Ch. 2 (IPCC, WMO, 2018).

  9. 9.

    Riahi, K. et al. The shared socioeconomic pathways and their energy, land use and greenhouse gas emissions implications: an overview. Glob. Environ. Change 42, 153–168 (2017).

    Google Scholar 

  10. 10.

    van Vuuren, D. P. et al. The shared socio-economic pathways: trajectories for human development and global environmental change. Glob. Environ. Change 42, 148–152 (2017).

    Google Scholar 

  11. 11.

    O’Neill, B. C. et al. A new scenario framework for climate change research: the concept of shared socioeconomic pathways. Climatic Change 122, 387–400 (2014).

    Google Scholar 

  12. 12.

    Moss, R. H. et al. The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010).

    CAS  Google Scholar 

  13. 13.

    van Vuuren, D. P. et al. The representative concentration pathways: an overview. Climatic Change 109, 5–31 (2011).

    Google Scholar 

  14. 14.

    World Energy Outlook 2019 (International Energy Agency, 2019); https://www.iea.org/reports/world-energy-outlook-2019

  15. 15.

    Annual Energy Outlook 2019 with Projections to 2050 (Energy Information Administration, 2019).

  16. 16.

    Napp, T. A. et al. The role of advanced demand-sector technologies and energy demand reduction in achieving ambitious carbon budgets. Appl. Energy 238, 351–367 (2019).

    Google Scholar 

  17. 17.

    Gambhir, A. et al. Assessing the feasibility of global long-term mitigation scenarios. Energies 10, 89 (2017).

    Google Scholar 

  18. 18.

    Zhang, R., Fujimori, S. & Hanaoka, T. The contribution of transport policies to the mitigation potential and cost of 2 °C and 1.5 °C goals. Environ. Res. Lett. 13, 5 (2018).

    Google Scholar 

  19. 19.

    Fujimori, S. et al. Will international emissions trading help achieve the objectives of the Paris Agreement? Environ. Res. Lett. 11, 10 (2016).

    Google Scholar 

  20. 20.

    Kriegler, E. et al. The role of technology for achieving climate policy objectives: overview of the EMF 27 study on global technology and climate policy strategies. Climatic Change 123, 353–367 (2014).

    Google Scholar 

  21. 21.

    Luderer, G., Bertram, C., Calvin, K., De Cian, E. & Kriegler, E. Implications of weak near-term climate policies on long-term mitigation pathways. Climatic Change 136, 127–140 (2016).

    Google Scholar 

  22. 22.

    McPherson, M., Johnson, N. & Strubegger, M. The role of electricity storage and hydrogen technologies in enabling global low-carbon energy transitions. Appl. Energy 216, 649–661 (2018).

    CAS  Google Scholar 

  23. 23.

    Clarke, L. et al. in Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) 413–510 (IPCC, Cambridge Univ. Press, 2014).

  24. 24.

    Emissions Gap Report 2019 (United Nations Environment Programme, 2019).

  25. 25.

    Nachmany, M., Fankhauser, S., Setzer, J. & Averchenkova, A. Global Trends in Climate Change Legislation and Litigation: 2017 Update (Grantham Research Institute on Climate Change and the Environment, 2017); http://www.lse.ac.uk/GranthamInstitute/publication/global-trends-in-climate-change-legislation-and-litigation-2017-update/.

  26. 26.

    Mager, B., Grimes, J. & Becker, M. Business as unusual. Nat. Energy 8, 17150 (2017).

    Google Scholar 

  27. 27.

    Winning, M. et al. Nationally determined contributions under the Paris Agreement and the costs of delayed action. Clim. Policy 19, 947–958 (2019).

    Google Scholar 

  28. 28.

    Hausfather, Z. & Peters, G. P. Emissions – the ‘business as usual’ story is misleading. Nature 577, 2020–2022 (2020).

    Google Scholar 

  29. 29.

    Metayer, M., Breyer, C. & Fell, H.-J. The projections for the future and quality in the past of the World Energy Outlook for solar PV and other renewable energy technologies. In 31st Eur. PV Solar Energy Conf. Exhib. (EU PVSEC, 2015); http://doi.org/cbwn.

  30. 30.

    Vartiainen, E., Breyer, C., Moser, D. & Medina, E. R. Impact of weighted average cost of capital, capital expenditure, and other parameters on future utility-scale PV levelised cost of electricity. Prog. Photovolt. Res. Appl. 28, 439–453 (2019).

    Google Scholar 

  31. 31.

    Hausfather, Z. Explainer: the high-emissions ‘RCP8.5′ global warming scenario. Carbon Brief https://www.carbonbrief.org/explainer-the-high-emissions-rcp8-5-global-warming-scenario (2019).

  32. 32.

    Lawrence, J., Haasnoot, M. & Lempert, R. Climate change: making decisions in the face of deep uncertainty. Nature 580, 456–456 (2020).

    CAS  Google Scholar 

  33. 33.

    Hsiang, S. et al. Estimating economic damage from climate change in the United States. Science 356, 1362–1369 (2017).

    CAS  Google Scholar 

  34. 34.

    Burke, M., Davis, W. M. & Diffenbaugh, N. S. Large potential reduction in economic damages under UN mitigation targets. Nature 557, 549–553 (2018).

    CAS  Google Scholar 

  35. 35.

    Kriegler, E. et al. Fossil-fueled development (SSP5): an energy and resource intensive scenario for the 21st century. Glob. Environ. Change 42, 297–315 (2017).

    Google Scholar 

  36. 36.

    Lomborg, B. U. N. Ignores economics of climate. Wall Street Journal https://www.wsj.com/articles/u-n-ignores-economics-of-climate-1539125496 (2018).

  37. 37.

    Stern, N. Stern Review: The Economics of Climate Change (HM Treasury, 2006).

  38. 38.

    Glanemann, N., Willner, S. N. & Levermann, A. Paris Climate Agreement passes the cost-benefit test. Nat. Commun. 11, 110 (2020).

    CAS  Google Scholar 

  39. 39.

    Hof, A. F. et al. Global and regional abatement costs of nationally determined contributions (NDCs) and of enhanced action to levels well below 2 °C and 1.5 °C. Environ. Sci. Policy 71, 30–40 (2017).

    Google Scholar 

  40. 40.

    Mace, M. J. Mitigation commitments under the Paris Agreement and the way forward. Climate Law 6, 21–39 (2016).

    Google Scholar 

  41. 41.

    Kriegler, E. et al. Making or breaking climate targets — the AMPERE study on staged accession scenarios for climate policy. Technol. Forecast. Soc. Change 99, 273–276 (2015).

    Google Scholar 

  42. 42.

    McCollum, D. L. et al. Energy investment needs for fulfilling the Paris Agreement and achieving the Sustainable Development Goals. Nat. Energy 3, 589–599 (2018).

    Google Scholar 

  43. 43.

    Fawcett, A. A. et al. Can Paris pledges avert severe climate change? Science 350, 1168–1169 (2015).

    CAS  Google Scholar 

  44. 44.

    van Soest, H. L. et al. Early action on Paris Agreement allows for more time to change energy systems. Clim. Change 144, 165–179 (2017).

    Google Scholar 

  45. 45.

    Clarke, L., Weyant, J. & Birky, A. On the sources of technological change: assessing the evidence. Energy Econ. 28, 579–595 (2006).

    Google Scholar 

  46. 46.

    Grubb, M., Köhler, J. & Anderson, D. Induced technical change in energy and environmental modeling: analytic approaches and policy implications. Annu. Rev. Environ. Resour. 27, 271–308 (2002).

    Google Scholar 

  47. 47.

    Yu, C. F., Van Sark, W. G. J. H. M. & Alsema, E. A. Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects. Renew. Sustain. Energy Rev. 15, 324–337 (2011).

    Google Scholar 

  48. 48.

    Zheng, C. & Kammen, D. M. An innovation-focused roadmap for a sustainable global photovoltaic industry. Energ. Policy 67, 159–169 (2014).

    Google Scholar 

  49. 49.

    Nemet, G. F. Beyond the learning curve: factors influencing cost reductions in photovoltaics. Energ. Policy 34, 3218–3232 (2006).

    Google Scholar 

  50. 50.

    Gallagher, K. S., Grübler, A., Kuhl, L., Nemet, G. & Wilson, C. The energy technology innovation system. Annu. Rev. Environ. Resour. 37, 137–162 (2012).

    Google Scholar 

  51. 51.

    Jamasb, T. Technical change theory and learning curves: patterns of progress in energy technologies. Energ. J. 28, 51–71 (2006).

    Google Scholar 

  52. 52.

    Nagy, B., Farmer, J. D., Bui, Q. M. & Trancik, J. E. Statistical basis for predicting technological progress. PLoS ONE 8, e52669 (2013).

    CAS  Google Scholar 

  53. 53.

    Moore, G. E. Cramming more components onto integrated circuits. Electronics 38, 114 (1965).

    Google Scholar 

  54. 54.

    Wright, T. P. Factors affecting the cost of airplanes. J. Aeronaut. Sci. 3, 122–128 (1936).

    Google Scholar 

  55. 55.

    Clarke, L., Weyant, J. & Edmonds, J. On the sources of technological change: what do the models assume? Energy Econ. 30, 409–424 (2008).

    Google Scholar 

  56. 56.

    Azar, C. & Dowlatabadi, H. Review of technical change in assessment of climate policy. Annu. Rev. Energy Environ. 24, 513–544 (1999).

    Google Scholar 

  57. 57.

    Gambhir, A., Sandwell, P. & Nelson, J. The future costs of OPV – a bottom-up model of material and manufacturing costs with uncertainty analysis. Sol. Energy Mater. Sol. Cells 156, 49–58 (2016).

    CAS  Google Scholar 

  58. 58.

    Creutzig, F. et al. The underestimated potential of solar energy to mitigate climate change. Nat. Energy 2, 17140 (2017).

    Google Scholar 

  59. 59.

    Sussams, L. & Leaton, J. Expect the Unexpected: The Disruptive Power of Low-carbon Technology (Carbon Tracker Initiative, Imperial College London, 2017); https://www.imperial.ac.uk/media/imperial-college/grantham-institute/public/publications/collaborative-publications/Expect-the-Unexpected_CTI_Imperial.pdf

  60. 60.

    Nykvist, B. & Nilsson, M. Rapidly falling costs of battery packs for electric vehicles. Nat. Clim. Change 5, 100–103 (2015).

    Google Scholar 

  61. 61.

    Kavlak, G., McNerney, J. & Trancik, J. E. Evaluating the causes of cost reduction in photovoltaic modules. Energ. Policy 123, 700–710 (2018).

    Google Scholar 

  62. 62.

    Krey, V. et al. Looking under the hood: a comparison of techno-economic assumptions across national and global integrated assessment models. Energy 172, 1254–1267 (2018).

    Google Scholar 

  63. 63.

    Current and Future Cost of Photovoltaics: Long-term Scenarios for Market Development, System Prices and LCOE of Utility-Scale PV Systems (Fraunhofer ISE, 2015).

  64. 64.

    The Power to Change: Solar and Wind Cost Reduction Potential to 2025 (International Renewable Energy Agency, 2016).

  65. 65.

    Schröder, A. et al. Current and Prospective Costs of Electricity Generation until 2050 (DIW Berlin, German Institute for Economic Research, 2013).

  66. 66.

    2019 ATB. U.S. Department of Energy https://atb.nrel.gov/electricity/2019/ (2019).

  67. 67.

    Vaidyula, M. & Hood, C. Accounting for Baseline Targets in NDCs: Issues and Options for Guidance (OECD/IEA, 2018).

  68. 68.

    UK Department for Business Energy and Industrial Strategy (BEIS). UK becomes first major economy to pass net zero emissions law. Gov.uk https://www.gov.uk/government/news/uk-becomes-first-major-economy-to-pass-net-zero-emissions-law (2019).

  69. 69.

    Riahi, K. et al. Locked into Copenhagen pledges — implications of short-term emission targets for the cost and feasibility of long-term climate goals. Technol. Forecast. Soc. Change 90, 8–23 (2015).

    Google Scholar 

  70. 70.

    Krey, V., Luderer, G., Clarke, L. & Kriegler, E. Getting from here to there — energy technology transformation pathways in the EMF27 scenarios. Climatic Change 123, 369–382 (2014).

    Google Scholar 

  71. 71.

    Dessens, O., Anandarajah, G. & Gambhir, A. Limiting global warming to 2 °C: what do the latest mitigation studies tell us about costs, technologies and other impacts? Energy Strateg. Rev. 13–14, 67–76 (2016).

    Google Scholar 

  72. 72.

    van Vliet, J. et al. The impact of technology availability on the timing and costs of emission reductions for achieving long-term climate targets. Climatic Change 123, 559–569 (2014).

    Google Scholar 

  73. 73.

    Lempert, R. J. & Collins, M. T. Managing the risk of uncertain threshold responses: comparison of robust, optimum, and precautionary approaches. Risk Anal. 27, 1009–1026 (2007).

    Google Scholar 

  74. 74.

    Lamontagne, J. R. et al. Large ensemble analytic framework for consequence-driven discovery of climate change scenarios. Earth’s Future 6, 488–504 (2018).

    Google Scholar 

  75. 75.

    Lempert, R. Scenarios that illuminate vulnerabilities and robust responses. Climatic Change 117, 627–646 (2013).

    Google Scholar 

  76. 76.

    Lempert, R. in Decision Making under Deep Uncertainty: From Theory to Practice (eds Marchau, V. et al.) 23–52 (2019).

  77. 77.

    McCollum, D. L., Gambhir, A., Rogelj, J. & Wilson, C. Energy modellers should explore extremes more systematically in scenarios. Nat. Energy 5, 104–107 (2020).

    Google Scholar 

  78. 78.

    Hall, J. W. et al. Robust climate policies under uncertainty: a comparison of robust decision making and info-gap methods. Risk Anal. 32, 1657–1672 (2012).

    Google Scholar 

  79. 79.

    Lempert, R., Nakicenovic, N., Sarewitz, D. & Schlesinger, M. Characterizing climate-change uncertainties for decision-makers. An editorial essay. Climatic Change 65, 1–9 (2004).

    Google Scholar 

  80. 80.

    EU Reference Scenario 2016: Energy, Transport and GHG emissions: Trends to 2050 (European Commission, 2016).

  81. 81.

    Updated Energy and Emissions Projections 2018 (UK Department for Business Energy and Industrial Strategy, 2019).

  82. 82.

    Bodansky, D. The Paris climate change agreement: a new hope? Am. J. Int. Law 110, 1–43 (2016).

    Google Scholar 

  83. 83.

    Vinuales, J. in German Yearbook of International Law (eds von Arnauld, A. & von der Decken, K.) 11–45 (Duncker & Humblot, 2017).

  84. 84.

    Brunnermeier, S. B. & Cohen, M. A. Determinants of environmental innovation in US manufacturing industries. J. Environ. Econ. Manage. 45, 278–293 (2003).

    Google Scholar 

  85. 85.

    Taylor, M. R., Rubin, E. S. & Hounshell, D. A. Effect of government actions on technological innovation for SO2 control. Environ. Sci. Technol. 37, 4527–4534 (2003).

    CAS  Google Scholar 

  86. 86.

    Palmer, K. & Jaffe, A. B. Environmental regulation and innovation: a panel data study. Rev. Econ. Stat. 79, 610–619 (1997).

    Google Scholar 

  87. 87.

    Grubb, M. J., Hope, C. & Fouquet, R. Climatic implications of the Kyoto Protocol: the contribution of international spillover. Climatic Change 54, 11–28 (2002).

    Google Scholar 

  88. 88.

    Weber, C. et al. Mitigation scenarios must cater to new users. Nat. Clim. Change 8, 845–848 (2018).

    Google Scholar 

  89. 89.

    DeCarolis, J. et al. Formalizing best practice for energy system optimization modelling. Appl. Energy 194, 184–198 (2017).

    Google Scholar 

  90. 90.

    Iyer, G. & Edmonds, J. Interpreting energy scenarios. Nat. Energy 3, 357–358 (2018).

    Google Scholar 

  91. 91.

    Strachan, N., Fais, B. & Daly, H. Reinventing the energy modelling–policy interface. Nat. Energy 1, 16012 (2016).

    Google Scholar 

  92. 92.

    Peace, J. & Weyant, J. White Paper on Insights not Numbers: the Appropriate use of Economic Models (Pew Center on Global Climate Change, 2008).

Download references

Acknowledgements

N.G. was supported by the Natural Environment Research Council (NERC) (grant no. NE/L002515/1) as well as the Department for Business, Energy and Industrial Strategy (BEIS). A.G. and A.H. acknowledge support from the H2020 European Commission Project PARIS REINFORCE (grant no. 820846). N.G. thanks the Science and Solutions for a Changing Planet Doctoral Training Partnership at the Grantham Institute for support during their PhD studies. We thank J. Rogelj and S. Dietz for insightful comments on an earlier draft. The authors take sole responsibility for the final content of the Perspective.

Author information

Affiliations

Authors

Contributions

N.G. and A.G. conceived of the initial theme for the Perspective. N.G. wrote the paper. A.G., A.H. and T.N. supported in the development of the arguments and editing of the paper.

Corresponding author

Correspondence to Neil Grant.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Hadi Dowlatabadi, Vanessa Schweizer and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Grant, N., Hawkes, A., Napp, T. et al. The appropriate use of reference scenarios in mitigation analysis. Nat. Clim. Chang. 10, 605–610 (2020). https://doi.org/10.1038/s41558-020-0826-9

Download citation