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A multi-model analysis of long-term emissions and warming implications of current mitigation efforts

Nature Climate Change volume 11, pages 1055–1062 (2021)Cite this article

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Abstract

Most of the integrated assessment modelling literature focuses on cost-effective pathways towards given temperature goals. Conversely, using seven diverse integrated assessment models, we project global energy CO2 emissions trajectories on the basis of near-term mitigation efforts and two assumptions on how these efforts continue post-2030. Despite finding a wide range of emissions by 2050, nearly all the scenarios have median warming of less than 3 °C in 2100. However, the most optimistic scenario is still insufficient to limit global warming to 2 °C. We furthermore highlight key modelling choices inherent to projecting where emissions are headed. First, emissions are more sensitive to the choice of integrated assessment model than to the assumed mitigation effort, highlighting the importance of heterogeneous model intercomparisons. Differences across models reflect diversity in baseline assumptions and impacts of near-term mitigation efforts. Second, the common practice of using economy-wide carbon prices to represent policy exaggerates carbon capture and storage use compared with explicitly modelling policies.

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Fig. 1: Global energy CO2 emissions and temperature estimates.
Fig. 2: Decomposition of global energy CO2 emissions.
Fig. 3: Final energy consumption by fuel and by sector.
Fig. 4: CCS in carbon-price-only scenarios and in main scenarios.

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Data availability

The datasets40 generated during, and analysed in, the current study are available from a public repository (https://doi.org/10.5281/zenodo.5562199). Source data are provided with this paper.

Code availability

The code for the analysis in this paper is available upon request to the corresponding author. The code availability for the individual models used in this paper varies and contact should be made to individual modelling groups. The GCAM model is available for download from https://github.com/JGCRI/gcam-core. Detailed model documentation for all seven models is available online at https://www.i2am-paris.eu/detailed_model_doc.

Change history

  • 08 December 2021

    There were errors in the Fig. 1 Source Data initially presented online. The errors do not affect any conclusions in the paper, and the Source Data have been replaced as of 8 December 2021.

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Acknowledgements

I.S., A.A.-K., H.B., L.C., E.D., H.D., A.G., S.G., A.H., A.C.K., A.K., S.M., J.M., A.N., S.P., G.P.P., J.R., D.-J.v.d.V. and M.V. acknowledge support from the H2020 European Commission Project PARIS REINFORCE (grant no. 820846). 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).

Author information

Authors and Affiliations

  1. CICERO Center for International Climate Research, Oslo, Norway

    Ida Sognnaes & Glen P. Peters

  2. Grantham Institute for Climate Change and the Environment, Imperial College London, London, UK

    Ajay Gambhir, Neil Grant, Alexandre C. Köberle, Shivika Mittal & Joeri Rogelj

  3. Basque Centre for Climate Change (BC3), Leioa, Spain

    Dirk-Jan van de Ven & Jorge Moreno

  4. Energy Policy Unit, School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece

    Alexandros Nikas & Haris Doukas

  5. Climate Change Policy Group, Centre for Atmospheric Science, University of Cambridge, Cambridge, UK

    Annela Anger-Kraavi

  6. Cambridge Econometrics, Cambridge, UK

    Ha Bui

  7. RFF-CMCC European Institute on Economics and the Environment (EIEE), Venice, Italy

    Lorenza Campagnolo & Elisa Delpiazzo

  8. Department of Environmental Sciences, Informatics and Statistics, Ca’Foscari University of Venice, Venice, Italy

    Lorenza Campagnolo & Elisa Delpiazzo

  9. Euro-Mediterranean Center on Climate Change (CMCC), Venice, Italy

    Lorenza Campagnolo & Elisa Delpiazzo

  10. Department of Chemical Engineering, Imperial College London, London, UK

    Sara Giarola & Adam Hawkes

  11. Institute of Economic Forecasting of the Russian Academy of Sciences, Moscow, Russia

    Andrey Kolpakov

  12. École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

    Sigit Perdana & Marc Vielle

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

    Joeri Rogelj

Authors
  1. Ida Sognnaes
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Contributions

I.S. and G.P.P. coordinated the protocol for scenarios, which were designed by all authors, with notable contributions from L.C., H.D., A.G., S.G., A.C.K., S.M., A.N., S.P., J.R., D.-J.v.d.V. and M.V.; A.G., S.G., S.M., A.N. and D.-J.v.d.V. coordinated the harmonization protocol; all authors were involved in the model analysis, with notable contributions from D.-J.v.d.V., J.M. (GCAM), A.G., A.C.K., N.G., S.M. (TIAM), S.G., A.H. (MUSE), A.K. (FortyTwo), S.P., M.V. (GEMINI), L.C., E.D. (ICES), A.A.-K. and H.B. (E3ME). I.S. and G.P.P. compiled and analysed the results and created the figures, with feedback from all other authors. I.S. coordinated the conception and writing of the paper; all authors provided feedback and contributed to writing the paper.

Corresponding author

Correspondence to Ida Sognnaes.

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The authors declare no competing interests.

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

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Extended data

Extended Data Fig. 1 Carbon price scenario implementation.

a, Implementation of CP_Price scenarios. First, current policies are explicitly implemented to 2030, and the resulting emissions in 2030 are recorded. Second, models are re-run to reach the same levels of emissions as in the previous step using a carbon price (C1) alone. Third, scenarios are extended post-2030 by growing the carbon price (C1) with GDP per capita. The resulting emissions pathways (P1(t)) are recorded. Fourth, models are re-run with current policies explicitly implemented to 2030, and as constant or minimum bounds on effort post-2030. The emissions pathways achieved in the previous step (P1(t)) are implemented as upper bounds on emissions. b, Implementation of NDC_Price scenarios follows the implementation of CP_Price scenarios, except for the first step. First, current policies are explicitly implemented to 2030. Then, the emissions levels achieved in 2030 in each model region are compared with NDC targets. When additional effort is required to achieve NDC targets, this is implemented on top of current policies. See Supplementary Text 2 for the full scenario protocol.

Supplementary information

Supplementary Information

Supplementary Figs. 1–11, Tables 1–4, Text 1–5 and references.

Supplementary Data

Inventory of current policies used in the analysis.

Source data

Source Data Fig. 1

Data for Fig. 1.

Source Data Fig. 2

Data for Fig. 2.

Source Data Fig. 3

Data for Fig. 3.

Source Data Fig. 4

Data for Fig. 4.

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Sognnaes, I., Gambhir, A., van de Ven, DJ. et al. A multi-model analysis of long-term emissions and warming implications of current mitigation efforts. Nat. Clim. Chang. 11, 1055–1062 (2021). https://doi.org/10.1038/s41558-021-01206-3

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