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The costs of achieving climate targets and the sources of uncertainty

Nature Climate Change volume 10, pages 329–334 (2020)Cite this article

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Abstract

Effective climate policy requires information from various scientific disciplines. Here, we construct a metamodel from climate and integrated assessment models that assesses the emissions budget, costs and uncertainty sources of achieving temperature targets. By calibrating to the model-based literature range, the metamodel goes beyond the parametric uncertainty of individual models. The resulting median estimates for the cumulative abatement costs (at 5% discount rate) for 2 °C and 1.5 °C targets are around US$15 trillion and US$30 trillion, but estimates vary over a wide range (US$10–100 trillion for the 1.5 °C target). The sources determining this uncertainty depend on the climate target stringency. Climate system uncertainty dominates at high warming levels, but uncertainty in emissions reductions costs dominates for the Paris Agreement targets. In fact, costs differences between different socio-economic development paths can be larger than the difference in median estimates for the 2 °C and 1.5 °C targets. This simple metamodel helps to explore implications of scenario uncertainty and identify research priorities.

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Fig. 1: Key relationships in the literature relevant to the costs of achieving climate targets.
Fig. 2: Application of the metamodel.
Fig. 3: The relative contribution of single factors in the overall variance in mitigation costs.

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Data availability

The data used to assess the impact of non-CO2 emissions and the mitigation costs that support the findings of this study are publicly available online at the scenario databases hosted by IIASA: https://tntcat.iiasa.ac.at/SspDb/dsd (ref. 4), https://tntcat.iiasa.ac.at/AR5DB/dsd (ref. 2) and https://data.ene.iiasa.ac.at/iamc-1.5c-explorer/#/workspaces (ref. 18). The data for each figure are available at the PBL/IMAGE website.

Code availability

Model codes are available at https://github.com/kvanderwijst/variancedecomposition-IAM (https://doi.org/10.5281/zenodo.3633944).

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Acknowledgements

The research presented in this paper benefitted from funding under the European Union’s Horizon 2020 Framework Programme for Research and Innovation under grant agreement nos. 82112 (NAVIGATE) and 641816 (CRESCENDO). In addition, C.J. was supported by the Joint UK BEIS/Defra Met Office Hadley Centre Climate Programme (grant no. GA01101).

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Authors and Affiliations

  1. PBL Netherlands Environmental Assessment Agency, the Hague, the Netherlands

    D. P. van Vuuren, Kaj-Ivar van der Wijst, Stijn Marsman, Maarten van den Berg & Andries F. Hof

  2. Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, the Netherlands

    D. P. van Vuuren, Kaj-Ivar van der Wijst & Andries F. Hof

  3. Mathematical Institute, Utrecht University, Utrecht, the Netherlands

    Kaj-Ivar van der Wijst

  4. Met Office Hadley Centre, Exeter, UK

    Chris D. Jones

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  1. D. P. van Vuuren
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Contributions

D.P.v.V., K.-I.v.d.W. and S.M. designed the metamodel and the experiments. All authors contributed to the elaboration of the model and the writing of the article.

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Correspondence to D. P. van Vuuren.

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The authors declare no competing interests.

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

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Supplementary information

Supplementary Information

Supplementary Discussions 1–4, Figs. 1–14 and Table 1.

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van Vuuren, D.P., van der Wijst, KI., Marsman, S. et al. The costs of achieving climate targets and the sources of uncertainty. Nat. Clim. Chang. 10, 329–334 (2020). https://doi.org/10.1038/s41558-020-0732-1

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