Abstract
Under the UN Paris Agreement, countries committed to limiting global warming to well below 2 °C and to actively pursue a 1.5 °C limit. Yet, according to the 2018 Economics Nobel laureate William Nordhaus, these targets are economically suboptimal or unattainable and the world community should aim for 3.5 °C in 2100 instead. Here, we show that the UN climate targets may be optimal even in the Dynamic Integrated Climate–Economy (DICE) integrated assessment model, when appropriately updated. Changes to DICE include more accurate calibration of the carbon cycle and energy balance model, and updated climate damage estimates. To determine economically ‘optimal’ climate policy paths, we use the range of expert views on the ethics of intergenerational welfare. When updates from climate science and economics are considered jointly, we find that around three-quarters (or one-third) of expert views on intergenerational welfare translate into economically optimal climate policy paths that are consistent with the 2 °C (or 1.5 °C) target.
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Data availability
The data that support the plots within this paper and other findings of this study are available in the Source data provided with this paper.
Code availability
All code used to produce the analysis is available at the following repository: https://www.openicpsr.org/openicpsr/project/119395/version/V1/view/ under a Creative Commons 4.0 license. Details of implementation can be found in the Supplementary Information.
Change history
31 March 2021
A Correction to this paper has been published: https://doi.org/10.1038/s41558-021-01021-w
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Acknowledgements
We thank G. Asheim, P. Courtois, M. Cropper, F. Diekert, S. Dietz, P. Ferraro, D. Garrick, T. Goeschl, C. Gollier, A. Gouldson, B. Harstad, C. Hepburn, H. Holtermann, M. Kotchen, S. Lewandowsky, J. Marotzke, K. Nyborg, B. O’Neill, G. Perino, M. Persson, B. Pizer, W. Rickels, M.-C. Riekhof, C. Traeger, M. Weitzman and S. Yeh for helpful discussions and A. Mahler for research assistance. The views expressed in this paper are those of the authors alone. M.A.D. was supported by the DFG under Germany’s Excellence Strategy (EXC 2037 and CLICCS) project no. 390683824, contribution to the CEN of Universität Hamburg. F.N. is grateful for financial support from CREE, Oslo Centre for Research on Environmentally Friendly Energy (Norwegian Research Council no. 209698) and NATCOOP (European Research Council no. 678049). C.A. is grateful for financial support from Carl Bennet AB Foundation. T.S. and D.J.A.J. acknowledge support from MISTRA Carbon Exit and also for T.S. the Biodiversity and Ecosystem Services in a Changing Climate Consortium.
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M.A.D., M.C.F., B.G., M.C.H. and F.N. conceived the study on DICE focusing on the role of discounting and the damage function, which merged with parallel work on the role of the carbon cycle, the EBM and non-CO2 forcers in DICE developed by C.A. and D.J.A.J. at a workshop organized by T.S. in Gothenburg. M.C.H. performed the numerical modelling, data analysis and graphical representation of results with substantive input from D.J.A.J. and close feedback from M.A.D. and F.N. The writing of the manuscript was led by M.A.D., B.G., M.C.H. and F.N. with substantive input from all other authors.
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Extended data
Extended Data Fig. 1 Optimal dynamics for atmospheric carbon under Nordhaus discounting.
The black line depicts the standard DICE 2016R2 result; the red line shows the updated optimal dynamics for atmospheric carbon for the case with the updated carbon cycle model but without considering other updates.
Extended Data Fig. 2 Optimal dynamics for atmospheric temperature change from 1850–1900 levels under Nordhaus discounting.
The black line depicts the standard DICE 2016R2 result; the red line shows the optimal path resulting from the updated EBM without considering other updates.
Extended Data Fig. 3 Optimal economic damages from temperature increases under Nordhaus discounting.
The black line depicts the standard DICE 2016R2 result. Without considering other updates, the red line shows the economic damages as a fraction of global GDP based on the preferred specification in Howard and Sterner (2017)28.
Extended Data Fig. 4 Exogenous path for non-CO2 forcers.
The black line depicts the standard DICE 2016R2 assumption; the red line shows the updated path based on the REMIND SSP2.6 scenario.
Extended Data Fig. 5 Nordhaus DICE 2016R2 with an updated carbon cycle.
a shows each expert’s value judgements on the rate of pure time preference and inequality aversion. The triangle indicates the position implied by the choice of discount parameters in Nordhaus (2018a) and the blue square the median expert’s view social discounting. b–d depict the 95 (grey-shaded area) and 66 (blue-shaded area) percentile ranges in terms of experts’ value judgements for three climate policy measures: the social cost of CO2 (in US$ per ton), industrial emissions (in gigatons of CO2) and global mean temperature increases from 1850–1900 levels (in degrees Celsius). They also compare climate policy pathways implied by Nordhaus’ discounting parameters (black line) to those resulting from the median expert’s view (blue line) and the median expert path (green line).
Extended Data Fig. 6 Nordhaus DICE 2016R2 with updated carbon cycle and EBM.
a shows each expert’s value judgements on the rate of pure time preference and inequality aversion. The triangle indicates the position implied by the choice of discount parameters in Nordhaus (2018a) and the blue square the median expert’s view social discounting. b–d depict the 95 (grey-shaded area) and 66 (blue-shaded area) percentile ranges in terms of experts’ value judgements for three climate policy measures: the social cost of CO2 (in US$ per ton), industrial emissions (in gigatons of CO2) and global mean temperature increases from 1850–1900 levels (in degrees Celsius). They also compare climate policy pathways implied by Nordhaus’ discounting parameters (black line) to those resulting from the median expert’s view (blue line) and the median expert path (green line).
Extended Data Fig. 7 Nordhaus DICE 2016R2 with updated carbon cycle, EBM and temperature–damage relationship.
a shows each expert’s value judgments on the rate of pure time preference and inequality aversion. The triangle indicates the position implied by the choice of discount parameters in Nordhaus (2018a) and the blue square the median expert’s view social discounting. b–d depict the 95 (grey-shaded area) and 66 (blue-shaded area) percentile ranges in terms of experts’ value judgements for three climate policy measures: the social cost of CO2 (in US$ per ton), industrial emissions (in gigatons of CO2) and global mean temperature increases from 1850–1900 levels (in degrees Celsius). They also compare climate policy pathways implied by Nordhaus’ discounting parameters (black line) to those resulting from the median expert’s view (blue line) and the median expert path (green line).
Extended Data Fig. 8 Nordhaus DICE 2016R2 with updated carbon cycle, EBM, temperature–damage relationship and non-CO2 forcing.
a shows each expert’s value judgments on the rate of pure time preference and inequality aversion. The triangle indicates the position implied by the choice of discount parameters in Nordhaus (2018a) and the blue square the median expert’s view social discounting. b–d depict the 95 (grey-shaded area) and 66 (blue-shaded area) percentile ranges in terms of experts’ value judgements for three climate policy measures: the social cost of CO2 (in US$ per ton), industrial emissions (in gigatons of CO2) and global mean temperature increases from 1850–1900 levels (in degrees Celsius). They also compare climate policy pathways implied by Nordhaus’ discounting parameters (black line) to those resulting from the median expert’s view (blue line) and the median expert path (green line).
Extended Data Fig. 9 Nordhaus DICE 2016R2 with updated carbon cycle, EBM, temperature–damage relationship, non-CO2 forcing and NETs available by 2050.
a shows each expert’s value judgments on the rate of pure time preference and inequality aversion. The triangle indicates the position implied by the choice of discount parameters in Nordhaus (2018a) and the blue square the median expert’s view social discounting. b–d depict the 95 (grey-shaded area) and 66 (blue-shaded area) percentile ranges in terms of experts’ value judgements for three climate policy measures: the social cost of CO2 (in US$ per ton), industrial emissions (in gigatons of CO2) and global mean temperature increases from 1850–1900 levels (in degrees Celsius). They also compare climate policy pathways implied by Nordhaus’ discounting parameters (black line) to those resulting from the median expert’s view (blue line) and the median expert path (green line).
Extended Data Fig. 10 Effects of each sequential model update on optimal climate policy paths including 95-percentile ranges.
The figure shows how each expert’s value judgements on the pure rate of time preference and inequality aversion translates into the optimal temperature change by 2100 from 1850–1900 levels (a), the years to decarbonization (b) and the social cost of carbon in 2020 (c) for each sequential update to DICE considered in this paper. Starting from the DICE 2016R2 Baseline (b) we change the carbon cycle (CC), second the EBM, third the temperature–damage relationship (d), fourth the exogenous path for non-CO2 forcing (nCO2), fifth the availability of negative emissions technologies (NET) and sixth the technologically feasible speed of decarbonization (feas). The figure depicts the 66 (boxplot) and 95 (whiskers) percentile ranges. The triangle indicates the optimal path that is consistent with the Nordhaus choice of discount parameters (2018a), the blue square reflects the median expert’s view on intergenerational fairness, and the green bar the path implied by the median path.
Supplementary information
Supplementary Information
Supplementary Figs. 1–3 and discussion.
Supplementary Data
Extended data for Supplementary Figs. 1–3.
Source data
Source Data Fig. 2
Climate policy pathways in the updated climate–economy model DICE.
Source Data Fig. 3
Effects of each sequential model update on optimal climate policy paths.
Source Data Extended Data Fig. 1
Optimal dynamics for atmospheric carbon under Nordhaus’ discounting.
Source Data Extended Data Fig. 2
Optimal dynamics for atmospheric temperature change from 1850 to 1900 levels under Nordhaus’ discounting.
Source Data Extended Data Fig. 3
Optimal economic damages from temperature increases under Nordhaus’ discounting.
Source Data Extended Data Fig. 4
Exogenous path for non-CO2 forcers.
Source Data Extended Data Fig. 5
Nordhaus’ DICE 2016R2 with an updated carbon cycle.
Source Data Extended Data Fig. 6
Nordhaus’ DICE 2016R2 with updated carbon cycle and EBM.
Source Data Extended Data Fig. 7
Nordhaus’ DICE 2016R2 with updated carbon cycle, EBM and temperature–damage relationship based on ref. 28.
Source Data Extended Data Fig. 8
Nordhaus’ DICE 2016R2 with updated carbon cycle, EBM, temperature–damage relationship and non-CO2 forcing.
Source Data Extended Data Fig. 9
Nordhaus’ DICE 2016R2 with updated carbon cycle, EBM, temperature–damage relationship, non-CO2 forcing and negative emissions technologies available by 2050.
Source Data Extended Data Fig. 10
Effect of each sequential model update on climate policy paths including 95th percentile ranges.
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Hänsel, M.C., Drupp, M.A., Johansson, D.J.A. et al. Climate economics support for the UN climate targets. Nat. Clim. Chang. 10, 781–789 (2020). https://doi.org/10.1038/s41558-020-0833-x
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DOI: https://doi.org/10.1038/s41558-020-0833-x
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