Global heating increases household and industrial energy use (for cooling) *especially in Australia* further increasing household energy bills

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Estimating a social cost of carbon for global energy consumption

Nature volume 598, pages 308–314 (2021)Cite this article

Abstract

Estimates of global economic damage caused by carbon dioxide (CO2) emissions can inform climate policy1,2,3. The social cost of carbon (SCC) quantifies these damages by characterizing how additional CO2 emissions today impact future economic outcomes through altering the climate4,5,6. Previous estimates have suggested that large, warming-driven increases in energy expenditures could dominate the SCC7,8, but they rely on models9,10,11 that are spatially coarse and not tightly linked to data2,3,6,7,12,13. Here we show that the release of one ton of CO2 today is projected to reduce total future energy expenditures, with most estimates valued between −US$3 and −US$1, depending on discount rates. Our results are based on an architecture that integrates global data, econometrics and climate science to estimate local damages worldwide. Notably, we project that emerging economies in the tropics will dramatically increase electricity consumption owing to warming, which requires critical infrastructure planning. However, heating reductions in colder countries offset this increase globally. We estimate that 2099 annual global electricity consumption increases by about 4.5 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in global mean surface temperature (GMST), whereas direct consumption of other fuels declines by about 11.3 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in GMST. Our finding of net savings contradicts previous research7,8, because global data indicate that many populations will remain too poor for most of the twenty-first century to substantially increase energy consumption in response to warming. Importantly, damage estimates would differ if poorer populations were given greater weight14.

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Data availability

The data for replicating the findings of this study are available on Zenodo at https://doi.org/10.5281/zenodo.5099834.

Code availability

The code for replicating the findings of this study is available on GitHub at https://github.com/ClimateImpactLab/energy-code-release-2020/.

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Acknowledgements

This project is an output of the Climate Impact Lab consortium that gratefully acknowledges funding from the Carnegie Corporation, Energy Policy Institute of Chicago (EPIC), the International Growth Centre, the National Science Foundation (SES1463644), the Sloan Foundation and the Tata Center for Development. T.C. acknowledges funding from the US Environmental Protection Agency Science To Achieve Results Fellowship (FP91780401). J.R. acknowledges funding from the H2020-MSCA-RISE project GEMCLIME-2020 GA number 681228. We thank L. Alcocer, T. Bearpark, T. Chong, Z. Delgerjargal, G. Dobbels, D. Gergel, R. Goyal, S. Greenhill, I. Higuera-Mendieta, D. Hogan, A. Hussain, T. Kulczycki, R. Li, B. Malevich, M. Norman, O. Nwabuikwu, S. Annan-Phan, C. Schwarz, N. Sharma, J. Simcock, Y. Song, E. Tenezakis, J. Wang and J. Yang for research assistance during all stages of this project, and we thank S. Anderson, J. Chang, M. Landín and T. Mayer for project management. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for the CMIP, and we thank the climate modelling groups (listed in Extended Data Fig. 2b) for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank seminar participants at the UC Berkeley Energy Camp, the University of Chicago EPIC Lunch Series and the Mansueto Institute Lunch Colloquium, LSE Workshop in Environmental Economics, International Energy Workshop, International Workshop on Empirical Methods in Energy Economics, the University of Michigan Sustainability and Development Conference, the Berkeley/Harvard/Yale Environmental and Energy Economics Seminar, the NBER EEE Summer Institute, the UCLA Luskin Center for Innovation Climate Adaptation Research Symposium and the Federal Reserve Bank of Richmond Climate Change Economics Workshop for helpful comments.

Author information

Affiliations

  1. Energy Policy Institute, University of Chicago, Chicago, IL, USA

    Ashwin Rode & Andrew Hultgren

  2. Bren School of Environmental Science and Management, University of California, Santa Barbara, Santa Barbara, CA, USA

    Tamma Carleton

  3. National Bureau of Economic Research, Cambridge, MA, USA

    Tamma Carleton, Michael Greenstone, Solomon Hsiang & Amir Jina

  4. Rhodium Group, New York, NY, USA

    Michael Delgado, Trevor Houser & Kelly E. McCusker

  5. Department of Economics, University of Chicago, Chicago, IL, USA

    Michael Greenstone & Andrew Hultgren

  6. Global Policy Laboratory, Goldman School of Public Policy, University of California, Berkeley, Berkeley, CA, USA

    Solomon Hsiang

  7. Harris School of Public Policy, University of Chicago, Chicago, IL, USA

    Amir Jina

  8. Department of Earth & Planetary Sciences, Rutgers University, New Brunswick, NJ, USA

    Robert E. Kopp

  9. Rutgers Institute of Earth, Ocean, and Atmospheric Sciences, Rutgers University, New Brunswick, NJ, USA

    Robert E. Kopp

  10. Department of Economics, Princeton University, Princeton, NJ, USA

    Ishan Nath

  11. School of Marine Science and Policy, University of Delaware, Newark, DE, USA

    James Rising

  12. Department of Atmospheric and Oceanic Sciences, Fudan University, Shanghai, China

    Jiacan Yuan

  13. Institute of Atmospheric Sciences, Fudan University, Shanghai, China

    Jiacan Yuan

  14. IRDR ICoE-RIG-WECEIPHE, Fudan University, Shanghai, China

    Jiacan Yuan

  15. Big Data Institute for Carbon Emission and Environmental Pollution, Fudan University, Shanghai, China

    Jiacan Yuan

Contributions

A.R., S.H., M.G., R.K., T.H., A.J., J.R., M.D. and T.C. conceived and planned the study. J.Y., K.E.M., M.D., R.K., A.R., A.J. and T.C. prepared the historical climate data. J.Y., K.E.M., M.D. and R.K. created and prepared the climate projection data. A.R., T.C., A.H., M.D., I.N. and T.H. prepared the energy data. A.R., T.C., A.H., I.N., A.J., J.R., S.H. and MG estimated energy–climate response functions. J.R. and A.R. computed projected impacts of future climate change. A.R., M.D., T.C., K.E.M., A.H., I.N., A.J., J.R., S.H. and M.G. constructed damage functions and computed partial social cost of carbon. A.R., S.H. and M.G. wrote the main text, A.R., T.C., A.J., M.D., J.R., J.Y. and K.M. wrote the supplementary materials, and all authors edited.

Corresponding authors

Correspondence to Ashwin Rode or Solomon Hsiang.

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