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The surprisingly inexpensive cost of state-driven emission control strategies

Nature Climate Change volume 11, pages 738–745 (2021)Cite this article

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Abstract

Traditionally, analysis of the costs of cutting greenhouse gas emissions has assumed that governments would implement idealized, optimal policies such as uniform economy-wide carbon taxes. Yet actual policies in the real world, especially in large federal governments, are often highly heterogeneous and vary in political support and administrative capabilities within a country. While the benefits of heterogeneous action have been discussed widely for experimentation and leadership, little is known about its costs. Focusing on the United States, we represent plausible variation (by more than a factor of 3) in the stringency of state-led climate policy in a process-based integrated assessment model (GCAM-USA). For a wide array of national decarbonization targets, we find that the nationwide cost from heterogeneous subnational policies is only one-tenth higher than nationally uniform policies. Such results hinge on two critical technologies (advanced biofuels and electricity) for which inter-state trade ameliorates the economic efficiencies that might arise with heterogeneous action.

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Fig. 1: State-level variations in public support for climate policy and its impact on carbon pricing under the Heterogeneous approach.
Fig. 2: Model-computed state-level carbon prices in 2050 to achieve a national target of 40% decarbonization by 2050 relative to 2005 under three subnational policy approaches.
Fig. 3: Reduction in energy-related CO2 emissions and carbon prices in 2050 in low- and high-supporting states.
Fig. 4: Reduction in energy-related CO2 emissions.
Fig. 5: Carbon mitigation cost in 2050 as a fraction of projected 2050 gross domestic product (GDP), by national mitigation effort (20–80% decarbonization, indicated as 20–80% D) and by subnational policy approach (Uniform, Hybrid and Heterogeneous).
Fig. 6: Sensitivity analysis of carbon mitigation cost for two levels of national mitigation effort.

Data availability

The datasets generated during and analysed in the current study are available from a public repository (https://doi.org/10.5281/zenodo.5061357).

Code availability

The GCAM and GCAM-USA model are available for download from https://github.com/JGCRI/gcam-core. Detailed model documentation is available online at http://jgcri.github.io/gcam-doc/gcam-usa.html.

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Acknowledgements

We thank B. Keohane, D. Tingley, L. Stokes, J. Jenkins, K. Fisher-Vanden and participants at seminars at Penn State University (September 2019), Johns Hopkins University (September 2019) and Princeton University (November 2019) on related themes. W.P. received a summer research stipend from Penn State School of International Affairs. G.I., M.B. and J.A.E. received support from the Global Technology Strategy Program. D.G.V. draws funding, in part, from the Electric Power Research Institute, a nonprofit R&D organization focused on the electric power sector. D.G.V. is also supported partly by donations to the Scripps Institutional Oceanography for research on emergency responses to climate change.

Author information

Authors and Affiliations

  1. School of International Affairs and Department of Civil and Environmental Engineering, Pennsylvania State University, University Park, PA, USA

    Wei Peng

  2. Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, USA

    Gokul Iyer, Matthew Binsted & James A. Edmonds

  3. School of the Environment, Yale Program on Climate Change Communication, Yale University, New Haven, CT, USA

    Jennifer Marlon

  4. Center for Global Sustainability, School of Public Policy, University of Maryland, College Park, MD, USA

    Leon Clarke

  5. School of Global Policy and Strategy, University of California San Diego, La Jolla, CA, USA

    David G. Victor

  6. Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA

    David G. Victor

  7. Mechanical and Aerospace Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA

    David G. Victor

  8. The Brookings Institution, Washington, DC, USA

    David G. Victor

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Contributions

W.P., G.I. and D.G.V conceived and designed the study. W.P., G.I. and M.B performed the model simulations with data input from J.M. W.P. analysed the data. W.P., G.I. and D.G.V wrote the manuscript with important input from all authors.

Corresponding author

Correspondence to Wei Peng.

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Competing interests

D.G.V. is a consultant to the shareholder group Engine No. 1. The other authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Aleh Cherp, Laurent Drouet 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.

Extended data

Extended Data Fig. 1 Reduction in energy-related CO2 emissions for four levels of national mitigation efforts under two subnational policy approaches.

Here we show the reduction in CO2 emissions in 2050 relative to 2005. The first and second rows show the results under the uniform and heterogeneous approach, respectively. Different colors of the bars show the mitigation in different economic sectors. The white numbers represent the percent contribution of electricity sector to total CO2 mitigation. Low, Medium and High represents the low-, medium-, and high-supporting states, respectively.

Extended Data Fig. 2 Net electricity trade in 2050 for 15 grid regions.

a, ‘80% Uniform’: 80% national decarbonization with the uniform approach; b, ‘80% Heterogeneous’: 80% national decarbonization with the heterogeneous approach; c, Changes in ‘80% Heterogeneous’ relative to ‘80% Uniform’. For a) and b), the background colors represent the net electricity export from a grid region (orange) or the net import into a grid region (blue). The electricity transmission patterns remain largely the same under these two subnational policy approaches. For c), the background colors represent the absolute differences in net electricity export (that is, generation minus demand) between these two approaches. The black numbers show the percent differences: the positive numbers indicate that a net exporting (importing) grid in “80% Uniform” further increases its export (import) in “80% Heterogeneous”, while the negative numbers indicate that a net exporting (importing) grid in “80% Uniform” reduces its export (import) in “80% Heterogeneous”. In other words, 13 out of the 15 grids increase their electricity trade with other grids under the Heterogeneous approach. The 15 electricity grid regions are presented in Supplementary Fig. 5.

Extended Data Fig. 3 CO2 sequestration by bioenergy with carbon capture and storage (BECCS) technology in 2050.

a, Total CO2 sequestration from BECCS; b, CO2 sequestration from BECCS for bioliquids production; c, CO2 sequestration from BECCS for electricity production. 20%-80% represent the levels of national mitigation effort. ‘U’ and ‘H’ represent Uniform and Heterogeneous policy approaches, respectively. Low, Medium and High represent low-, medium-, and high-supporting states.

Extended Data Fig. 4 Variations in state-level carbon intensity and mitigation costs to achieve 80% decarbonization nationally.

a, Carbon intensity in 2015; b, Reduction in carbon intensity in 2050 relative to 2015, to achieve 80% national decarbonization with uniform or heterogeneous approach; c, Mitigation cost in 2050 as a fraction of 2050 GDP, to achieve 80% national decarbonization with uniform or heterogeneous approach. All economic values are presented in US$2015.

Extended Data Fig. 5 Carbon mitigation costs for four levels of national mitigation efforts under alternative formations of policy heterogeneity.

Here we show the carbon mitigation cost in 2050 as a fraction of projected 2050 GDP, by three groups of states (low, medium and high-supporting states). ‘Uni’ stands for the uniform approach. Het, Het (Gov), Het (LN), Het (+range), Het (3 zero), Het (5 zero) and Het (AP) represent different heterogeneous approaches with detailed description in the Sensitivity Analysis section and Supplementary Methods. The inserted figure shows the contribution by low-, medium-, and high-supporting states to national total CO2 emissions in 201650.

Extended Data Fig. 6 Reduction in energy-related CO2 emissions when carbon capture and storage (CCS) technology is not available.

Here we show the reduction in energy-related CO2 emissions in 2050 relative to 2015 for: a, National total; b, Low-supporting states; c, Medium-supporting states; d, High-supporting states. Different colors of the bars represent different economic sectors. The white numbers represent the percent contribution of the electricity sector to total CO2 mitigation. 40% U – 40% decarbonization with uniform approach; 40% H – 40% decarbonization with heterogeneous approach; 80% U – 80% decarbonization with uniform approach; 80% H - 80% decarbonization with heterogeneous approach.

Supplementary information

Supplementary information

Supplementary Notes 1–4, Methods and Figs. 1–12.

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Peng, W., Iyer, G., Binsted, M. et al. The surprisingly inexpensive cost of state-driven emission control strategies. Nat. Clim. Chang. 11, 738–745 (2021). https://doi.org/10.1038/s41558-021-01128-0

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