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A simple carbon cycle representation for economic and policy analyses

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  • Michael Glotter
  • Raymond Pierrehumbert
  • Joshua Elliott
  • Nathan Matteson
  • Elisabeth Moyer

Abstract

Integrated Assessment Models (IAMs) that couple the climate system and the economy require a representation of ocean CO 2 uptake to translate human-produced emissions to atmospheric concentrations and in turn to climate change. The simple linear carbon cycle representations in most IAMs are not however physical at long timescales, since ocean carbonate chemistry makes CO 2 uptake highly nonlinear. No linearized representation can capture the ocean’s dual-mode behavior, with initial rapid uptake and then slow equilibration over ∽10,000 years. In a business-as-usual scenario followed by cessation of emissions, the carbon cycle in the 2007 version of the most widely used IAM, DICE (Dynamic Integrated model of Climate and the Economy), produces errors of ∽2 ∘ C by the year 2300 and ∽6 ∘ C by the year 3500. We suggest here a simple alternative representation that captures the relevant physics and show that it reproduces carbon uptake in several more complex models to within the inter-model spread. The scheme involves little additional complexity over the DICE model, making it a useful tool for economic and policy analyses. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Michael Glotter & Raymond Pierrehumbert & Joshua Elliott & Nathan Matteson & Elisabeth Moyer, 2014. "A simple carbon cycle representation for economic and policy analyses," Climatic Change, Springer, vol. 126(3), pages 319-335, October.
  • Handle: RePEc:spr:climat:v:126:y:2014:i:3:p:319-335
    DOI: 10.1007/s10584-014-1224-y
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    References listed on IDEAS

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    1. Schultz, Peter A & Kasting, James F, 1997. "Optimal reductions in CO2 emissions," Energy Policy, Elsevier, vol. 25(5), pages 491-500, April.
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    8. Elisabeth J. Moyer & Mark D. Woolley & Nathan J. Matteson & Michael J. Glotter & David A. Weisbach, 2014. "Climate Impacts on Economic Growth as Drivers of Uncertainty in the Social Cost of Carbon," The Journal of Legal Studies, University of Chicago Press, vol. 43(2), pages 401-425.
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    Cited by:

    1. Nicolas Taconet & Céline Guivarch & Antonin Pottier, 2021. "Social Cost of Carbon Under Stochastic Tipping Points," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 78(4), pages 709-737, April.
    2. Timothy J Garrett & Matheus Grasselli & Stephen Keen, 2020. "Past world economic production constrains current energy demands: Persistent scaling with implications for economic growth and climate change mitigation," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-19, August.
    3. Louise Kessler, 2017. "Estimating The Economic Impact Of The Permafrost Carbon Feedback," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 1-23, May.
    4. Louise Kessler, 2015. "Estimating the economic impact of the permafrost carbon feedback," GRI Working Papers 219, Grantham Research Institute on Climate Change and the Environment.
    5. Manoussi, Vassiliki & Xepapadeas, Anastasios & Emmerling, Johannes, 2018. "Climate engineering under deep uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 94(C), pages 207-224.
    6. Christian Azar & Jorge García Martín & Daniel JA. Johansson & Thomas Sterner, 2023. "The social cost of methane," Climatic Change, Springer, vol. 176(6), pages 1-22, June.
    7. Elisabeth J. Moyer & Mark D. Woolley & Nathan J. Matteson & Michael J. Glotter & David A. Weisbach, 2014. "Climate Impacts on Economic Growth as Drivers of Uncertainty in the Social Cost of Carbon," The Journal of Legal Studies, University of Chicago Press, vol. 43(2), pages 401-425.

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