Optimal carbon mitigation strategy under non-linear feedback effects and in the presence of permafrost release trigger hazard

  • Ram RanjanEmail author
Original Article


The threat of release of methane sequestered in the circumpolar Arctic regions of the world creates the possibility of triggering additional feedback effects from the terrestrial and the deep ocean systems which could potentially add large amounts of carbon (C) into the atmosphere. This paper analyses the implications for C mitigation policy under the threats of a substantial permafrost methane release. Several insights emerge from the analysis. First, the presence of non-linear feedbacks creates a bifurcation zone in the C emissions-stock space, on one side of which large accumulations of atmospheric C materialize leading to significant damages. Second, the bifurcation line does not have a steep slope, implying that it would be possible to avoid falling on the wrong side of this zone even if the current atmospheric stock of C were higher than what they are today. Third, when the release of permafrost C is uncertain, there is benefit in reducing anthropogenic C more than what would be optimal under a certain release of the same. Fourth, higher abatement cost scenarios do not necessarily imply significantly reduced abatement efforts. On the contrary, abatement efforts, which are only reduced marginally under this scenario, ensure that long run carbon path is stabilized. This is done in order to avoid incurring substantial costs of abatement in the future when non-linear feedback effects kick in.


Permafrost methane Climate change catastrophe Non-linear feedback effects Carbon abatement Catastrophe Hazard model 



This work benefited from numerous meetings and discussions held with Larry Karp over model formulation and empirical calibration. Any remaining flaws are author’s alone.


  1. Archer D, Buffett B (2005) Time Dependent Response of the Global Ocean Clathrate Reservoir to Climatic and Anthropogenic Forcing. Geochemistry, GeoPhysics and GeoSystems, Vol. 6, No. 3Google Scholar
  2. Detlef P, Van Vuuren J, Love ES, Gohar L, Hof AF, Hope C, Warren R, Meinshausen M, Plattner GK (2011) How well do integrated assessment models simulate climate change? Clim Chang 104:255–285. doi: 10.1007/s10584-009-9764-2 CrossRefGoogle Scholar
  3. Dietz S, Stern N (2008) Why economic analysis supports strong action on climate change: a response to the stern Review’s critics. Rev Environ Econ Policy 2(1):94–113CrossRefGoogle Scholar
  4. Dutta K, Schuur EAG, Neff JC, Zimov SA (2006) Potential C release from permafrost soils of Northeast Siberia. Glob Chang Biol 12:2336–2351CrossRefGoogle Scholar
  5. Enkvist PA, T Naucler, J Rosander (2007) A cost curve for greenhouse gas reduction, The McKinsey quarterly number 1, McKinsey & Company, pp 35–45Google Scholar
  6. Friedlingstein P, Bopp L, Ciais P, Dufresne J-L, Fairhead L, Le Treut H, Monfray P, Orr J (2001) Positive feedback between future climate change and the C cycle. Geophys Res Lett 28:1543–1546CrossRefGoogle Scholar
  7. Harvey LD, Huang Z (1995) Evaluation of the potential impact of methane clathrate destabilization on future global warming. J Geophys Res 100(No. D2):2905–2976CrossRefGoogle Scholar
  8. IPCC (2007a) Climate Change 2007: Working Group I: The Physical Science Basis, url:
  9. IPCC (2007b) Climate Change 2007: Working Group II: Impacts Adaptation and Vulnerability, url:
  10. Kriegler E, Hallc JW, Helda H, Dawson R, Schellnhubera HJ (2009) Imprecise probability assessment of tipping points in the climate system. PNAS 106(13):5041–5046CrossRefGoogle Scholar
  11. Keller K, Yohe G, Schlesinger M (2008) Managing the risks of climate thresholds: uncertainties and information needs. An editorial essay. Clim Chang 91:5–10CrossRefGoogle Scholar
  12. Koven CD, Ringeval B, Friedlingstein P, Ciais P, Cadule P, Khvorostyanov D, Krinner G, Tarnocai C (2011) Permafrost Carbon-Climate Feedbacks Accelerate Global Warming. Proceedings of the National Academy of the Sciences of the United States of America 108(36):14769–14774CrossRefGoogle Scholar
  13. Lawrence DM, AG Slater (2005) A projection of severe near-surface permafrost degradation during the 21st century. Geophysical research letter, p 32. doi: 10.1029/2005GL025080
  14. Lenton TM (2011) Early warming of climate tipping points. Nature Climate Change 1:201–209. doi: 10.1038/nclimate1143 CrossRefGoogle Scholar
  15. Mastrandrea MD, Schneider SH (2001) Integrated assessment of abrupt climatic changes. Climate Policy 1:433–449Google Scholar
  16. Nordhaus WD (1993) Rolling the dice: an optimal transition path for controlling greenhouse gases. Resource and Energy Economics 15(1):27–50CrossRefGoogle Scholar
  17. Nordhaus WD (1999) The economic impacts of abrupt climate change, paper prepared for a meeting on abrupt climate change: The role of oceans, atmosphere, and the polar regions, National Research Council. Available at:
  18. Reagan MT, G Moridis (2008) Dynamic response of oceanic hydrate deposits to ocean temperature change. J Geophys Res, p 113. doi: 10.1029/2008JC004938
  19. Scheneider B, M Latif, A Schmittner (2007) Evaluation of different methods to assess model projections of the future evolution of the atlantic meridional overturning circulation. J Clim 20(10):2121-2132Google Scholar
  20. Schimel J (2004) Playing scales in the methane cycle: from microbial ecology to the globe. PNAS 101(34):12400–12401CrossRefGoogle Scholar
  21. Schuur EAG, Bockheim J, Canadell J, Euskirchen E, Field CB, Goryachkin SV, Hagemann S, Kuhry P, Lafleur P, Lee H, Mazhitova G, Nelson FE, Rinke A, Romanovsky V, Shiklomanov N, Tarnocai C, Venevsky S, Vogel JG, Zimov SA (2008) Vulnerability of permafrost C to climate change: implications for the global C cycle. BioScience 58:701–714CrossRefGoogle Scholar
  22. Schneider von Deimling T, Meinshausen M, Levermann A, Huber V, Frieler K, Lawrence DM, Brovkin V (2012) Estimating the near-surface permafrost-carbon feedback on global warming. Biogeosciences 9:649–665. doi: 10.5194/bg-9-649-2012 CrossRefGoogle Scholar
  23. Schuur EAG, Abbot B (2011) Climate change: high risk permafrost thaw. Nature 480:32–33. doi: 10.1038/480032a CrossRefGoogle Scholar
  24. Tol RSJ (2008) The social cost of C: trends, outliers and catastrophes. Economics: the open access, Open-Assessment E-Journal, Vol. 2, Available at
  25. Waelbroeck C, Monfray P, Oechel WC, Hastings SJ, Vourlitis GL (1997) The impact of thawing on the C dynamics of Tundra. Geophys Res Lett 24:229–232CrossRefGoogle Scholar
  26. Weitzman M (2009) On modeling and interpreting the economics of catastrophic climate change. Rev Econ Stat 91(1):1–19CrossRefGoogle Scholar
  27. Weitzman M (2010) What is the damages function for global warming—and what difference might it make? Clim Chang Econ 1(1):57–69CrossRefGoogle Scholar
  28. Weyant JP (2008) A critique of the stern Review’s mitigation cost analyses and integrated assessment, symposium: the economics of climate change: the stern review and its critics. Rev Environ Econ Policy 2(1):77–93CrossRefGoogle Scholar
  29. Wright EL, Erickson JD (2003) Incorporating catastrophes into integrated assessment: science, impacts and adaptation. Clim Chang 57(3):265–286CrossRefGoogle Scholar
  30. Zimov SA, Schuur EAG, Chapin FS III (2006) Permafrost in the global C budget. Science 312:1612–1613CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Graduate School of the EnvironmentMacquarie UniversityMacquarie ParkAustralia

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