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Carbon capture and storage & the optimal path of the carbon tax

Author

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  • Lontzek, Thomas S.
  • Rickels, Wilfried

Abstract

In the presence of rising carbon concentrations more attention should be given to the role of the oceans as a sink for atmospheric carbon. We do so by setting up a simple dynamic global carbon cycle model with two reservoirs containing atmosphere and two ocean layers. The net flux between these reservoirs is determined by the relative reservoir size and therefore constitutes a more appropriate description of the carbon cycle than a proportional decay assumption. We exploit the specific feature of our model, the mixing of the carbon reservoirs, by allowing for a special form of carbon capture and storage: The capture of CO2 from the air and the sequestration of CO2 into the deep ocean reservoir. We study the socially optimal anthropogenic intervention of the global carbon cycle using a non-renewable resource stock. We find that this kind of carbon capture and storage facilitates achieving strict stabilization targets for the atmospheric carbon content. It accelerates the slow natural flux within the carbon cycle, and because of its temporary abatement character it dampens the overshooting of the atmospheric reservoir. Furthermore, we analyze the optimal paths of the carbon tax. The carbon tax shows to be inverted u-shaped but depending on the initial sizes of the reservoirs and the speed of carbon fluxes between the reservoirs we also find the optimal tax to be increasing, decreasing or u-shaped. Finally, we suggest to link the level of the carbon tax to the declining ability of the deep ocean to absorb atmospheric carbon.

Suggested Citation

  • Lontzek, Thomas S. & Rickels, Wilfried, 2008. "Carbon capture and storage & the optimal path of the carbon tax," Kiel Working Papers 1475, Kiel Institute for the World Economy (IfW Kiel).
  • Handle: RePEc:zbw:ifwkwp:1475
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    References listed on IDEAS

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    4. Wilfried Rickels & Thomas S. Lontzek, 2012. "Optimal global carbon management with ocean sequestration," Oxford Economic Papers, Oxford University Press, vol. 64(2), pages 323-349, April.
    5. Toman, Michael A. & Withagen, Cees, 2000. "Accumulative pollution, "clean technology," and policy design," Resource and Energy Economics, Elsevier, vol. 22(4), pages 367-384, October.
    6. McFarland, James R. & Herzog, Howard J., 2006. "Incorporating carbon capture and storage technologies in integrated assessment models," Energy Economics, Elsevier, vol. 28(5-6), pages 632-652, November.
    7. Edmonds, Jae & Clarke, John & Dooley, James & Kim, Son H. & Smith, Steven J., 2004. "Stabilization of CO2 in a B2 world: insights on the roles of carbon capture and disposal, hydrogen, and transportation technologies," Energy Economics, Elsevier, vol. 26(4), pages 517-537, July.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Grimaud, André & Rouge, Luc, 2014. "Carbon sequestration, economic policies and growth," Resource and Energy Economics, Elsevier, vol. 36(2), pages 307-331.
    2. Alain Jean-Marie & Michel Moreaux & Mabel Tidball, 2011. "Carbon sequestration in leaky reservoirs," Post-Print hal-00863230, HAL.
    3. John F. Raffensperger, 2020. "A price on warming with a supply chain directed market," Papers 2003.05114, arXiv.org, revised Mar 2021.

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    More about this item

    Keywords

    Exhaustible resource; CCS; ocean sinks; ocean sequestration; air capture; carbon tax; carbon cycle;
    All these keywords.

    JEL classification:

    • Q32 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - Exhaustible Resources and Economic Development
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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