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The Use of CCS in Global Carbon Management: Simulation with the DICE Model

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  • Daiju Narita

Abstract

This study attempts a numerical simulation of potential CCS (carbon dioxide capture and storage) use by using a modified version of the DICE (Dynamic Integrated model on Climate and Economy) model (Nordhaus, 1994; Nordhaus and Boyer, 2000). In DICE, CO2 emissions are controlled to the extent in which a hypothetical optimal carbon tax justifies CO2 reduction by firms: in our analysis, CCS is used when the optimal tax level is higher than the price of CCS. The analysis assesses the economic optimality of CCS use with a range of different assumptions. The simulation particularly focuses on the difference of results originating from two sets of general assumptions on climate change modeling, reflecting the current debate on the economics of climate change (see for example, Heal, 2008): (1) Parameterization of the standard DICE; (2) Alternative assumptions whose hints are drawn from Stern (2007). In the standard DICE cases, the model calculation shows that at the price level of $25/tCO2 ($92/tC), CCS is introduced around in the middle of the twenty-first century. With the alternative assumptions (e.g., near-zero discount rate), CCS begins to be utilized massively earlier in the century. The two sets of results lead to contrasting policy implications on the future CCS use; this is particularly problematic in the CCS context since its benefits are not always clear-cut (e.g., limitedness of secondary benefits besides CO2 reduction, uncertainties about the validity of technology itself). Settlement of the current intellectual debate on the economics of climate change would greatly benefit the debate on the role of CCS as well

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Bibliographic Info

Paper provided by Kiel Institute for the World Economy in its series Kiel Working Papers with number 1440.

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Length: 41 pages
Date of creation: Aug 2008
Date of revision:
Handle: RePEc:kie:kieliw:1440

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Keywords: Carbon capture and storage (CCS); climate change; energy; integrated assessment models; dynamic optimization;

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References

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  1. Reyer Gerlagh & Bob van der Zwaan, 2006. "Options and Instruments for a Deep Cut in CO2 Emissions: Carbon Dioxide Capture or Renewables, Taxes or Subsidies?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 25-48.
  2. Thomas Sterner & U. Martin Persson, 2008. "An Even Sterner Review: Introducing Relative Prices into the Discounting Debate," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 2(1), pages 61-76, Winter.
  3. Minh Ha-Duong & David Keith, 2003. "Carbon storage: the economic efficiency of storing CO2 in leaky reservoirs," Post-Print halshs-00003927, HAL.
  4. McFarland, J. R. & Reilly, J. M. & Herzog, H. J., 2004. "Representing energy technologies in top-down economic models using bottom-up information," Energy Economics, Elsevier, vol. 26(4), pages 685-707, July.
  5. Riahi, Keywan & Rubin, Edward S. & Taylor, Margaret R. & Schrattenholzer, Leo & Hounshell, David, 2004. "Technological learning for carbon capture and sequestration technologies," Energy Economics, Elsevier, vol. 26(4), pages 539-564, July.
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Cited by:
  1. Soren Lindner & Sonja Peterson & Wilhelm Windhorst, 2010. "An economic and environmental assessment of carbon capture and storage (CCS) power plants: a case study for the City of Kiel," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 53(8), pages 1069-1088.

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