IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v81y2014icp192-204.html
   My bibliography  Save this article

Resolving or managing uncertainties for carbon capture and storage: Lessons from historical analogues

Author

Listed:
  • Watson, Jim
  • Kern, Florian
  • Markusson, Nils

Abstract

Carbon capture and storage (CCS) technologies are often highlighted as a crucial component of future low carbon energy systems in the UK and internationally. Whilst these technologies are now in the demonstration phase world-wide, they are still characterised by a range of technical, economic, policy, social and legal uncertainties. This paper applies a framework for the analysis of these uncertainties that was previously developed by the authors to a historical evidence base. This evidence base comprises nine case studies, each of which focuses on a technology that is partly analogous to CCS. The paper's analysis of these case studies examines the conditions under which the uncertainties concerned have been at least partly resolved, and what lessons can be drawn for CCS. The paper then uses the case study evidence to discuss linkages between the uncertainties in the analysis framework, and how these linkages differ from those that were originally expected. Finally, the paper draws conclusions for the methodological approach that has been used and for strategies to develop and deploy CCS technologies.

Suggested Citation

  • Watson, Jim & Kern, Florian & Markusson, Nils, 2014. "Resolving or managing uncertainties for carbon capture and storage: Lessons from historical analogues," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 192-204.
  • Handle: RePEc:eee:tefoso:v:81:y:2014:i:c:p:192-204
    DOI: 10.1016/j.techfore.2013.04.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162513000929
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2013.04.016?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Colpier, Ulrika Claeson & Cornland, Deborah, 2002. "The economics of the combined cycle gas turbine--an experience curve analysis," Energy Policy, Elsevier, vol. 30(4), pages 309-316, March.
    2. Reiner, D.M & Herzog, H.J, 2004. "Developing a set of regulatory analogs for carbon sequestration," Energy, Elsevier, vol. 29(9), pages 1561-1570.
    3. Grubler, Arnulf, 2010. "The costs of the French nuclear scale-up: A case of negative learning by doing," Energy Policy, Elsevier, vol. 38(9), pages 5174-5188, September.
    4. Rubin, Edward S. & Yeh, Sonia & Antes, Matt & Berkenpas, Michael & Davison, John, 2007. "Use of experience curves to estimate the future cost of power plants with CO2 capture," Institute of Transportation Studies, Working Paper Series qt46x6h0n0, Institute of Transportation Studies, UC Davis.
    5. Cowan, Robin, 1990. "Nuclear Power Reactors: A Study in Technological Lock-in," The Journal of Economic History, Cambridge University Press, vol. 50(3), pages 541-567, September.
    6. Markusson, Nils & Kern, Florian & Watson, Jim & Arapostathis, Stathis & Chalmers, Hannah & Ghaleigh, Navraj & Heptonstall, Philip & Pearson, Peter & Rossati, David & Russell, Stewart, 2012. "A socio-technical framework for assessing the viability of carbon capture and storage technology," Technological Forecasting and Social Change, Elsevier, vol. 79(5), pages 903-918.
    7. Hadjilambrinos, Constantine, 2000. "Understanding technology choice in electricity industries: a comparative study of France and Denmark," Energy Policy, Elsevier, vol. 28(15), pages 1111-1126, December.
    8. Rubin, Edward S & Taylor, Margaret R & Yeh, Sonia & Hounshell, David A, 2004. "Learning curves for environmental technology and their importance for climate policy analysis," Energy, Elsevier, vol. 29(9), pages 1551-1559.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dimitrios Mendrinos & Spyridon Karytsas & Olympia Polyzou & Constantine Karytsas & Åsta Dyrnes Nordø & Kirsti Midttømme & Danny Otto & Matthias Gross & Marit Sprenkeling & Ruben Peuchen & Tara Geerdin, 2022. "Understanding Societal Requirements of CCS Projects: Application of the Societal Embeddedness Level Assessment Methodology in Four National Case Studies," Clean Technol., MDPI, vol. 4(4), pages 1-15, September.
    2. Watson, Jim & Gross, Rob & Ketsopoulou, Ioanna & Winskel, Mark, 2015. "The impact of uncertainties on the UK's medium-term climate change targets," Energy Policy, Elsevier, vol. 87(C), pages 685-695.
    3. Kern, Florian & Gaede, James & Meadowcroft, James & Watson, Jim, 2016. "The political economy of carbon capture and storage: An analysis of two demonstration projects," Technological Forecasting and Social Change, Elsevier, vol. 102(C), pages 250-260.
    4. Torabi, Nooshin & Bekessy, Sarah A., 2015. "Bundling and stacking in bio-sequestration schemes: Opportunities and risks identified by Australian stakeholders," Ecosystem Services, Elsevier, vol. 15(C), pages 84-92.
    5. Jingjing Xie & Yujiao Xian & Guowei Jia, 2023. "An investigation into the public acceptance in China of carbon capture and storage (CCS) technology," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 28(5), pages 1-22, June.
    6. Themann, Dörte & Brunnengräber, Achim, 2021. "Using socio-technical analogues as an additional experience horizon for nuclear waste management A comparison of wind farms, fracking, carbon capture and storage (CCS) with a deep-geological nuclear w," Utilities Policy, Elsevier, vol. 70(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Neij, Lena, 2008. "Cost development of future technologies for power generation--A study based on experience curves and complementary bottom-up assessments," Energy Policy, Elsevier, vol. 36(6), pages 2200-2211, June.
    2. Hernandez-Negron, Christian G. & Baker, Erin & Goldstein, Anna P., 2023. "A hypothesis for experience curves of related technologies with an application to wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    3. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
    4. Muratori, Matteo & Ledna, Catherine & McJeon, Haewon & Kyle, Page & Patel, Pralit & Kim, Son H. & Wise, Marshall & Kheshgi, Haroon S. & Clarke, Leon E. & Edmonds, Jae, 2017. "Cost of power or power of cost: A U.S. modeling perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 861-874.
    5. Wu, X.D. & Yang, Q. & Chen, G.Q. & Hayat, T. & Alsaedi, A., 2016. "Progress and prospect of CCS in China: Using learning curve to assess the cost-viability of a 2×600MW retrofitted oxyfuel power plant as a case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1274-1285.
    6. Samadi, Sascha, 2018. "The experience curve theory and its application in the field of electricity generation technologies – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2346-2364.
    7. Lovering, Jessica R. & Yip, Arthur & Nordhaus, Ted, 2016. "Historical construction costs of global nuclear power reactors," Energy Policy, Elsevier, vol. 91(C), pages 371-382.
    8. van den Broek, Machteld & Berghout, Niels & Rubin, Edward S., 2015. "The potential of renewables versus natural gas with CO2 capture and storage for power generation under CO2 constraints," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 1296-1322.
    9. Yeh, Sonia & Rubin, Edward S., 2012. "A review of uncertainties in technology experience curves," Energy Economics, Elsevier, vol. 34(3), pages 762-771.
    10. Schmidt, Tobias S. & Battke, Benedikt & Grosspietsch, David & Hoffmann, Volker H., 2016. "Do deployment policies pick technologies by (not) picking applications?—A simulation of investment decisions in technologies with multiple applications," Research Policy, Elsevier, vol. 45(10), pages 1965-1983.
    11. Comello, Stephen & Reichelstein, Stefan, 2014. "Incentives for early adoption of carbon capture technology," Energy Policy, Elsevier, vol. 74(C), pages 579-588.
    12. Diaz-Maurin, François & Giampietro, Mario, 2013. "A “Grammar” for assessing the performance of power-supply systems: Comparing nuclear energy to fossil energy," Energy, Elsevier, vol. 49(C), pages 162-177.
    13. Leibowicz, Benjamin D. & Krey, Volker & Grubler, Arnulf, 2016. "Representing spatial technology diffusion in an energy system optimization model," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 350-363.
    14. Santhakumar, Srinivasan & Smart, Gavin & Noonan, Miriam & Meerman, Hans & Faaij, André, 2022. "Technological progress observed for fixed-bottom offshore wind in the EU and UK," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    15. Sascha Samadi, 2016. "A Review of Factors Influencing the Cost Development of Electricity Generation Technologies," Energies, MDPI, vol. 9(11), pages 1-25, November.
    16. Martin Junginger & Wilfried van Sark & André Faaij (ed.), 2010. "Technological Learning in the Energy Sector," Books, Edward Elgar Publishing, number 13741.
    17. Cristóbal, Jorge & Guillén-Gosálbez, Gonzalo & Kraslawski, Andrzej & Irabien, Angel, 2013. "Stochastic MILP model for optimal timing of investments in CO2 capture technologies under uncertainty in prices," Energy, Elsevier, vol. 54(C), pages 343-351.
    18. Elia, A. & Kamidelivand, M. & Rogan, F. & Ó Gallachóir, B., 2021. "Impacts of innovation on renewable energy technology cost reductions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    19. Li, Sheng & Zhang, Xiaosong & Gao, Lin & Jin, Hongguang, 2012. "Learning rates and future cost curves for fossil fuel energy systems with CO2 capture: Methodology and case studies," Applied Energy, Elsevier, vol. 93(C), pages 348-356.
    20. Santhakumar, Srinivasan & Meerman, Hans & Faaij, André, 2021. "Improving the analytical framework for quantifying technological progress in energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:81:y:2014:i:c:p:192-204. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.