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Optimal Spatial Deployment of CO2 Capture and Storage Given a Price on Carbon

Author

Listed:
  • Michael J. Kuby

    (School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ, USA, mikekuby@asu.edu)

  • Jeffrey M. Bielicki

    (Center for Science, Technology, and Public Policy, Humphrey School, University of Minnesota, Minneapolis, MN, USA)

  • Richard S. Middleton

    (Los Alamos National Laboratory, Earth and Environmental Sciences, Los Alamos National Laboratory, Los Alamos, NM, USA)

Abstract

Carbon dioxide capture and storage (CCS) links together technologies that separate carbon dioxide (CO 2 ) from fixed point source emissions and transport it by pipeline to geologic reservoirs into which it is injected underground for long-term containment. Previously, models have been developed to minimize the cost of a CCS infrastructure network that captures a given amount of CO 2 . The CCS process can be costly, however, and large-scale implementation by industry will require government regulations and economic incentives. The incentives can price CO 2 emissions through a tax or a cap-and-trade system. This paper extends the earlier mixed-integer linear programming model to endogenously determine the optimal quantity of CO 2 to capture and optimize the various components of a CCS infrastructure network, given the price per tonne to emit CO 2 into the atmosphere. The spatial decision support system first generates a candidate pipeline network and then minimizes the total cost of capturing, transporting, storing, or emitting CO 2 . To illustrate how the new model based on CO 2 prices works, it is applied to a case study of CO 2 sources, reservoirs, and candidate pipeline links and diameters in California.

Suggested Citation

  • Michael J. Kuby & Jeffrey M. Bielicki & Richard S. Middleton, 2011. "Optimal Spatial Deployment of CO2 Capture and Storage Given a Price on Carbon," International Regional Science Review, , vol. 34(3), pages 285-305, July.
    • Handle: RePEc:sae:inrsre:v:34:y:2011:i:3:p:285-305
    DOI: 10.1177/0160017610397191
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    References listed on IDEAS

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    Cited by:

    1. Massol, Olivier & Tchung-Ming, Stéphane & Banal-Estañol, Albert, 2018. "Capturing industrial CO2 emissions in Spain: Infrastructures, costs and break-even prices," Energy Policy, Elsevier, vol. 115(C), pages 545-560.
    2. Jeffrey M. Bielicki & Guillaume Calas & Richard S. Middleton & Minh Ha‐Duong, 2014. "National corridors for climate change mitigation: managing industrial CO 2 emissions in France," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 4(3), pages 262-277, June.
    3. Massol, Olivier & Tchung-Ming, Stéphane & Banal-Estañol, Albert, 2015. "Joining the CCS club! The economics of CO2 pipeline projects," European Journal of Operational Research, Elsevier, vol. 247(1), pages 259-275.
    4. Knoope, M.M.J. & Ramírez, A. & Faaij, A.P.C., 2015. "The influence of uncertainty in the development of a CO2 infrastructure network," Applied Energy, Elsevier, vol. 158(C), pages 332-347.
    5. Phillips, Benjamin R. & Middleton, Richard S., 2012. "SimWIND: A geospatial infrastructure model for optimizing wind power generation and transmission," Energy Policy, Elsevier, vol. 43(C), pages 291-302.
    6. Middleton, Richard S. & Eccles, Jordan K., 2013. "The complex future of CO2 capture and storage: Variable electricity generation and fossil fuel power," Applied Energy, Elsevier, vol. 108(C), pages 66-73.
    7. Sun, Liang & Chen, Wenying, 2017. "Development and application of a multi-stage CCUS source–sink matching model," Applied Energy, Elsevier, vol. 185(P2), pages 1424-1432.

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