A dynamic model for optimally phasing in CO 2 capture and storage infrastructure

Richard S. Middleton, Michael Kuby, Ran Wei, Gordon N. Keating, Rajesh J. Pawar

Research output: Contribution to journalArticlepeer-review

69 Scopus citations


CO 2 capture and storage (CCS) is a climate-change mitigation strategy that requires an investment of many billions of dollars and tens of thousands of miles of dedicated CO 2 pipelines. To be effective, scientists, stakeholders, and policy makers will have to understand how as well as when to deploy large-scale CCS infrastructure. This will require comprehensive modeling that takes into account detailed costs, engineering, and environmental concerns. We introduce a new and comprehensive model, SimCCS TIME, that is capable of spatially and temporally optimizing CO 2 management-capture, transport, and storage of large quantities of CO 2. The model minimizes CCS infrastructure costs while simultaneously deciding where, how much, and when to capture, transport, and store CO 2. We demonstrate the SimCCS TIME model using real data from the Texas panhandle. Results show that the model minimizes CCS costs, while meeting rising demand to capture and store CO 2, by gradually expanding the CCS network. The model identifies non-intuitive cost savings by overbuilding infrastructure in early time periods, and then fully utilizing this infrastructure in later years. Further, results show that there is significant benefit for planning a cooperative and integrated CCS system. Finally, we show how SimCCS TIME offers significant advantages over myopic models that cannot integrate infrastructure through time.

Original languageEnglish (US)
Pages (from-to)193-205
Number of pages13
JournalEnvironmental Modelling and Software
StatePublished - Nov 2012


  • CO capture and storage
  • Climate-change policy
  • Infrastructure modeling
  • Pipeline modeling
  • SimCCS
  • Spatiotemporal optimization

ASJC Scopus subject areas

  • Software
  • Environmental Engineering
  • Ecological Modeling


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