A dynamic model for optimally phasing in CO2 capture and storage infrastructure

Environmental Modelling & Software, Volume 37, November 2012, Pages 193–205
A dynamic model for optimally phasing in CO2 capture and storage infrastructure
Richard S. Middleton a, Michael J. Kuby b, Ran Wei b, Gordon N. Keating a, Rajesh J. Pawar a
a Los Alamos National Laboratory, Earth and Environmental Sciences, Los Alamos, NM 87545, USA
b School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287, USA
Abstract
CO₂ 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 CO₂ pipelines. For these pipelines to be effective, scientists, stakeholders, and policy makers will have to understand how as well as when to deploy large-scale CCS infrastructure.
The effort requires comprehensive modeling that takes into account detailed costs, engineering, and environmental concerns. Authors present a novel comprehensive model called SimCCSTIME. It is capable of spatially and temporally optimizing CO₂ management—capture, transport, and storage of large quantities of CO₂. The SimCCSTIME model is demonstrated using actual data from the Texas panhandle. The model identifies non-intuitive cost savings by overbuilding infrastructure in early time periods, and then fully utilizing this infrastructure in later years.
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