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

Carbon dioxide capture and storage (CCS) links together technologies that separate carbon dioxide (CO2) 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 CO2. The CCS process can be costly, however, and large-scale implementation by industry will require government regulations and economic incentives. The incentives can price CO2 emissions, through a tax or a cap-and-trade system, or involve the purchase of CO2 by oil companies for enhanced oil recovery from depleted oil fields. This paper extends the earlier mixed-integer linear programming model to endogenously determine the optimal quantity of CO2 to capture and optimize the various components of a CCS infrastructure network, given the prices to emit CO2 into the atmosphere or inject it into oil fields. The model minimizes the cost of capturing, transporting, storing, selling, or emitting CO2. The model is applied to a network of CO2 sources, CO2 reservoirs, and candidate CO2 pipeline links and diameters in California.