CCS (carbon dioxide capture and storage) is an issue which has received increasing attention in the debate on climate change over the last several years because of its relative technical simplicity and very large potential in reducing carbon dioxide emissions. The absence of secondary benefits and uncertainties associated with this approach, however, would require analysts to conduct fine cost-benefit comparisons vis-à-vis other mitigation options. The paper is to provide a perspective on future cost-benefit discussions of CCS by highlighting the optimality of CCS use viewed as a non-renewable resource with a limited capacity. Scarcity of CCS (storage) capacity should involve a shadow price which could raise CCS's effective price - this is a fair assumption given the technological assessments of CCS so far, but no economic study has explicitly investigated this characteristic before. By using a simple analytical dynamic optimization model, we examine the optimal paths of CCS use, CCS's real price inclusive of the shadow price, and their difference from the operational price. A particular implication of the model is that if all else is equal, the shadow price of CCS could make the technology relatively less attractive than renewable energy due to CCS's reliance on scarce reservoirs and the resultant shadow value. This serves as a justification for giving differentiated incentives to different CO2 reduction options: more precisely, more encouragement should be given to renewable energy in comparison to CCS.
Carbon dioxide capture and storage (CCS) climate change energy dynamic optimization