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Over the past decade, carbon capture and storage (CCS) has moved from the planning phase to experimental phase (e.g., Alabama Gulf Coast-Plant Barry and Illinois Basin-Decatur), but has yet to be implemented at a commercial scale from an Electric Utility Generating Unit (EGU). Barriers to commercial-scale deployment of CCS include concerns regarding potential risks and financial liability related to human health, safety, the environment, and business interruption. Although the probability of a release may be small, prudent risk management requires estimates of the funds required to remediate or compensate for harm, should a release occur. The analytic tools exist to estimate dollar values of potential risks. Such estimates are a function of location, plant design (fuel source, technology), and must be estimated on a site-specific basis. This paper applies a stochastic Monte Carlo model (“CCSvt Model”) that estimates financial consequences arising from potential human health, safety, environmental and business interruption risks (events) associated with CCS, in light of their anticipated site-specific likelihood and magnitude. The authors contend that use of the CCSvt Model, and corresponding results, foster a best practice understanding of the potential risks and financial liabilities associated with proposed CCS projects. In the authors’ view, the results of the CCSvt Model can contribute to a more productive public dialogue regarding CCS, improved siting of CCS projects, and ultimately support the commercial-scale deployment of CCS- technology. The authors conclude that the CCSvt Model is sufficiently flexible in design that it can be adapted to estimate damages distribution curves for myriad types of CCS projects, scaled for plant design and geographic location. As a proof of concept, the authors apply the CCSvt Model to the Alabama Gulf Coast-Plant Barry pilot project in Mobile, Alabama. [ABSTRACT FROM AUTHOR]

Abstract: Carbon Capture and Storage (CCS) represents a potentially effective means of addressing climate change. However, CCS processes create a suite of risks, including possibly injury to private and public sector interests, which will continue beyond the operational life of the project. Concerns regarding potential damages and attendant financial liability remain a barrier to commercial-scale deployment of CCS. The public dialogue on ‘liability’ as it relates to CCS has been clouded by a failure to clearly define what is at risk, and whether the consequences of such risks are material from a financial perspective. Focus on anecdotal references has contributed to unreasonable expectations and misunderstanding with respect to the amount and timing of funds necessary for the responsible deployment of CCS. Analytic evaluation of the range of potential impacts and calculation of financial consequences can illuminate: (1) the dollar amounts that need to be managed; (2) the set of circumstances under which amounts will present; and (3) the time frame over which these dollars will be needed. This paper applies an analytic framework drawn from damages estimation methodologies used in comparable contexts and incorporates risk-based probabilistic modeling to assist stakeholders in evaluating the potential consequences of CO2 migration at three candidate CCS sites. Specifically, it presents preliminary, order-of-magnitude estimates for potential public human health impacts associated with the operational phase of CCS activities at three proposed, non-selected USDOE FutureGen sites: (1) Tuscola, Illinois; (2) Jewett, Texas; and (3) Odessa, Texas. Attendant analyses applying the same methodology currently are underway to value damages associated with environmental resources, e.g., ground water, and atmospheric releases of CO2, as well as damages associated with the post-operational period. [Copyright &y& Elsevier]

Abstract: This paper explores the mismatch between the widely held public policy view of the long-term risk profile for carbon dioxide (CO2) storage with the emerging science and engineering of CO2 storage. We review the key issues of fit, interplay, and scalability associated with a trust fund funded by a hypothetical $ 1/ton CO2 tipping fee for each ton of CO2 stored in the United States under WRE450 and WRE550 climate policies. Left to grow unchecked, this hypothetical tipping fee fund would accumulate hundreds of billions to trillions of dollars before it would be expected to pay out claims caused by potential damage arising from CO2 storage. The authors conclude there is no intrinsic value in creating a trust fund predicated solely on collecting a tipping fee. Rather than mitigating the financial consequences of long-term CCS risks, this analysis suggests a blanket $ 1/ton CO2 tipping fee may increase the probability and frequency of long-term risk by eliminating financial incentives for sound operating behavior and site selection criteria–contribute to moral hazard. At a minimum, effective use of a trust fund requires: (1) strong oversight regarding site selection and fund management, and (2) a clear process by which the fund is periodically valued and funds collected are mapped to the risk profile of the pool of covered CCS sites. Without appropriate checks and balances, there is no a priori reason to believe that the amount of funds held in trust will map to the actual amount of funds needed to address long-term care expenses and delimited compensatory damages. [Copyright &y& Elsevier]

Abstract: Geologic sequestration (GS) holds promise as a safe and effective approach for addressing climate change. However, concern about potential “liability” associated with GS often is cited as a significant barrier to project deployment. However, the authors contend that the term “liability” is poorly defined and conflates concerns about the uncertainty in the timing and magnitude of potential damages with the call for long-term stewardship of certified closed sites. This paper offers an analytic framework predicated on the use of risk-based probabilistic modeling to assist stakeholders in evaluating the potential environmental, human health and financial consequences of GS projects. Use of this framework will inform siting decisions for specific GS projects and provide maximum loss values and probabilistic estimates of expected loss values that can inform policy discussions addressing the “liability” issue. [Copyright &y& Elsevier]