A Multicriteria Decision Analysis Model and Risk Assessment Framework for Carbon Capture and Storage. Issue 9 (28th April 2014)

• Record Type: Journal Article
• Authors: Humphries Choptiany, John Michael; Pelot, Ronald
• Is Part Of: Risk analysis. Volume 34:Issue 9(2014)
• Page Start: 1720
• Page End: 1737
• Publication Date: 2014-04-28
• Subjects: Technology -- Risk assessment -- Periodicals; 658.403
• DOI: 10.1111/risa.12211
• Languages: English
• ISSNs: 0272-4332

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>Multicriteria decision analysis (MCDA) has been applied to various energy problems to incorporate a variety of qualitative and quantitative criteria, usually spanning environmental, social, engineering, and economic fields. MCDA and associated methods such as life‐cycle assessments and cost‐benefit analysis can also include risk analysis to address uncertainties in criteria estimates. One technology now being assessed to help mitigate climate change is carbon capture and storage (CCS). CCS is a new process that captures CO<sub>2</sub> emissions from fossil‐fueled power plants and injects them into geological reservoirs for storage. It presents a unique challenge to decisionmakers (DMs) due to its technical complexity, range of environmental, social, and economic impacts, variety of stakeholders, and long time spans. The authors have developed a risk assessment model using a MCDA approach for CCS decisions such as selecting between CO<sub>2</sub> storage locations and choosing among different mitigation actions for reducing risks. The model includes uncertainty measures for several factors, utility curve representations of all variables, Monte Carlo simulation, and sensitivity analysis. This article uses a CCS scenario example to demonstrate the development and application of the model based on data derived from published articles and publicly available sources. The model allows high‐level DMs to better understand project risks and the tradeoffs inherent in modern, complex energy decisions.</p> </abstract>