Formalizing an integrated decision-making model for the risk assessment of carbon capture, utilization, and storage projects: From a sustainability perspective

Abstract

Climate change exacerbated by carbon emissions is a major challenge faced by countries worldwide. China has envisioned achieving a carbon peak by 2030 and carbon neutrality by 2060. Carbon capture, utilization, and storage (CCUS), an emerging technology, is capable of reducing carbon emissions. Existing theoretical research has paid little attention to comprehensive risk assessments for CCUS projects from a sustainability viewpoint. Therefore, this study formalizes an integrated decision-making model for the risk assessment of CCUS projects. An indicator system consisting of environmental, social, economic, governance and technological sustainability dimensions was developed to assess the risk of CCUS projects. Furthermore, a multiattribute group decision-making process was modeled in intuitionistic fuzzy (IF) and linguistic (LIN) environments, both of which are interconvertible. To automate the risk assessment process for different CCUS project contexts, an integrated decision prototype programmed in Microsoft Excel 2016 was designed. Then, two case studies from the Shengli Power Plant CCUS project were conducted to validate the integrated decision-making model. A risk assessment table and risk assessment chart were leveraged to analyze, visualize, and rank the decision alternatives according to their risk performance. The results show that the post-combustion capture technology is selected as the optimal alternative option in three capture technologies; Of the four storage sites, site A is selected as the optimal alternative option. The result of carbon capture technology is in line with the real decision made by Shengli Power Plant, which proves the validity of the model. The optimal option is the same in both IF and LIN environments, which shows the consistency of the model. Theoretically, an integrated decision-making model not only contributes to assessing the risk of CCUS projects through the lens of sustainable development but advances group decision-making modeling by identifying experts’ preferences for obtaining effective evaluation results. Practically, this study could help stakeholders comprehensively and promptly evaluate the risk performance of CCUS projects before making development decisions regarding sustainability.