PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
June 11, 2024ACS Sustainable Chemistry & Engineering47 citations

Comparative Evaluation of Carbon Capture, Utilization, and Storage (CCUS) Technologies Using Multi-Criteria Decision-Making Approaches

View Full Paper
ADAfshin Davarpanah

Key Points

Key points are not available for this paper at this time.

Abstract

In this study, we employ three multicriteria decision-making (MCDM) methods containing the analytic hierarchy process (AHP), the technique for order of preference by similarity to ideal solution (TOPSIS), and multiattribute utility theory (MAUT), to analyze and rank carbon capture, utilization, and storage (CCUS) technologies based on various criteria. The AHP analysis underscores carbon capture efficiency (CCE) and safety and risk management (SRM) as paramount for CCUS projects, closely followed by technological maturity (TM) and environmental impact (EI), with CCE having the highest priority, followed by SRM, TM, and EI. Conversely, TOPSIS highlights cryogenic processes as the most significant CCUS criterion, followed by membrane, adsorption, and absorption methods. On the other hand, MAUT ranks absorption technology as the most effective, followed by membrane, cryogenic, and adsorption methods, emphasizing its effectiveness in carbon capture based on overall utility scores. These divergent rankings underscore the complexity of MCDM methods in CCUS projects and emphasize the importance of considering multiple perspectives. By integrating insights from these methodologies, stakeholders can make informed decisions to enhance the effectiveness and sustainability of CCUS technologies, thereby contributing to global efforts to move the energy transition toward a low-carbon future.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Afshin Davarpanah (2024) studied this question.

synapsesocial.com/papers/68e6541cb6db6435875e2c64https://doi.org/10.1021/acssuschemeng.4c03025
Ask AI
Helpful
Bookmark
Share
View Full Paper