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Purpose: Carbon capture and storage (CCS) has been well recognized as an effective approach to reducing CO2 emissions, but the emergence of various CCS technologies has resulted in the challenge of selecting the most sustainable alternative. This study aims to develop a mathematical framework to evaluate the sustainability of different CCS technologies determe the best-performing one and identify the key affecting criteria. Methods: The mathematical framework was developed by combining the multi-criteria decision-making (MCDM) approach with the life cycle assessment (LCA), which can overcome the difficulty to obtain the criteria data, especially for the environmental aspect. A novel weighting method of grey correlation weighting (GCW), which is more applicable to the criteria data obtained by LCA, is presented for objectively weighting the criteria and identifying key criteria with the consideration of criteria interaction. The sustainability of different CCS technologies is ranked by using the method of similarity to the ideal solution (TOPSIS). The effectiveness of the developed mathematical framework is verified by a case study with 9 different CCS technologies. Results: The results show that the CCS process with the pre-combustion capture technology by using CaO as the absorbent is the most sustainable one. For both pre-combustion and post-combustion capture technologies, it is critical to improve their environmental performance for enhancing their sustainability, while for increasing the sustainability of the oxyfuel combustion technology, the key is to reduce the "capital cost". The validity of the developed framework was demonstrated through sensitivity analysis and comparison with conventional MCDM methods. Conclusions: The developed LCA-MCDM methodology is effective to assess the sustainability of various CCS technologies. The results of the sustainability evaluation using the methodology demonstrated that the environmental performance of the CCS technologies has the largest impact on sustainability, while if the cost of the air separation process can be addressed, the sustainability of oxyfuel combustion technologies can be greatly improved. [ABSTRACT FROM AUTHOR]

A multicriteria decision-making methodology for the sustainability prioritization of industrial systems is proposed. The methodology incorporates a fuzzy Analytic Hierarchy Process method that allows the users to assess the soft criteria using linguistic terms. A fuzzy Analytic Network Process method is used to calculate the weights of each criterion, which can tackle the interdependencies and interactions among the criteria. The Preference Ranking Organization Method for Enrichment Evaluation approach is used to prioritize the sustainability sequence of the alternative systems. Moreover, a sensitivity analysis method was developed to investigate the most critical and sensitive criteria. The developed methodology was illustrated by a case study to rank the sustainability of five alternative hydrogen production technologies. The advantages of the developed methodology over the previous approaches were demonstrated by comparing the results determined by the proposed framework with those determined using the pervious approaches. [ABSTRACT FROM AUTHOR]

Hydrogen has attracted considerable attention as a clean and renewable energy carrier to potentially solve the increasingly serious problems of energy security and environmental pollution. As it can be produced from diverse feedstocks by using a variety of technologies, this study aims to develop a novel multi-criteria decision making (MCDM) mathematical framework for the sustainability assessment of multiple hydrogen production technologies (HPTs). In the proposed method, the criteria weights were determined by combining the grey relational analysis (GRA) and DEMATEL method, which can realize a relatively objective weighting process by considering the causal relationships among criteria. Moreover, the alternatives are also ranked by using the GRA approach to attain the grey correlation coefficients as indicators, which measures the closeness of the corresponding alternative with the ideal scheme. Finally, the developed MCDM method was illustrated by the sustainability prioritization of 9 HPTs. • A MCDM method was established for more objective sustainability assessment of HPTs. • An GRA-incorporated DEMATEL method was developed for determining the criteria weight. • The GRA approach was adopted for ranking the sustainability of HPTs. [ABSTRACT FROM AUTHOR]

Hydrogen has emerged as one of the most promising players in the future energy system for a better life due to multiple advantages, it is important to identify the most sustainable technology for producing hydrogen among several alternatives. This study aims to propose a novel multi-criteria decision making (MCDM) framework for prioritizing hydrogen production technologies under data uncertainties by combining the methods of interval best-worst method (IBWM), interval entropy technique (IET), and interval best-worst projection (IBWP). In the framework, the IBWM and the IET methods were integrated to offer a comprehensive weighting result by capturing both the uncertain subjective judgments and uncertain objective information regarding the importance of multiple criteria; the IBWP approach was introduced to offer a rigorous ranking result by aggregating both the absolute performance and relative balance of the alternatives regarding the multi-criteria system in uncertain conditions. An illustrative case considering five hydrogen production technologies was studied to verify the feasibility of the proposed framework, while results comparisons and sensitivity analysis were implemented to indicate the necessities and advantages of the developed MCDM methods. • A novel framework was proposed for selecting hydrogen production technology. • Uncertainties were incorporated into the sustainability assessment framework. • The interval BWM and the interval entropy were combined for weighting the criteria. • A novel IBWP method was developed for ranking technology alternatives. [ABSTRACT FROM AUTHOR]