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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]

A novel two-stage multi-criteria decision making (MCDM) method is proposed with the aim to select the most sustainable hydrogen production technology (HPT) by considering the preference information on both attributes and alternatives. In the first stage of the method, the initial sustainability ranking of the alternative HPTs was achieved by using the FBWM (Fuzzy Best-Worst Method) to determine the weights of the criteria and the fuzzy TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method to prioritize the sustainability of alternative HPTs. While, in the second stage, a novel Preference Ranking Linear Programming Method (PRLPM) was used to acquire the final sustainability ranking according to the alternative preference information by following the principle of the outranking method. The proposed method was illustrated by a case study with 8 HTPs, demonstrating that the developed two-stage MCDM method can reflect the alternative preference of the decision-maker more accurately for selecting the most preferred alternative among various HTPs. • The MCDM framework divides the sustainability decision-making into two stages. • Fuzzy best-worst method and fuzzy TOPSIS were used in the first stage. • A novel method based on preference information on alternatives is proposed. • The framework combines preference information on attributes and alternatives. [ABSTRACT FROM AUTHOR]

Sustainability is an important and difficult consideration for the stakeholders/decision-makers when planning a biofuel supply network. In this paper, a Mixed-Integer Non-linear Programming (MINLP) model was developed with the aim to help the stakeholders/decision-maker to select the most sustainable design. In the proposed model, the emergy sustainability index of the whole biodiesel supply networks in a life cycle perspective is employed as the measure of the sustainability, and multiple feedstocks, multiple transport modes, multiple regions for biodiesel production and multiple distribution centers can be considered. After describing the process and mathematic framework of the model, an illustrative case was studied and demonstrated that the proposed methodology is feasible for finding the most sustainable design and planning of biodiesel supply chains. [ABSTRACT FROM AUTHOR]