Life cycle sustainability decision-support framework for CO2 chemical conversion technologies under uncertainties

[Display omitted] •Establishing a life cycle sustainability evaluation system from technical, economic, and environmental perspectives.•Proposing a novel integrated MCDM model to aggregate multi-dimensional sustainability performances.•Coping with the external and internal uncertainties in judgments...

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Published in:Energy conversion and management Vol. 288; p. 117113
Main Authors: Gao, Ruxing, Wang, Lei, Zhang, Leiyu, Zhang, Chundong, Liu, Tao, Jun, Ki-Won, Kim, Seok Ki, Gao, Ying, Zhao, Tiansheng, Wan, Hui, Guan, Guofeng
Format: Journal Article
Language:English
Published: Elsevier Ltd 15.07.2023
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ISSN:0196-8904, 1879-2227
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Abstract [Display omitted] •Establishing a life cycle sustainability evaluation system from technical, economic, and environmental perspectives.•Proposing a novel integrated MCDM model to aggregate multi-dimensional sustainability performances.•Coping with the external and internal uncertainties in judgments and decision-making.•Providing a well-informed benchmark to support the screening and selection of CO2 conversion technologies.•Exploring the improvement opportunities and limits for short- and mid-term implementation in industries. With the emergence of numerous CO2 chemical conversion technologies to simultaneously reduce CO2 emissions and produce value-added products, it is of great importance to compare their difference and select the most sustainable routes for future development. This study quantitatively evaluated the sustainability performances of 21 alternative CO2 conversion technologies from economic, technical, and environmental perspectives and developed a novel Multi-criteria Decision-making (MCDM) model to prioritize the alternatives. To cope with the external and internal uncertainties during the decision-making, Interval-Rough Numbers (IRNs) were firstly used to deal with subjective vagueness and information incompleteness involved in the group judgements unavoidably. Secondly, DEMATEL-ANP was employed based on IRNs to specify the correlation type and degree among diverse criteria for determining the global weights accurately. Lastly, a Vector-based Algorithm method was applied to measure the alternatives’ overall performance and figure out the final ranking scores of sustainability. The results revealed that CO2 to methane, urea, methanol, dimethyl ether, and acetic acid were the top five promising conversion technologies with the highest R&D priority over the next decades from a sustainability perspective. Moreover, a detailed sensitivity analysis of criteria weights was conducted to scrutinize the effectiveness of the ranking results and to validate the reliability of the new proposed MCDM model. Furthermore, in consideration of the complexity of future technological advance, market transformation, economic and social trends, this life cycle sustainability decision-support framework for CO2 conversion technologies provides a well-informed benchmark to support the screening and selection of candidate technologies including both the existing and emerging processes, and strategically explore the development opportunities and limits under uncertainties.
AbstractList [Display omitted] •Establishing a life cycle sustainability evaluation system from technical, economic, and environmental perspectives.•Proposing a novel integrated MCDM model to aggregate multi-dimensional sustainability performances.•Coping with the external and internal uncertainties in judgments and decision-making.•Providing a well-informed benchmark to support the screening and selection of CO2 conversion technologies.•Exploring the improvement opportunities and limits for short- and mid-term implementation in industries. With the emergence of numerous CO2 chemical conversion technologies to simultaneously reduce CO2 emissions and produce value-added products, it is of great importance to compare their difference and select the most sustainable routes for future development. This study quantitatively evaluated the sustainability performances of 21 alternative CO2 conversion technologies from economic, technical, and environmental perspectives and developed a novel Multi-criteria Decision-making (MCDM) model to prioritize the alternatives. To cope with the external and internal uncertainties during the decision-making, Interval-Rough Numbers (IRNs) were firstly used to deal with subjective vagueness and information incompleteness involved in the group judgements unavoidably. Secondly, DEMATEL-ANP was employed based on IRNs to specify the correlation type and degree among diverse criteria for determining the global weights accurately. Lastly, a Vector-based Algorithm method was applied to measure the alternatives’ overall performance and figure out the final ranking scores of sustainability. The results revealed that CO2 to methane, urea, methanol, dimethyl ether, and acetic acid were the top five promising conversion technologies with the highest R&D priority over the next decades from a sustainability perspective. Moreover, a detailed sensitivity analysis of criteria weights was conducted to scrutinize the effectiveness of the ranking results and to validate the reliability of the new proposed MCDM model. Furthermore, in consideration of the complexity of future technological advance, market transformation, economic and social trends, this life cycle sustainability decision-support framework for CO2 conversion technologies provides a well-informed benchmark to support the screening and selection of candidate technologies including both the existing and emerging processes, and strategically explore the development opportunities and limits under uncertainties.
With the emergence of numerous CO₂ chemical conversion technologies to simultaneously reduce CO₂ emissions and produce value-added products, it is of great importance to compare their difference and select the most sustainable routes for future development. This study quantitatively evaluated the sustainability performances of 21 alternative CO₂ conversion technologies from economic, technical, and environmental perspectives and developed a novel Multi-criteria Decision-making (MCDM) model to prioritize the alternatives. To cope with the external and internal uncertainties during the decision-making, Interval-Rough Numbers (IRNs) were firstly used to deal with subjective vagueness and information incompleteness involved in the group judgements unavoidably. Secondly, DEMATEL-ANP was employed based on IRNs to specify the correlation type and degree among diverse criteria for determining the global weights accurately. Lastly, a Vector-based Algorithm method was applied to measure the alternatives’ overall performance and figure out the final ranking scores of sustainability. The results revealed that CO₂ to methane, urea, methanol, dimethyl ether, and acetic acid were the top five promising conversion technologies with the highest R&D priority over the next decades from a sustainability perspective. Moreover, a detailed sensitivity analysis of criteria weights was conducted to scrutinize the effectiveness of the ranking results and to validate the reliability of the new proposed MCDM model. Furthermore, in consideration of the complexity of future technological advance, market transformation, economic and social trends, this life cycle sustainability decision-support framework for CO₂ conversion technologies provides a well-informed benchmark to support the screening and selection of candidate technologies including both the existing and emerging processes, and strategically explore the development opportunities and limits under uncertainties.
ArticleNumber 117113
Author Gao, Ying
Zhang, Leiyu
Zhang, Chundong
Jun, Ki-Won
Wan, Hui
Gao, Ruxing
Wang, Lei
Guan, Guofeng
Zhao, Tiansheng
Liu, Tao
Kim, Seok Ki
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  givenname: Guofeng
  surname: Guan
  fullname: Guan, Guofeng
  organization: State Key Laboratory of Materials-Oriented Chemical Engineering, College of Chemical Engineering, Nanjing Tech University, Nanjing 211816, PR China
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Keywords Uncertain information
Sensitivity analysis
CO2 conversion
Sustainability prioritization
Multi-criteria decision-making
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Snippet [Display omitted] •Establishing a life cycle sustainability evaluation system from technical, economic, and environmental perspectives.•Proposing a novel...
With the emergence of numerous CO₂ chemical conversion technologies to simultaneously reduce CO₂ emissions and produce value-added products, it is of great...
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SubjectTerms acetic acid
algorithms
carbon dioxide
CO2 conversion
energy conversion
markets
methane
methanol
Multi-criteria decision-making
Sensitivity analysis
Sustainability prioritization
Uncertain information
urea
value added
Title Life cycle sustainability decision-support framework for CO2 chemical conversion technologies under uncertainties
URI https://dx.doi.org/10.1016/j.enconman.2023.117113
https://www.proquest.com/docview/3040438208
Volume 288
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