TY - JOUR
T1 - Evaluating alternative low carbon fuel technologies using a stakeholder participation-based q-rung orthopair linguistic multi-criteria framework
AU - Yang, Zaoli
AU - Ahmad, Salman
AU - Bernardi, Andrea
AU - Shang, Wen long
AU - Xuan, Jin
AU - Xu, Bing
N1 - Funding Information:
We are grateful for constructive comments and suggestions from several anonymous reviewers and the editor of this journal. We would like to thank Prof Patricia Thornley and all Supergen Bioenergy Hub members for their valuable comments. We also appreciate for those who have participated in our online survey. The authors wish to acknowledge the financial support provided by the UK Supergen Bioenergy Hub and the Department for Transport (Grant number: SGBH FF Feb2019 1).
Publisher Copyright:
© 2022 The Author(s)
PY - 2023/2/15
Y1 - 2023/2/15
N2 - It is widely believed that alternative low carbon fuels (ALCF) can be instrumental in achieving the transportation sector's decarbonization goal. Unlike conventional fossil-based fuels, ALCF can be produced through a combination of different chemical processes and feedstocks. The inherent complexity of the problem justifies the multi-criteria decision-making (MCDM) approach to support decision-making in the presence of multiple criteria and data uncertainty. In this paper, we propose a novel stakeholder participation-based MCDM framework integrating experts' perspectives on ALCF production pathways using the analytics hierarchy process (AHP) and the q-rung orthopair linguistic partition Bonferroni mean (q-ROLPBM) operator. The key merit of our approach lies in treating criteria of different dimensions as heterogeneous indicators while considering the mutual influence between criteria within the same dimension. The proposed framework is applied to evaluate four ALCF production pathways against 13 criteria categorised under economic, environmental, technical, and social dimensions for the case of the United Kingdom (UK). Our analysis revealed the environmental and the economic dimensions to be the most important, followed by the social and technical evaluation dimensions. The e-fuel followed by the e-biofuel are found to be the two top-ranked production pathways that utilise the electrochemical reduction process and its combination with anaerobic digestion. These findings, along with our recommendations, provide decision-makers with guidelines on ALCF production pathway selection and formulate effective policies for investment.
AB - It is widely believed that alternative low carbon fuels (ALCF) can be instrumental in achieving the transportation sector's decarbonization goal. Unlike conventional fossil-based fuels, ALCF can be produced through a combination of different chemical processes and feedstocks. The inherent complexity of the problem justifies the multi-criteria decision-making (MCDM) approach to support decision-making in the presence of multiple criteria and data uncertainty. In this paper, we propose a novel stakeholder participation-based MCDM framework integrating experts' perspectives on ALCF production pathways using the analytics hierarchy process (AHP) and the q-rung orthopair linguistic partition Bonferroni mean (q-ROLPBM) operator. The key merit of our approach lies in treating criteria of different dimensions as heterogeneous indicators while considering the mutual influence between criteria within the same dimension. The proposed framework is applied to evaluate four ALCF production pathways against 13 criteria categorised under economic, environmental, technical, and social dimensions for the case of the United Kingdom (UK). Our analysis revealed the environmental and the economic dimensions to be the most important, followed by the social and technical evaluation dimensions. The e-fuel followed by the e-biofuel are found to be the two top-ranked production pathways that utilise the electrochemical reduction process and its combination with anaerobic digestion. These findings, along with our recommendations, provide decision-makers with guidelines on ALCF production pathway selection and formulate effective policies for investment.
KW - Alternative low carbon fuels (ALCF)
KW - Analytics hierarchy process (AHP)
KW - e-fuels
KW - MCDM
KW - q-rung orthopair linguistic partition Bonferroni mean operator
KW - UK transportation sector
UR - http://www.scopus.com/inward/record.url?scp=85144351280&partnerID=8YFLogxK
U2 - 10.1016/j.apenergy.2022.120492
DO - 10.1016/j.apenergy.2022.120492
M3 - Article
AN - SCOPUS:85144351280
SN - 0306-2619
VL - 332
JO - Applied Energy
JF - Applied Energy
M1 - 120492
ER -