Risk-based uncertainty assessment to identify key sustainability hurdles for emerging CO2 utilization technologies
- Authors
- Lee, Jeehwan S.; Jung, Juyeong; Roh, Kosan; Heo, Seongmin; Lee, Ung; Lee, Jay H.
- Issue Date
- 2022-06
- Publisher
- Royal Society of Chemistry
- Citation
- Green Chemistry, v.24, no.11, pp.4588 - 4605
- Abstract
- The development of carbon dioxide utilization (CDU) technologies is heavily influenced by policy priorities such as access to renewable energy resources and the country's economic structure. At the same time, most conversion-based CDU technologies are early-stage technologies characterized by significant uncertainties due to a nascent knowledgebase and limited available data. Consequently, identifying major sustainability hurdles and hotspots is crucial in ensuring effective allocations of R&D resources in technology upgrading and upscaling. In this study, we formulate the task of identifying sustainability hurdles as assessing and ranking key sources of risk that influence whether a given CDU technology is sustainable or not. To this end, we propose a novel methodology for risk-based uncertainty assessment through classification based on stakeholder-set sustainability decision rules. Risk is subsequently quantified by comparing the class likelihoods. For multiple sustainability criteria scenarios, additional stakeholder input in the form of joint conditional probabilities is implemented in the decision rules. We demonstrate the methodology by applying it to the CO2 hydrogenation to formic acid process employing heterogeneous Ru/bpyTN-30-CTF catalysts, being developed as part of the ongoing Carbon-to-X R&D initiative in South Korea. The proposed methodology is most applicable to CDU technologies with TRLs between 3 and 5 in which the core utilization concepts have already been experimentally validated and the conceptual design process has started.
- Keywords
- KERNEL DENSITY-ESTIMATION; FORMIC-ACID; CARBON-DIOXIDE; ELECTROCHEMICAL CONVERSION; PHOTOCATALYTIC CONVERSION; ENVIRONMENTAL EVALUATION; FRAMEWORK; METHANOL; CAPTURE; DESIGN
- ISSN
- 1463-9262
- URI
- https://pubs.kist.re.kr/handle/201004/115152
- DOI
- 10.1039/d2gc00514j
- Appears in Collections:
- KIST Article > 2022
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