AUTHOR=Zimmermann Arno W. , Langhorst Tim , Moni Sheikh , Schaidle Joshua A. , Bensebaa Farid , Bardow André TITLE=Life-Cycle and Techno-Economic Assessment of Early-Stage Carbon Capture and Utilization Technologies—A Discussion of Current Challenges and Best Practices JOURNAL=Frontiers in Climate VOLUME=4 YEAR=2022 URL=https://www.frontiersin.org/journals/climate/articles/10.3389/fclim.2022.841907 DOI=10.3389/fclim.2022.841907 ISSN=2624-9553 ABSTRACT=

The mitigation of climate change requires research, development, and deployment of new technologies that are not only economically viable but also environmentally benign. Systematic and continuous technology assessment from early technology maturity onwards allows assessment practitioners to identify economic and environmental characteristics. With this information, decision-makers can focus time and resources on the most promising technologies. A broad toolset for technology assessment exists—stretching from the well-established life cycle assessment (LCA) methodology to more loosely defined techno-economic analysis (TEA) methods and the increasingly popular principles of technology maturity assessment such as the concept of technology readiness levels (TRL). However, current technology assessment practice faces various challenges at early stages, resulting in a potential mismatch of study results and stakeholders' needs and an escalation of assessment effort. In this practice review, we outline current challenges in the interplay of LCA, TEA, and TRL and present best practices for assessing early-stage climate change mitigation technologies in the field of carbon capture and utilization (CCU). The findings help practitioners systematically identify the TRL of a technology and adapt technology assessment methodologies accordingly. We highlight the methodological challenges for practitioners when adapting the goal and scope, identifying benchmark technologies, creating a comprehensive inventory, comparing early stage to commercial stage, ensuring clarity of recommendations for decision-making under high uncertainty, and streamlining conventional LCA and TEA assessment approaches and provide actionable recommendations. Overall, this work contributes to identifying promising technologies faster and more systematically, accelerating the development of new technologies for climate change mitigation and beyond.