Publication | Open Access
Apples and Apples: A Shortcut Assessment Framework for Early‐Stage Carbon Capture and Utilization Technologies Based on Efficiency, Feasibility, and Risk
15
Citations
51
References
2020
Year
Shortcut Assessment FrameworkEngineeringEconomic AssessmentAgricultural EconomicsCarbon AccountingClimate PolicyUtilization TechnologiesClimate Change MitigationCarbon Capture And StorageCarbon CreditCarbon NeutralityEarly‐stage Carbon CaptureGreenhouse Gas MeasurementClimate ChangeCarbon SequestrationGreenhouse Gas Emission ReductionCo 2Low-carbon Energy SystemsSustainable ProductionLow-carbon DevelopmentEnvironmental EngineeringSustainable EnergyCarbon UtilizationShortcut Tea Assessment
Climate change is one of the largest current challenges to humankind, requiring a steep emissions reduction. One promising approach is using CO 2 as a resource. Research and development of carbon capture and utilization (CCU) technologies have increased in recent years, putting early‐stage techno‐economic assessment (TEA) in a key role to derive recommendations systematically, to allocate resources efficiently, and overall to push commercialization successfully. Shortcut TEA assessment approaches that reduce assessment detail and effort compared with conventional, full‐scope studies have gained popularity in recent years but have been criticized as comparing apples with oranges. Several open methodological questions remain such as how to implement global assessment standards, how to reduce subjective judgments, and how to compare technologies at different maturities. Herein, a shortcut assessment framework for early‐stage CCU technologies is proposed, based on the perspectives of efficiency, feasibility, and risk (Efferi). The Efferi framework implements the Global CO 2 Initiative's Guidelines, enables comparisons at different technology maturities, and systematically reduces subjective judgments. The Efferi framework provides a starting point for a more robust and easy assessment of early‐stage CCU technologies, leading to clearer go/no‐go recommendations at reduced assessment effort and enabling fairer, “apples to apples” comparisons.
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