Economic and Environmental Assessment of an Integrated Carbon Capture and Utilization Pathway
Bibliographic record
Abstract
It is becoming increasingly evident that major abatement strategies need to be implemented to tackle anthropogenic greenhouse gas (GHG) emissions. Balancing the expected growth of global energy demand while mitigating CO2 emissions is an urgent challenge of this century. With the growing interest in carbon capture and conversion technologies, there is a growing need to assess the economic feasibility and environmental benefit of these technologies. While broad deployment of carbon capture and sequestration (CCS) has significant potential for carbon mitigation, the potential value that can be created by utilizing the captured CO2 in a way that can create economic value, often referred to as carbon capture and utilization (CCU), is receiving growing momentum globally. Many proposals for CCU technologies assume that the capture and utilization facilities are geographically isolated, necessitating transport of captured CO2 and raising questions on the economic and environmental feasibility of the overall process. An alternative approach would be to develop an integrated process, wherein a utilization (i.e., conversion herein) process would likely be directly coupled with a compatible CO2 capture process, leading to in situ production of carbon-based fuels and feedstocks. In this context, high temperature fuel cell-based carbon capture technology (i.e., molten carbonate fuel cell or MCFC) offers an interesting opportunity, as it simultaneously produces electricity and concentrates CO2 (>96%) for subsequent utilization. Therefore, its is important to reveal the economic feasibility, environmental impacts and any trade-offs of an integrated carbon capture and utilization (CCU) for in situ production of fuels and chemicals. Here, we propose and subsequently assess an integrated electrochemical CCU process and compare with CCS route from economic and environmental aspects. This technoeconomic analysis reveals under baseline CCU scenario, carbon products reap either economic (67% and 10% gross margin increase for carbon monoxide and n-propanol, respectively) or environmental benefits (formic acid production would reduce ~721 thousand ton CO2e/year) relative to CCS route. Under optimistic scenario, while all the CO2 derived products are economically compelling over CCS route, only formic acid production would reduce ~1465 thousand ton CO2e/year over CCS (~575 thousand ton CO2e/year). This study may serve as a framework to decide whether a CCS or CCU pathway would be compelling under a given scenario when fuel cell-based CO2 capture technology is utilized to reduce carbon emissions and create economic value from fossil-based power plants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".