Modeling the Reduction of Ship Exhaust Emissions through CO<sub>2</sub> Capture/Chemical Conversion and SO<sub>2</sub> Seawater Scrubbing
Bibliographic record
Abstract
Developing innovative, energy-efficient technologies to capture CO 2 from marine emissions and convert it represents an effective way to move toward a circular approach to reduce CO 2 emissions. Additionally, SO 2 removal, as a short-term interim solution for the current maritime sector, allows the use of less desulfurized/expensive fuels to meet International Maritime Organization emission standards. In this context, we investigated an integrated process of capturing CO 2 /SO 2 onboard ships and converting captured CO 2, thus initiating a process close to carbon neutrality. CO 2 absorption by monoethanolamine and SO 2 scrubbing with seawater were envisaged in packed-bed columns, whose hydrodynamics and performance were analyzed under vertical, inclined, and rolling conditions using three-dimensional (3D) Eulerian models to understand their behavior under changing ocean states. CO 2 conversion via an integrated process combining a sorption-enhanced reverse water gas shift and sorption-enhanced methanol synthesis was proposed. By including a reverse water gas shift and in situ H 2 O removal, CO and methanol yields were significantly improved.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".