Design considerations for the marinisation of offshore direct air capture
Bibliographic record
Abstract
Direct air capture is a method for removing carbon dioxide ( CO 2 ) directly from atmospheric air. To date, only land based installations have been considered, but with growing competition for land and resources, offshore locations are beginning to be contemplated. Offshore locations offer close proximity to vast renewable energy potential, and robust CO 2 storage locations, but come with a large degree of uncertainty on performance and cost. The current study explores considerations for offshore operation, and reviews parallel technologies that have undergone similar transitions to use in offshore environments. A baseline energy calculation is completed under the assumption that air would need to be pre-treated prior to entering conventional DAC units. A design is proposed using wire mesh demister pads to collect and remove liquid particles containing salt from the air prior to entering the air contactor and coming into contact with capture materials. The pressure loss, and additional fan power required to overcome this is computed. Demister pads increase overall pressure drop by 20%–28% for solid sorbents, and by 79% for aqueous based DAC solvents, resulting in an additional fan energy requirement of 38.1 kWh/t- CO 2 and 194.44 kWh/t- CO 2 respectively. Until further experimental studies are completed to better understand the impacts, this design serves as a worst-case scenario for comparison. Once further experimental data becomes available, it can be determined whether the additional components for pre-treatment of air are necessary. • Pioneering design considerations for offshore direct air capture systems. • Introduced wire mesh demister pads to remove salt particles from offshore air. • Demister pads increase pressure drop: 20%–28% for sorbents, 79% for solvents. • Additional fan energy demand: 38.1 kWh/t-CO 2 (sorbents) and 194.4 kWh/t-CO 2 (solvents). • Proposed design serves as a baseline for future experimental validations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".