Ocean Alkalinity Enhancement Using Bipolar Membrane Electrodialysis: Technical Analysis and Cost Breakdown of a Full-Scale Plant
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Bibliographic record
Abstract
A detailed techno-economic analysis was performed for a bipolar membrane electrodialysis (BMED) full-scale plant designed to produce large volumes of dilute alkaline solution for use in ocean alkalinity enhancement (OAE). OAE is a process by which the surface of the oceans is realkalinized to promote CO 2 absorption from air by converting CO 2 to carbonates for long-term storage in the oceans. The capacity of the BMED stack was designed to process ∼139 000 m 3 /year of desalination brine, resulting in 47 200 t/year of 2.1 wt % NaOH solution. The OAE plant was modeled using colocation with a desalination plant in southern California. Three scenarios were investigated, each focused on a different valorization of the BMED process byproduct of 46 600 t/year of 1.8 wt % HCl solution: selling (1) dilute HCl without further processing, (2) dilute HCl distilled to 20 wt % using carbon-free (solar) energy, and (3) dilute HCl distilled to 20 wt % using waste heat from a nearby power plant. The levelized cost of CO 2 sequestration from the OAE plant, assuming no return on investment, ranged from 848 to 1076 USD/t of CO 2, depending on the scenario. Subsequently, a discounted cash flow analysis was conducted to assess the price at which carbon credits would have to be sold as revenue source to make a profit on the plant. Our analysis indicates that the cost of energy, labor, loan repayment, and membrane replacement, as well as the inefficiency of commercial membranes, drive the economics of BMED for OAE, while highlighting the necessity to generate alternative byproducts other than HCl. Nevertheless, these high costs (1395–2315 USD/t of CO 2 ) align with carbon credit prices currently indicated in contracts signed within the voluntary carbon market. A reliable outlook indicates that technical improvements and better economic perspectives can reduce the levelized cost of CO 2 down to 394 USD/t of CO 2 .
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it