Magnesium hydroxide addition reduces aqueous carbon dioxide in wastewater discharged to the ocean
Bibliographic record
Abstract
Abstract Ocean alkalinity enhancement (OAE) reduces the concentration of dissolved carbon dioxide (CO 2 ) in seawater, leading to atmospheric carbon dioxide removal (CDR). Here we report laboratory experiments and a field-trial of alkalinity enhancement through addition of magnesium hydroxide to wastewater and its subsequent discharge to the coastal ocean. In wastewater, a 10% increase of average alkalinity (+0.56 mmol/kg) led to a 74% reduction in aqueous CO 2 (−0.41 mmol/kg) and pH increase of 0.4 units to 7.78 (efficiency 0.73 molCO 2 /mol alkalinity). The alkalinization signal was limited to within a few metres of the ocean discharge, evident as 27.2 μatm reduction in CO 2 partial pressure and 0.017 unit pH increase, and was consistent with rapid dilution of the alkali-treated wastewater. While this proof of concept field trial did not achieve CDR due to its small scale, it demonstrated the potential of magnesium hydroxide addition to wastewater as a CDR solution.
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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 | 0.000 | 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) | 0.001 | 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".