Phosphorus Removal from Lake Water Using Basic Oxygen Furnace Slag: System Performance and Characterization of Reaction Products
Bibliographic record
Abstract
Effectiveness of basic oxygen furnace slag (BOFS) for removing dissolved phosphorus (P) was evaluated in a hypolimnetic withdrawal system. Lake water collected from the hypolimnion, with phosphate (PO4-P) concentrations of 0.25 to 0.49 mg/L, was passed through a pilot-scale (pore volume, ∼0.87 m3) treatment system over two successive summers. In year 1, the hydraulic retention time (HRT) varied from 0.58 to 1.64 days and 96.1–98.1% PO4-P was removed. The HRT in year 2 was 0.31 to 0.48 days and PO4-P removal was 97.4–99.9%. Effluent pH was 11.37±0.17 and 11.96±0.17 in years 1 and 2, respectively, with the increase attributed to dissolution of CaO and Ca(OH)2 from the BOFS. The effluent was neutralized by addition of CO2(g) before the water was discharged. Vanadium and aluminum were released from the BOFS, and were subsequently removed through addition of a filter containing 5 wt.% granular zero valent iron with a balance of silica sand and by neutralizing pH. Solid phase analyses conducted on the spent media, including FESEM-EDX, XPS, FTIR, and XANES spectroscopy, confirmed the presence of calcium carbonate and calcium phosphate minerals. Diminished hydraulic performance was observed in year 1, which was attributed to CaCO3 accumulation on the spent BOFS media. Restricting ingress of atmospheric CO2 into the system in year 2 minimized the extent of CaCO3 accumulation on the treatment media and led to improved hydraulic characteristics. Results show potential for long-term removal of phosphorus.
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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".