Influence of nutrient supplementation on DOC removal in drinking water biofilters
Bibliographic record
Abstract
Analysis of the impacts of nitrogen, phosphorus and potassium supplementation on biofilter performance for organic carbon removal was studied on laboratory-scale biofilter columns. Three dual media biofilter columns were fed with synthetic raw water C:N:P ratios of 546:24:1, 100:10:1, and 25:5:1 (w/w) to simulate nutrient limited and two nutrient supplemented conditions, respectively. Research found that air-scour versus water only backwash improved the nutrient limited dissolved organic carbon (DOC) removal by 8%. In addition, nutrient supplementation and backwash alteration improved DOC removals by 19% for the 25:5:1 column and 14% for the 100:10:1 column. Potassium supplementation with the 25:5:1 C:N:P ratio column had no discernible effect on DOC removal. No correlation with phospholipid (7–474 nmol P/g media) and adenosine triphosphate (ATP) (0.6 × 105–32.74 × 105 pg ATP/g media) values with DOC removal were found. Nutrient availability was found to influence DOC removal, demonstrating its importance when utilizing biofiltration for treatment of source waters.
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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 | 0.001 |
| 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 | 0.001 | 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 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".