Full‐Scale Prechlorine Removal: Impact on Filter Performance and Water Quality
Bibliographic record
Abstract
Conversion from direct filtration to biofiltration in a full‐scale drinking water treatment plant in Halifax, N.S., was assessed in terms of filter performance (e.g., turbidity, head loss) and water quality during a 48‐month project. Conversion was achieved by removing prechlorination, with the overall objective of reducing disinfection by‐product formation. As a result of prechlorine removal, it was hypothesized that the anthracite‐sand filters would provide both particle removal and biological treatment in a single process step. When prechlorine was removed, adenosine triphosphate concentrations on the filter media increased from ∼50 to ∼200–500 ng/cm3. Filter performance analysis revealed that conversion increased the filter effluent turbidity and reduced the filter head loss accumulation rate. Unit filter run volumes and filter run times were maintained. Water quality monitoring indicated that finished water total disinfection by‐products were reduced by ∼10–20 μg/L for trihalomethanes and ∼6–10 μg/L for haloacetic acids.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".