Side-Stream Comparison of Peracetic Acid and Chlorine as Hypochlorite for Disinfection of Municipal Wastewater Effluent at a Full-Scale Treatment Facility, Ontario, Canada
Bibliographic record
Abstract
Peracetic acid (PAA) has been used as a municipal wastewater disinfectant for over 2 decades, but information about its virucidal performance is limited. Here, we report on a 2 year study of virus disinfection with PAA and chlorine as hypochlorite (NaClO) in a secondary wastewater treatment plant. During year 1, we conducted a side-stream comparison of PAA dosed at 4 mg/L (minus a demand of about 10%) and NaClO at 7.3 mg/L against indigenous enteroviruses and noroviruses, as well as coliphages and Escherichia coli, while assessing PAA fish toxicity under flow-through conditions. During year 1, PAA and NaClO produced poor median log 10 reductions (LRs) against enteroviruses and noroviruses, although NaClO LRs were significantly higher. PAA and NaClO performed better against coliphages, but differences were not significant. Against E. coli, PAA and NaClO performed well. 96 hour toxicity testing was done only during year 1, revealing that PAA residual was lethal to rainbow trout only prior to quenching. The PAA dose was reduced to 3 mg/L (minus a demand of about 10%) during year 2 when we enumerated only coliphages and E. coli . F + male-specific coliphage LRs significantly dropped from 1.2 to 0.5, while E. coli LR remained unchanged. To ensure protection of aquatic life, an interim 0.27 mg/L PAA residual discharge limit was derived.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".