Evaluation of photoreactivation of <i>Escherichia coli</i> and enterococci after UV disinfection of municipal wastewater
Bibliographic record
Abstract
Because chlorine disinfection is not permitted in the province of Quebec, wastewater disinfection by ultraviolet (UV) light has been used for years in wastewater treatment plants. Thermotolerant coliforms discharge criteria are set for each plant and are adjusted by a factor of 1 log to compensate for photoreactivation in UV-disinfected effluents. The current study evaluated levels of Escherichia coli and enterococci photoreactivation from disinfected wastewater under varying temperature, visible light, and type of UV lamps. Escherichia coli photoreactivation increased significantly after exposure to 5600 lx compared with 1600 lx of visible light. This increase was significantly higher in warm water (25 degrees C) than cold water (4 degrees C). The level of photoreactivation of E. coli was also higher after wastewater disinfection by low-pressure UV lamps as opposed to medium-pressure UV lamps. Enterococci, however, were not photoreactivated under any test conditions. This result suggests that enterococci could be a better indicator than thermotolerant coliforms or E. coli. The use of enterococci would also eliminate the requirement to set different discharge criteria based on disinfection type (UV or chemical) and would also provide a better assessment of treatment efficiency for more resistant microorganisms.
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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 | 0.000 | 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".