Establishing minimum free chlorine residual concentration for microbial control in a municipal drinking water distribution system
Bibliographic record
Abstract
Distribution system data from a Nova Scotia municipal drinking water supply was collected over four years, including free chlorine residual concentration, heterotrophic plate count (HPC) bacteria, and temperature. These data were analyzed for occurrences of HPC bacteria greater than 500 colony forming units (CFU)/mL. The municipality was interested in determining if secondary chlorination practices were sufficient in maintaining microbial health in their distribution system. Coliform data were non-detect (total coliforms and Escherichia coli) in the distribution system over this period and thus heterotrophic bacteria were used to assess microbial health. Results were compared to similar data collected from pilot-scale studies that had been carried out using the same municipal water as the source. Analysis showed that a similar trend was observed between pilot- and full-scale samples. Full-scale data analysis revealed that the minimum disinfection requirement of 0.2 mg/L did not consistently control occurrences of heterotrophic bacteria from being greater than 500 CFU/mL. By comparison, maintaining a concentration of 0.3 mg/L or above, particularly in warm-weather systems, maintained the number of heterotrophic bacteria at below 500 CFU/mL. Fortunately the majority of samples collected in the full-scale distribution system (>89%) had a free chlorine residual concentration of greater than 0.30 mg/L. While it is recognized that this system had 100% compliance for E. coli, the goal of this work will help utilities understand how to utilize microbial data to inform operational disinfection targets for their distribution system.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".