Impact of UV and secondary disinfection on microbial control in a model distribution system
Bibliographic record
Abstract
This study evaluates the synergistic effects of ultraviolet (UV) and secondary disinfectants on water quality in a model distribution system. Chemical disinfectants evaluated for residual disinfection include chlorine dioxide, monochloramine, and free chlorine. Results suggest that there may be synergistic effects between UV and the chemical disinfectants for controlling microbiological re-growth in drinking water distribution systems. UV disinfection appeared to increase the vulnerability of bacteria located in suspension or within biofilms to chemical disinfection, although only at low disinfectant residual concentrations of 0.25, 0.50, and 1.0 mg/L for chlorine dioxide, free chlorine, and monochloramines, respectively. At high disinfectant residual concentrations of 0.50, 1.0, and 2.0 mg/L for chlorine dioxide, free chlorine, and monochloramines, respectively, results indicated that chemical disinfection alone would be adequate for microbial control. In the reactors receiving UV pre-treatment, both chlorine dioxide and free chlorine disinfection were far more effective in reducing the growth of suspended heterotrophic bacteria than without UV pre-treatment. Similar biofilm and suspended bacterial levels were observed without subsequent chemical disinfection regardless of the presence or absence of UV treatment. Overall, these findings imply that UV treatment prior to chemical disinfection enhances microbial control in distribution systems. These results indicate the use of UV pre-treatment can be effective at reducing the disinfectant concentration necessary for microbial control, therefore reducing the potential for the formation of disinfectant by-product in the system.Key words: drinking water, UV pre-treatment, chlorine dioxide, chlorine, monochloramines, disinfection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 teacher head, 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".