Assessment of chloramine decay and nitrification potential following orthophosphate addition in a full-scale drinking water distribution system
Bibliographic record
Abstract
Orthophosphate is added into drinking water distribution systems (DWDSs) to reduce lead levels, but its effects on monochloramine decay and microbial activity are underexplored. The main purpose of this study was to determine the effect of orthophosphate addition and increasing monochloramine levels on monochloramine decay in a phosphorus-limited full-scale DWDS using batch tests. The study also evaluated nitrification potential at selected sites in this DWDS after seven years of orthophosphate application, comparing them with findings from a previous study conducted before its introduction. This comparison provides new insights related to orthophosphate's effects in a full-scale DWDS. In the batch test, samples were divided into unprocessed and microbiologically inhibited groups to observe chemical and microbial monochloramine decay over three weeks. The results suggest that orthophosphate may increase microbiological monochloramine decay. Below certain monochloramine levels, defined in previous research as a critical threshold residual (CTR) (0.4–0.7 mg Cl 2 /L), an accelerated decay rate of monochloramine occurred. The study noted higher CTR values in post-orthophosphate samples, suggesting the need for higher minimum monochloramine levels in the DWDS to prevent accelerated decay when using orthophosphate. Nitrite formation during the batch test was more pronounced in post-orthophosphate samples, suggesting that orthophosphate may enhance nitrification potential. • Assessed nitrification and chloramine decay post-orthophosphate addition by a batch test. • Approaches used: chloramine decay coefficients and curves, threshold residual, nitrite formation. • Orthophosphate and high water age increased microbial chloramine decay and nitrification potential. • Higher initial chloramine levels improved chloramine stability.
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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 | 0.000 | 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".