Formation of <i>N</i>-Nitrosodiphenylamine and Two New N-Containing Disinfection Byproducts from Chloramination of Water Containing Diphenylamine
Bibliographic record
Abstract
N-nitrosodiphenylamine (NDPhA) is a disinfection byproduct (DBP) in drinking water. However, it is not known what governs the formation of NDPhA and which precursor(s) in the raw water is responsible for its formation. We report here diphenylamine (DPhA) as a key precursor of NDPhA, and we describe the effect of water pH and chloramination conditions on the formation of NDPhA. To identify precursors of NDPhA, raw water samples were collected from the same drinking water system in which NDPhA was previously detected. Analysis of the raw water samples showed the presence of 1.3 ng/L of DPhA and no detectable NDPhA. Seven hours after the treatment of the raw water with chloramines, the concentration of DPhA decreased to 0.4 ng/L with corresponding formation of NDPhA (0.4 ng/L). Controlled experiments involving chloramination of DPhA in water showed that chloramines were essential to the formation of NDPhA, and that increasing the pH from 4 to 10 resulted in 64-fold enhancement in NDPhA formation. Removal of DPhA and formation of NDPhA was found by mass imbalance, which led to the identification of two new DBPs, phenazine (MW 180 Da) and a chlorinated phenazine derivative (MW 216 Da), using liquid chromatography tandem mass spectrometry and gas chromatography mass spectrometry. Both new DBPs were detected only in the treated water and not in the raw water. Phenazine and N-chlorophenazine have never been reported as DBPs and neither their occurrence in drinking water nor their health effects are known.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".