Characterization of New Nitrosamines in Drinking Water Using Liquid Chromatography Tandem Mass Spectrometry
Bibliographic record
Abstract
N-Nitrosodimethylamine (NDMA), a member of a group of probable human carcinogens, has been detected as a disinfection byproduct (DBP) in drinking water supplies in Canada and the United States. To comprehensively investigate the occurrence of possible nitrosamines in drinking water supplies, a liquid chromatography-tandem mass spectrometry technique was developed to detect both thermally stable and unstable nitrosamines. This technique consisted of solid-phase extraction (SPE), liquid chromatography (LC) separation, and tandem quadrupole linear ion trap mass spectrometry (MS/MS) detection. It enabled the determination of sub-ng/L levels of nine nitrosamines. Isotope-labeled N-nitrosodimethylamine-d6 (NDMA-d6) was used as the surrogate standard for determining recovery, and N-nitrosodi-n-propylamine-dl4 (NDPA-dl4) was used as the internal standard for quantification. The method detection limits were estimated to be 0.1-10.6 ng/L, and the average recoveries were 41-111% for the nine nitrosamines; of these, NDMA, N-nitrosopyrrolidine (NPyr), N-nitrosopiperidine (NPip), and N-nitrosodiphenylamine (NDPhA) were identified and quantified in drinking water samples collected from four locations within the same distribution system. In general, the concentrations of these four nitrosamines in this distribution system increased with increasing distance from the water treatment plant, indicating that the amount of formation was greater than the amount of decomposition within this time frame. The identification of NPip and NDPhA in drinking water systems and the distribution profiles of these nitrosamines have not been reported previously. These nitrosamines are toxic, and their presence as DBPs in drinking water may have toxicological relevance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".