Determination of 14 Nitrosamines at Nanogram per Liter Levels in Drinking Water
Bibliographic record
Abstract
N-Nitrosamines, probable human carcinogens, are a group of disinfection byproducts under consideration for drinking water regulation. Currently, no method can determine trace levels of alkyl and tobacco-specific nitrosamines (TSNAs) of varying physical and chemical properties in water by a single analysis. To tackle this difficulty, we developed a single solid-phase extraction (SPE) method with high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) for the determination of 14 nitrosamines of health concern with widely differing properties. We made a cartridge composed of a vinyl/divinylbenzene polymer that efficiently concentrated the 14 nitrosamines in 100 mL of water (in contrast to 500 mL in other methods). This single SPE-HPLC-MS/MS technique provided calculated method detection limits of 0.01-2.7 ng/L and recoveries of 53-93% for the 14 nitrosamines. We have successfully demonstrated that this method can determine the presence or absence of the 14 nitrosamines in drinking water systems (eight were evaluated in Canada and the U.S.), with occurrence similar to that in other surveys. N-Nitrosodimethylamine (NDMA), N-nitrosodiphenylamine, and the TSNA 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol were identified and quantified in authentic drinking water. Formation potential (FP) tests demonstrated that NDMA and TSNA precursors were present in (1) water samples in which tobacco was leached and (2) wastewater-impacted drinking water. Our results showed that prechlorination or ozonation destroyed most of the nitrosamine precursors in water. Our new single method determination of alkylnitrosamines and TSNAs significantly reduced the time and resource demands of analysis and will enable other studies to more efficiently study precursor sources, formation mechanisms, and removal techniques. It will be useful for human exposure and health risk assessments of nitrosamines in drinking water.
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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) | 0.002 | 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".