Occurrence of <i>N</i>-nitrosamines in Alberta public drinking-water distribution systems
Bibliographic record
Abstract
Since the 1974 discovery of trihalomethanes as disinfection by-products (DBPs) in drinking water, the regulatory and public health focus has been primarily directed at halogenated compounds, even though it is well established that chlorination and chloramination also produce non-halogenated DBPs. Specific halogenated DBPs that could reasonably explain the correlation of some adverse health outcomes with consumption of disinfected drinking water in a number of epidemiologic studies have yet to be identified. We therefore explored an emerging class of non-halogenated DBPs, N-nitrosamines, which warrant consideration given public health concerns regarding possible correlations of bladder cancer with exposure to chlorinated drinking water. We developed a dual media (Ambersorb® 572 and LiChrolut® EN), off-line, solid-phase extraction method that utilized a modified commercially-available extraction manifold combined with our previous GC–MS ammonia positive chemical ionization (PCI) quantitative method for analyzing N-nitrosamines in drinking water. We surveyed 20 Alberta municipal drinking-water distribution systems for the presence of N-nitrosodimethylamine (NDMA) and seven other N-nitrosamine species. Analytical results revealed the occurrence of NDMA (up to 100 ng/L) as well as two other N-nitrosamines (N-nitrosopyrrolidine and N-nitrosomorpholine) within select Alberta drinking water supplies.Key words: Alberta, chloramination, disinfection by-products, distribution system, drinking water, N-nitrosamines, NDMA, public health, survey.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".