Occurrence and in vitro toxicity of unregulated disinfection by-products in two Saskatchewan drinking water treatment plants
Bibliographic record
Abstract
Halogenated disinfection by-products (DBPs) are a diverse class of compounds formed during the treatment of drinking water through reactions between natural organic matter (NOM), inorganic precursors such as bromide, and applied disinfectants. Health Canada regulates a handful of DBPs, but there are over 700 unregulated DBPs that have been described and many of these are more toxic than the regulated DBPs. Here, a data-independent precursor isolation and characteristic fragment (DIPC-Frag) method operated on a Q ExactiveTM Hybrid Quadrupole-OrbitrapTM Mass Spectrometer equipped with a UHPLC system was adapted for the detection of brominated and iodinated DBPs (Br-DBPs and I-DBPs) in chlorinated water. Extraction and analytical conditions were optimized, chemometric strategies were applied, and a library of 553 Br-DBPs and 112 I-DBPs was established with structures predicted for the most abundant compounds. As the method exhibited good precision (~15% RSD), it was then used to study trends of formation and temporal trends of unregulated Br-DBPs in a year-long study that sampled raw, clearwell, and finished waters. While most Br-DBPs increased through the treatment process, cluster I Br-DBPs decreased between the clearwell and finished stages, a pattern significantly related to their chemical properties of low O/C and Br/C ratios. Correlation matrices were used to determine if quality parameters of the source waters (e.g. NOM, turbidity, river level, temperature, bromine (Br)) could explain monthly variations of Br-DBPs, but few significant relationships were found. Unexpectedly, total Br increased from 0.013-0.038 mg/L in raw water to 0.04-0.12 mg/L in finished water, which indicated introduction of Br during disinfection. Concentrations of Br in clearwell and finished water were significantly correlated to detection of 34/54 Br-DBPs at α=0.05 and 14/54 Br-DBPs at α=0.001. As few studies have evaluated toxicity of DBPs in mixtures, the next goal of this thesis was to explore temporal changes in whole mixture toxicity and to determine if raw water parameters could predict toxicity of finished water. By use of a 72 h CHO-K1 cytotoxicity assay and an Nrf2/ARE oxidative stress assay, results indicated cytotoxicity was greatest in finished water collected in November and March while oxidative stress was greatest in June and November, both of which could be related to seasonal trends in unregulated Br-DBPs. These toxic endpoints were correlated (R2 = 0.53, p = 7.4x10-3) and three classes of Br-DBPs (Br2, BrCl, S-DBPs) demonstrated significant correlations to both. The greatest predictors of mixture toxicity were concentration of Br and applied doses of chlorine at related stages. These were equally correlated to both cytotoxicity (R2 = 0.43, p = 0.002) and oxidative stress (R2 = 0.67, p = 0.001). This study is the first to explore temporal trends in whole mixture toxicity of DBPs. It is also the first to suggest that the concentration of Br may be a predictor of the occurrence of unregulated Br-DBPs as well as whole mixture toxicity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".