Trace Analysis of 61 Emerging Br-, Cl-, and I-DBPs: New Methods to Achieve Part-Per-Trillion Quantification in Drinking Water
Bibliographic record
Abstract
Disinfection byproducts (DBPs) are a ubiquitous source of chemical exposure in drinking water and have been associated with serious health impacts in human epidemiologic studies. While toxicology studies have pinpointed DBPs with the greatest toxic potency, analytical methods have been lacking for quantifying complete classes of most toxic DBPs at sufficiently low quantification limits (ng/L). This new method reports the parts-per-trillion quantification for 61 toxicologically significant DBPs from 7 different chemical classes, including unregulated iodinated haloacetic acids (HAAs) and trihalomethanes (THMs), haloacetaldehydes, haloketones, haloacetonitriles, halonitromethanes, and haloacetamides, in addition to regulated HAAs and THMs. The final optimized method uses salt-assisted liquid-liquid extraction in a single extraction method for a wide range of DBPs, producing the lowest method detection limits to-date for many compounds, including highly toxic iodinated, brominated, and nitrogen-containing DBPs. Extracts were divided for the analysis of the HAAs (including iodinated HAAs) by diazomethane derivatization and analysis using a GC-triple quadrupole mass spectrometer with multiple reaction monitoring, resulting in higher signal-to-noise ratios, greater selectivity, and improved detection of these compounds. The remaining DBPs were analyzed using a GC-single quadrupole mass spectrometer with selected ion monitoring, utilizing a multimode inlet allowed for lower injection temperatures to allow the analysis of thermally labile DBPs. Finally, the use of a specialty-phase GC column (Restek Rtx-200) significantly improved peak shapes, which improved separations and lowered detection limits. Method detection limits for most DBPs were between 15 and 100 ng/L, and relative standard deviations in tap water samples were mostly between 0.2 and 30%. DBP concentrations in real samples ranged from 40 to 17 760 ng/L for this study.
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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 | 0.001 |
| 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) | 0.001 | 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 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".