The DBP exposome: Development of a new method to simultaneously quantify priority disinfection by-products and comprehensively identify unknowns
Bibliographic record
Abstract
Disinfected drinking water contains hundreds of disinfection by-products (DBPs) that are formed by the reaction of disinfectants with natural and anthropogenic organic matter, bromide, and iodide. Understanding what these DBPs are is important because millions of people worldwide consume drinking water every day, and human epidemiologic studies have reported cancer, miscarriage, and birth defects from consuming such waters. While more than 600 DBPs are reported in the literature, very few studies quantify complete classes of chlorinated, brominated, and iodinated DBPs. Also, very few studies conduct comprehensive non-target analyses of unknown DBPs to characterize the complete DBP exposure (the exposome). We developed a new gas chromatography (GC)-mass spectrometry (MS) method that simultaneously quantifies 39 priority unregulated DBPs from six different chemical classes (haloacetaldehydes, haloketones, haloacetamides, haloacetonitriles, halonitromethanes, and iodinated-trihalomethanes) and analyzes unknown DBPs with mass accuracy <600 ppm under full-scan conditions. Using a new type of time-of-flight (TOF) mass spectrometer, which combines selected ion monitoring (SIM)-level sensitivity with mass accuracy of ±0.05 Da, method detection limits of 3-61 ng/L were achieved. These levels were found to be quite comparable to those of a widely used single quadrupole mass spectrometer (2-90 ng/L) operated in SIM mode. However, analysis using this TOF mass spectrometer offers two additional advantages over traditional quadrupole-MS: (1) full-scan data, which provides additional confidence for target analytes, as well as complete mass spectra for unknown analysis, and (2) two decimal place mass accuracy, which allows additional confidence for target analytes and importantly, molecular formula indication for unknowns. High resolution accurate mass TOF was also used to validate identification of selected compounds. This new method was demonstrated on finished drinking waters from three different drinking water plants, where target quantification and non-target unknown analyses were performed simultaneously during the same run. This enabled the quantification of 39 DBPs, along with the non-target identification of many other drinking water contaminants, including two additional non-target DBPs: N,N-dimethylacetamide and N-nitrosodibutylamine.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".