UV-Induced Transformation of Four Halobenzoquinones in Drinking Water
Bibliographic record
Abstract
Halobenzoquinones (HBQs) are a group of emerging disinfection byproducts (DBPs) found in treated drinking water. Because the use of UV treatment for disinfection is becoming more widespread, it is important to understand how the HBQs may be removed or changed due to UV irradiation. Water samples containing four HBQs, 2,6-dichloro-1,4-benzoquinone (DCBQ), 2,3,6-trichloro-1,4-benzoquinone (TCBQ), 2,6-dichloro-3-methyl-1,4-benzoquinone (DCMBQ), and 2,6-dichloro-1,4-benzoquinone (DBBQ), were treated using a modified bench scale collimated beam device, mimicking UV treatment. Water samples before and after UV irradiation were analyzed for the parent compounds and products using a high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) method. As much as 90% of HBQs (0.25 nmol L(-1)) in both pure water and tap water were transformed to other products after UV254 irradiation at 1000 mJ cm(-2). The major products of the four HBQs were identified as 3-hydroxyl-2,6-dichloro-1,4-benzoquinone (OH-DCBQ) from DCBQ, 5-hydroxyl-2,6-dichloro-3-methyl-1,4-benzoquinone (OH-DCMBQ) from DCMBQ, 5-hydroxyl-2,3,6-trichloro-1,4-benzoquinone (OH-TCBQ) from TCBQ, and 3-hydroxyl-2,6-dibromo-1,4-benzoquinone (OH-DBBQ) from DBBQ. These four OH-HBQs were further modified to monohalogenated benzoquinones when the UV dose was higher than 200 mJ cm(-2). These results suggested possible pathways of UV-induced transformation of HBQs to other compounds. Under the UV dose commonly used in water treatment plants, it is likely that HBQs are partially converted to other halo-DBPs. The occurrence and toxicity of these mixed DBPs warrant further investigation to understand whether they pose a health risk.
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 | 0.000 | 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) | 0.001 | 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".