From Micropollutant to DBP Driver: The Unexpected Reactivity of 1-Chlorobenzotriazole in Water Disinfection
Bibliographic record
Abstract
The increasing adoption of potable wastewater reuse is challenged by persistent micropollutants─such as benzotriazole─which are poorly removed by conventional treatment and may produce toxic disinfection byproducts (DBPs). This study investigated benzotriazole chlorination and identified 1-chlorobenzotriazole as the primary product, formed preferentially under near-neutral to acidic pH and excess chlorine─conditions typical in disinfected water. The DBP formation potential of 1-chlorobenzotriazole was evaluated using two organic matter standards and secondary wastewater effluents and compared against chlorine and monochloramine. Surprisingly, 1-chlorobenzotriazole formed DBP levels comparable to or greater than those from chlorine, including trihalomethanes, haloaldehydes, haloketones, haloacetonitriles, and halonitromethanes. This reactivity is attributed to 1-chlorobenzotriazole’s ability to function as a free chlorine reservoir, sustaining chlorination reactions and promoting continued DBP formation─unlike inorganic N -halamines. DBP speciation was strongly pH-dependent and mirrored chlorine behavior, supporting the chlorine reservoir effect. Additionally, 1-chlorobenzotriazole exhibited precursor- and matrix-dependent reactivity, especially with complex matrices like secondary wastewater effluents, where it acted as both a chlorine source and a direct DBP precursor. Overall, this work provides the first detailed evaluation of 1-chlorobenzotriazole DBP formation potential, revealing an overlooked pathway for halogenated DBP production in water disinfection, and emphasizes the importance of considering benzotriazole transformation products in advanced reuse systems.
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 | 0.001 |
| 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".