Comparison of Oxidants Used in Advanced Oxidation for Potable Reuse: Non-Target Analysis and Bioassays
Bibliographic record
Abstract
Free chlorine (HOCl) and monochloramine (NH 2 Cl) are less-used oxidants than hydrogen peroxide (H 2 O 2 ) in ultraviolet advanced oxidation processes (UV-AOPs) but have garnered interest from the water reuse industry and scientific community because they can be more cost-effective than H 2 O 2 and provide a protective disinfectant residual. The destruction of organic compounds, creation of UV-AOP byproducts, and change in toxicity during UV-AOP with H 2 O 2, HOCl, NH 2 Cl, or ambient residual chloramine were evaluated in recycled wastewater by suspect and non-target screening as well as bioanalytical tests (bioassays). Ten compounds were identified in reverse osmosis (RO) permeate via suspect screening with removal near 100% by UV/H 2 O 2 and UV/HOCl, greater than decomposition by UV/NH 2 Cl and UV/ambient (∼60%), based on suspect screening mass spectrometry peak area. Non-target analysis based on organic features in mixed-mode cation exchange cartridge extracts indicated that UV/H 2 O 2 destroyed a similar or slightly greater fraction of organic compounds, formed fewer transformation products, and reduced the summed peak area of non-target features to the greatest extent. Fewer chlorinated byproducts were produced from the RO permeate treated by UV/H 2 O 2 than exposure to the chlorine-containing oxidants. Addition of NH 2 Cl to RO permeate resulted in a slight increase in the bioassay oxidative stress response but dropped below the response limit for all samples after UV-AOP for all oxidants.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".