Low‐pressure UV/Cl<sub>2</sub> for advanced oxidation of taste and odor
Bibliographic record
Abstract
Ultraviolet (UV)‐based methods of advanced oxidation processes (AOPs), such as UV/hydrogen peroxide (H 2 O 2 ), can be used for removal of taste and odor contaminants in drinking water. However, significant disadvantages to UV/H 2 O 2 include incurred chemical costs associated with the addition of peroxide and quenching residual peroxide and the operational challenge of balancing peroxide quenching with secondary disinfection needs. Recent work has shown that H 2 O 2 can be replaced with chlorine (Cl2) for UV‐AOP and produce advantageous oxidation efficiencies for synthetic organic contaminants under certain conditions. This article uses modeling of the photochemistry of UV/H 2 O 2 and UV/Cl 2 to compare emerging and state‐of‐the‐art UV‐AOPs for control of the taste and odor‐inducing compounds geosmin and 2‐methylisoborneol. Although UV/H 2 O 2 has a decided advantage with respect to oxidation efficiency in surface waters at neutralto‐ basic pH, UV/C 12 can provide a cost‐effective AOP alternative, with a low risk of added trihalomethane and haloacetic acid formation in some surface waters.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".