Temporal and Spatial Variation in Hydroxyl Radical Scavenging Capacity in Drinking Water and Correlation to Water Quality Parameters
Bibliographic record
Abstract
Advanced oxidation processes (AOPs) are being used more frequently in drinking water treatment plants for purposes such as removing taste and odor-causing compounds or to control recalcitrant organic contaminants. Water’s hydroxyl radical scavenging capacity ( S c ) is an important parameter for AOP design and operation, but due to complexity in its measurement, S c data are limited and knowledge of its temporal and spatial variation is sparse. Furthermore, the feasibility of estimating S c through monitoring common water quality parameters is unclear. The variability in S c of water from five surface water plants and one groundwater plant was measured for 1 year along with total organic carbon, total inorganic carbon, ultraviolet absorbance at 254 nm, and fluorescence emission-excitation matrices. The results showed about a 10–25% variation in the S c, and S c was not well-correlated with any of the water quality parameters measured. The reduction in S c across ultrafiltration treatment was similar to that across conventional treatment (15–30%). Due to the scavenging capacity of the added oxidant, the modeled variation in UV/H 2 O 2 or UV/chlorine performance due to S c variation was small (∼5–10% change in the pollutant removal rate).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".