TiO<sub>2</sub>/UV: Single stage drinking water treatment for NOM removal?
Bibliographic record
Abstract
Problems arise at water treatment works due to the reaction of natural organic matter with chlorine to produce disinfection by-products (DBP). Trihalomethanes (THMs) are the main DBP regulated in various countries. The UK THM standard is 100 μg L –1 while in the USA it is 80 μg L –1 . At certain times of the year the efficiency of conventional treatment processes is compromised due to seasonal increases in the concentration of natural organic matter (NOM). During these periods water treatment works generally increase the coagulant dose but this subsequently increases the volume of potable sludge generated. Advanced oxidation processes have the potential to remove NOM and thereby reduce the DBP formation. Here the adsorption of NOM onto pelletised titanium dioxide (TiO 2 ) and the oxidation of the surface of the pellets by UV light have been shown to reduce the dissolved organic carbon (DOC) concentration of source water by 70%. Key words: photocatalysis, titanium dioxide, natural organic matter (NOM), trihalomethanes, sludge reduction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 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 teacher head, 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".