Evaluations of conventional, ozone and UV/H2O2 for removal of emerging contaminants and THM-FPs
Bibliographic record
Abstract
Although potential risk of pharmaceuticals and personal care products (PPCPs) and endocrine disrupting compounds (EDCs) and trihalomethanes to humans is small or unconfirmed, it is advisable to remove these wastewater-related contaminants to increase public confidence and acceptance as a precautionary principle and consequently their elimination or reduction during drinking water treatment is warranted. Experiments were conducted using the dual train pilot-scale conventional treatment plant with ozone and ultraviolet/hydrogen peroxide (UV/H2O2) with three different raw water sources. Reductions of trihalomethanes-formation potentials (THM-FPs) were 8–52%. Ozone was found to decrease THM-FPs while UV/H2O2 was found to increase THM-FPs in most of the experiments under experimental conditions. Conventional treatment poorly removed the selected PPCPs and EDCs while ozone + conventional treatment provided excellent removal. Conventional + UV/H2O2 treatment also demonstrated effective removal. However, removal of PPCPs and EDCs by conventional + UV/H2O2 treatment provided lower efficacy for Sites B and C, likely due to the presence of scavengers such as organics, bicarbonates, carbonates and particles.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".