UV disinfection of wastewater flocs: the effect of secondary treatment conditions
Bibliographic record
Abstract
Activated sludge flocs that are carried to the final effluent can significantly decrease the effectiveness of ultraviolet (UV) disinfection of wastewater. This effect is detected in a typical UV dose-response curve, where at higher UV doses there is a decrease in the inactivation rate (tailing). In this study, the effect of activated sludge process conditions on the UV inactivation kinetics of flocs was investigated. The conditions compared were nitrifying vs. non-nitrifying vs. an enhanced biological nutrient removal-University of Cape Town (BNR-UCT) system. The results showed that the flocs generated in the BNR-UCT process were easier to disinfect. The final effluent from the BNR-UCT process also showed improved kinetics of inactivation and reached higher levels of disinfection. The nitrifying system's final effluent had a lower number of initial fecal coliforms, which contributed to reaching higher disinfection levels compared to the non-nitrifying system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".