Bench-Scale Evaluation of Sonication as a Pretreatment Process for Ultraviolet Disinfection of Wastewater
Bibliographic record
Abstract
Abstract It is generally known that sonication improves ultraviolet (UV) disinfection kinetics of municipal effluents by breaking large suspended particles. However, the feasibility of sonication as a pretreatment technology largely depends on wastewater quality and discharge requirements. The purpose of this study was to investigate the potential benefits of ultrasound for improving the UV disinfectability of various effluent types, including primary, activated sludge, and trickling filter effluents. It was found that the tailing level of the dose-response curve at high UV doses (>40 mJ/cm2) decreased with the increased sonication time. The reduction in the tailing level had a strong correlation with the decrease in the number concentration of large particles (<60 µm) such that 1 log reduction in the number concentration of large particles resulted in 1.4, 1.1, and 1.7 log reductions in the tailing level for primary, activated sludge, and trickling filter effluents, respectively. However, the improvement in the UV disinfectability due to sonication was partly offset by the reduction in the UV transmittance of the effluent.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".