Ozone disinfection: main parameters for process design in wastewater treatment and reuse
Bibliographic record
Abstract
Wastewater disinfection by ozone was investigated at pilot and full scale on different wastewater effluents and two types of ozone reactors. It was demonstrated that water quality and, in particular, suspended solids and organic content strongly influence the required ozone dose for a given level of disinfection. The increase in contact time and residual ozone concentration did not improve the log removal of viruses and bacteria. However, the ‘Ct’ approach, commonly applied in drinking water treatment can be used for wastewater ozonation, if a sufficient ozone dose can be transferred to the effluent resulting in an ozone residual which can be measured. These considerations should be taken into account for the improved design of ozonation facilities. It should be underlined that short contact times are only possible if fast balanced distribution of the ozone dose is achieved as rapidly as possible, in order to satisfy fast chemical reactions (colloidal matter destabilisation, zeta potential, etc.) and enable a uniform distributed ozone residual for the slower reactions (disinfection, oxidation of micropollutants, etc.).
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".