Disinfection of an Advanced Primary Effluent with Peracetic Acid and Ultraviolet Combined Treatment: A Continuous‐Flow Pilot Plant Study
Bibliographic record
Abstract
Disinfection of an advanced primary effluent using a continuous-flow combined peracetic acid/ultraviolet (PAA/UV) radiation system was evaluated. The purpose was to determine whether the maximum microbial content, established under Mexican standards for treated wastewaters meant for reuse--less than 240 most probable number fecal coliforms (FC)/100 mL--could be feasibly accomplished using either disinfectant individually, or the combined PAA/UV system. This meant achieving reduction of up to 5 logs, considering initial concentrations of 6.4 x 10(+6) to 5.8 x 10(+7) colony forming units/100 mL. During the tests performed under these experiments, total coliforms (TC) were counted because FC, at the most, will be equal to TC. Peracetic acid disinfection achieved less than 1.5 logs TC reduction when the C(t) x t product was less than 2.26 mg x minimum (min)/L; 3.8 logs for C(t) x t 4.40 mg x min/L; and 5.9 logs for C(t) x t 24.2 mg x min/L. In continuous-flow UV irradiation tests, at a low-operating flow (21 L/min; conditions which produced an average UV fluence of 13.0 mJ/cm2), the highest TC reduction was close to 2.5 logs. The only condition that produced a disinfection efficiency of approximately 5 logs, when both disinfection agents were used together, was the combined process dosing 30 mg PAA/L at a pilot plant flow of 21 L/min and contact time of 10 minutes to attain an average C(t) x t product of 24.2 mg x min/L and an average UV fluence of 13 mJ/cm2. There was no conclusive evidence of a synergistic effect when both disinfectants were employed in combination as compared to the individual effects achieved when used separately, but this does not take into account the nonlinearity (tailing-off) of the dose-response curve.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".