Treatment of wastewater from a school in a decentralized filtration system by percolation over organic packing media
Bibliographic record
Abstract
Based on results obtained in the laboratory a WWTP composed of a septic tank and an aerated percolating filter packed with organic media was built for a school. The system can treat 18 m3 d(-1) and was operated with a hydraulic loading rate of 0.078 (m3 m(-2) d(-1). For 360 days different operational conditions including start-up; stabilization; operation with aeration and non aeration; effect of rainy season, breaks from activities due to holidays and restart; were monitored and described in the article. Once stabilized, the system was able to remove, without the need for mechanical aeration, 97% of BOD5, 71% of COD, 93% of TKN, 11% of PO(4-)-P, 95% of TSS, 96% of VSS, in addition to having a removal efficiency of 4 log units of Faecal Coliforms (FC) and 100% helminthes eggs (HE). With this quality, the treated wastewater can be chlorinated and reused to irrigate green areas and/or in toilets. Although sanitary wastewater has a high concentration of Total-N (250 mg L(-1)) and a C/N ratio of less than 1, the system removed 65% of Total-N. Finally it was observed that after non activity periods, there was neither system failure nor the need to re-stabilize the system.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".