RESPIROMETRIC STUDIES ON THE IMPACT OF HUMIC SUBSTANCES ON THE ACTIVATED SLUDGE TREATMENT: MITIGATION OF AN INHIBITORY EFFECT CAUSED BY DIESEL OIL
Bibliographic record
Abstract
This paper describes the results of aerobic respirometric studies on the application of humic substances (humate) to mitigate an inhibitory effect of petroleum hydrocarbons (diesel oil) on the returned activated sludge (RAS) in sewage from a municipal treatment plant. Initial results of the respirometric tests and non-linear regression analysis showed that diesel oil had an inhibitory effect on the activity of biomass and that kinetic data complied with the Haldane model for inhibitory wastes. Humate addition significantly enhanced the oxygen uptake by RAS. Application of humate at the dose of 2000 mg 1(-1) to the sewage contaminated with 10 mg l(-1) of diesel oil resulted in almost complete recovery of the biomass oxygen uptake. Non-linear regression analysis of the respirometric data indicated that this system complied with the Monod model for non-inhibitory wastes. Thus, the application of humic substances to mitigate the inhibitory effects of oil spills in wastewater treatment plants seems to be an attractive alternative to the treatments using activated carbon or specialized sorbents.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".