Biological treatment of oily wastewater from gas stations by membrane bioreactor
Bibliographic record
Abstract
In many Asian countries, rapid industrialization and urbanization has led to an increased number of cars, making wastewater from gas stations an important issue of concern in urban environment. This wastewater is characterized by high concentration of oil–water emulsion, which cannot be effectively removed by a conventional gravity separator. An experimental investigation on the treatability of oily wastewater from gas stations using a membrane bioreactor (MBR) system revealed that MBR system could achieve good removal efficiency with stability against shock loading. Optimum operating conditions were found to be at a hydraulic retention time of 4 h and an oil-loading rate of 1.8 kg oil m–3·d–1. It was anticipated that adding powdered activated carbon (PAC) in the MBR could help to adsorb the oils. However, operating the MBR with only microbial flocs has an advantage over adding PAC particles into the MBR, since the former condition could provide a prolonged cycle of filtration with a relatively lesser increase in transmembrane pressure. Key words: activated sludge process, membrane bioreactor, membrane fouling, oily wastewater, powdered activated carbon, transmembrane pressure.
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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 | 0.000 |
| 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) | 0.000 | 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".