Long-Term Performance of High-Rate Anaerobic Reactors for the Treatment of Oily Wastewater
Bibliographic record
Abstract
Complex oily wastewater from a food industry was treated in three different UASB reactors at different operating conditions. Although all three systems achieved fat, oil, and grease (FOG) and COD removal efficiencies above 80% at an organic loading of 3 kg COD/m3 x d, system performance deteriorated sharply at higher loading rates, and the presence of high FOG caused a severe sludge flotation resulting in failure. Initially, FOG accumulated onto the biomass which led to sludge flotation and washout of biomass. The loss of sludge in the bed increased the FOG loading to the biomass and failure ensued. Contrary to previous findings, accumulation of FOG rather than influent FOG concentrations or volumetric FOG loading rate was the most importantfactor governing the high-rate anaerobic reactor performance. The critical accumulated FOG loading was identified as 1.04 +/- 0.13 g FOG/g VSS for all three reactors. Furthermore, FOG accumulation onto the biomass was identified mainly as palmitic acid (>60%) whereas the feed LCFA contained only 30% of palmitic acid and 50% of oleic acid.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".