Influence of SRT and HRT on Bioprocess Performance in Anaerobic Membrane Bioreactors Treating Municipal Wastewater
Bibliographic record
Abstract
This study investigated the impact of Solid Retention Time (SRT) (40 to 100 days) and Hydraulic Retention Time (HRT) (2.5 to 8.5 hours) on the treatment of municipal wastewater in pilot and bench scale AnMBRs. The results revealed good permeate quality with respect to concentrations of COD (<40 mg/L) and BOD5 (<10 mg/L) was achieved under all conditions. Over the range of values tested SRT and HRTdid not significantly influence COD and BOD5 removal efficiencies. Extended SRTs resulted in reduced sludge production and enhanced methane production. Oversaturation of dissolved methane in permeate appears to have been responsible for a consistent lack of COD mass balance closure in all tests. After calibration of biokinetic coefficients, PetWin 4 (EnviroSim Canada) was found to effectively simulate the concentrations of particulate COD, readily biodegradable COD and acetic acid over a range of SRTs and HRTs. The calibrated saturation coefficients for hydrolysis and aceticlastic methanogenesis processes were comparable to those reported in literature. The saturation coefficient of fermentation was significantly lower than those reported in literature. The simulated methane mass flows were consistently higher than the measured values which was consistent with the lack of COD mass balance closure and was attributed to reduction of sulfate and oversaturation of the permeate with respect to Henry's Law.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".