Performance of an integrated reactor with airlift loop and sedimentation for municipal wastewater treatment: A 150 m<sup>3</sup>/d pilot case study
Bibliographic record
Abstract
Abstract A newly developed bio‐reactor design for municipal sewage treatment was evaluated on a pilot scale (150 m3/d). The reactor system included both anaerobic/anoxic and aerobic treatment stages with external/internal airlift circulation loops integrated with a central sedimentation chamber. The design was conceived to enhance the removal of organic compounds and nutrients (phosphorus and nitrogen) within a smaller footprint than existing treatment processes. The downcomer of the internal circulation loop is integrated with the sedimentation tank facilitating high efficiency solid‐liquid separation in a compact configuration. The external/internal airlift circulation stages increase the potential for bio‐reactivity, while reducing energy consumption for process flows. Overall, the integrated configuration reduces the footprint required compared to conventional systems with equivalent hydraulic loads, ie, hydraulic retention time of ~12.8 hours with a hydraulic loading area of 10.3 m3/d/m2. The trial run data indicated removal efficiencies for COD, phosphorous, ammonia, and total nitrogen of 94.5%, 94.5%, 96.8%, and 78.6% respectively. Moreover, the treatment system also demonstrated a robust capacity to handle a wide range of COD influent concentrations (ie, ~ 120‐860 mg/L).
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".