Treatment of synthetic wastewater and hog waste with reduced sludge generation by the multi-environment BioCAST technology
Bibliographic record
Abstract
Simultaneous removal of carbon, nitrogen and phosphorus was examined along with reduced generation of biological sludge during the treatment of synthetic wastewater and hog waste by the BioCAST technology. This new multi-environment wastewater treatment technology contains both suspended and immobilized microorganisms, and benefits from the presence of aerobic, microaerophilic, anoxic and anaerobic conditions for the biological treatment of wastewater. The influent concentrations during the treatment of synthetic wastewater were 1,300-4,000 mg chemical oxygen demand (COD)/L, 42-115 mg total nitrogen (TN)/L, and 19-40 mg total phosphorus (TP)/L. The removal efficiencies reached 98.9, 98.3 and 94.1%, respectively, for carbon, TN and TP during 225 days of operation. The removal efficiencies of carbon and nitrogen showed a minimal dependence on the nitrogen-to-phosphorus (N/P) ratio, while the phosphorus removal efficiency showed a remarkable dependence on this parameter, increasing from 45 to 94.1% upon the increase of N/P ratio from 3 to 4.5. The increase of TN loading rate had a minimal impact on COD removal rate which remained around 1.7 kg/m(3) d, while it contributed to increased TP removal efficiency. The treatment of hog waste with influent COD, TN and TP concentrations of 960-2,400, 143-235 and 25-57 mg/L, respectively, produced removal efficiencies up to 89.2, 69.2 and 47.6% for the three contaminants, despite the inhibitory effects of this waste towards biological activity. The treatment system produced low biomass yields with average values of 3.7 and 8.2% during the treatment of synthetic wastewater and hog waste, respectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".