Anaerobic co-digestion of municipal wastewater sludge and restaurant grease
Bibliographic record
Abstract
Co-digestion has drawn much attention because of its potential to increase biogas production among other benefits. Restaurant grease has high energy content and methane production potential and so is a promising substrate for co-digestion with municipal wastewater sludge. Anaerobic co-digestion of municipal wastewater sludge and restaurant grease was investigated at laboratory-scale under mesophilic conditions (37 °C). Increasing the chemical oxygen demand (COD) loading rate of the test digester by 387% (organic loading rate 4.235 kg VS/m3/d) relative to the control digester led to a 467% increase in daily biogas production, a 25.2% increase in methane yield (based on volatile solids (VS) destruction), a 29.8% increase in COD removal and a 27.2% increase in VS reduction. The biogas methane content ranged from 62.6 to 66.2% (v/v). No negative effect of the grease addition was observed in the test digester performance under the conditions investigated. The increases in biogas production and methane yield indicated enhanced digestion performance. In addition, partial alkalinity and pH proved to be good indicators of digester stability.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".