Comparing VFA Composition, Biomethane Potential, and Methane Production Kinetics of Different Substrates for Anaerobic Fermentation and Digestion
Bibliographic record
Abstract
Solid waste is one of the largest sources of greenhouse gases (GHGs) today. The carbon footprint of landfills also has a large impact on global warming. Therefore, it is becoming more urgent to study the possibility of better environmentally friendly approaches for solid waste management and its safe disposal. The digestion of solid waste is a biological process that breaks down the organic content of the solid waste and thus stabilizes it. It also allows the recovery of valuable resources (such as biogas) and the utilization of stabilized waste in various industries. In this study, six substrates were studied to determine their biomethane potential (BMP) in anaerobic digestion. The substrates were fermented and digested anaerobically, and the biogas production was measured. The methane yield of food waste substrates had a higher methane yield between 354 and 347 mL/g-TCOD, and a biodegradability of 89–87%. Wastewater sludge substrates yielded between 324 and 288 mL/g-TCOD with a biodegradability of 81–73%. A kinetics analysis using first-order and Gompertz models was performed for biodegradation and methane production.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".