High-Solids Anaerobic Digestion Followed by Ultrasonication of Digestate and Wet-Type Anaerobic Digestion for Enhancing Methane Yield from OFMSW
Bibliographic record
Abstract
High-solids anaerobic digestion of organic fraction of municipal solid waste often shows inefficient biomethane recovery due to mass transfer limitations. Consequently, this study presents a two-stage anaerobic digestion process combining high-solids anaerobic digestion followed by ultrasonication of digestate and wet-type anaerobic digestion for effective biomethane recovery from the organic fraction of municipal solid waste. The high-solids anaerobic digestion yielded methane production of 210 L CH4/kg volatile solids (VS). The digestate from the high-solids anaerobic digestion process was ultrasonicated at three different specific energy inputs (1000, 2500, and 5000 kJ/kg total solids (TS)). The increases in the soluble chemical oxygen demand (SCOD) concentrations (8%–32%) and volatile solids (VS) removal efficiencies (3.5%–10%) at different specific energy inputs were linearly correlated (R2 = 0.9356). Thus, ultrasonication led to the solubilization of particulate organics and released soluble organic matters. All ultrasonicated digestate samples showed significantly higher biomethane yields than that observed for the untreated digestate samples. The highest methane yield of 132 L CH4/kg VS was observed for a specific energy input of 5000 kJ/kg TS, which was 1.94 times higher than the control (68 L CH4/kg VS). Although specific energy inputs of 1000 kJ/kg TS and 2500 kJ/kg TS showed comparable methane yields (113–114 L CH4/kg VS), they were ~1.67 times higher than the control. Overall, our results suggest that an integrated system of high-solids and wet-type anaerobic digestion with pre-ultrasonication of digestate has the potential to provide a technically viable solution to enhance biomethane recovery from the organic fraction of municipal solid waste.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".