Supplemental Sewage Scum and Organic Municipal Solid Waste Addition to the Anaerobic Digestion of Thickened Waste Activated Sludge: Biomethane Potential and Microbiome Analysis
Bibliographic record
Abstract
Sewage scum (SS) is collected from sedimentation tanks in wastewater treatment plants (WWTPs). Despite its huge biogas potential, there is limited information on its potential as a co-substrate and microbial ecology, especially during anaerobic co-digestion (ACo-D) of the organic fraction of municipal solid waste (OFMSW) and thickened waste activated sludge (TWAS). In this biomethane potential (BMP) study, the bioenergy yield achieved by the supplemental addition of SS and OFMSW to TWAS was investigated, along with the microbial ecology. Compared with the digestion of TWAS alone, which produced 184.6 mLCH4 gVS−1, biomethane yield was enhanced by as much as 32.4–121.6% in trinary mixtures with SS and OFMSW, mainly due to the positive synergistic effect. Furthermore, a mixture of 40%SS + 10%TWAS + 50%OFMSW produced the highest biogas yield of 407 mLCH4 gVS−1, which is proof that existing WWTPs can produce additional energy by incorporating external bioresources, thereby reducing greenhouse gas emissions. Modified Gompertz and logistic function estimates showed that methane production rate improved by as much as 60% in a trinary mixture compared with the digestion of TWAS alone. The genus Methanosaeta, capable of generating methane by the acetoclastic methanogenic pathway among all the archaeal communities, was the most prominent, followed by hydrogenotrophic methanogen Methanospirillum.
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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) | 0.001 | 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 | 0.000 | 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".