Thermal chemical pretreatment of waste-activated sludge for enhanced solubilization and biogas production: a review
Bibliographic record
Abstract
ABSTRACT Waste-activated sludge (WAS) generation is increasing due to the increased generation of wastewater owing to industrialization and urbanization. The disposal of WAS is a significant environmental and financial concern that can be offset by stabilization and valorization via anaerobic digestion (AD). However, the biodegradation is limited due to microbial cells and extracellular polymeric substances (EPS). Physical, chemical, biological, and hybrid pretreatments and the addition of accelerant materials for enhancing direct interspecies electron transfer (DIET) are among the strategies to overcome the poor biodegradation of WAS. Alkaline pretreatment disintegrates the floc structure of WAS by increasing the osmotic pressure, while microwave irradiation has thermal and a-thermal effects and increases the availability of organics for biodegradation. Moreover, the combination of alkaline and thermal pretreatments has synergic effects on solubilization, biogas production, and dewaterability. The disintegration of WAS is recognized by alteration in volatile solid (VS) content, sCOD, BOD/sCOD, turbidity, nutrients solubilization, dewaterability, particle size, specific surface area, change functional group, alteration in microorganism community, microorganism abundance, color, moisture content, lag phase, and biogas production. Higher doses of pretreatment increase COD solubilization but not biodegradable COD. Maximum COD solubilization ranged from 2 to 37% in alkaline, 21 to 260% in the microwave (MW), and 28 to 624% in hybrid pretreatments.
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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) | 0.001 | 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 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".