Enhancing Single- and Two-Stage Anaerobic Digestion of Thickened Waste-Activated Sludge through FNA-Heat Pretreatment
Bibliographic record
Abstract
This study aimed to investigate the effect of combined Free Nitrous Acid (FNA)-Heat (i.e., FNH) pretreatment on single- and two-stage anaerobic digestion (AD) of thickened waste-activated sludge (TWAS). Single-stage AD was conducted in batches, while two-stage AD involved acidogenic fermentation under semi-continuous flow followed by batch methanogenesis. FNH pretreatment was applied before the acidogenic stage, using 1.4 mg HNO2-N/L FNA concentration at 25 °C, 37 °C, and 60 °C for 24 h. Among the scenarios, the most promising results were observed with two-stage AD fed with FNH-pretreated TWAS at 60 °C, showing higher COD solubilization and a reduction in volatile solids. Combined FNA-Heat pretreatment in two-stage AD yielded elevated methane production (363–415 mL CH4/g VS added) compared to single-stage digestion. Methane yields from FNA-Heat pretreated single-stage ranged from 332 to 347 mL CH4/g VS added, contrasting with 212 mL CH4/g VS added for untreated TWAS. Methane generation commenced early in both untreated and pretreated samples, attributed to soluble substrate abundance.
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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) | 0.000 | 0.001 |
| 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) | 0.001 | 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".