Resource Recovery From Municipal and Industrial Organic Waste: The Effect of Substrate Type on Anaerobic Fermentation, Biological Denitrification, and Anaerobic Digestion
Bibliographic record
Abstract
This study aims to recover volatile fatty acids (VFAs) from the anaerobic fermentation of industrial and municipal waste and investigate the effectiveness of using the produced VFAs as carbon sources for denitrification and as feedstocks for methane production via anaerobic digestion (AD) process. Six different wastes were used in this study, three industrial wastes: bakery processing and kitchen waste (BP+KW), whey powder (WP) and fat, oil, and grease (FOG), and three municipal wastes: food waste (FW), primary sludge (PS), and thickened waste activated sludge (TWAS). The experimental results showed that WP exhibited the maximum VFAs yield of 266 mg COD/ gTCOD added. In the denitrification experiments, all the fermentation filtrates exhibited higher specific denitrification rates (SDNRs) than conventional external carbon sources (i.e., methanol and acetate), with WP filtrate having the highest SDNR of 17.3 mg NOx-N/gVSS/hr. In the AD experiment, BP+KW and WP exhibited the highest methane yields of 354 and 350 mL CH4/ gTCOD added,respectively.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".