Assessment of the Feasibility of Converting the Liquid Fraction Separated from Fruit and Vegetable Waste in a UASB Digester
Bibliographic record
Abstract
Anaerobic digestion of food waste still faces important challenges despite its world-wide application. An important fraction of food waste is composed of organic material having a low hydrolysis rate and which is often not degraded in digesters. The addition of this less hydrolysable fraction into anaerobic digesters requires a longer hydraulic residence time, and therefore leads to oversizing of the digesters. To overcome this problem, the conversion of the highly biodegradable liquid fraction from fruit and vegetable waste in a up-flow anaerobic sludge blanket (UASB) digester is proposed and demonstrated. The more easily biodegradable fraction of the waste is concentrated in the liquid phase using a 2-stage screw press separation. Then, this liquid fraction is digested in a 3.5 L UASB digester at a high organic loading rate. A good and stable performance was observed up to an organic loading rate (OLR) of 12 g COD/(Lrx.d), with a specific methane production of 2.6 L CH4/(Lrx.d) and a degradation of 85% of the initial total COD. Compared to the conversion of the same initial waste with a continuously stirred tank reactor (CSTR), this new treatment strategy leads to 10% lower COD degradation, but can produce the same amount of methane with a digester that is twice as small. The scale-up of this process could contribute to reduced costs related to the anaerobic digestion of food waste, while reducing management efforts associated with digestate handling and increasing process stability at high organic loading rates.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".