Valorization of winery waste through hydrothermal carbonization: A sustainable route to solid biofuel production
Bibliographic record
Abstract
The winemaking industry generates large quantities of seasonal waste creating significant environmental and management troubles. Hydrothermal carbonization (HTC) is one of the most promising thermochemical processes for converting wet biomass into added-value products for different applications. In this work, grape stalks, a considerable portion of winery waste, were used as starting feedstock for the HTC process to produce a solid biofuel. A 3-liter HTC reactor was used to investigate the effects of reaction temperature (180–250 °C) and residence time (1–8 h) on the product characteristics generated during the HTC process. The resulting solid product, hydrochar, was characterized for its proximate and elemental composition, heating value, and combustion behavior. In addition, the process water was evaluated by determining its total organic carbon and total nitrogen content, while the permanent gas was characterized by measuring the fractions of CO 2 , CO, H 2 , CH 4 , and C 2 −C 4 hydrocarbons. The hydrochar obtained from the HTC tests exhibits enhanced physicochemical properties compared to the original feedstock. Under higher severity conditions, the carbon content of hydrochar increased to 64 wt%, representing a 39 % increase over the original raw biomass. This enhancement led to a notable increase in calorific value, rising to 26 MJ/kg (+23 %). However, the yield of hydrochar decreased by 22 wt%. The yield and calorific value influenced the energy yield of hydrochar, which resulted in higher values at lower severity conditions. Therefore, hydrochar produced under these less severe conditions is more beneficial for energy recovery and the economic sustainability of the HTC process.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".