Methane production from citrus wastes: process development and cost estimation
Bibliographic record
Abstract
Abstract BACKGROUND: Because of its extreme toxicity for microorganisms, the limonene content of citrus wastes (CWs) has been a major obstacle to the conversion of CWs to biofuels. The main objective of this study was to develop a new process for the utilization of CWs that can be economically feasible when the supply of CW is low. RESULTS: Steam explosion pre‐treatment was applied to improve the anaerobic digestibility of CWs, resulting in a decrease of initial limonene concentration by 94.3%. A methane potential of 0.537 ± 0.001 m3 kg−1 VS (volatile solids) was obtained during the following batch digestion of treated CWs, corresponding to an increase of 426% compared with that of the untreated samples. Long‐term effects of the treatment were further investigated by a semi‐continuous co‐digestion process. A methane production of 0.555 ± 0.0159 m3 CH4 kg−1 VS day−1 was achieved when treated CWs (corresponding to 30% of the VS load) were co‐digested with municipal solid waste. CONCLUSION: The process developed can easily be applied to an existing biogas plant. The equipment cost for this process is estimated to be one million USD when utilizing 10 000 tons CWs year−1. 8.4 L limonene and 107.4 m3 methane can be produced per ton of fresh citrus wastes in this manner. Copyright © 2011 Society of Chemical Industry
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".