H2-rich syngas production from gasification of cannabis waste in a downdraft gasifier
Bibliographic record
Abstract
The growth of the cannabis industry emphasizes the importance of valorizing renewable waste, which can be used to produce sustainable fuels. Gasification is an effective thermochemical process for converting biomass and waste into synthesis gas, providing a valuable renewable energy source. In this context, this study proposes the valorization of cannabis waste, specifically hemp, through the gasification process, using a downdraft gasifier and a mixture of air and steam as the gasifying agent to produce synthesis gas. The main operating parameters influencing the gasification process (biomass/steam ratio, equivalence ratio, and temperature) were evaluated, as well as the influence of the steam explosion as a pre-treatment of the cannabis waste. The highest H 2 , CO concentrations, and LHV were observed among the evaluated parameters at an S/B ratio of 1 ER = 0.25 and T = 900 °C. With H₂ contents above 40 % vol, the gasification process demonstrated significant potential for energy valorization of cannabis waste compared to other biomass sources. • H 2 -rich syngas has been produced from the gasification of cannabis waste for the first time. • The potential of steam as a gasification agent was presented. • Temperature, equivalence ratio, and steam/biomass ratio were evaluated. • A semi-pilot downdraft gasifier was used to produce H 2 -rich syngas. • Evaluation of the steam explosion as a biomass pretreatment for gasification.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".