A critical review on biomass gasification, co-gasification, and their environmental assessments
Bibliographic record
Abstract
Gasification is an efficient process to obtain valuable products from biomass with several potential applications, which has received increasing attention over the last decades. Further development of gasification technology requires innovative and economical gasification methods with high efficiencies. Various conventional mechanisms of biomass gasification as well as new technologies are discussed in this paper. Furthermore, co-gasification of biomass and coal as an efficient method to protect the environment by reduction of greenhouse gas (GHG) emissions has been comparatively discussed. In fact, the increasing attention to renewable resources is driven by the climate change due to GHG emissions caused by the widespread utilization of conventional fossil fuels, while biomass gasification is considered as a potentially sustainable and environmentally-friendly technology. Nevertheless, social and environmental aspects should also be taken into account when designing such facilities, to guarantee the sustainable use of biomass. This paper also reviews the life cycle assessment (LCA) studies conducted on biomass gasification, considering different technologies and various feedstocks.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".