Pyrolysis of Wood Residues in a Cylindrical Batch Reactor: Effect of Operating Parameters on the Quality and Yield of Products
Bibliographic record
Abstract
Appropriate technology for conversion of waste biomass into valuable products has often been overlooked in Sub-Saharan Africa. The influence of operating parameters such as; type of technology, and biomass type, on the conversion process, is a barely known. This contribution aimed at studying the pyrolysis of wood residues and the specific objectives included; (1) characterization of the organic products (wood vinegar and tar) of pyrolysis of wood residues, (2) investigation of the effect of temperature and feedstock type on the yield of products and (3) to carry out an energy balance of the pyrolysis reactor system. Wood residues were pyrolysed in a cylindrical batch reactor at temperatures 300-350, 400-450 and 500-5500C and the organic were characterised using a gas chromatograph (GC) fitted with a flame ionisation detector (FID). The most notable compounds in the wood vinegar and tar were; alcohols, acids, furans, phenols, aldehydes, and ketones. The yield of vinegar, tar and char reduced significantly with increase in temperature and the maximums were produced at 300-3500C whereas the yield of non-condensable gases increased with increase in temperature. The type of feedstock used had no significant effect on the yield and distribution of products. The energy balance of the system revealed that the process was 78% efficient. The presence of the oxygenated aliphatic and aromatic hydrocarbons makes the wood vinegar and tar potential sources of chemicals and engine fuels. Preliminary trials with wood vinegar were lethal to black ants that are predominantly a menace to farmers in Sub-Saharan Africa.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".