Pyrolysis of Woody Residue Feedstocks: Upgrading of Bio-oils from Mountain-Pine-Beetle-Killed Trees and Hog Fuel
Bibliographic record
Abstract
Liquid transportation fuel blendstocks were produced by pyrolysis and catalytic upgrading of woody residue biomass. Mountain-pine-beetle-killed (MPBK) wood and hog fuel from a saw mill were pyrolyzed in a 1 kg/h fluidized bed reactor and, subsequently, upgraded to hydrocarbons in a continuous fixed bed hydrotreater. Upgrading was performed by catalytic hydrotreatment in a two-stage bed at 170 and 405 °C with a per bed liquid hourly space velocity between 0.17 and 0.19. The overall yields from biomass to upgraded fuel were similar for both feeds (24–25%), despite the differences in bio-oil (intermediate) mass yield. The pyrolysis bio-oil mass yield was 61% from MPBK wood, and subsequent upgrading of the bio-oil gave an average mass yield of 41% to liquid fuel blend stocks. Hydrogen was consumed at an average of 0.042 g/g of bio-oil fed, with a final oxygen content in the product fuel ranging from 0.3 to 1.6% over the course of the test. Comparatively, for hog fuel, the pyrolysis bio-oil mass yield was lower at 54% because of inorganics in the biomass, but subsequent upgrading of that bio-oil had an average mass yield of 45% to liquid fuel, resulting in a similar final mass yield to fuel compared to the cleaner MPBK wood. Hydrogen consumption for the hog fuel upgrading averaged 0.041 g/g of bio-oil fed, and the final oxygen content of the product fuel ranged from 0.09 to 2.4% over the run. While it was confirmed that inorganic-laden biomass yields less bio-oil, this work demonstrated that the resultant bio-oil can be upgraded to hydrocarbons at a higher yield than bio-oil from clean wood. Thus, the final hydrocarbon yield from clean or residue biomass pyrolysis/upgrading was similar.
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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".