Biorefineries in Kraft pulp mills for biofuels production: A critical review
Bibliographic record
Abstract
Abstract Kraft pulp production generates residues and by‐products of significant importance to the mill. Solid residues from forestry activities are commonly used to generate steam in power boilers. In the recovery cycle, black liquor generates steam (and subsequently energy) by burning in the Tomlinson boiler, while white liquor is regenerated. Well‐developed alternative technologies can use these residues and by‐products to generate different types of biofuels. This review addresses the use of such technologies integrated with Kraft mills, in the concept of biorefineries, showing advantages, disadvantages, and successful examples. Solid residues from forestry can be used to produce bio‐oil through processes such as fast pyrolysis and hydrothermal liquefaction. Bio‐oils are currently used for heating through combustion in commercial/industrial boilers, but greater appreciation occurs if used as biofuels, which is done through catalytic upgrading processes. Black liquor gasification generates synthesis gas, which can be burned for energy co‐generation, used to produce synthetic fuels, or as a hydrogenating agent for bio‐oil or crude tall oil catalytic upgrading. Kraft biorefineries are gradually being implemented, justifying efforts to improve existing and new biomass conversion technologies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| 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".