Guidelines for Transportation, Handling, and Use of Fast Pyrolysis Bio-Oil. 1. Flammability and Toxicity
Bibliographic record
Abstract
An alternative sustainable fuel, biomass-derived fast pyrolysis oil or “bio-oil”, is coming into the market in Europe. Fast pyrolysis pilot and demonstration plants for fuel applications producing tonnes of bio-oil are in operation, and commercial plants are under design. There will be increasingly larger amounts of bio-oil transportation on water and by land, leading to a need for further specifications and supporting documentation. The properties of bio-oil are different from conventional liquid fuels and, therefore, may need to overcome both technical and marketing hurdles for its acceptability in the fuels market. Multiple material safety data sheets (MSDSs) are currently being used by different producers, but there is a desire to update these as more information becomes available. In order to standardize bio-oil, quality specifications are being adopted. The first bio-oil burner fuel standard in ASTM D7544 was approved in 2010. CEN standardization has been initiated in Europe. In the EU, a new chemical regulation system REACH (Registration, Evaluation and Authorisation of Chemicals) exists. Registration under REACH has to be perfomed if bio-oil is produced or imported into the EU. In the USA and Canada, bio-oil has to be filed under the TSCA (US Toxic Substances Control Act) and DSL (Domestic Substance List), respectively. In this paper, the state of the art on standardization is discussed, and new data for the transportation guidelines is presented. The focus is on flammability and toxicity.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.035 | 0.052 |
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".