Ecotoxicity of canola and tallow biodiesel blends to selected soil organisms
Bibliographic record
Abstract
In view of depleting fossil fuel resources and environmental concern, biodiesel couldpotentially replace petroleum-derived diesel. Aquatic toxicity of diesel and biodiesel has beenextensively studied over the past decades but little is still known about their toxicity in soilenvironment. The scope of this study was to evaluate the environmental impact of biodiesel,biodiesel blends and petroleum diesel in soil using direct contact toxicity assays. The selectedbiodiesels included canola-source biodiesel (B100 and B20). and tallow-source biodiesel (B100and B20), which were compared to petroleum ultra-low-sulfur based diesel (ULSD). Selectedstandard terrestrial toxicity tests included ryegrass Lolium perenne seedling emergence andgrowth, earthworm Eisenia fetida survival, and soil microbial dehydrogenase activity. Soilcharacterization included the quantification of total extractable materials (corresponding to the n-alkane range of C10-C34). Preliminary results indicate that: 1) canola and tallow B20 biodieselblends were less toxic to earthworm than ULSD; 2) canola and tallow B20 blends had similartoxic effects to ryegrass as ULSD; and 3) petroleum ULSD inhibited the DHA activity at allconcentrations tested, and B20 canola biodiesel had a deleterious effect on the DHA activity atthe lowest nominal loadings tested (1 and 10 ml/kg dry soil). Therefore, this study providesuseful toxicological data for the evaluation of potential adverse impact of biodiesel in theenvironment, such as an accidental release or spill. This project was funded by EnvironmentCanada and Natural Resources Canada and is part of the Advanced Fuels and Technologies forEmissions Reduction (AFTER) Program for energy research and development (PERD).
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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 | 0.000 | 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) | 0.001 | 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 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".