Diluted Bitumen: Physicochemical Properties, Weathering Processes, Emergency Response, and Recovery
Bibliographic record
Abstract
Bitumen, an unconventional crude oil, has received much attention with the increasing consumption and the shrinking storage of conventional crude oils. Bitumen is highly viscous and, thus, is commonly diluted for transportation purposes. Spills of diluted bitumen could occur during the transportation from reservoirs to refineries via pipeline, rail, and marine vessels. Although some laboratory and numerical modeling studies have been contributed to study the spill of diluted bitumen from different aspects, there is no systematic review in the field yet. Therefore, this study first conducted a review on different types of diluted bitumen based on their physicochemical properties, followed by their weathering processes including spreading, evaporation, emulsification, photooxidation, biodegradation, and sinking. Second, the numerical modeling on the fate and behavior of spilled diluted bitumen was summarized and analyzed. Finally, the techniques for spilled oil recovery were discussed, as well as the disposal/treatment of oily waste. Currently, a rare attempt has been made to turn the recovered oily waste into wealth (reutilization/valorization of oily waste). Using the recovered oily waste as the feedstock/processing medium for an emerging thermochemical conversion technique (hydrothermal liquefaction of biomass for crude bio-oil production) is highly recommended. Overall, this article summarized the state-of-the-art knowledge of the spill of diluted bitumen, with the hope to create a deep and systematic understanding on the spill of diluted bitumen for researchers, relevant companies, and decision makers.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".