Meso-scale studies on the penetration and retention of diluted bitumen in different types of shorelines, Northern British Columbia, Canada
Bibliographic record
Abstract
ABSTRACT 2017-210 Compared to conventional oil, diluted bitumen (dilbit) spills in the environment could be challenging due to the rapid increase in density, viscosity and adhesion properties associated with accelerated weathering. To enhance the response in case of an accidental dilbit spill in the marine environment, a Research & Development program has been developed by the Emergencies Science and Technology Section (ESTS) of Environment and Climate Change Canada (ECCC) as a part of the Federal Government’s Enhancing Marine Safety Strategy. One of the goals of this project was to develop science-based decision support for a dilbit spill to the shorelines of northern British Columbia (BC). In response to this objective, the contractor Coastal and Ocean Resources Inc. has conducted a meso-scale Diluted Bitumen Sediment Interactions Experiments (Bit_EX) to evaluate the potential of penetration and retention of dilbit in different types of sediments. In total, two dilbits, Access Western Blend (AWB) and Cold Lake Blend (CLB) at three weathered states (0%, 17% and 26% mass loss), were tested against seven types of sediments (from coarse sand to very large pebble). The adhesion of dilbit on bare cobbles and on cobbles covered with barnacles and seaweed (fucus) was also tested for different time of exposure. Results showed that unweathered (or fresh) dilbit has its maximum penetration and retention in coarse sand or granule whereas moderately weathered dilbit has maximum penetration and retention in small pebbles or larger sediment sizes. Heavily weathered dilbits have very limited penetration in finer sediments but are expected to penetrate and have high retention in permeable coarse sediments. Moreover, we have observed that dilbit adherence could be enhanced with longer drying time. In northern BC, the bedrock platforms with thin overlays of various types of sediment, from sand to boulders, are common and presents a complex case for treatment. Because dilbit characteristics change rapidly, early SCAT survey data combined with rapid decision and operational response in the initial stages of the spill could reduce dilbit retention and adhesion. The Bit_EX also suggests that existing techniques for protection and cleanup of conventional oil on shorelines could be applicable or can be adjusted for dilbit spills. This experiment provides information suitable to a first response guide for protecting and cleaning shorelines in case of bitumen spills in northern BC.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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".