Advanced characterisation of organic matter in oil sands and tailings sands used for land reclamation by Fourier transform-ion cyclotron resonance-mass spectrometry (FT-ICR-MS)
Bibliographic record
Abstract
The Athabasca region of northern Alberta, Canada, is home to deposits of oil sands containing vast amounts (~ 173 billion barrels) of heavily biodegraded petroleum. Oil sands are recovered by surface mining or by in situ steam injection. The extraction of bitumen from oil sands by caustic hot water processing results in large volumes of fluid tailings, which are stored in on-site settling basins. There the tailings undergo a compaction and dewatering process, producing a slowly densifying suspension. The released water is recycled for extraction. The fine tailings will be reclaimed as either dry or wet landscapes. [1] To produce 1 barrel of crude oil, 2 tons of oil sand and 2 - 3 tons of water (including recycled water) are required. [2] Open pit mining and the extraction of the bitumen from the oil sands create large and intense disturbances of different landscapes. The area currently disturbed by mining operations covers about 530 km2 and the area of tailing ponds surpasses 130 km2. An issue of increasing importance is the land remediation and reclamation of oil sand areas in Canada and the reconstruction of these disturbed landscapes back to working ecosystems similar to those existing prior to mining operations. An important issue in this context is the identification of oil sand-derived organic compounds in the tailings, their environmental behaviour and the resulting chances and limitations with respect to land reclamation. Furthermore the biodegradation processes that occur in the tailings and that could lead to a decrease in hazardous organic compounds are important challenges, which need to be investigated. This presentation will give a detailed overview of our compositional and quantitative characterisation of the organic matter in oil sand, unprocessed and processed mature fine tailings samples as well as in tailings sands used as part of land reclamation. The analytical characterisation is based on the extraction of the soluble organic matter, its subsequent separation into asphaltenes, aliphatic hydrocarbons, aromatic hydrocarbons, neutral nitrogen, sulphur, oxygen (NSO) compounds and carboxylic acids. The asphaltene fractions are analysed using pyrolysis-GC, all other fractions are analysed by GC-MS. Additionally Fourier transform-ion cyclotron resonance-mass spectrometry (FT-ICR-MS) is used to study the chemical composition of the samples on the molecular level using different ionisation methods.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".