Exploring the complexity of oil sands process‐affected water by high efficiency supercritical fluid chromatography/orbitrap mass spectrometry
Bibliographic record
Abstract
RATIONALE: Approximately 1 billion m(3) of oil sands process-affected water (OSPW) is currently stored in tailings ponds in Northern Alberta, Canada. The dissolved organic compounds in OSPW have been termed a supercomplex mixture of bitumen-derived substances and continuing efforts to understand its underlying chemical composition are important for evaluating its environmental hazards. METHODS: Packed column supercritical fluid chromatography (SFC) was applied to OSPW analysis for the first time. By combining four columns in series (each 25 cm × 4.6 mm I.D., 5.0 µm bare silica) approximately 80,000 plates were achieved on a 1 m column. Using a simple fixed restrictor, the SFC eluent was coupled directly to ultrahigh-resolution orbitrap mass spectrometry (SFC/Orbitrap-MS). RESULTS: SFC/Orbitrap-MS, with positive and negative atmospheric pressure chemical ionization (APCI +/-), revealed the partial or full chromatographic separation of isomers for a wide array of chemical species, including naphthenic acids (Cn H2n + Z O2 ) and unknown sulfur- and nitrogen-containing molecules. For smaller compounds (e.g. naphthenic acids where n ≤10), or for larger structurally constrained compounds (e.g. C16 naphthenic acid with 9 double-bond equivalents), apparent baseline resolution of many isomers was possible. Isomer-specific MS/MS experiments furthermore allowed characterization of functional groups in novel species. For example, in APCI+ mode, up to 16 isomers of C6 H11 ON were revealed to have amide and amino functionalities. CONCLUSIONS: This combination of high efficiency chromatography and ultra-high mass resolution detection resulted in a powerful method with capabilities for characterizing or 'fingerprinting' unknown species with little interference. The method has great promise for environmental monitoring and forensics in the oil sands region, as well as for further studies on the composition of dissolved organic compounds in OSPW.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".