Metabolism of BTEX and Naphtha Compounds to Methane in Oil Sands Tailings
Bibliographic record
Abstract
Naphtha, comprising low molecular weight aliphatics and aromatics (C3-C14), is used as a diluent in processing of bitumen from oil sands. A small fraction (<1%) is lost to tailings waste and incorporated into mature fine tailings (MFT). BTEX (benzene, toluene, ethylbenzene, and xylenes) and whole naphtha were assessed for biodegradation under methanogenic conditions using MFT from an oil sands tailings settling basin. MFT spiked with 0.05-0.1% w/v of BTEX compounds produced up to 2.1 (+/-0.1) mmol of methane during 36 weeks of incubation. Metabolism of 0.5-1.0% w/v naphtha in MFT yielded up to 5.7 (+/-0.2) mmol of methane during 46 weeks of incubation. Gas chromatographic analyses showed that BTEX degraded in the sequence: toluene > o-xylene > m- plus p-xylene > ethylbenzene > benzene. Only 15-23% of whole naphtha, mainly n-alkanes (in the sequence: nonane > octane > heptane) and some BTEX compounds (toluene > o-xylene > m-xylene), was metabolized. Other naphtha constituents, such as iso-paraffins and naphthenes, remained unchanged during this period. These results suggest that the microbial communities in the MFT can readily utilize certain fractions of unrecovered naphtha in oil sands tailings and support methanogenesis in settling basins. Current study findings could influence extraction process, MFT management, and reclamation options.
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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".