Anaerobic Biodegradation of Longer-Chain <i>n</i>-Alkanes Coupled to Methane Production in Oil Sands Tailings
Bibliographic record
Abstract
Extraction of bitumen from mined oil sands ores produces enormous volumes of tailings that are stored in settling basins (current inventory ≥ 840 million m(3)). Our previous studies revealed that certain hydrocarbons (short-chain n-alkanes [C(6)-C(10)] and monoaromatics [toluene, o-xylene, m-xylene]) in residual naphtha entrained in the tailings are biodegraded to CH(4) by a consortium of microorganisms. Here we show that higher molecular weight n-alkanes (C(14), C(16), and C(18)) are also degraded under methanogenic conditions in oil sands tailings, albeit after a lengthy lag (~180 d) before the onset of methanogenesis. Gas chromatographic analyses showed that the longer-chain n-alkanes each added at ~400 mg L(-1) were completely degraded by the resident microorganisms within ~440 d at ~20 °C. 16S rRNA gene sequence analysis of clone libraries implied that the predominant pathway of longer-chain n-alkane metabolism in tailings is through syntrophic oxidation of n-alkanes coupled with CO(2) reduction to CH(4). These studies demonstrating methanogenic biodegradation of longer-chain n-alkanes by microbes native to oil sands tailings may be important for effective management of tailings and greenhouse gas emissions from tailings ponds.
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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) | 0.000 | 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".