High Potential for Anaerobic Microbial Sulfur Oxidation in Oil Sands Tailings Ponds
Bibliographic record
Abstract
The biogenic production of toxic H2S gas in sulfate-rich oil sands tailings ponds is associated with strong environmental concerns. Beside precipitation into sulfide minerals and chemical re-oxidation, microbial sulfur oxidation may catalyze sulfide re-cycling but potentially contributes to acid rock drainage (ARD) generation. To evaluate the microbial potential for sulfur oxidation, we conducted a microcosm-based pilot study with tailings of an active pond. Incubations were performed under oxic and anoxic conditions, with and without KNO3 as an electron acceptor and thiosulfate as a common substrate for microbial sulfur oxidation. The highest potentials of sulfur oxidation occurred in oxic assays (1.21 mmol L−1 day−1). Under anoxic conditions, rates were significantly lower and dominated by chemical transformation (0.09 mmol L−1 day−1; p < 0.0001). The addition of KNO3 to anoxic incubations increased microbial thiosulfate oxidation 2.5-fold (0.23 mmol L−1 day−1; p = 0.0474), with complete transformation to SO42− coupled to NO3− consumption, pointing to the activity of sulfur-oxidizing bacteria (SOB) under nitrate-reducing conditions. Importantly, in the presence of KNO3, a decrease in sedimentary sulfides was associated with an increase in S0, which indicates the potential for microbially mediated oxidation of sulfide minerals and ARD generation. Furthermore, the comparative analysis of sediments from other anthropogenic aquatic habitats demonstrated high similarities with respect to viable SOB counts and corresponding activity rates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 teacher head, 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".