Biodegradation of Naphthenic Acids by Microorganisms Originating from Alberta's Oil Sands Surface Mining Operations
Bibliographic record
Abstract
Billions of liters of tailings water are produced from oil sands surface mining operations each year. Reclamation of tailings ponds is now a legislated process that must occur within 10 years after the end of an oil sands mining operation. To reclaim these waste ponds back to a natural landscape, toxic compounds must first be removed, including naphthenic acids (NAs), which are the primary toxic components. I investigated the biodegradation ability of three different microbial culture sets - photosynthetic algal-bacterial communities, aerobic bacterial communities, and a nitrate-reducing bacterial community - for their ability to metabolize the two model NAs cyclohexanecarboxylic acid (CHCA) and 1-adamantanecarboxylic acid (1-ADCA). Using gas chromatography-mass spectrophotometry, DNA stable isotope probing, and 16S/18S rRNA gene sequencing techniques, the work in this thesis illustrates the metabolism and organisms responsible for the biodegradation of the model NAs studied. All three microbial culture sets successfully biodegraded CHCA, while the structurally more complex 1-ADCA could only be biodegraded by the algal-bacterial communities, suggesting the potential value of such consortia for treating NA in oil sands tailings ponds. The DNA stable isotope probing experiments revealed that of the algae, members of the family Scenedesmaceae and the class Trebouxiophyceae both contribute to the biodegradation of CHCA. Brevundimonas and Rhodococcus were the two primary genera found associated with the biodegradation of CHCA in the aerobic bacterial communities. Sequencing results revealed that the nitrate-reducing bacterial community was primarily composed of known sulfate-reducing microorganisms, an intriguing result that warrants additional study.
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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) | 0.001 | 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 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".