Degradation of naphthenic acids by sediment micro-organisms
Bibliographic record
Abstract
AIMS: Naphthenic acids (NAs) are naturally occurring, linear and cyclic carboxylic surfactants associated with the acidic fraction of petroleum. NAs account for most of the acute aquatic toxicity of oil sands process-affected water (OSPW). The toxicity of OSPW can be reduced by microbial degradation. The aim of this research was to determine the extent of NA degradation by sediment microbial communities exposed to varying amounts of OSPW. METHODS AND RESULTS: Eleven wetlands, both natural and process-affected, and one tailings settling pond in Northern Alberta were studied. The natural wetlands and process-affected sites fell into two distinct groups based on their water chemistry. The extent of degradation of a 14C-labelled monocyclic NA surrogate [14C-cyclohexane carboxylic acid (CCA)] was relatively uniform in all sediments (approximately 30%) after 14 days. In contrast, degradation of a bicyclic NA surrogate [14C-decahydronaphthoic acid (DHNA)] was significantly lower in non process-affected sediments. Enrichment cultures, obtained from an active tailings settling pond, using commercially available NAs as the sole carbon source, resulted in the isolation of a co-culture containing Pseudomonas putida and Pseudomonas fluorescens. Quantitative GC-MS analysis showed that the co-culture removed >95% of the commercial NAs, and partially degraded the process NAs from OSPW with a resulting NA profile similar to that from 'aged wetlands'. CONCLUSIONS: Exposure to NAs induced and/or selected micro-organisms capable of more effectively degrading bicyclic NAs. Native Pseudomonas spp. extensively degraded fresh, commercial NA. The recalcitrant NAs resembled those found in process-affected wetlands. SIGNIFICANCE AND IMPACT OF THE STUDY: These results suggest that it may be possible to manipulate the existing environmental conditions to select for a microbial community exhibiting higher rates of NA degradation. This will have significant impact on the design of artificial wetlands for water treatment.
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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".