Influence of Molecular Structure on the Biodegradability of Naphthenic Acids
Bibliographic record
Abstract
Large volumes of toxic aqueous tailings containing a complex mixture of naphthenic acids (NAs; CnH2n+ZO2) are produced in northern Alberta by the oil sands industry. Because of their persistence and contribution to toxicity, there is an urgent need to understand the fate of NAs under a variety of remediation scenarios. In a previous study, we developed a highly specific HPLC-high resolution mass spectrometry method for the analysis of NAs. Here we apply this method to determine quantitative structure-persistence relationships and kinetics for commercial NAs and NAs in oil sands process water (OSPW) during aerobic microbial biodegradation. Biodegradation of commercial NAs revealed thatthe mixture contained a substantial labile fraction, which was rapidly biodegraded, and a recalcitrant fraction composed of highly branched compounds. Conversely, NAs in OSPW were predominantly recalcitrant, and degraded slowly by first-order kinetics. Carbon number (n) had little effect on the rate of biodegradation, whereas a general structure-persistence relationship was observed indicating that increased cyclization (Z) decreased the biodegradation rate for NAs in both mixtures. Time to 50% biodegradation ranged from 1 to 8 days among all NAs in the commercial mixture, whereas half-lives for OSPW NAs ranged from 44 to 240 days, likely a result of relatively high alkyl branching among OSPW NAs. It is anticipated that these data will facilitate development of strategic solutions for remediating billions of cubic meters of OSPW stored, or predicted to be generated, in Northern Alberta.
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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".