Solar-activated tin oxide photocatalysis for efficient naphthenic acids removal and toxicity reduction in oil sands process water
Bibliographic record
Abstract
This research studied, for the first time, the effect of activating tin oxide (SnO 2 ) under simulated solar light for treating real oil sands process water (OSPW). The solar/SnO 2 system effectively eliminated fluorophore organic contaminants, classical naphthenic acids (O 2 -NAs), and oxidized NAs (Oxy-NAs) from OSPW. The best experimental conditions to remove over 90 % of O 2 -NAs were found to be 0.5 g/L SnO 2 under 8 h of irradiation. HO • and O 2 •– species identified by electron paramagnetic resonance (EPR) analysis played an important role in the degradation of NAs and other contaminants in real OSPW. The initial toxic effects of untreated OSPW were noticeably reduced after treatment, with a reduction of approximately 50 % in acute toxicity using Microtox® bioassay and over 80 % in the level of bioavailable hydrocarbons. In addition, the process also demonstrated a significant reduction in immunotoxicity as measured using an immune cell bioassay and reduced the toxic effects on Staphylococcus warneri using an adapted bacterial minimal inhibitory concentration (MIC) viability assay. These results suggest that treated OSPW by SnO 2 under solar light has high environmental compatibility, indicating it is safe for reuse in further applications. • SnO 2 under simulated solar light effectively degraded NAs and other organic compounds in OSPW. • Over 90 % of classical NAs were removed by SnO 2 (0.5 g/L) after 8 h under solar light. • Hydroxyl and superoxide radicals were dominant in the photocatalytic reactions. • NAs degradation is structurally dependent, and influenced by DBE and carbon number. • A significant reduction in toxicity was observed in treated OSPW.
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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) | 0.000 | 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 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".