Attenuation of phenylnaphthenic acids related to oil sands process water using solar activated calcium peroxide: Influence of experimental factors, mechanistic modeling, and toxicity evaluation
Bibliographic record
Abstract
Refractory naphthenic acids (NAs) are among the primary toxic compounds in oil sands process water (OSPW), a matrix with a complex chemical composition that poses challenges to its remediation. This study evaluated the effectiveness of calcium peroxide (CaO2) combined with solar radiation (solar/CaO2) as an advanced water treatment process for degrading model NAs (1,2,3,4-tetrahydronaphthalene-2-carboxylic acid, pentanoic acid, and diphenylacetic acid) in synthetic water (STW) and provide preliminary insights in treating real OSPW. Solar light and CaO2 acted synergistically to degrade target NAs in STW (>67 of synergistic factor) following a pseudo-first-order kinetic (R2 ≥ 0.95), with an optimal CaO2 dosage of 0.1 g L–1. Inorganic ions and dissolved organic matter were found to hinder the degradation of NAs by solar/CaO2 treatment; however, the complete degradation of NAs was reached in 6.7 h of treatment. The main degradation mechanism involved the generation of hydroxyl radicals (•OH), which contributed ∼90% to the apparent degradation rate constant (K), followed by H2O2 (4–5%) and 1O2 (0–5%). The tentative transformation pathways of three NAs were proposed, confirming an open-ring reaction and resulting in short-chain fatty acid ions as final products. Furthermore, a reduction in acute microbial toxicity and genotoxic effect was observed in the treated samples, suggesting that solar/CaO2 treatment exhibits high environmental compatibility. Furthermore, the solar/CaO2 system was successfully applied as a preliminary step for real-world applications to remove natural NAs, fluorophore organic compounds, and inorganic components from OSPW, demonstrating the potential use of this technology in the advanced treatment of oil-tailing-derived NAs.
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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".