Metal sulfides in aged-coarse sands tailings facilitate naphthenic acids removal from oil sands process water
Bibliographic record
Abstract
• Aged-CST exhibited enhanced NAs removal efficiency, linked to high MeS content. • MeS in aged-CST enhanced the chemical reactivity and surface heterogeneity. • Chemisorption, precipitation with MeS, and acid hydrolysis were likely mechanisms. • Hydrocarbon degraders contributed to slow degradation of organics in the long term. • Elevated sulfate levels and sulfur-related toxicity remain outstanding concerns. The use of natural substrates for oil sands process water (OSPW) reclamation offers advantages such as onsite availability and scalability. This study evaluated potential of aged and fresh coarse sand tailings (CST) towards removal of classical naphthenic acids (NAs) from a real OSPW obtained from an oil sands’ tailing ponds in Alberta (NAs: 4.87 mg/L). Aged-CST achieved superior removal efficiencies of NAs (96.5 %), aromatics (>90 %), and acid-extractable organics (∼95 %), compared to fresh-CST, which showed limited removal (∼34.3 %) similar to conventional slow sand filters (∼30–45 %). Although limited surface area of both CST materials (∼1.82 m 2 /g) was not conducive to physical adsorption, the oxidation of metal sulfides in aged-CST enhanced the chemical reactivity, surface heterogeneity, and microbial activity, facilitating efficient adsorption, precipitation, and biodegradation of NAs. Kinetics modelling indicated that aged-CST strongly fit the pseudo-second order (R² = 0.969, k₂ = 0.003 g mg⁻¹ h⁻¹) and Elovich model (R² = 0.876, 1/ b = 1.713 mg g⁻¹), indicating chemisorption as dominant removal mechanism, while fresh-CST exhibited poor fits and limited performance. Fourier-transform infrared spectroscopy and synchronous fluorescence spectroscopy analyses revealed that intensities of hydroxyl groups, aliphatic, carboxylic, and ester compounds significantly increased in aged-CST after filtration. A labelled isotope desorption study using Lauric-D23 acid cross-verified that adsorption and precipitation (∼65 %) with metal sulfides were key mechanisms, while remaining ∼35 % were chemically transformed by-products, as indicated by mass balance. Microbial community analysis showed that aged-CST had higher microbial richness (Chao1 ∼1000) compared to fresh-CST (∼500, respectively). Hydrocarbon-degrading bacteria (e.g., Rhodococcus and Sphingomonas ) and acidophilic bacteria ( Bryobacter, Candidatus Solibacter ) were dominant in aged-CST, facilitating NAs biodegradation. BE-SPME analysis confirmed successful removal (∼86 %) of bioavailable organics removing toxicity. This study highlights aged-CST as a viable natural substrate for OSPW reclamation, offering insights into its fate and opportunities for resource recovery.
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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".