Evaluating the attenuation of naphthenic acids in constructed wetland mesocosms planted with Carex aquatilis
Bibliographic record
Abstract
Abstract Surface oil sand mining and extraction in northern Alberta’s Athabasca oil sands region produces large volumes of oil sand process–affected waters (OSPW). OSPW is a complex mixture containing major contaminant classes including trace metals, polycyclic aromatic hydrocarbons, and naphthenic acid fraction compounds (NAFCs). Naphthenic acids (NAs) are the primary organic toxicants in OSPW and reducing their concentrations is a priority for all oil sands companies. Previous evidence has shown that constructed wetland treatment systems (CWTS) are capable of reducing the concentration of NAs and the toxicity of OSPW through bioremediation. In this study, we constructed greenhouse mesocosms with OSPW or lab process water (LPW, i.e., water designed to mimic OSPW minus the NAFC content) with three treatments: (1) OSPW planted with Carex aquatilis, (2) OSPW – no plants, and (3) LPW – no plants. The OSPW – C. aquatilis treatment saw a significant reduction in NAFC concentrations in comparison to OSPW- no plants treatments, but both changed the distribution of the NAFCs in similar ways. Upon completion of the study, treatments with OSPW saw fewer high molecular weight NAs and an increase in the abundance of O3– and O4–containing formulae. Results from this study provide invaluable information on how constructed wetlands can be used in future remediation of OSPW in a way that previous studies were unable to achieve due to uncontrollable environmental factors in field experiments and the active, high-energy processes used in CWTS pilot studies.
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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 | 0.001 |
| 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".