The Influence of Water Quality Characteristics on Vanadium Toxicity to Model Aquatic Organisms
Bibliographic record
Abstract
Vanadium (V) is a contaminant of emerging concern for the Alberta oil sands region that could present a risk for aquatic organisms. Petroleum coke (PC) has been experimentally used to treat oil sands process-affected water (OSPW) to reduce organic toxicants. However, PC contains up to 1,000 mg of V per kg of PC, and during OSPW treatment V leaches from coke reaching levels of up to 7 mg/L in “treated” OSPW, a concentration that is toxic to aquatic organisms. Little information is available on how common water quality variables affect the toxicity of V to aquatic organisms. Furthermore, there is no clear understanding of the mechanism(s) of toxicity of V in aquatic organisms. Vanadium is a transition metal with several oxidation states, and could potentially elicit its toxicity through either ion imbalance or oxidative stress. Therefore, the objectives of this research were to (i) investigate the influence of key water chemistry variables representative of the Alberta oil sands region on V toxicity to freshwater organisms, and (ii) determine if ion imbalance and oxidative stress are part of its mechanism of toxicity. To describe how water chemistry influences V toxicity to two representative freshwater organisms, Daphnia pulex and Oncorhynchus mykiss, descriptive relationships were developed between those parameters that differ the most between OSPW and the Athabasca River. Results indicate that an increase in pH increases V acute toxicity to both species, whereas increasing alkalinity and sulphate ameliorate V toxicity to both species. Sodium only causes amelioration of V toxicity to daphnids above 325 mg/L. The mechanistic studies with Daphnia magna and O. mykiss suggest that concentrations of V close to their respective median lethal concentration (LC50) cause sodium imbalance in both species, as well as calcium imbalance in rainbow trout, and oxidative stress in O. mykiss. In conclusion, the influence of pH, alkalinity and sulphate on V toxicity should be considered when creating new acute water quality guidelines or local benchmarks for V. The mechanism of V toxicity to aquatic organisms includes ion imbalance and oxidative stress, but further mechanistic research will be needed to increase knowledge on the ecological risks of V contamination, which will enable the formulation of possible mitigation strategies.
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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".