Potential impact of northern resource development on aquatic biota: toxicity of chromium and rare earth element processing reagent
Bibliographic record
Abstract
Chromite and rare earth element development was identified in the 2015 Canadian Federal budget as a significant opportunity, however, key data gaps exist regarding the environmental concerns related to these resource developments. Chromium is essential in the production of stainless steel, and no suitable substitute is known. Rare earth elements (REEs) are a series of metals that are composed of 15 lanthanides, as well as scandium and yttrium. Uses for REEs range from electronic devices (i.e. cell phones, computers, televisions) to magnets and controlling nuclear reactors. While commercial production of REEs signify a great economic opportunity for Canada, key data gaps regarding chemicals involved in processing REEs has been identified. The first objective of this study was to determine the acute toxicity of hexavalent chromium (Cr (VI)) to the invertebrate species Hyalella azteca and to identify the potential mitigating influences of cations and dissolved organic matter (DOM). The second objective was to evaluate the acute toxicity of flotation reagent AERO 6493, conduct toxicity identification/reduction studies, and test REE processing wastewater toxicity to H. azteca and Daphnia magna. Standard methods were followed for both 48 h (D. magna) and 96 h (H. azteca) acute toxicity tests, in media with pH 7.3 and water hardness of 120 mg CaCO3 /L (D. magna) and 60 mg CaCO3 /L (H. azteca) for both objectives. For objective 1, effect of altering water chemistry on Cr (VI) toxicity to H. azteca was tested with additions of Ca (0.5-3.5mM), Na (0.5-3 mM), Mg (0.13-0.64mM), as well as additions of natural sources of DOC (from Pickle Lake and Luther Marsh) at concentrations of 5 and 12 mg DOC/L. No protective effect was observed with additions of Na+, Pickle Lake and 2016 Luther Marsh DOC sources, but a significant protective effect was observed for 2015 Luther Marsh DOC, elevated Mg2+ and Ca2+ concentrations. For objective 2, LC50 was calculated based on survival/mortality for H. azteca (2.6 E-16 % dilution of parent AERO 6493 compound for fresh, 3.9 E-18 % for aged) and immobilization for D. magna (2.0E-5 %). Acute REE processing wastewater toxicity was also calculated for H. azteca (2.44%) and D. magna (23.35%). Studies conducted to determine acute toxicity of Cr (VI) to H. azteca not only lead to an improved understanding of site-specific Cr (VI) toxicity, but also may help to improve the water quality guidelines for protection of aquatic life. As for the toxicity of REE processing reagent AERO 6493, dilutions anticipating the worst possible scenario was tested to invertebrate species. Calculated LC50s and EC50s of parent AERO 6493 and wastewater will help develop a better understanding of toxicity of chemicals incorporated in REE processing, as well as potential suggestions for risk assessment and remediation steps.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".