Sm and Dy Interaction with Dissolved Organic Matter (DOM) in Freshwater Measured by Ion-Selective Electrode and Fluorescence Quenching Analytical Techniques
Bibliographic record
Abstract
With the increased demand for lanthanide metals in various industries, companies are looking into mining of these metals in Northern Canada. The release of these metals into the environment may have adverse effect on aquatic ecosystems; thus, it is important to understand potential toxicological effects of lanthanides on aquatic organisms. One way to predict these effects is by using a Biotic Ligand Model (BLM). Although incorporation of lanthanides into the model will require a substantial amount of future research, initial studies into speciation and toxicity can provide a useful basis for future reference. There are two main objectives to this thesis; (1) development and validation of analytical techniques for measurement of lanthanide speciation, (2) application of these techniques to assess the metal binding to dissolved organic matter (DOM) of variable sources. The techniques that were tested are fluorescence quenching (FQ) and ionselective electrode (ISE), and the experiments were done with Sm and Dy, as representatives of light and heavy groups of lanthanides, with five DOM sources. Lanthanide binding by DOM was observed by both techniques with generally good agreement between methods, as shown by similar values of free metal concentrations reported by both speciation techniques. These values were within one log unit of each other, and a large portion of them was within 0.3 log units. ISE revealed presence of nonfluorescent ligands that are able to bind Sm; such ligands cannot be measured by FQ, as it relies on the fluorescence of ligands. Although ISE produced a more complete model, there were intrinsic issues associated with cation competition. Due to this limitation, ISE analysis was not possible on the samples containing high concentrations of dissolved salts. ii Generally, the binding of lanthanides with DOM could be characterized as medium to strong with values for binding constants (log K) ranging, for both techniques, from 5.08±0.17 to 6.78±0.0170, with binding capacities varying from 0.53±0.00030 μM/mg C to 12.±1.6 μM/mg C, with little differences between Sm and Dy. There is some DOM source dependence between the colour and the source of samples, measured by SAC340 and FI370. The darkest and more allochthonous DOM (Luther Marsh DOM source with SAC340 and FI370 of 38.88 and 1.05, respectively) is able to bind more metal, especially evident in FQ experiments. The sensitivity of speciation models is observed with respect to pH and pKsp values of hydroxide and carbonate solids. The stability of pH measurements is essential for the determination of lanthanide species for the models to be applied in toxicity studies. Additionally, understanding of solid formation and experimentally determined solubility products may provide a more realistic picture of how lanthanides tend to distribute between species in samples. A generally accepted speciation model used in toxicity tests analysis is Windermere Humic Aqueous Model (WHAM). Both FQ and ISE models were compared to WHAM. The model shows a dramatic overestimation of DOM and metal binding at low concentrations of metal compared to the ISE and FQ models. One of the main disadvantages of the WHAM modeling is that it does not incorporate precipitation for lanthanides; however, solid formation is shown to be an important part of lanthanide speciation. Further research into speciation of these metals is required, before this model can be applied in the BLM calculations.
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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".