Choosing an appropriate digestion protocol for environmental risk assessments of mineralized earth materials
Bibliographic record
Abstract
Ecological and human health risk assessments at active and abandoned metal mines require accurate geochemical data for earth materials, including soils, sediments, dusts, and mine wastes. Reliable data on metal(loid) concentrations are also important for establishing geochemical baselines and to support environmental monitoring activities. However, the reported concentration for an element in a given sample can be affected by many factors, including mineralogy, grain size, laboratory digestion conditions (reagents, temperature, time), and the instrument(s) used for elemental analysis. In particular, aggressive multi-acid digestion methods used to provide 'near-total' data for some metals of environmental interest (e.g. chromium (Cr), uranium (U)) may result in the loss of other elements (e.g. antimony (Sb), arsenic (As), sulfur (S)) through volatilization prior to analysis. When comparing data from different studies or sampling periods, it is crucial to ensure that the analytical protocols used are consistent and that changes in element concentrations over time are not simply due to variations in sample processing or laboratory procedures. The purpose of this study is to compare common digestion protocols used in the analysis of geological materials and provide recommendations on the most appropriate techniques for use in environmental risk assessments. We analyzed samples of lake sediments, stream sediments, soils, and mine tailings collected at metal mine sites across Canada. These samples were digested using two of the most commonly employed procedures in exploration and environmental geochemistry: a modified aqua regia digestion and a 4-acid digestion. All solutions were analyzed using ICP-ES/MS, and certified reference materials (CRMs) and duplicate samples were used to monitor analytical accuracy and precision. The concentration of elements (e.g. Cr) hosted in relatively insoluble mineral phases are consistently higher following 4-acid digestions as compared to digestions using aqua regia, but generally lower than total values measured using direct methods of analysis (e.g. Instrumental Neutron Activation Analysis). In contrast, the concentrations of As are often higher in samples following aqua regia versus 4-acid digestions and generally in good agreement with total values in CRMs. The behaviour of other elements (e.g. Sb, copper (Cu), lead (Pb), S, zinc (Zn)) was more variable and for many samples, the results following 4-acid and aqua regia digestions were statistically indistinguishable. Variations in the mineralogy of different samples play a key role in determining the fraction of different metal(loid)s released by these digestion techniques. This poster highlights some of the advantages and disadvantages of using each of these digestion protocols for risk assessment and environmental monitoring purposes, and provides recommendations for using geochemical data to help guide environmental decision-making at both active and abandoned metal mines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.008 | 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 teacher head, 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".