Processes at the mineral-water interface in the acid soils of the Sudbury area
Bibliographic record
Abstract
Over a century of mining activities and smelting in the area of Sudbury, Ontario, Canada have resulted in the contamination of the local soils with metal(loid) bearing particulates. Minor and trace elements associated with these phases are released during their weathering. This release is therefore strongly dependent on the mineralogical and chemical character of the metal(loid) bearing phases. The metal(loid)s are then subject to transport before being attenuated through their incorporation into secondary phases. Elevated concentrations of metal(loid)s in silica rich alteration layers has recently been described for altered surfaces at the solid-water and solid-atmospheric interfaces in tailings, and in the vicinity of smelters, respectively. To determine if similar coatings occur in soils, samples were taken from areas around three major smelting centers in the area. Coated grains were extracted from these samples and individually mounted to be analysed. Particulate matter (representing primary metal(loid)-bearing phases) and coatings (secondary metal(loid)-bearing phases) were analysed using scanning electron microscopy, Raman spectroscopy, Laser-Ablation Inductively-coupled plasma mass spectroscopy, Micro-X-ray fluorescence, and X-ray photoelectron spectroscopy. The particulates were divided into three main groups: smelter-derived particles, sulfides, and nickel-oxides. Smelter derived particles contained the most elevated concentrations of metal(loid)s in their sulfide inclusions and metal(loid)-rich rims. The mobility of metal(loid)s in the identified mineral phases found within particulates mirrored the transport observed in the soil column; Zn>Cu>Ni>Pb. Once mobilized, these elements are subject to transport before being attenuated by secondary phases. Micro-coatings were found to be composed of hematite, schwertmannite, ferrihydrite, silica, and jarosite group minerals. Coatings are distinguished on the basis of their atomic Si:Fe ratios: FeOx coatings have Si:Fe <1, Si–FeOx coatings have Si:Fe between 1-10, and SiOx coatings iv have Si:Fe>10. Iron-rich coatings (FeOx) and silica-rich coatings (SiOx) have lower trace-metal concentrations than Fe-SiOx coatings. Micrometer-thick coatings are predominantly composed of hematite, schwertmannite, ferrihydrite and (amorphous) silica and contain elevated metal(loid) concentrations in the form of metal(loid)-rich phosphate minerals (mainly minerals of the jarosite group). A general model is developed that describes the formation of mineral coatings in acid soils and their important role in the uptake and retention of metal(loids). Here, micrometer-thick Fe-silica coatings form through adsorption, co-precipitation and dehydration processes involving amorphous silica and iron hydroxides. Metal(loid)-bearing phases nucleate within a gel-type matrix and are subsequently preserved during dehydration and solidification. Aluminum-rich surfaces form on mineral grains once the pH has been raised sufficiently high (pH~5-6) so as to lead to the complete removal of sulfate-bearing phases. The implications of this model are widespread in terms of the attenuation of metal(loid)s in acid soils and their retention or subsequent remobilization in recovered soils with near neutral pH.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".