The characterization of arsenic mineral phases from legacy mine waste and soil near Cobalt, Ontario
Notice bibliographique
Résumé
The Cobalt-Coleman silver (Ag) mining camp has a long history of mining dating back to 1903. Silver mineralization is hosted within carbonate veins and occurs in association with Fe-Co-Ni arsenide and sulpharsenide mineral species. The complex mineralogy presented challenges to early mineral processing methods with varying success of Ag recovery and a significant amount of arsenic (As) in waste material which was disposed in the numerous tailings deposits scattered throughout the mining camp, and in many instances disposed of uncontained. The oxidation and dissolution of As-bearing mineral phases in these tailings and legacy waste sites releases As into the local aquatic environment. Determining the distribution of primary and secondary As mineral species in different legacy mine waste materials provides an understanding of the stability of As. Few studies have included detailed advanced mineralogical characterization of As mineral species from legacy mine waste in the Cobalt area. \nAs part of this study, a total of 28 samples were collected from tailings, processed material near mill sites and soils from the legacy Nipissing and Cart Lake mining sites. The samples were analyzed for bulk chemistry to delineate material with strongly elevated As returned from all sample sites. This sampling returned highly elevated As with up to 6.01% As from samples near mill sites, 1.71% As from tailings and 0.10% As from soils. From the samples with elevated As, eight samples representative of the different sampling sites and material were selected for detailed mineralogical characterization using scanning electron microscopy (SEM) in conjunction with automated mineralogy using mineral liberation analysis (MLA). Common primary As-bearing minerals identified include sulpharsenides and arsenides such as cobaltite, arsenopyrite, gersdorffite, safflorite and skutterudite; with common secondary As-bearing minerals forming post-processing including erythrite-annabergite, Fe-Ca arsenates and Fe-oxides with As. This characterization study highlighted the localized variability of mineralogical speciation and variations in the abundance of these species from the different sampling sites. The majority of the samples were dominated by secondary As minerals forming from the dissolution and oxidation of primary As-bearing mineral species and occurring as rims on grain particles, grain cementation and replacement of primary minerals. A single sample from fine-grained water saturated tailings is distinctly dominated by primary As-bearing minerals which highlights the localized redox conditions controlling oxidation. The results of this work, as well as previous characterization studies improves the understanding of the mineralogical characteristics and distribution of As-bearing legacy mine waste material with As which is critical to understand the stability of As and improve remediation planning and design.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,002 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».