Hydrogeochemistry and Trace Element Mobility in an Acidic High-Sulfide Tailings Impoundment After 40 Years of Oxidation
Notice bibliographique
Résumé
Abandoned mine sites can create a legacy environmental contamination issue when the generation of acid mine drainage is allowed to continue with insufficient or absent remediation measures. The South Bay mine, a former underground Cu-Zn mine located in northwestern Ontario, is once such site with historical contamination. The mine wastes at South Bay contain high concentrations of sulfide minerals which continue to oxidize decades following mine closure, leading to acidic seepage with high concentrations of dissolved metals impacting the surrounding lakes. This aim of this study is to provide a characterization of the current hydrogeology, geochemistry, mineralogy, and microbiology of the South Bay tailings so that this information can inform future remediation work. \nInstrument installation and collection of core samples of the tailings was performed at five locations within the tailings impoundment area. Pore-water samples were collected from piezometer and soil water sampler nests. Sub-samples of tailings cores were collected and analysed using optical microscopy, scanning electron microscopy, selective extractions, total carbon/sulfur, X-ray diffraction, X-ray fluorescence, synchrotron, and DNA sequencing techniques. Mineralogical analysis indicated that pyrite was the main sulfide mineral in the tailings, with lesser amounts of sphalerite and chalcopyrite and trace amounts of pyrrhotite, galena, and arsenopyrite. The oxidation zone in which sulfide minerals are depleted is restricted to the upper 0-15 cm of tailings. The moisture content within the tailings is relatively high, contributing to a low O2 diffusion rate into the tailings. High proportions of acidophilic microorganisms capable of catalyzing Fe and S oxidation reactions were found in the shallow tailings. Sulfide oxidation modelling has indicated that oxidation of sulfide minerals in the South Bay tailings may continue for decades to millennia before all sulfide minerals are depleted in the vadose zone. \nProlonged sulfide mineral oxidation has led to acidic pore waters with pH as low as 1.26 with high concentrations of dissolved metals, including Fe, Zn, Cu, As, Pb, and Co. The lowest pH and highest concentrations of dissolved metals tends to occur in the shallow tailings near the region of active sulfide-mineral oxidation. High concentrations of dissolved rare earth elements (REEs), up to 9.45 mg/L total REEs, were also found within the shallow acidic pore-waters. Dissolution of gangue minerals and secondary minerals contributes to acid neutralization, with pH increasing to circumneutral values below the water table. Metals and metalloids may be attenuated through adsorption or co-precipitation with secondary mineral phases. Copper was found to be attenuated through covellite precipitation, Pb was attenuated through anglesite precipitation, and As was attenuated by adsorption or co-precipitation with Fe(III) (oxy)hydroxides. Metal(loid)s sequestered within Fe(III) (oxy)hydroxides may be susceptible to remobilization through reductive dissolution should environmental conditions imposed by future remediation efforts induce strong reductive conditions.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| 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 source (Gemma direct ou Codex distillé), 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 ».