Source and Fate of Contaminants in a Pit Lake and Water Treatment at the Faro Mine Complex
Notice bibliographique
Résumé
The Faro Mine Complex (FMC) is an abandoned zinc-lead mine in Yukon, Canada that requires extensive remediation efforts to manage the environmental liabilities associated with mine wastes stockpiled at the site. Active care and maintenance are necessary to manage surface water and groundwater impacted by acid rock drainage (ARD) and metal leaching (ML). The Faro Pit lake (FPL) is the largest reservoir of water at the FMC, multiple mine impacted water sources are pumped to the pit lake for storage and mixing. The FPL is also the main influent source to the FMC treatment plant. Active pumping from other mine components and continuous degradation of ARD seepage quality flowing into the pit lake alter the concentration and distribution of contaminants at the FMC. Changes to the load balance of the site may therefore affect contaminant removal processes at the FMC treatment plant. This research project aims to combine a mass balance of contaminant loading in water at the FMC with the characterization of metal removal during the treatment of mine waters. The results would characterize the source, distribution, and fate of contaminants within the FPL. \n \n \nA sampling apparatus was installed into the FPL on two occasions, in September 2019 and September 2021. Profile samples and in situ measurements were obtained to a depth of 47 m in 2019 and 25 m in 2021. In both years, the pit lake was thermally stratified with a well-defined thermocline between 8 m and 10 m depth. The stratification is caused by the difference in specific density of water at 10 ⁰C and 4 ⁰C, in the epilimnion and hypolimnion respectively. Multiple parameters changed sharply at the well-defined thermocline because mixing between the epilimnion and hypolimnion is limited. In 2019, most concentrations of dissolved species were higher in the hypolimnion than in the epilimnion, whereas the concentrations were generally higher in the epilimnion in 2021. The pH was higher in the epilimnion in 2019, and in 2021 it was lower in the epilimnion at pH 3.8. Increasing contaminant loads from the tailings area Intermediate Pond and seepage from the mine waste surrounding the Faro Pit drive geochemical changes in the pit-lake water quality. \n \n \nBatch experiments were conducted to understand the processes resulting in removal of dissolved metals during treatment of mine-impacted waters. FPL water samples were placed in a stirred cell reactor (SCR) and dosed with calcium hydroxide to a pH of 10. Samples were collected for characterization of kinetic and thermodynamic controls during water treatment. Contaminant removal during lime treatment is controlled by processes that occur consistently over narrow pH ranges. Results of the batch experiments show that most Fe removal occurred at pH 6.5, Zn was removed at pH 9, Mn removal at pH 9.7, and Ni and Cd removal occurred above pH 10. Characterization of the precipitated solids showed that Fe and some Zn coprecipitated in the initial stage of the experiments. Later in the experiment, Zn precipitated separately, likely as amorphous Zn hydroxides, mixed with Mn (hydr)oxides. The solution remained undersaturated in respect to gypsum and minimal removal of SO4 from solution was observed. \n \n \nThe results from all components of this study suggest that changing geochemical conditions and additional load sources have the potential to change the contaminant distribution and effectiveness of treatment process. This study increased the understanding of the necessary actions to efficiently remove contaminants from a mine with deteriorating water quality and changing operating conditions.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».