Assessment of Gold and Mercury Losses in an Artisanal Gold Mining Site in Nigeria and Its Implication on the Local Economy and the Environment
Notice bibliographique
Résumé
The objective of this work was to establish the gold and mercury losses in an artisanal mining deposit (Uke) in Nigeria to convince miners about their inefficiency and suggest changes in their gold extraction practices. Samples of feeds and tailings from five sluice box concentration processes previously ground in hammer mills below 1 mm (P80 = 0.5 mm) were systematically sampled every 15 min. for 4 h and sent for gold analyses by a fire assay and intensive cyanidation. Dry grain size analyses of primary and amalgamation tailings allowed us to find out in which size fraction gold and mercury are lost. Total mercury losses in sixteen operations were obtained by weighing mercury at the beginning and in all steps of the concentrates’ amalgamation. After analyses, the average gold grade in the feed resulted in 3.80 ± 1.52 ppm (two standard deviations). The gold recovery was 29.24 ± 13.24%, which is low due to a lack of liberation of the fine gold particles from the gangue (silicates). Finer grinding would be necessary. The mercury balance revealed that 42% of the mercury added is lost, in which 26% involves tailings and 16% evaporated. The HgLost-to-AuProduced ratio was found to be 3.35 ± 9.46, which is exceedingly high for this type of amalgamation process that should have this ratio around 1. One reason is the excessive amount of mercury in the amalgams, 76.5 ± 38.12%, when the normal is around 40%–50%. Mercury lost by evaporation in open bonfires is clearly contaminating amalgamation operators (usually children), neighbours, and the environment. The Hg-contaminated tailings and primary tailings are sold to local cyanidation plants, and this can form toxic soluble Hg(CN)2 in the process. The results of this research were brought to the attention of the miners and other stakeholders, including the regulatory agencies of the government. The % gold recovery by amalgamation was not established in this study, but if this process recovers 50 to 60% of the liberated gold particles in a concentrate and 30% of gold was recovered in the sluice boxes, then the total gold recovery should be between 15 and 20; i.e., 80 to 85% of gold mined is lost. On average, an operation produces 8.26 g of gold/month, which is split to six miners, representing USD 69/month/miner or USD 2.3/day. It was discussed with miners, authorities, and community members (in particular female miners) how to avoid exposure to mercury, how to improve gold recovery without mercury, and the health and environmental effects of this pollutant.
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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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 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) | 0,000 | 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 ».