Exploration
Marco Antonio Cotrina-Teatino; Jairo Jhonatan Marquina-Araujo; Jose Nestor Mamani-Quispe; Jorge Chira-Fernandez; Cesar De la cruz-Poma; Solio Marino Arango-Retamozo
Abstract
The sustained increase in mining waste, particularly in the form of tailings, poses a significant environmental and economic challenge, especially in contexts where these deposits retain residual metal content. This study assessed the gold potential of Tailings Deposit I at La Cienega (Peru) by integrating ...
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The sustained increase in mining waste, particularly in the form of tailings, poses a significant environmental and economic challenge, especially in contexts where these deposits retain residual metal content. This study assessed the gold potential of Tailings Deposit I at La Cienega (Peru) by integrating geostatistical estimation and machine learning models optimized through metaheuristic algorithms. The methodology involved geochemical characterization, three-dimensional estimation using Ordinary Kriging (OK) as a geostatistical method, and prediction of gold grades through three models: XGBoost optimized with Particle Swarm Optimization (XGB+PSO), Support Vector Regression with Genetic Algorithm (SVR+GA), and Random Forest optimized using Ant Colony Optimization (RF+ACO). Estimates were validated using Leave-One-Out cross-validation and performance metrics including RMSE, MAE, Bias, and correlation coefficient (R). The RF+ACO model achieved an RMSE of 0.32 ppm, MAE of 0.24 ppm, Bias of 0.006, and an R value of 0.56. Average predicted grades ranged from 1.14 to 1.33 ppm, with estimated gold contents between 981.00 and 1,147.12 ounces, while OK yielded 1,028.77 ounces at an average grade of 1.19 ppm. These findings suggest that properly optimized machine learning models can provide reasonable estimates of metal content in tailings, particularly in settings characterized by high spatial heterogeneity and limited geological continuity.
Environment
Ali Najmeddin; Taha Salahjou; Kimia Zendehdel
Abstract
Porphyry copper mining generates substantial volumes of tailings, which pose considerable environmental and public health hazards due to their capacity for acid generation and the release of potentially toxic elements (PTEs). This study provides an integrated environmental and human health risk assessment ...
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Porphyry copper mining generates substantial volumes of tailings, which pose considerable environmental and public health hazards due to their capacity for acid generation and the release of potentially toxic elements (PTEs). This study provides an integrated environmental and human health risk assessment of tailings from the Sungun porphyry copper mine in northwestern Iran. A comprehensive and multidisciplinary approach was employed, combining physicochemical, mineralogical and geochemical analyses with statistical methods. Chemical speciation was done by employing a modified procedure suggested by the BCR (European Community Bureau of Reference) which has also been used in numerous studies to assess the geochemical fractionation and mobility of elements. The main goal was to advance from total concentration analysis to a more precise, bioavailability-based risk evaluation utilizing the USEPA framework for both children and adults. Mineralogical investigation indicated a net acid-generating capability, with pyrite content (~4%) typically surpassing that of the principal neutralizing mineral, calcite (~2%). Geochemical analyses verified that the tailings exhibit significant enrichment in Cu and Mo, along with moderate enrichment of As and Co. Among the studied elements, the highest mobility factors belonged to Cu (81.49%), Pb (76.71%), Zn (71.65%) and Mo (59.27%), respectively. The non-carcinogenic hazard index (HI) for children was 2.04, exceeding the safety threshold of 1.0, with bioavailable vanadium recognized as the principal risk factor. These findings highlight that relying solely on total PTE concentrations can be misleading, reinforcing the need for speciation-based assessments to accurately characterize the environmental behavior and health risks of mine tailings.
S. Tabasi; H. Hassani; A.R. Azadmehr
Abstract
The present work was planned to evaluate the phytoextraction of metal mine tailings, Sarcheshmeh copper mine, SE of Iran, by the endemic plant species Medicago sativa L. (Alfalfa). In this pot experiment, we investigated the effects of seven amendments on the growth of alfalfa and uptaking metals from ...
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The present work was planned to evaluate the phytoextraction of metal mine tailings, Sarcheshmeh copper mine, SE of Iran, by the endemic plant species Medicago sativa L. (Alfalfa). In this pot experiment, we investigated the effects of seven amendments on the growth of alfalfa and uptaking metals from the mine tailings and stream sediment of tailing dam surface. The mean metal concentrations in both the tailing and stream sediment increased in the order of Hg < Te < Ag < Re < Ge < In < Ga
N Mathiyazhagan; Natarajan D
Abstract
An ex-situ experiment to assess the metal extractive potential of fourteen agriculture plants (Vigna unguiculata, Gossypium hirsutum, Jatropha curcas, etc.) was conducted on Magnesite mines which had above permissible levels of Cadmium and Lead. There was no much difference in the total chlorophyll a ...
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An ex-situ experiment to assess the metal extractive potential of fourteen agriculture plants (Vigna unguiculata, Gossypium hirsutum, Jatropha curcas, etc.) was conducted on Magnesite mines which had above permissible levels of Cadmium and Lead. There was no much difference in the total chlorophyll a and b, carbohydrate and protein contents in the plants grown in the mining soil and adjacent control area (farm soil). While considering the phytoextractive potential, among the 14 plants studied, V. ungiculata, O. sativa, S. bicolour, S. indium, R. communis, M. uniflorum, G. hirsutum and J. curcas contained considerable amount of heavy metals Cd and Pb other test plants. The experiment confirms that these plants have potential to accumulate the toxic trace elements from soil especially mining waste or dump. The subsequent confirmation studies on their metal tolerant index, metal transfer factor, translocation factor and MREI index values auger their potential phyto-extractive properties. The present study will pave way for in depth related studies in future.
