Biological copper extraction from melting furnaces dust of Sarcheshmeh copper mine

This paper deals with bacterial leaching of copper dust emanating from furnaces at Sarcheshmeh copper complex. Regarding the considerable amount of acid leachable copper, a sulphuric acid leaching process was performed prior to bacterial leaching. Some shake flask and then bioreactor tests were conducted using a mixed culture of Acidithiobacilli and the effect of significant parameters such as culture medium, pulp density and bacterial inoculation rate were investigated. By increasing the pulp density because of higher toxicity and shear stress much more microorganisms and richer nutrient medium were needed. Favoured conditions that governed the agitated bioreactors caused a remarkable promotion in metal dissolution rate in comparison with shake flask. Copper recovery by bacterial leaching in shaking flasks and chemical leaching after 22 d were 87% and 38%, respectively. At the same condition, the maximum copper recovery in bioreactor was 91% within 6.5 d.     

Spatial modelling of hazardous elements at waste dumps using geostatistical approach: a case study Sarcheshmeh copper mine,Iran

Mining activities and resulting wastes can be considered as one of the most important sources of hazardous elements in the environment. Knowledge of the spatial distribution of toxic elements in waste dump systems is necessary to assess environmental hazard and strategy. To achieve this goal, this paper investigates spatial distribution of toxic elements using statistical and geostatistical analysis. A total of 58 soil samples were collected, and the amount of As, Cd, Co, Cr, Cu, Mn, Mo, Ni, Pb and Zn was then determined at “Sarcheshmeh” copper mine waste dumps. In order to evaluate the presence of multivariate outliers, Mahalanobis distance technique (D ²) was applied and the multivariate outlier samples were removed. This resulted in an increase in correlation coefficient. To reduce dimension of data set, principal component analysis was applied and four principal components were determined which indicate 83.463% of the total variance of data set. Estimated PCs together with the toxic elements maps based on the ordinary kriging display aggregation of toxic elements in some parts, and validity of predictions was evaluated using the leave-one-out cross-validation method. The regression coefficients of estimated and observed values presented the reliability of the kriging estimates. Sequential Gaussian simulation method was applied for principal components due to similar results of estimated principal components and toxic elements. The results of simulation maps are almost identical to estimated outcomes.     

Prediction of heavy metals in acid mine drainage using artificial neural network from the Shur River of the Sarcheshmeh porphyry copper mine,Southeast Iran

Water is one of the basic and fundamental requirements for the survival of human beings. Mining of the sulphide mines usually produce a significant amount of acid mine drainage (AMD) contributing to huge amounts of chemical components and heavy metals in the receiving waters. Prediction of the heavy metals in the AMD is important in developing any appropriate remediation strategy. This paper attempts to predict heavy metals (Cu, Fe, Mn, Zn) from the AMD using backpropagation neural network (BPNN), general regression neural network (GRNN) and multiple linear regression (MLR), by taking pH, sulphate (SO₄) and magnesium (Mg) concentrations in the AMD into account in Shur River, Sarcheshmeh porphyry copper deposit, southeast Iran. The comparison between the predicted concentrations and the measured data resulted in the correlation coefficients, R, 0.92, 0.22, 0.92 and 0.92 for Cu, Fe, Mn and Zn ions using BPNN method. Moreover, the R values were 0.89, 0.37, 0.9 and 0.91 for Cu, Fe, Mn, and Zn taking the GRNN method into consideration. However, the correlation coefficients were low for the results predicted by MLR method (0.83, 0.14, 0.9 and 0.85 for Cu, Fe, Mn and Zn ions, respectively). The results further indicate that the ANN can be used as a viable method to rapidly and cost-effectively predict heavy metals in the AMD. The results obtained from this paper can be considered as an easy and cost-effective method to monitor groundwater and surface water affected by AMD.     

Spectroscopic-based assessment of the content and geochemical behaviour of arsenic in a highly heterogeneous sulphide-rich mine waste dump

Soil pollution by arsenic is a serious environmental problem in many mining areas. Quick identification of the amount and extent of the pollution is an important basis for developing appropriate remediation strategies. In a case study, 55 soil samples were collected from a highly heterogeneous waste dump around the Sarcheshmeh copper mine, south east Iran. Samples’ visible and near-infrared (VNIR) reflectance spectra were measured, transformed to absorbance and then pre-processed using Savitzky–Golay first-derivative (FD) and Savitzky–Golay second-derivative (SD) transformation methods. The obtained spectra were then subjected to three regression models including principal component regression (PCR), partial least squares regression (PLSR) and support vector regression (SVR) for predicting arsenic concentration. The best prediction accuracies were obtained by SVR and PLSR methods applied on first-derivative pre-processed spectra with R ² values of 0.81 and 0.69, respectively. It was found that VNIR spectroscopy is a successful method for predicting As concentration in contaminated soils of the dumpsites. Study of the prediction mechanism showed that the intercorrelation between arsenic and spectral features of soil including iron oxy/hydroxides and clay minerals was the major mechanism enabling the prediction of arsenic concentration. However, higher values of correlation coefficients at ~460, ~560 and ~590 nm suggested the internal association between arsenic and iron minerals as the more important mechanism for prediction. This conclusion supported previous speciation studies conducted in the same waste dump using improved correlation analysis and chemical sequential extraction method.     

Failure of a mine waste dump in Zimbabwe: Causes and consequences

A combination of factors are considered important in causing the failure and subsequent development of a flowslide of a gold mine waste dump (or tailings dam) at Arcturus, near Harare, Zimbabwe. These factors comprise poor basal drainage, steep perimeter walls, saturation of the walls and basal sediments through continued spigoting of slurry during a period of heavy rainfall, and the effect of this saturation on the tailings. Properties of the tailings, eyewitness accounts, documentary evidence, and site characteristics are discussed. The failure and subsequent development of a fatal 300-m flowslide are reconstructed in a five-phase developmental model. The general applicability of the results is discussed.     

Characterisation of the Sarcheshmeh copper mine tailings,Kerman province,southeast of Iran

Mineral processing operation at the Sarcheshmeh porphyry copper mine has produced huge quantities of tailings materials containing sulphide minerals in particular pyrite. These tailings materials were geochemically and mineralogically characterised to assess pyrite and chalcopyrite oxidation, acid mine drainage generation, and trace element mobility to lead development of a proper remediation plan. Five vertical trenches up to 4.2 m deep were excavated from the tailings surface, and 70 solid samples were taken in 0.3 m intervals. The samples were first mineralogically analysed. Pyrite was the main sulphide mineral found in the tailings. The gangue minerals include quartz ± muscovite–illite ± chlorite ± albite ± orthoclase ± halite. The samples were geochemically analysed for total concentrations of 62 elements, paste pH, SO₄ ^2?, CO₃ ^2?, and HCO₃ ^?. The maximum concentrations of SO₄ ^2? (1,300, 1,170, 1,852, 1,960 and 837 mg/L) were observed at a depth of 0.9 m in profiles A, B, C, D and E, respectively. The tailings have a high acid-producing potential and low acid-neutralising potential (pyrite 4–6 wt %, calcite 1 wt %). Fe₂(SO₄)₃, CuSO₄, MgSO₄ and MnSO₄ were the dominant secondary sulphate minerals in the tailings. The lowest pH values (2.9, 3 and 3) were measured at a depth of 0.3 m in the profiles A, B and C, 3.9 at a depth of 0.6 m in the profile D and 3 at a depth of 0.9 m in the profile E. The upper portions of the profiles C (1.8 m) and D (2.1 m) were moderately oxidised, while oxidation in the profiles A, B and E did not extend more than 1.2, 1.2 and 1.5 m beneath the tailings surface. Zn, Pb, Rb, U, Hf, Nd, Zr and Ga show almost a constant trend with depth. Cd, Sr, Th, La and Ce increased with increasing depth of the tailings materials while, Co, V, Ti, Cr, Cu, As, Mn, Ag, Mo and Ni exhibit initially a decreasing trend from tailings surface to the depths that vary between 0.9 and 1.2. They then remained constant with the depth. The results show pyrite and chalcopyrite oxidation at surface layers of the tailings and subsequent leaching of the oxidation products and trace elements by infiltrated atmospheric precipitation.     

Geochemical evolution and quality assessment of water resources in the Sarcheshmeh copper mine area (Iran) using multivariate statistical techniques

Hydrochemical data were gathered throughout the last 12 years from 57 sampling stations in the drainage basin of the Sarcheshmeh copper mine, Kerman Province, Iran. The mean values of these data for each sampling station were used to evaluate water quality and to determine processes that control water chemistry. Principal component analyses specified the oxidation of sulfide minerals, dissolution of carbonate and sulfate minerals and weathering of silicate minerals as the principal processes responsible for the chemical composition of water in the study area. Q-mode cluster analysis revealed three main water groups. The first group had a Ca-HCO₃–SO₄ composition whereas the second and third groups had Ca–SO₄ and Ca–Mg–SO₄ composition, respectively. The results of this study clearly indicated the role of sulfide minerals oxidation and the buffering processes in the geochemical evolution of water in the Sarcheshmeh area. Due to these processes, extensive changes occurred in the chemical composition of water by passage through the mining area or waste and low-grade dumps, so that the fresh water of the peripheral area of the pit evolved to an acid water rich in sulfate and heavy metals at the outlet of the pit and in the seepages of waste and low-grade dumps.     

黄土区露天煤矿排土场人工林下植被发育动态

基于安太堡露天煤矿南排土场1 hm²“刺槐(Robinia pseudoacacia)+榆树(Ulmus pumila)+臭椿(Ailanthus altissima)”配置模式动态监测样地复垦17年和22年的调查数据,采用多项指标对人工林下草本层植物物种多样性进行测度,同时利用方差比率法(VR )、χ²检验和Spearman秩相关系数检验对群落草本层物种总体关联性和主要物种的种间联结性进行了分析。结果表明:(1)复垦17年后,人工林下草本层共调查到20科46属62种植物,以菊科植物优势地位明显;复垦22年后,共记录到 18科39属53种草本层植物,禾本科植物的重要值逐渐增加。5年间,优势成分由大籽蒿(Artemisia sieversiana)变为鹅观草(Roegneria kamoji)。与原地貌自然植被相似,人工林下多年生和中生植物在两次调查中均占优势。随着复垦年限的增加,人工林下1年生、1-2年生及中生植物重要值下降,多年生和旱生、中旱生、旱中生植物的重要值有所增加。(2)复垦17年后,人工林下草本层植物物种丰富度已超过原地貌自然植被。随着演替的进展,Patrick丰富度指数有所降低,Shannon-Wiener多样性指数和Pielou均匀度指数均呈现增加趋势。复垦22年后,人工林下草本层植物物种多样性已修复至原地貌自然植被的94.12%。(3)人工林下草本层植物总体关联性由显著负关联变为不显著负关联。主要物种正负关联比由0.30上升至0.79,但均小于1,并且呈极显著和显著关联的种对数较少,说明人工林下草本层植物群落种间联结较为松散,各物种间的关系以竞争为主。主要种针茅(Stipa capillata)与榆树(U.pumila)幼苗呈显著正相关,它们均为地带性物种,生态适应性强,可用于该矿区植被恢复的优选物种进行混合种植。该研究可为矿区植被重组和生物多样性保护提供理论依据。     

Prediction of blasting-induced fragmentation in Meydook copper mine using empirical,statistical, and mutual information models

One of the most important aims of blasting in open pit mines is to reach desirable size of fragmentation. Prediction of fragmentation has great importance in an attempt to prevent economic drawbacks. In this study, blasting data from Meydook mine were used to study the effect of different parameters on fragmentation; 30 blast cycles performed in Meydook mine were selected to predict fragmentation where six more blast cycles are used to validate the results of developed models. In this research, mutual information (MI) method was employed to predict fragmentation. Ten parameters were considered as primary ones in the model. For the sake of comparison, Kuz-Ram empirical model and statistical modeling were also used. Coefficient of determination (R ²), root mean square error (RMSE), and mean absolute error (MAE) were then used to compare the models. Results show that MI model with values of R ², RMSE, and MAE equals 0.81, 10.71, and 9.02, respectively, is found to have more accuracy with better performance comparing to Kuz-Ram and statistical models.     

Evaluation of proposed waste rock dump designs using the SIBERIA erosion model

Computer-based landscape evolution models offer the ability to evaluate landscape stability over the short (annual), medium (decades to hundreds of years) and long-term (thousands of years). Modeling has advantages in that design ideas can be tested, different surface material properties can be evaluated and risk analysis carried out. Landscape evolution models allow landscape surface change through time. These models also offer the advantage that the landscape can be evaluated visually as it develops through time, which is not possible with other types of models. Landscape evolution models can be used for not only soil loss assessment (i.e. tonnes/hectare/year), but also to evaluate the method of soil loss (i.e. rill or interrill erosion). This study examines a range of waste rock dump designs for the Minera Alumbrera Ltd. copper mine, Argentina. An erosion assessment using the SIBERIA erosion model over a 1000-year simulation period demonstrates waste rock dump designs using a conventional stepped design of backsloping benches and caps with angle of repose slopes provide the lowest average erosion rates and depths of incision than do other designs. Caution should be applied in interpreting these results as the SIBERIA erosion model is sensitive to parameter input and in this case was calibrated and run using a generic set of parameters that are not site specific. Nevertheless, the results provide a guide as to the strengths and weaknesses of different rehabilitation designs and demonstrate the insights that modeling studies can provide.     

Environmental geochemistry of toxic heavy metals in soils around Sarcheshmeh porphyry copper mine smelter plant,Rafsanjan, Kerman,Iran

The Sarcheshmeh copper mine smelter plant is one of the biggest copper producers in Iran. Long-time operation of about 25 years of the smelter plant causes release of potentially toxic heavy metals into the environment. In this paper, geochemical distribution of toxic heavy metals in 28 soil samples was evaluated around the Sarcheshmeh smelter plant. Soils developed over the nonmineralized and uncontaminated areas have an average background concentration of 41.25 mg kg⁻¹ Cu, 26.6 mg kg⁻¹ As, 12.7 mg kg⁻¹ Pb, 0.9 mg kg⁻¹ Sb, 1.9 mg kg⁻¹ Mo, 1.7 mg kg⁻¹ Sn, 0.2 mg kg⁻¹ Cd, 0.15 mg kg⁻¹ Bi, 235 mg kg⁻¹ S and 73.4 mg kg⁻¹ Zn, respectively. As a result of smelting process, the upper soil layers (0–5 cm) were polluted by Cu (>1,397 mg kg⁻¹), Cd (>3.42 mg kg⁻¹), S (>821 mg kg⁻¹), Mo (>10.3 mg kg⁻¹), Sb (>11.7 mg kg⁻¹), As (>120.6 mg kg⁻¹), Pb (>83.8 mg kg⁻¹), Zn (>214.9 mg kg⁻¹), and Sn (>3.7 mg kg⁻¹), respectively. These values are much higher than the normal concentration of the elements in the uncontaminated soil layers. The elemental values decrease with distance travelled away of the smelter plant, especially at minimum wind direction. Furthermore, high contaminated values of Cu (8,430 mg kg⁻¹), As (500 mg kg⁻¹), Pb (331 mg kg⁻¹), Mo (61 mg kg⁻¹), Sb (56.2 mg kg⁻¹), Zn (664 mg kg⁻¹), Cd (17.2 mg kg⁻¹), Bi (13.4 mg kg⁻¹), and S (3,780 mg kg⁻¹) were observed in the upper soil layers close to the smelting waste dumps. Sequential extraction analysis shows that about 270 mg kg⁻¹ Cu, 28 mg kg⁻¹ Pb, 50.33 mg kg⁻¹ Zn, and 47.84 mg kg⁻¹ As were adsorbed by Fe and Mn oxides. The carbonate phases include 151 mg kg⁻¹ Cu, 28 mg kg⁻¹ Pb, 25 mg kg⁻¹ Zn, and 32.99 mg kg⁻¹ As. Organic matter adsorbed 314.6 mg kg⁻¹ Cu and 29.18 mg kg⁻¹ Zn.     

基于AHP-TOPSIS方法的薛家湾—龙口镇露天煤矿大型排土场生态修复效果评价

排土场修复是矿山生态修复取得突破性进展和显著成效的关键之一。为进一步优选排土场生态修复技术组合,支撑矿山生态修复和绿色矿山建设,以薛家湾—龙口镇露天煤矿5个不同修复技术组合排土场板块为研究对象,选取生态效益和经济效益2类9个评价指标,运用层次分析(analytic hierarchy process,AHP)法和优劣解距离(technique for order preference by similarity to an ideal solution,TOPSIS)法构建排土场生态修复效果综合评价模型,确定最终权重并进行综合评价。研究区排土场修复最优解决方案为: 工程措施采用平整覆土+挡水围堰+坡面整形+条播技术; 植被措施采用柳树+沙打旺+草木犀+苜蓿+冰草+老芒麦。研究表明,在矿山生态修复效果的成效评价中,使用定性加定量的评价方法,能更好地反映出生态修复效果,可为科学评价生态修复效果提供支撑。     

Hydrochemistry, mineralogy and chemical fractionation of mine and processing wastes associated with porphyry copper mines: A case study from the Sarcheshmeh mine, SE Iran

The Sarcheshmeh is one of the largest Oligo-Miocene porphyry Cu deposits in the world. Comparative hydrochemical, mineralogical and chemical fractionation associated with mining efflorescence salts and processing wastes of this mine are discussed. Hydrochemical results showed that rock waste dumps, reject wastes and old impoundments of tailings are the main sources of acid mine drainage waters (AMD) that contain potentially toxic metals such as Cd, Co, Cu, Mn, Ni and Zn as well as Al. Episodic fluxes of highly contaminated acidic waters were produced in a tailings dam over a short period of time. Secondary soluble minerals provide important controls on the quality of AMD produced, especially in old, dry tailings impoundments. Secondary sulfate minerals such as gypsum, magnesiocopiapite, hydronium jarosite, kornelite and coquimbite were found in rock waste drainages and in old weathered reject wastes. Highly soluble secondary minerals such as gypsum, eriochalcite, and bonattite are also observed in an evaporative layer on old tailings impoundments. Chemical fractionation patterns of potentially toxic elements showed that the geochemical behavior of metals is primarily controlled by the mineralogical composition of waste samples. Elements such as Co, Cr, Cu, Mn, Ni and Zn are readily released into the water soluble fraction from efflorescence salts associated with rock waste drainages, as well as from the evaporative layer of old tailings. Potentially toxic elements, such as As, Mo and Pb, are principally adsorbed or co-precipitated with amorphous and crystalline Fe oxides, but they may also be associated with oxidizing, primary sulfides and residual fractions. Following the development of the dammed tailings pond, the secondary minerals were dissolved, producing acidic waters contaminated by Al (154 mg L⁻¹), Cu (150 mg L⁻¹), Cd (0.31 m gL⁻¹), Co (2.13 mg L⁻¹), Mn (73.7 mg L⁻¹), Ni (1.74 mg L⁻¹), Zn (20.3 mg L⁻¹) and Cl (1690 mg L⁻¹). Therefore, the potential use of recycled water from the Sarcheshmenh dammed tailings pond is diminished by the presence of corrosive ions like Cl⁻ in highly acidic fluids that promote corrosion of pipes and pumps in the water recycling system.     

Dating of mine waste in lacustrine sediments using cesium-137

For over a century Medicine Lake in northern Idaho has received heavy-metal-laden tailings from the Coeur d'Alene mining district. Establishing the depositional chronology of the lake bottom sediments provides information on the source and rate of deposition of the tailings. Cesium-137, an isotope produced in the atmosphere by nuclear bomb tests, was virtually absent in the environment prior to 1951, but reached its apex in 1964. Our analysis of cesium-137 in the sediments of Medicine Lake revealed that 14 cm of fine-grained tailings were deposited in the lake from 1951 to 1964 and tailing deposition downstream was greatly reduced by the installation of tailings dams in the district in 1968. Cesium-137 analysis is accomplished by a fairly simple gamma-ray counting technique and should be a valuable tool for analyzing sedimentation in any lacustrine environment that was active during the 1950s and 1960s.     

Use of sample color to estimate oxidized Fe content in mine waste rock

 Color, a readily perceived feature of natural earth materials, including mine waste, often represents compositional variation as a result of oxidative processes involving Fe. Near surface samples from excavated trenches in a mine-waste rock pile were collected to investigate the relationship between color and contents of Fe, Cu, and S. The silt+clay fraction (<0.05 mm) was isolated from recognizable colored material of the bulk sample for determination of pH, total and extractable Fe and Cu, and bulk mineralogy. Rock fragments within the pile exhibited coatings of crystalline gypsum and amorphous Fe. These coatings result from weathering (secondary products) and play important roles in surface reactions of waste rock piles, such as adsorption of anions (SO₄ ^2–) or coprecipitation of Fe with Cu. The correlation between color (Hurst method) and extractable Fe was high. Although color is influenced by site conditions such as original mineral composition, materials handling, weathering conditions etc., the results suggest that color measurements may provide an inexpensive and rapid estimation for secondary iron compounds and associated sorbed elements. Received: 5 April 1998 · Accepted: 30 June 1998     

短波红外光谱矿物测量技术在普朗斑岩铜矿区热液蚀变矿物填图中的应用

利用便携式短波红外光谱测量仪（PIMA）在云南普朗斑岩铜矿区开展了短波红外光谱测量工作,通过系统的野外数据采集,获得了研究区蚀变矿物组合及主要蚀变矿物的分布,并建立了普朗斑岩铜矿区蚀变矿物分带模式。在此基础上,建立了斑岩铜矿床找矿模型,该模型对普朗铜矿区及其外围的找矿工作具有积极的指导意义。     

Characterisation of the environmental impact of the Rodalquilar mine,Spain by ground-based reflectance spectroscopy

This study has investigated the utility of using field-based reflectance spectroscopy to characterise the distribution and nature of the dispersion of tailings material from the Rodalquilar mine, Spain. Field spectral measurements covering the visible to shortwave infrared wavelengths (0.35 to 2.5 m) and laboratory analyses were performed on samples collected along the length of the main river within the Rodalquilar valley. The nature and degree of contamination at locations within the river channel were calculated by a range of spectrometric analyses. The resulting mineral maps identified that tailings material with significant amounts of hematite with minor jarosite, ferrihydrite and goethite, and clays, primarily alunite and kaolinite, with minor smectite and illite, had been dispersed along the length of the river. These results have been used to improve understanding of the erosion and remediation history of the Rodalquilar mine. This study has shown the potential of field-based reflectance spectroscopy, integrated with ground positioning and digital mapping systems, as a real-time mapping methodology enabling immediate, accurate characterisation of the nature and scale of tailings material dispersion.     

Determination of metamorphic grade in siliceous muscovite-bearing rocks in Madagascar using reflectance spectroscopy

Visible short-wave infrared laboratory reflectance spectra of quartzites and micaschists from the Precambrian basement of central-western Madagascar are dominated by the muscovite spectrum. The spectra were measured from rock samples collected along an E–W traverse across a metamorphic sequence recording progressively higher metamorphic grades. The wavelength of the Al–OH band around 2200 nm decreased westward and was inversely correlated with Al^VI content of muscovite in rocks showing the same nonlimiting assemblage. This shift is correlated also with an increase of band intensity, which is attributed to the progressive increase of metamorphic grade. All of these variations in rock spectral properties can be detected by the high spectral resolution MIVIS and AVIRIS sensors, as well as by the lower resolution TM sensor.