Distribution Of Geochemical Elements Research Articles

Geochemical distribution of elements in the environmental media from the surroundings of open pit areas

The results of geochemical investigations - carried out within the framework of the European project LIFE IP RESTART - in the degraded areas of the Kopriva (deposit of natural stone-limestone) and Lipovški vrh (deposit of limestone for industrial purposes) open pits are presented. There test sites of the installation of secondary raw materials (a mixture of recycled materials and mineral raw materials) with the aim of revitalizing degraded surfaces are planned. The main goal of this study is to define the baseline geochemical distribution of elements in environmental materials (rocks, soil, stream sediment and surface water) for the purpose of monitoring the potential environmental impacts of installed secondary raw materials. In rocks Ca content predominates due to the geological setting (predominantly limestone) of the studied areas. According to the legislative guidelines for soil, exceedances have been found for Pb in one sample (origin can be natural or anthropogenic) and Ni in two samples (presumably natural origin) from the area of Kopriva. In the area of Lipovški vrh in the stream Suhi Potok, higher contents of Mg, Na, Sr, Ca, Mn and S occur in the downstream sediment compared to upstream sediment. It is assumed higher contents occur due to anthropogenic contribution of carbonate material along the stream (washing of materials from nearby open pit and road). In the surface water of Suhi Potok, higher concentrations of S, Sr, B, U and Zn were determined. However, the concentrations did not exceed the legislative guidelines.

Bedrock characterization and geochemical evolution of whole-rock weathering profile at GAG Ni laterite deposit, Southwest Papua, Indonesia

Abstract A series of laboratory analyses were conducted to investigate the correlation of petrography analyses of a bedrock coupled with microscope observation and X-Ray Diffraction (XRD) then compared with distribution of geochemical elements of whole-rock weathering profile by X-Ray Fluorescence (XRF). The microscope identification revealed that the bedrock was marked by the appearance of pyroxene predominantly surrounding olivine and serpentine, then magnetite, while XRD clarified that the bedrock was predominantly contained by a number of serpentine (lizardite), then pyroxene (enstatite), and magnetite. The geochemical evolution by bulk major-minor elements geochemistry as well as gain and losses of elements (τ) and compared with the equation from the ultramafic index alteration (UMIA) revealed that Fe2O3, NiO, Al2O3, CoO, Cr2O3 and MnO contents in the bedrock were 7.18wt%, 0.23 wt%, 1.23wt%, 0.01wt%, 0.35wt%, and 0.11wt%, respectively, then strongly increased towards the transition zone to 35.89wt%, 2.04wt%, 9.01wt%, 0.10wt%, 1.87wt%, and 0.51wt%, respectively. SiO2 and MgO revealed an inverted trend where it enriched in the bedrock then extremely decreased limonite layer with SiO2 (τ = ~ -0.92) and MgO (τ = ~ -0.99). The highest value of UMIA as well as consequently the highest degree of chemical weathering in this study was located in the upper limonite with a value of 63.87.

Spatial and temporal distribution of geochemical elements and their processes in different size fractions–Miri River (NW Borneo)

The toxicity, persistence, and propensity for accumulation of metals in aquatic environments have raised significant concerns globally. Expansion of urbanization with the growth of industrial and agricultural sectors in Miri City results in a high concentration of pollutants that flow directly into the Miri River. Hence, this study provides a comprehensive analysis of the Miri River water quality, focusing on spatial and temporal variations. River water samples were collected in two different time periods and analysed for physico-chemical parameters includes major ions, nutrients, metals and isotopes. Particularly, the metals were analysed in different size fractions (particulate and colloid) of the suspended solids. Geochemical plots, pollution index, geochemical modelling and factor analysis were used for the data analysis. Interpretation of data reveals that the mean concentration of metals in river water were increased from downstream to the upstream of the river irrespective of the seasons. Major ions were mostly derived from the chemical weathering of source rocks, which was supported by the Gibbs plot. Piper plot indicates the seasonal shifting of water types from Ca–Mg to Na–Cl. Isotopic signatures reveal direct atmospheric precipitation and evaporation were the major origins of river water. Fe was the dominant metal concentration in river water irrespective of the seasons (mean concentration 1.05 mg/L). Fe and Zn were the dominant metal concentration observed in all the 3 size fractions of suspended solids. Industrial activities and seawater influx dominate in the downstream, whereas weathering and agricultural inputs are significant in the upstream of the river. Particulate and colloidal fractions are the major contributors for the metal transport in the midstream and downstream of the river. The outcome of this study offer a thorough understanding of the seasonal elemental distribution at different size fractions, geochemical behaviour and the pollution status of the Miri River. With this knowledge, sustainable management strategies can be developed for this crucial water resource to the benefit of Miri community.

Insights into mineralogical distribution mechanism and environmental significance from geochemical behavior of sediments in the Yellow River Basin, China

Mineralogical investigations on fluvial sedimentary sequences could provide historical environmental information on the effects of human activities and natural events. This study aims to identify the mineralogical distribution mechanism and environmental significance of sediments of the Yellow River Basin based on topographic analysis, statistics, weathering and recycling indices. In total, 107 samples were collected from sedimentary sequences in the source area, and the upper, middle, and lower reaches and analyzed for grain size, major elements, and mineral composition. The results showed that the climate conditions were cold and arid, where weak hydrolysis under continental weathering and strong erosion accelerated physical weathering. Clay minerals in the upper reaches primarily originated from the Tibetan Plateau, whereas the middle and lower reaches received input of aeolian deposits from Northern China. Quartz and feldspar in the middle and lower reaches may derive from the source area and upper reaches. Meanwhile, calcite and dolomite formed through diagenesis, with loess input from the Chinese Loess Plateau. Regarding heavy minerals, the dominant determinative factors of pyrite were post-depositional diagenesis and leaching. Hematite and amphibole primarily formed through magnetite conversion and contribution from regional sources, respectively. Moreover, the mineral distribution mechanism significantly affected the mobility and distribution of geochemical elements through diagenesis and alteration. The findings are instrumental in reconstructing the environmental evolution of large-scale watersheds across multiple climatic zones.

Occurrence and distribution of geochemical elements in Miri estuary, NW Borneo: Evaluating for processes, sources and pollution status

In this study, estuarine water samples were collected at diverse hot spots in Miri River Estuary, East Malaysia to appraise the geochemical processes, which controls the river water quality. The collected water samples were analysed for various physicochemical parameters (insitu parameters, nutrients, major ions and trace metals), including stable isotopes (oxygen and hydrogen). Suspended solids are also extracted from the water samples and analysed for trace metals. Standard graphs, Piper plot, Gibbs diagram, water quality indices, geochemical modelling and statistical analysis were used for the data analysis. The acquired water quality data was compared with national and international guidelines for the suitability of water for various purposes. Interpretation of data reveals that the estuarine water quality is deemed unsuitable to be used for both drinking and irrigation purposes. Overall, the elemental concentrations are increasing from downstream to river mouth. Based on pollution indices (HEI and Cd), downstream region shows high vulnerability to metal pollution due to anthropogenic disturbance. Isotope values of river water indicate direct atmospheric precipitation with minimal evaporation. Factor analysis reveals that seawater influx, urban pollution, domestic and agricultural discharges at the downstream region are the main controlling factors to the river water quality. It is also deduced that suspended solids play a vital role in the adsorption and desorption of trace metals in the estuarine water. The outcome of this study provides a comprehensive information on pollution status of Miri estuary, which helps the policy makers to practice sustainable management of this water resource for Miri community.

Characterization of geochemical elements in surface sediments from Chinese deserts

Northern China has 12 main deserts that range from extremely arid regions in the west to semi-arid or semi-humid regions in the east. Based on their geographical locations, we divided these deserts into western, central, and eastern deserts. We investigated the geochemical elements in their surface sediments and found that the concentration of the major element SiO2 gradually increased from west to east, whereas the other major elements tended to decrease; however, the CaO concentration was unusually high in the Taklimakan and Qaidam Basin deserts. The spatial distribution of geochemical elements was more homogeneous in the western and central deserts than in the eastern. Unlike the eastern deserts, the western and central deserts show greater physical than chemical weathering and lower mineral maturity due to the extremely low precipitation and a continuous supply of younger materials. Most major trace elements in the eastern deserts were more depleted relative to the upper continental crust than in the western deserts, but were moderately depleted in the central deserts. The potential source rocks of central and western deserts are composed of intermediate igneous source rocks, while the sediments in eastern deserts are derived from the mixing of felsic and intermediate igneous source rocks or the mixing of quartzose deposits and intermediate igneous source rocks. The spatial distribution of geochemical elements showed similar provenances of aeolian material in the Taklimakan Desert and Kumtag Desert, and similar provenances of aeolian material in the Badain Jaran, Tengger, Ulan Buh, and Hobq deserts. There were no obvious provenance relationships for the Otindag, Horqin, and Hulun Buir sandy lands in the central and western deserts.

Particle size effect on geochemical composition of experimental soil mixtures relevant for unmixing modelling

Sediment fingerprinting experiments have been used to demonstrate the sensitivity of numerical mixing model outputs to different particle size distributions in source materials and experimental sediment mixtures. The study aims to examine further grain size effects in the distribution of geochemical elements by soils through a laboratory experiment simulating mixing and sorting processes, to investigate if different size fractions are influencing fingerprinting analyses and unmixing model results. Multiple particle size fractions are analysed to understand the relationship between particle size and source signal through elemental signatures. FingerPro model was applied to unmix six experimental mixtures with known percentages contribution from three experimental sources. The experimental design comprised four different setups with a specific size fraction for sources (S) and mixtures (M). Setups A (S <63 and M <63 μm) and B (S <20 and M <20 μm) relies upon a comparable particle size fraction for sources and mixtures, while C (S <63 and M <20 with PSC) and D (S <63 and M <20) address particle size impacts simulating fine enrichment, with and without a single particle size correction factor, respectively. Tracers were extracted after applying two statistical tests, the range test (RT) and a combination of RT, Kruskal-Wallis (KW) and DFA tests thus obtaining the set of optimum tracers for each mixture. Our findings indicate that source apportionment results are sensitive to tracer selection and particle size. The most accurate source apportionment results were achieved when comparing sources and mixtures with the <63 μm grain-size fraction (setup A) by using the set of tracers extracted after RT, KW and DFA tests, (mean RMSE: 2%, AE: 2%). Larger errors were obtained progressively for setups B, C and D with better results when using more number of tracers from RT (mean RMSE: 7, 10, 13%, AE: 8, 11, 15%, respectively). The main strength of using experimental mixtures with a known contribution of the sources relies on reducing the uncertainty of the unmixing model outputs, one of the main limitations in fingerprint studies. The impact of SSA on the elemental concentration is difficult to predict because the positive linearity between them does not apply equally to all elements and this assumption needs to be constantly examined and considered for fingerprinting studies. Otherwise, the use of a single particle size correction factor could negatively affect unmixing results. The outcomes of this research will help to develop appropriate strategies for sediment fingerprinting, contributing to our knowledge of processes affecting sediment geochemistry and sediment transport across different particle sizes.

Role of bedrock serpentinization on the development of nickel laterite deposit in Sorowako, Sulawesi, Indonesia

The objective of this research is to analyze the role of bedrock serpentinization on the development of Ni-Laterite deposits in Sorowako, Sulawesi Island, Indonesia. Samples were obtained from coring data in three areas, namely the West Block, East Block, and Petea, which are subject to mineralogical and geochemical analyses. Petrography of the bedrocks was conducted to analyze the mineral composition, texture, and serpentinization degree, and later correlated with the distribution of geochemical elements from X-ray fluorescence method in each laterite zone. The bedrock in the West Block is dunite which consists of predominantly olivine with low degree serpentinization. The bedrock in the East Blocks and Petea consists of peridotite in the form of lherzolite and harzburgite which have been moderate to highly serpentinized. The distribution of elements in each block shows that MgO, SiO2, and Ca elements significantly decrease towards the upper laterite profile while Fe, Al, and Cr are enriched in the limonite zone and Ni, Mn, and Co are significantly enriched in the saprolite zone. Ni, Fe, SiO2, Cr, MgO, and Mn in the West Block are relatively higher than the East Block and Petea. This study shows that Ni content is relatively higher in West Block compare to East Block and Petea in averages of 1.7%, 1.53%, and 1.3%, respectively. Olivine-rich bedrock and a low degree of serpentinization resulted in high-Ni concentration in the laterite profile, particularly in the saprolite layer. This means that bedrock characteristics and degree of serpentinization were responsible for the development of nickel.

Spatial modelling of hydrothermal mineralization-related geochemical patterns using INLA+SPDE and local singularity analysis

The complexity of geochemical patterns in surficial media makes it necessary to consider the uncertainty when identifying geochemical anomalies in geochemical prospecting. In this contribution, the type of uncertainty related to spatial modelling of geochemical element distribution based on a limited number of observations is considered. A hybrid method combining the integrated nested Laplace approximation (INLA) and the stochastic partial differential equation (SPDE), commonly termed “INLA + SPDE”, is employed to simulate the spatial distribution of a geochemical variable. The local singularity analysis (LSA) is then performed on each realization simulated by INLA + SPDE. Based on the ensemble of local singularity exponent maps, geochemical anomalies can be evaluated by considering both the intensity and uncertainty of local singularity. A case study of processing 1:50, 000 stream sediment samples collected from the Fanshan district, Fujian province of China, further illustrates and validates the procedure, and enhance the knowledge of hydrothermal mineralization-related geochemical patterns in this region. The findings indicate that (1) INLA + SPDE offers a viable alternative to existing methods for simulating spatial distribution of geochemical element distributions, with advantages in quantifying uncertainties of model responses as well as model parameters, computational efficiency due to INLA, etc.; (2) it is an effective way to combine INLA + SPDE and LSA to facilitate identifying geochemical anomalies by considering both the intensity and uncertainty of geochemical patterns. The delineated geochemical anomalies based on the mean of local singularity exponents should be paid attention in further geochemical exploration, but those associated with high uncertainty should be taken care of and further verified by other evidences. The workflow that combines INLA + SPDE and LSA can also be used to obtain information from other types of geoscientific data, and can hence enrich the toolbox for further mineral exploration.

Late Paleozoic Element Migration and Accumulation under Intracontinental Sinistral Strike‐slip Faulting in the West Junggar Orogenic Belt, NW China

AbstractThe migration, accumulation and dispersion of elements caused by tectonic dynamics have always been a focus of attention, and become the basis of tectono‐geochemistry. However, the effects of faulting, especially strike‐slip faulting, on the adjustment of geochemical element distribution, are still not clear. In this paper, we select the West Junggar Orogenic Belt (WJOB), NW China, as a case study to test the migration behavior of elements under tectonic dynamics. The WJOB is dominated by NE‐trending large‐scale sinistral strike‐slip faults such as the Darabut Fault, the Mayile Fault, and the Baerluke Fault, which formed during the intracontinental adjustment under N–S compression during ocean‐continental conversion in the Late Paleozoic. Geochemical maps of 13 elements, Al, W, Sn, Mo, Cu, Pb, Zn, As, Sb, Hg, Fe, Ni, and Au, are analyzed for the effects of faulting and folding on element distribution at the regional scale. The results show that the element distribution in the WJOB is controlled mainly by two mechanisms during tectonic deformation: first is the material transporting mechanism, where the movement of geological units is consistent with the direction of tectonic movement; second is the diffusion mechanism, especially by tectonic pressure dissolution driven by tectonic dynamics, where the migration of elements is approximately perpendicular or opposite to the direction of tectonic movement. We conclude that the adjustment of element distributions has been determined by the combined actions of transporting and diffusion mechanisms, and that the diffusion mechanism plays an important role in the formation of geochemical Au blocks in the WJOB.

Exploring the Potential of HySpex Hyperspectral Imagery for Extraction of Copper Content.

Detritus geochemical information has been proven through research to be an effective prospecting method in mineral exploration. However, the traditional detritus metal content monitoring methods based on field sampling and laboratory chemical analysis are time-consuming and may not meet the requirements of large-scale metal content monitoring. In this study, we obtained 95 detritus samples and seven HySpex hyperspectral imagery scenes with a spatial resolution of 1 m from Karatag Gobi area, Xinjiang, China, and used partial least squares and wavebands selection methods to explore the usefulness of super-low-altitude HySpex hyperspectral images in estimating detritus feasibility and effectiveness of Cu element content. The results show that: (1) among all the inversion models of transformed spectra, power-logarithm transformation spectrum was the optimal prediction model (coefficient of determination(R2) = 0.586, mean absolute error(MAE) = 21.405); (2) compared to the genetic algorithm (GA) and continuous projection algorithm (SPA), the competitive weighted resampling algorithm (CARS) was the optimal feature band-screening method. The R2 of the inversion model was constructed based on the characteristic bands selected by CARS reaching 0.734, which was higher than that of GA (0.519) and SPA (0.691), and the MAE (19.926) was the lowest. Only 20 bands were used in the model construction, which is lower than that of GA (105) and SPA (42); (3) The power-logarithm transforms, and CARS combined with the model of HySpex hyperspectral images and the Cu content distribution in the study area were obtained, consistent with the actual survey results on the ground. Our results prove that the method incorporating the HySpex hyperspectral data to invert copper content in detritus is feasible and effective, and provides data and a reference method for obtaining geochemical element distribution in a large area and for reducing key areas of geological exploration in the future.

Three-dimensional modelling of alteration zones based on geochemical exploration data: An interpretable machine-learning approach via generalized additive models

The inference of deep alterations plays an important role in the analysis of deep geological processes and the targeting of buried mineral resources. However, the construction of three-dimensional (3D) models of alteration zones based on geochemical data is challenging due to the diverse geological processes and scarcity of information related to deep alterations. In this paper, we propose an interpretable machine-learning method to infer 3D geological models of alteration zones based on geochemical data from the Dayingezhuang area, China. To expose the information hidden in geochemical data that is indirectly and weakly related to alteration zones, a generalized additive model (GAM) is used. It learns a nonlinear, intelligible model associating geochemical anomalies (extracted by PCA) with alteration features. The model learned via GAM and is then combined with a Bayesian framework to infer the thickness of alterations in a no-drilling area, thus enabling 3D modelling of deep alteration zones. With such an intelligible model, geologists are capable of inspecting the reliability of the model and better understanding the association between the distribution of geochemical elements and deep alterations. The inference results show that the relationship between geochemical anomalies and alteration depth is significant, while the relationship with alteration thickness is complex. The results of this study provide the underlying insights needed to guide the analysis of deep geological mineralization processes.

Predictive modeling and comparative evaluation of geostatistical models for geochemical exploration through stream sediments

Geochemical exploration of stream sediments is an important step for the identification of areas of interest with potential mineralization, particularly in the early stages of mineral exploration. A total of 407 sample points for 15 different geochemical traces were collected from Central Wales and classified into two groups: a training group consisting of 285 samples and a testing group consisting of 122 samples. Geospatial characterization of each parameter at stream level was performed using two different prediction models; the inverse distance weighting and the geostatistical kriging. Several variations of the IDW model was applied based on the power function and the number of the sample points, and the best one selected based on “root mean square prediction error” statistic. The same statistic was also used in the best-fitted semivariogram models including the circular, spherical, exponential and Gaussian for each geochemical parameter in Kriging. Finally, the mineral prospectivity map of the area was developed based on the geochemical accumulation index (GAI) using multivariate overlay analysis. The experimental results show that there is no single method that can be used independently to predict the spatial distribution of geochemical elements in streams. Instead, a combinatory approach of IDW and kriging is advised in order to generate more accurate predictions. The mineral prospectivity map based on GAI showed that most of the mineral-enriched streams were found in northwest, northeast, and south part of the study area which was also confirmed with the existing mining activities in the region.

Quantifying the Distribution Characteristics of Geochemical Elements and Identifying Their Associations in Southwestern Fujian Province, China

The distribution of geochemical elements in the surficial media is the end product of geochemical dispersion under complex geological conditions. This study explored the frequency and spatial distribution characteristics of geochemical elements and their associations. It quantifies the frequency distribution via mean, variance, skewness and kurtosis, followed by measuring the spatial distribution characteristics (i.e., spatial autocorrelation, heterogeneity and self-similarity) via semivariogram, q-statistic and multifractal spectrum, and further identify the elemental associations based on these distribution parameters using hierarchical clustering. A criterion was defined to identify the importance of parameters in the clustering procedure. A case study processing a geochemical dataset of stream sediment samples collected in southwestern Fujian province of China was carried out to illustrate and validate the procedure. The results indicate that studies of the frequency and spatial distribution characteristics of geochemical elements can enhance the knowledge of geochemical dispersions. The associations identified based on the frequency and spatial distribution parameters are different from those obtained by conventional cluster analysis. Spatial distribution characteristics cannot be neglected when investigating the distribution patterns of geochemical elements and their associations. The findings can enhance the knowledge of the geochemical dispersion in the study area and might benefit the following-up mineral exploration.

Memory Impairment and Intelligence Retardation with Exposure to Fluoride and Arsenic​

Due to the uneven distribution of geochemical elements and environmental pollution caused by industrial development, the environmental media in some areas are rich in fluorine and arsenic. High-fluorine, high-arsenic, and double high regions of both fluorine and arsenic exist widely in the world. The attention to the harm of endemic fluoride, arsenic and their combined poisoning on the intelligence, learning and memory of children has been paid. We herein reviewed the research results on the effects of fluorine, arsenic and their combined effects on learning and memory.

FastICA and total variation algorithm for geochemical anomaly extraction

Because the ore-forming system in the crust of the Earth is a highly nonlinear system, geochemical anomaly classification is very important for improving the accuracy of metallogenic prediction. Further, since the distribution of the geochemical elements usually presents nonlinear characteristics due to the complexity and uncertainty of geology factors, the traditional linear data processing method has limited applications for an ore-forming system. The FastICA algorithm is applied to preprocessed geochemical data to reduce the interference information between elements. On the basis of obtaining the separated geochemical elements, the continuity of the spatial distribution of geochemical elements is considered, and combined with the application of the total variation (TV) in image processing; thus the total variation is introduced when processing geochemical data for anomaly analysis to eliminate the influence of singular geochemical data values. To measure the spatial distribution of geochemical elements, assays of the 1:10000 soil geochemical data in the area of Dachaidan in the Qinghai province of China are processed. The elemental anomaly zoning sequences are divided into three levels of anomaly: 85%, 90% and 95%. The anomaly isograms of Au and Cu processed by FastICA and the total variation algorithm predict the geological background of the study area better than the traditional cumulative frequency method. These results indicate that the application of the FastICA algorithm and the total variation algorithm to process geochemical data processing is valid and effective.

Co-simulated Size Number: An Elegant Novel Algorithm for Identification of Multivariate Geochemical Anomalies

Identification of geochemical anomalies is of particular importance for tracing the footprints of anomalies. This can be implemented by advanced techniques of exploratory data analysis, such as fractal/multi-fractal approaches based on priori or posteriori distribution of geochemical elements. The latter workflow involves analysis of 2D/3D produced maps, which can be mostly obtained by geostatistical algorithms. There are two challenging issues for such an analysis. The first one corresponds to handling the cross-correlation structures among the data, and the second one relates to the compositional nature of data. To tackle these problems, this paper investigates the application of Gaussian co-simulation for modeling the cross-correlated compositional data in order to recognize the multivariate geochemical anomalies in integration with fractal analysis. In this context, an innovative algorithm, namely co-simulated size number (CoSS-N), is introduced for this purpose. The compositional nature of data is addressed by additive log-ratio transformation of original data while the Gaussian co-simulation handles the reproduction of cross-correlation among the components. The co-simulated outputs are then taken into account for capturing different geochemical populations, showing different levels of backgrounds and anomalies. The algorithm is illustrated via a real case study located in Philippine wherever seven geochemical components are required to be considered. The accuracy of results is examined by statistical validation techniques, indicating the capability of the CoSS-N algorithm for multivariate identification of geochemical anomalies.

Memory Impairment and Intelligence Retardation with Exposure to Fluoride and Arsenic​

Due to the uneven distribution of geochemical elements and environmental pollution caused by industrial development, the environmental media in some areas are rich in fluorine and arsenic. High-fluorine, high-arsenic, and double high regions of both fluorine and arsenic exist widely in the world. The attention to the harm of endemic fluoride, arsenic and their combined poisoning on the intelligence, learning and memory of children has been paid. We herein reviewed the research results on the effects of fluorine, arsenic and their combined effects on learning and memory.

Separation of a geochemical anomaly from background by fractal and U-statistic methods, a case study: Khooni district, Central Iran

Separation of geochemical anomalies from background are one of the important steps in mineral exploration. The Khooni mineral district (Central Iran) has complex geochemical surface expression due to a complex geological background. This region was chosen as a study area for recognition of the spatial distribution of geochemical elements and separating anomalies from background using stream sediment geochemical data. In the past decades, geochemical anomalies have been identified by means of various methods. Some of these separation methods include: statistical analysis methods, spatial statistical methods and fractal and multi-fractal methods. In this article, two efficient methods, i.e. U-statistics and the fractal concentration-area for separation and detection of anomalous areas of the background were used. The U spatial statistic method is a weighted mean, which considers sampling point positions and their spatial relation in the estimation of anomaly location. Also, fractal and multi-fractal models have also been applied to separate anomalies from background values. In this paper, the concentration–area model (C–A) was suggested to separate the anomaly of background. For this purpose, about 256 stream sediment samples were collected and analyzed. Then anomaly maps of elements were generated based on U spatial statistics and the C-A fractal methods for Au, As and Sb elements. According to obtained results, the U-statistics method performed better than C-A method. Because the comparisons of the known deposits and occurrences against the anomalous area created using thresholds from U-statistics and C-A method show that the spatial U-statistics method hits all of 3 known deposits and occurrences, the C-A fractal method hits 1 and fails 2. In addition, the results showed that these methods with regard to spatial distribution and variability within neighboring samples, in addition to concentration value frequency distributions and correlation coefficients, have more accurate results than the traditional approaches.

Multifractal distribution of geochemical elements in Dexing porphyry copper deposit, Jiangxi Province, China

Hydrothermal mineralization can cause enrichment or depletion of elements in ore bodies and surrounding country rocks. Local metal-enriched rocks can become an ore body that can be mined at an economic profit. Therefore, understanding the spatial distribution of elements caused by mineralization is crucial for mineral exploration and resource assessment. In this study, a total of 24 representative samples were collected from different veins within the Tongchang ore body of the Dexing porphyry Cu–Mo Deposit. The objectives of this work were firstly to identify different vein types and secondly to evaluate the potential of multifractal parameters, constructed using the so-called method of moments, to characterize the spatial and temporal distribution patterns of concentration of elements on mineral surfaces, which may provide insight into hydrothermal mineralization and its effect on spatial and temporal distribution of element concentration. Based on the analytical results and previous investigations, the vein systems within the deposit can be divided into four main types as follows: (1) early quartz veins (A-type veins) related to K-feldspar alteration; (2) quartz-pyrite-molybdenite-chalcopyrite veins (B-type veins) related to chlorite+illite alteration; (3) quartz-pyrite-chalcopyrite veins (D-type veins) related to late phyllic (muscovite+quartz) alteration; and (4) the latest carbonate-sulphate-oxide veins (H-type veins). The multifractal distributions of concentration of chemical elements on the surface of pyrite crystals selected from veins of different types were investigated using digital images generated by means of ESEM. To achieve our goal, the distribution patterns of element concentration values of eight elements (Cu, Fe, Mn, Ni, P, S, Si and Ti) on the pyrite surface selected from B-type, D-type and H-type veins and veinlets were represented by multifractal spectra. Several multifractal parameters were calculated; however, the most significant ones are ∆α and ∆αL. These parameters are found to be higher in the D-type veins related to late phyllic alteration and mineralization in comparison with other veins and vein systems, indicating that the ore minerals containing Cu and Fe sulphides are highly enriched in D-type veins. This result is consistent with previous research on the area as well as new field observations, chemical and petrographic analysis carried out for this study. Therefore, the multifractal parameters, particularly ∆α and ∆αL, appear to be promising to discriminate between mineralized veins developed during different stages of hydrothermal activity which led to development of the porphyry system at Tongchang ore body.