Stream Sediment Samples Research Articles

Multi-method machine learning techniques in gold pathfinder elements prediction in central parts of Tanzania using stream sediment geochemical data

Prediction models using machine learning techniques have proven to be a reliable technique in mineral exploration. A combination of these techniques is very robust and reliable in exploration targeting and much dependable as an approach in greenfield. In this study, multi-machine learning methods: random forest (RF), support vector machine (SVM), and artificial neural network (ANN) were employed to conduct a data-driven gold (Au) prospectivity modelling in the Central parts of the Tanzania Craton (TC). A total of 166 samples with Au concentrations from stream sediment samples were considered. Based on the modeling results, the RF model demonstrates superior prediction accuracy compared to the SVM (MSE of 0.89) and ANN models (MSE of 1.21), achieving an MSE of less than 0.82. In terms of overall predictive performance and efficiency, the RF model outperforms other ML models deployed in this research. Therefore, it is deemed the suitable model for gold (Au) prediction in the TC catchments. According to the geological interpretation derived from the model, anomalies in arsenic (As), nickel (Ni), and tungsten (W) now emerge as significant predictors in the quest for gold. This implies that the association of As–Ni–W are potential pathfinder elements in the exploration of gold in the central part of the TC.

Mineralization, geochemical signatures, and provenance of stream sediments on the Jos Plateau, Northcentral Nigeria

This study aimed at determination of mineralization, geochemical signatures and provenance of stream sediments on the Jos Plateau, northcentral Nigeria. Ten (10) stream sediments samples collected were air-dried and subjected to X-Ray Fluorescence analysis. The SiO2 value of 49.79 to 77.03 wt%, Fe2O3 value of 1.30 to 28.84 wt%, Al2O3 value of 5.27 to 18.25 wt%, CaO value of 0.22 to 1.88 wt%, MgO value of 0.12 to 0.92 wt%, K2O value of 0.44 to 2.00 wt% and Na2O value of 0.02 to 0.65 wt%. The low values of CaO (0.22-1.88 wt %) and Na2O (0.02-0.65 wt %) could be associated with the destruction of plagioclase feldspar while low K2O composition (0.44-2.00 wt%) could be associated with the destruction of K-feldspar during weathering. The concentration of MnO (0.06-0.12 wt%) indicates manganite enrichment, the high TiO2 value (0.63-4.25 wt%) shows rutile enrichment while ZrO2 value (0.48-18.48 wt%) indicates zircon mineralization from the underlying lithologies. The high values of pathfinder elements (Y, Zn and Nb) could be attributed to the presence of Older and Younger Granites at the upstream of the study area. Samples 4, 5, 8 and 9 have Thorium (Th) concentrations >15 ppm threshold which point to areas favorable for Th mineralization. Enrichment Factor (EF) ranges from 3.03 to 42.42 indicating moderate, significant, very high enrichment and extremely high enrichment. The Contamination Factor (CF) of 1.27 to 201.03 indicates moderate and very high contamination possibly from geogenic sources. The provenance of stream sediments is associated with felsic and mafic sources

Mapping geochemical anomalies by accounting for the uncertainty of mineralization-related elemental associations

Abstract. Geochemical mapping is a fundamental tool for elucidating the distribution and behaviour of economically significant elements and providing valuable insights into geological processes. Nevertheless, the quantification of uncertainty associated with geochemical mapping has only recently become a subject of widespread concern. This study presents a procedure that primarily consists of the determination of homogeneous clusters, the recognition of elemental associations for each cluster, and the identification of geochemical anomalies, with the aim of accounting for the uncertainty of elemental association in geochemical mapping. To illustrate and validate the procedure, a case study was conducted wherein geochemical stream-sediment samples from the northwestern region of the province of Sichuan, China, were processed to map anomalies associated with disseminated gold mineralization. The results indicate that (1) the representativeness of elemental association for the underlying geological process is an important source of uncertainty for geochemical mapping; (2) the procedure presented here is effective in addressing the uncertainty of elemental associations in geochemical mapping; and (3) the study area can be classified into two clusters, each characterized by unique elemental associations that align well with the distribution of Paleozoic and Triassic lithological units, respectively. Furthermore, the region still holds great potential for the discovery of gold deposits, particularly in areas proximal to known mineralization sites.

Geochemical anomaly recognition using Shapley values and cell-wise outlier detection: a case study in the Yuanbo Nang District, Gansu Province, China

Geochemical pattern recognition has long been of interest for geologists to reveal geochemical anomalies associated with mineralization. In regional-scale exploration, geochemical anomalies are derived conventionally from stream sediment samples and processed in the form of vectors, resulting in row-wise outliers. However, geochemical anomalies derived through various means of pattern recognition have shown their limits in depicting complex geochemical distributions. In this paper, we propose to utilize the Shapley value, linked to the Mahalanobis distance (MD), and cell-wise outlier detection to facilitate the recognition of anomalous geochemical indicator elements. First, by considering the compositional nature of geochemical data, multivariate outliers are detected based on the MD in isometric log-ratio coordinates. Secondly, to quantify the contributions of individual elements to the outlyingness of an outlier, Shapley values are used to express the MDs of data as outlyingness contributions of single elements. Finally, cell-wise outlier detection is introduced to examine and quantify the outlyingness of each cell in a geochemical data matrix. The outlying cells serve as criteria for further recognition of element associations. By analysing the Shapley values of individual elements and the outlying cells in a geochemical data matrix, more information contained in multivariate outliers can be recognized. Using this proposed methodology, the element associations that relate to regional mineralization in the study area were Au-only anomalies, Au–As–Sb anomalies, As–Sb–Hg anomalies and Ag-related anomalies.

Source and Migration Pathways of Heavy Metals in Soils from an Iron Mine in Baotou City, China

The exploitation of iron ore could cause heavy metals pollution in the soils, which threatens the ecosystem and human health. In this study, soil, stream sediment, tailings, rock, and atmospheric deposition samples were collected from an iron mine in Baotou City. The concentrations of As, Cd, Cr, Cu, Hg, Ni, Pb, Zn, Al2O3, CaO, K2O, MgO, Na2O, SiO2, and Fe2O3, as well as the mineral composition and heavy metal speciation of the samples, were analyzed for pollution assessment and source identification of heavy metals. The results reveal that the concentration of Cu in the soils was significantly higher than the background value, and an unpolluted to moderately polluted state was the main pollution level. By analyzing the relationship between Cu/Al2O3 and CaO in different samples, as well as the characteristics of the chemical index of alteration (CIA), mineral composition, and the chemical speciation of Cu in soils and profiles, the results suggest that tailings were the source of Cu pollution in soils. The distribution characteristics of Cu and CaO in stream sediments indicated that hydraulic transport may be one of the main migration pathways. In addition, wind transport may also be a pathway of migration.

RECOGNITION OF PORPHYRY QUARTZ IN STREAM SEDIMENTS BY FLUID INCLUSION PETROGRAPHY AND CATHODOLUMINESCENCE MICROSCOPY: RESULTS OF SYSTEMATIC DISPERSION STUDIES AND POTENTIAL APPLICATIONS IN PORPHYRY EXPLORATION

Abstract Regional stream sediment surveys are an important exploration tool used in the search for concealed or partially concealed porphyry deposits. It is shown here that quartz contained in the coarse fraction of stream sediments can be used as an indicator mineral to supplement geochemical analyses conducted on the fine fraction, such as the measurement of the bulk cyanide leach extractable gold content. A method is proposed that allows separation of quartz grains from the coarse rejects of stream sediment samples to prepare grain mounts for petrographic analysis. Based on optical cathodoluminescence microscopy and fluid inclusion petrography, the number of porphyry quartz grains in each grain mount is then identified. Case studies conducted at Vert de Gris in Haiti and Hides Creek in Papua New Guinea show that porphyry quartz grains could be confidently identified in sediments in the catchment areas of both porphyries. Because the cost of microscopic analysis of quartz is small compared to the expense of sampling and geochemical analysis, the developed technique could be routinely used in large greenfield exploration programs. It is envisaged here that petrographic analysis of quartz grains can contribute valuable information for prioritization of targets defined based on their geochemical signatures.

Source, distribution patterns and resources potential of selenium in soil of north Pakistan: Revealed by a national-scale geochemical mapping

During national scale geochemical mapping in Pakistan, 69 elements including selenium were analyzed in 2563 stream sediment samples, which filled the gap of selenium distribution in the middle section of Tethyan metallogenic belt. The sampling density was 1–2 sites /100 km2. The geochemical concentration of selenium in the samples range from 0.008 to 6.849 mg/kg with an average value of 0.306 mg/kg. The highest average concentration of Se was found in the Suleiman Fold and Thrust Belt (anomaly III3), whereas the lowest is in WKLT Kohistan-Ladakh Island Arc. The type of soil in Pakistan with the highest Se concentration is entisol. The high selenium anomalies are delineated in the northeast of Quetta, near Muslim Bagh, in Mekhtar-Musa Khel area and its southwest region, north of Quetta and Khushab. Three strong selenium anomalies have also been identified in the northeast of Islamabad, northwest of Rawalpindi and the east of Dargai, respectively. It is suggested that selenium anomalies, having a correlation with elements of Mo, CaO, S, Sr, are mainly caused by geological background of shale, coal and coal-bearing formations. Negative anomalies are mainly distributed in the northern Pakistan, which is mostly consists of bedrocks with no or very thin layer of soil. The product of anomaly intensity and variance are defined as prospecting favorable degree (Pfd). The product of Pfd and area (S) are defined as Quantity of Mineral (Qm). There are two anomalies with the highest Pfd in the east of Quetta city, and the anomaly in the southwest of Kundian ranks third. The selenium anomalies indicate the areas of potential Se enrichment and supply basic data and information for geochemical investigation on a larger scale or selenium relevant research.

A New Discovery of Cu Mineralization in the North Qaidam, Tibet via Log-Ratio, Robust Factor Analysis, and Spectrum–Area Modeling

The Qinghai–Tibet Plateau, abundant in mineral resources, is a treasure trove for geological explorers. However, exploration has been hindered by the presence of dense vegetation, weathering layers, and desert cover, particularly in the North Qaidam region. As a result, there is an urgent need to develop efficient geochemical composition methods. In a study of stream sediment geochemical data from the Lüliangshan area of the North Qaidam, the log-ratio transformation was used for data processing, Robust Factor Analysis (RFA) was used for model construction, and the spectrum–area (S-A) model was used for anomaly separation. The outcomes identified two distinct groups of element combinations associated with mineralization. The first group consisted of Au + Ag + Pb + Sb + Hg linked to tectonic-altered rock-type Au (antimony) deposits, while the second group consisted of Cu + Zn + Co and was closely associated with Cu-Ni sulfide deposits. The S-A fractal filtering technique amplified weak anomalies and minimized the area of anomalies against strong backgrounds. The study successfully detected substantial Cu mineralization in the source areas of geochemical anomalies in the Lüliangshan region. Consequently, the log-ratio–RFA–S-A fractal model has been proven to be an effective combination of methods for identifying and extracting geochemical anomalies from stream sediment samples and for mineral exploration in covered areas.

Assessment of ecological and health risk impact of heavy metals contamination in stream sediments in Itapaji-Ekiti, SW Nigeria

BackgroundHeavy metal contamination in aquatic ecosystems is a major environmental and health concern globally. This study assessed the ecological and health risks associated with heavy metal pollution in stream sediments in Itapaji-Ekiti, Southwest Nigeria. The study contributes collectively to a comprehensive understanding of the geochemical dynamics and contamination factors affecting the studied stream sediments. MethodsHeavy metals study was conducted on stream sediments within the geographical confines of sheet 244, Ado map. Seventeen stream sediment samples were obtained from various sites and subjected to analysis to determine the concentrations of heavy metals such as lead (Pb), copper (Cu), zinc (Zn), chromium (Cr), cadmium (Cd), barium (Ba), arsenic (As), nickel (Ni) and vanadium (V) using X-ray Fluorescence (XRF). The results showed that the concentrations of these metals exceeded permissible levels at most sampling sites, indicating significant contamination of the stream sediments. The concentrations and pollution levels of the heavy metals from selected sampling sites were documented for ecological and health risk evaluations. ResultThe findings revealed that the concentrations of these metals surpassed acceptable thresholds at the majority of sampling locations, indicating significant contamination of the stream sediments. The concentrations of heavy metals, specifically Cr and Cd, exhibit moderate contamination, while Pb and Ba demonstrates a significant contamination factor with moderate to extreme degree of contamination. Several ecological risk indices were calculated to evaluate the potential ecological risks. The results revealed that the stream sediments posed considerable to very high ecological risks at most sites based on the risk quotient, contamination factor and pollution load index. The non-carcinogenic and carcinogenic risk assessments for heavy metals in stream sediments exposed potential health risks, especially for children, indicating the need for protective measures. The cumulative cancer risk, particularly for adults, raised concerns about the overall health implications of prolonged exposure to the heavy metal concentrations in the streams. ConclusionThe study also evaluated ecological and health risks, revealing potential risks from heavy metals. Hazard and cancer risk assessments suggested the increasing potential of heavy metals to pose health risks, particularly for inhabitants of the area.

Stream sediment pollution: a compositional baseline assessment

AbstractA high concentration of potentially toxic elements (PTEs) can affect ecosystem health in many ways. It is therefore essential that spatial trends in pollutants are assessed and monitored. Two questions must be addressed when quantifying pollution: how to define a non-polluted sample and how to reduce the problem’s dimensionality. A geochemical dataset is a composition of variables (chemical elements), where the components represent the relative importance of each part of the whole. Therefore, to comply with the compositional constraints, a compositional approach was used. A novel compositional pollution indicator (CPI) based on compositional data (CoDa) principles such as the properties of sparsity and simplicity was computed. A dataset of 12 chemical elements in 33 stream-sediment samples were collected from depths of 0–10 cm in a grid of 1 km × 1 km and analyzed. Maximum concentrations of 3.8% Pb, 750 µg g−1 As, and 340 µg g–1 Hg were obtained near the mine tailings. The methodological approach involved geological background selection in terms of a trimmed subsample that could be assumed to contain only non-pollutants (Al and Fe) and the selection of a list of pollutants (As, Zn, Pb, and Hg) based on expert knowledge criteria and previous studies. Finally, a stochastic sequential Gaussian simulation of the new CPI was performed. The results of the hundred simulations performed were summarized through the mean image map and maps of the probability of exceeding a given statistical threshold, allowing the characterization of the spatial distribution and the associated variability of the CPI. A high risk of contamination along the Grândola River was observed. As the main economic activities in this area are agricultural and involve animal stocks, it is crucial to establish two lines of intervention: the installation of a surveillance network for continuous control in all areas and the definition of mitigation actions for the northern area with high levels of contamination. Graphical Abstract

National-scale Geochemical Survey: Distribution of chemical elements in stream sediment of South and Central Asia

This work was carried out as the Pakistani, Uzbekistani, Tajikistani, and Kyrgyzstani contribution to the National-scale Geochemical Survey of South and Central Asia (NGSSCA) project, the objective of which was to document and study the amounts and distribution of chemical elements in stream sediment of South and Central Asia where such national-scale geochemical mapping is launched for the first time. In the framework of the NGSSCA project deployed in Pakistan, Uzbekistan, Tajikistan, and Kyrgyzstan, 9237 stream sediment samples (<2 mm grain-size fraction in alpine desert and mountainous area) were collected at an average density of 1 sample site/100 km2, on the basis of a common stream sediment sampling protocol. The resultant compositional data sets and cartographic products will vastly benefit future mineral exploration activity, surficial (and even solid Earth) geochemical processes studies (e.g., chemical weathering), and environmental evaluation. Eight elements of economic interests (e.g., Ag, Sb, W, Mo, Li, Be, Cu, and Co) are selected to demonstrate their distribution pattern in stream sediment and the main controlling factors. It's concluded that the anomalies for the selected elements in the NGSSCA project can thus be directly linked to different geogenic sources, e.g., underlying bedrock, soil type, mineralization or ore deposits, and large-scale fault systems. Based on the results and the integrated anomaly maps, some new target areas for the corresponding metallic mineralization are predicted, which will provide a basis for further mineral exploration.

Recognition of REEs anomalies using an image Fusion fractal-wavelet model in Tarom metallogenic zone, NW Iran

This study aims to detect REE geochemical anomalies in relationship to Iron-apatite ores utilizing an image Fusion based on Deep Learning (FDL). The geochemical data was modeled for elements related to Iron-apatite mineralization using multi b Spline B. The results were fusioned in applying the Deep learning method based on pre-trained networks. Wavelet-Number (WN) fractal model classified the best results based on the combination of a two-dimensional Discrete Wavelet Transformation (DWT) signal analysis and a Concentration-Area (C-A) fractal modeling. Sym8 carried the DWT as a selected wavelet pattern for REE based on Stream sediment samples collected from the Tarom region (NW Iran). In addition, the DWT was decomposed by wavelet coefficients at five levels. Furthermore, the DWT data were classified using a fractal-wavelet model to delineate REE anomalies from background levels in this region. Overlayed with the catchment basins model and weighted using the upstream and downstream parts. As a result, the prominent REE source anomalies are located in the southern parts of the study area. The results obtained by the proposed fractal-wavelet modeling are in connection with field check anomaly samples and the rock samples collected from the Iron-Apatite ore deposits.

Size Distribution And Heavy Mineral Pattern In Some E Gbe Streams, Southwestern Nigeria

The Egbe-Isanlu schist belt has received scholarly attention from several researchers but there is no documented report on types and the distribution of heavy minerals in streams of the area. This study is intended to reveal the types of heavy minerals, the distribution and possible source rocks to guide prospectors in gems. The study area lies within latitude 08o 03' and 08o 16 ' and longitude 05o 31' and 05o 43’ of the Southwestern Basement Complex terrain in Nigeria. Fifteen stream sediment samples were collected at appropriate points along river channels, air dried at room temperature, sieved and subjected to heavy mineral separation process using bromoform. Graphic mean, sorting, skewness and kurtosis were determined and heavy minerals identified under microscope. The graphic mean ranges between 0.67 (coarse sand) to 2.49 (fine sand), skewness between 0.75 and -0.10 and Kurtosis between 0.87 and 1.88. The calculated ZTR index ranges between 6.86% and 3.35.0%. The identified heavy minerals in the study area included tourmaline, epidote, rutile, zircon, kyanite, staurolite, garnet and zeolite. These minerals are modernly distributed across the sampled area and in some locations, they are relatively high in abundance. Some of the heavy minerals are angular to sub-angular in shape suggesting a short distance of travel from source. The graphic mean gives values that suggests a moderately to poorly sorted sediment and skewness indicated a platykurtic and leptokurtic nature for the sediments. Calculated ZTR index classified the sediments as immature to sub-mature indicating a short distance of travel suggesting that the sediments could have been derived within the catchment area. The presence of zircon, tourmaline and rutile suggests that the sediments might probably have its source from acid intrusive rocks and pegmatites.&#x0D; &#x0D; &#x0D;

National-scale Geochemical Baseline of 69 elements in Papua New Guinea stream sediments

This study presents the first Papua New Guinea geochemical baseline values of 69 elements. The National-scale Geochemical Baseline project of Papua New Guinea (PNG-NGB) were conducted during 2015–2018, covered an area of approximately 128,000 km2. A total of 1399 stream sediment samples were collected at an average density of 1 sample/100 km2, and 69 elements were analyzed. The results of PNG-NGB values are studied by R-mode factor analysis, and scatter plot analysis, the relationship between the 69 elements and the geological background, mineralization, and human activities are discussed as well. The median values of element contents related to the upper continental crust values were: TFe2O3, TC, Br, Co, Cr, Cu, Hg, Mn, N, Sc, Se, Te, Ti, V and Zn >1.3 times; Na2O, K2O, Ba, Be, Bi, Cl, Cs, F, I, Mo, Rb, S, Sb, Sr, Th, Tl, Zr, La, Ce, Pr and Nd <0.7 times; and SiO2, Al2O3, CaO, MgO, Ag, As, Au, B, Cd, Ga, Ge, Hf, In, Li, Nb, Ni, P, Pb, Sn, Ta, W, U, Y, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu, 0.7–1.3 times. R-mode factor analysis based on principal component analysis and varimax rotation showed that they fall into14 factors related to bedrock, mineralization, and human activities. This study provides basic geochemical data for many fields, including geology, mineral exploration, environmental protection, and agricultural production in Papua New Guinea.

The search for plausible economic mineral deposits in the central parts of Tanzania; insight from stream sediment geochemistry, multivariate statistics and geostatistics

Exploration success relies heavily on the data obtained, but, significantly on the type of analytical methods deployed and the interpretation reached. A poorly analyzed data may obscure the true reflectivity of the data, and thus, compromised the decision made. A combined data processing approach of descriptive statistics, enrichment-depletion data normalization, geospatial elemental distribution, and stacked overlayed comparison of elements have been used in this study. The prime purpose was to demonstrate potential elemental anomalies, and predict areas of higher degree of confidence for subsequent exploration and mineral resource evaluation. One-hundred and sixty-six stream sediment samples from the Dodoma Region of the Tanzania Craton have been examined; to reveal potential elements or mineral commodity that warrant further exploration. Forty-three elements of target were examined, as this craton is globally known for its rich earth mineral commodity. Our result indicates an enrichment of transition metals (TMs) (Cu, Ni, Co, Cr, Mn and Zn), High Field Strength Elements (Y, Th, U, Zr, Nb, Hf, Ta and Pb), Large Ion Lithophile Elements (Ba and Rb) and Rare-Earth Elements (La and Ce), Platinum Group Element (Pd and Pt) and other metals (Au, As, Bi, W, Mo and Li).Obtained results point to a likely poly-metallic sources and processes; as the underlain geology is marked largely by pegmatite and migmatites, and moderate proportion of fine clastic sedimentary rocks, and minor volcanic rocks mostly to the northern domain. Theoretically, the Large Ion Lithophile Elements (LILEs), Rare-Earth Elements (REEs) and Platinum Group Elements (PGEs) are associated with felsic rocks or variable stages of plutonic granitization. Although, the TMs are often associated with mafic-ultramafic rocks, the linkage of such metals with organic-rich shales been reported elsewhere. These rocks may equally contribute to the occurrence of other metals as stated in this paper. Its intriguing to note a strong positive correlation of Li with TMs, possibility of Li control by mafic minerals in pegmatite bodies. This work proposes a polymetallic enrichment controlled by the area geology. To suggest an alluvial mining potential of the above elements in the area, resource evaluation is a requirement. The geospatial maps reveal areas worth focusing for subsequent exploration. The adopted geostatistical methods and other approach utilized in this research are effective, indicative of handling bulk exploration data for decision and subsequent exploration.

Spatial-temporal variation, source apportionment and risk assessment of lead in surface river sediments over ∼20 years of rapid industrialisation in the Pearl River Basin, China

Lead (Pb) is a highly toxic element and is not essential to the human body. Lead pollution caused by human activities and a high geological background is considered a global environmental issue. According to the China Geochemical Baseline (CGB) project, the Pearl River Basin had the highest Pb content in alluvial sediments of 30 first-level basins in China. For this reason, it is of great significance to determine the temporal and spatial variations in Pb and their influencing factors in the Pearl River Basin. In this study, 956 stream sediment samples collected in the 1980 s (early stage) and 129 river sediment samples collected from 2008 to 2010 (late stage) were used to study the background value and spatial-temporal variation characteristics of Pb in river sediments in the Pearl River Basin. The Pb source apportionment and an ecological risk assessment were also carried out. The background value of Pb (36.2 mg·kg–1) in the river sediments of the Pearl River Basin was significantly higher than that in China (22.1 mg·kg–1). The parent rocks determine the Pb background in sediments and the high Pb background areas mainly comprised carbonate rocks and acid volcanic rocks. Over 20 years of rapid industrialisation, the average Pb increased from 43.3 to 68.3 mg·kg–1 in the Pearl River Basin. The BCR analysis revealed that Pb mainly existed in the reducible phase (48 % on average) and residue phase (42 % on average). The enrichment factor and geo-accumulation index indicated that the late-stage sediments experienced more Pb pollution than the early-stage sediments. However, the risk assessment code (RAC) showed that there was a low ecological risk of Pb in the late-stage sediments. The factor analysis results for the two rounds of data were significantly different. The Pb content in early-stage sediments was closely related to Al2O3 and Zr, while Pb in the late-stage sediments was mainly related to Zn, As, Sb, Au and Hg, indicating that the increase in Pb in the later samples was mainly influenced by human activities. The Pb isotope composition of the late-stage sediments confirmed that low Pb content was mainly controlled by natural sources, while high Pb content was significantly affected by anthropogenic sources. Combining the results of spatial-temporal variation, chemical speciation and source apportionment indicated that the rapid rise of Pb in late-stage sediments in certain areas could be attributed to mining and smelting activities during the process of industrialisation over 20 years. The anthropogenic exogenous Pb could be immobilised by Fe-Mn (hydro)oxides when it entered the soil, so although there was a high background the ecological risk of Pb in river sediments was low. In the future, Pb pollution control and remediation needs to be strengthened in the Pearl River Basin to avoid the outbreak of potential ecological risks linked to Pb.

Recognizing Geochemical Anomalies Associated with Mineral Resources Using Singularity Analysis and Random Forest Models in the Torud-Chahshirin Belt, Northeast Iran

Identifying the local geochemical anomalies from stream sediment samples is challenging in regional-scale exploration programs. For this purpose, some robust and reliable techniques must be applied to distinguish the geochemical targets from the background values. In this research, a procedure of several tools, including singularity mapping (SM), random forests (RF), success-rate curves, and the t-Student method, were employed to analyze the geochemical anomalies within the intrusive-plutonic Torud-Chahshirin belt (TCB), northeast Iran. In this regard, the success-rate curves were initially applied to extract efficient geochemical signatures. Then, singularity analysis was used on the selected geochemical elements (Au, Cu, Pb, and Zn), which were transformed via centered log-ratio (clr) transformation. In the next step, due to the complexity of the ore-forming processes in the TCB, the structural factors (e.g., fault intersection and faults with different orientations) were determined. Based on the success-rate curves, NE-trending faults and fault density were distinguished as critical structural criteria. Afterward, the RF model as a robust machine learning algorithm was executed on the four efficient SM-based geochemical layers and two efficient structural factors. The anomaly map derived by the RF model (Accuracy = 98.85% and Error = 1.15%) illustrates a very high relationship with Cu ± Au mineral occurrences. Therefore, the RF algorithm assisted by the singularity method is more trustworthy for highlighting the weak geochemical prospectivity areas in the TCB.

Environmental Geochemical Analysis in the Yanomami Indigenous Land, Mucajaí River Basin, State of Roraima, Brazil.

The Yanomami Indigenous Land in the Amazon has a long history of illegal artisanal gold mining, leading to concerns about mercury (Hg) contamination. This study has conducted a geochemical analysis to assess Hg contamination from these mining activities. Geological materials, including river water and stream sediments, were collected from 14 predetermined points based on the Geological Survey of Brazil's methodology. The results revealed that water samples did not show Hg contamination above the limits set by the National Council of the Environment (Conama) Resolution 357. However, two stream sediment samples, particularly PJS009 and PJS010 collected from the Mucajaí River, exceeded the Conama Resolution 454's limit of 0.17 mg/kg. A Hg content of 0.344 mg/kg was found in the sediment sample PJS009, the one collected further upstream in the Mucajaí River, and 1.386 mg/kg was found in sample PJS010, also in the Mucajaí River in the region shortly before the Fumaça Waterfall, indicating that the sediments of the Mucajaí River may be contaminated with Hg from the Fumaça Waterfall upstream.

Assessment of Water and Stream Sediment Pollution Related to Artisanal Mining in Alga, Burkina Faso, West Africa

Burkina Faso, like several other countries in the Sahelo-Sahelian strip, has seen a significant change in its mining sector in recent years through the development of the industrial and artisanal mining sub-sectors. The purpose of this study is to assess the level of pollution of water and stream sediments in the study area. A total of twenty-eight samples were taken, including three surface water samples, nine groundwater samples, ten stream sediment samples and six mine tailings samples. The analysis of the physico-chemical parameters and the metal content (cadmium, chrome, copper, mercury, nickel, lead, zinc and arsenic) of the water show that the values meet the drinking water standards in force in Burkina Faso. However, the various indices calculated, namely the geo-accumulation index (Igeo), the contamination factor (CF) and the enrichment factor (EF) show that the total metal contents of stream sediments are not d lithogenic (natural) origin but attributable to artisanal mining in the village of Alga. They highlight metal pollution with high levels of arsenic and cadmium and extremely high levels of mercury.

Prediction of Au-Associated Minerals in Eastern Thailand Based on Stream Sediment Geochemical Data Analysis by S-A Multifractal Model

Conducted within the scope of geochemical exploration in eastern Thailand, this study aims to detect geochemical anomalies and potential mineral deposits. The objective was to interpret intricate spatial dispersion patterns and concentration levels of deposit pathfinder elements, specifically arsenic (As), copper (Cu), and zinc (Zn), using a comprehensive array of stream sediment geochemistry data. Methodologies involved integrating multifractal properties and traditional statistics, facilitated by the GeoDAS and ArcGIS platforms as instrumental analytical tools. In total, 5376 stream sediment samples were collected and evaluated, leading to the development of an in-depth geochemical map. The results indicated distinct geological units marked by substantially elevated average values of the aforementioned elements. Identification of geochemical anomalies was achieved through the spatial distribution method and the subsequent application of the spectrum-area (S-A) multifractal model. An intriguing link was found between high As concentrations and gold deposits in the area, suggesting As as a viable pathfinder element for gold mineralization. The anomaly maps, generated from the stream sediment data, spotlighted potential zones of interest, offering valuable guidance for future mineral exploration and geological inquiries. Nonetheless, it is vital to recognize that the increased values noted in these maps may be influenced by regional geological factors, emphasizing the necessity for a diverse set of analytical methods for accurate interpretation. This study’s significance lies in its pioneering use of the S-A multifractal model in geochemical data analysis. This innovative approach has deepened our comprehension of geochemical dispersion patterns and improved the precision of mineral exploration.