Search Results (268)

The Sichuan–Yunnan–Guizhou Pb-Zn metallogenic belt (SYG metallogenic belt), a crucial metallogenic unit on the southwestern margin of the Yangtze Block, is a key part of the South China low-temperature metallogenic domain. The incorporation mechanisms and distribution of trace elements (e.g., Ge, Ga, Cd) widely enriched in Pb-Zn sulfides throughout this region remain poorly understood. This study investigates main-ore-stage sulfides (sphalerite and pyrite) from the Maoping Pb-Zn deposit using in situ laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) analyses and mapping to systematically elucidate the partitioning and occurrence of these trace elements. The key findings are as follows: (1) Sulfides show distinct elemental partitioning: sphalerite preferentially concentrates Cd, Ag, Ge, Ga, and Se, whereas pyrite is significantly enriched in Mn, Ni, As, and Co. (2) Sphalerite is the primary host for many trace elements. Cadmium, Ge, Mn, Cu, and Ag mainly enter the sphalerite lattice by substituting for Zn²⁺. Coupled substitution mechanisms, such as Zn²⁺ ↔ Cd²⁺, 2Zn²⁺ ↔ Ge²⁺ + Cu²⁺, and 2Zn²⁺ ↔ Ga³⁺ + Cu⁺, facilitate the incorporation of Ge and Ga. (3) The sphalerite exhibits a trace element assemblage of high Cd-Ge and low Fe-Mn, which is geochemically similar to typical Mississippi Valley-type (MVT) deposits and differs significantly from sedimentary exhalative (SEDEX) and magmatic–hydrothermal deposits, indicating a medium- to low-temperature metallogenic environment. Based on these geochemical signatures and epigenetic textures, we confirm that the Maoping Pb-Zn deposit exhibits similarities with MVT deposits. Nevertheless, distinct differences in the tectonic setting and metal grades suggest it is a unique SYG-type Pb-Zn deposit. Full article

Population growth and agricultural expansion are threatening groundwater resources in the Maze Zenti catchment, Southern Ethiopia. This study evaluated groundwater suitability for drinking and irrigation by analyzing 30 samples using an integrated approach. This approach included GIS-based IDW interpolation, hydrochemical characterization, drinking water quality index, entropy weight, pollution index of groundwater, multivariate statistics, Piper, Gibbs, and Wilcox diagrams, ANOVA, and irrigation indices based on WHO standards. The correlation matrix revealed strong associations between Na⁺-TDS (r = 0.77) and Na⁺-Ca²⁺ (r = 0.68), indicating mineral dissolution, ion exchange, and agricultural inputs as key factors. Weak correlations were found for NO₃⁻ and F⁻, reflecting localized anthropogenic and geogenic influences. Component analysis identified four components explaining 78.2% (wet season) and 81.2% (dry season) of the variance, highlighting mineralization and anthropogenic inputs. Hydrochemical facies were mainly Ca-Mg-HCO₃ with some localized Na-HCO₃, suggesting that rock–water interactions are the primary source of geochemical control. Drinking water quality assessment showed that, during the wet season, 52.8% of the catchment had excellent water quality, 45.8% was good, and 1.4% was poor–very poor. In the dry season, 51.6% was excellent, 47.4% was good, 0.8% was poor, and 0.2% was very poor. The results of the entropy-weighted analysis indicated seasonal improvement, with excellent areas increasing from 13.1% to 31.4% and poor zones decreasing from 7.5% to 3.4%. Irrigation indices (Na%, PI, MAR, SAR) and Wilcox analysis (86.4% C2S1) suggested low sodicity and salinity hazards. This study provides the first integrated seasonal mapping of drinking and irrigation water quality, entropy-weighted water quality, and pollution index for the Maze Zenti catchment, establishing a hydrogeochemical baseline. Overall, groundwater in the area is generally suitable for drinking and irrigation. However, localized monitoring and sustainable land-use practices are recommended to mitigate contamination risks. Full article

The mineral-mapping capability of three spaceborne sensors with different spatial and spectral resolutions, the Environmental Mapping and Analysis Program (EnMap), Sentinel-2, and World View-3 (WV3), is assessed regarding bauxite mining wastes in Amphissa, Greece, with validation based on ground samples. We applied the well-established Linear Spectral Unmixing (LSU) and Spectral Angle Mapping (SAM) classification techniques utilizing endmembers of two established spectral libraries and incorporated ground data through geochemical and mineralogical analyses, X-ray fluorescence (XRF), Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS), and X-ray Diffraction (XRD), to assess classification performance. The main lithologies in this area are bauxites and limestones; therefore, aluminum oxyhydroxides, calcite, and iron oxide minerals were the dominant phases as indicated by the XRF/XRD results. Almost all target minerals were mapped with the three sensors and both methods. The performance of EnMap is affected by its coarser spatial resolution despite its higher spectral resolution using these methods. Sentinel-2 is most effective for mapping iron-bearing minerals, particularly hematite, due to its higher spatial resolution and the presence of diagnostic iron oxide absorption features in the VNIR. World View 3 Shortwave Infrared (WV3-SWIR) performs better when mapping calcite, benefiting from its eight SWIR spectral bands and very high spatial resolution (3.7 m). Hematite and calcite yield the highest accuracy, especially with SAM, indicating 0.80 for Sentinel-2 (10 m) for hematite and 0.87 for WV3-SWIR (3.7 m) for calcite. AlOOH shows higher accuracy with SAM, ranging from 0.57 to 0.80 across the sensors, while LSU shows lower accuracy, ranging from 0.20 to 0.73 across the sensors. This study showcases each sensor’s ability to map minerals while also demonstrating that spectral coverage and the spatial and spectral resolution, as well as the characteristics of the selected endmembers, exert a critical influence on the accuracy of mineral mapping in mine waste. Full article

The Paleoproterozoic Aravalli Supergroup in northwest India hosts one of the oldest phosphorite deposits on Earth, located in the Jhamarkotra Formation, which was deposited after ca. 1762 Ma. Secondary enrichment is identified in the eastern region, resulting in upgradation of phosphate content, while primary stromatolitic columns are well-preserved in the western area of the Jhamarkotra mines. In this study, drill-core samples were collected from the unaltered western Block B and the upgraded eastern Block E to understand the alteration process. Petrographic studies reveal evidence of structural deformation and alteration. Elemental mapping of petrographic thin sections, employing SEM-EDS, indicates that dolomite has been leached out, resulting in phosphorite upgrading in the E-block. The major element oxide data support the leaching of dolomite. In the upgraded E-block, the weighted average P₂O₅ content nearly doubled (from 21% to 38%), while the MgO content decreased from 21% to 4% compared to the B-block. REE+Y contents in Block E are increased with minor Ce and Eu anomalies developed compared to the B Block. The U and Sr concentrations are also increased in Block E phosphorites. The petrographic and geochemical studies indicate that phosphorite enrichment was driven by structurally controlled, low-temperature hydrothermal alteration in the Jhamarkotra mines. Full article

Ataúro Island, located in the inner Banda Arc, provides a natural laboratory to investigate the interplay between magmatic evolution, hydrothermal circulation, and near-surface weathering in an active arc–continent collision setting. This study presents the first systematic island-wide geochemical baseline for Ataúro Island, based on multi-element analyses of stream sediments integrated with updated geological, structural, and hydromorphological information. Compositional Data Analysis (CoDA–CLR–PCA), combined with anomaly mapping and spatial overlays, defines a coherent three-tier geochemical framework comprising: (i) a lithogenic component dominated by Fe–Ti–Mg–Ni–Co–Cr, reflecting the geochemical signature of basaltic to andesitic volcanic rocks; (ii) a hydrothermal component characterized by Ag–As–Sb–S–Au associations spatially linked to structurally controlled zones; and (iii) an oxidative–supergene component marked by Fe–V–Zn redistribution along drainage convergence areas. These domains are defined strictly on geochemical criteria and represent geochemical process domains rather than proven metallogenic provinces. Rare earth element (REE) systematics further constrain the geotectonic setting and indicate that the primary geochemical patterns are largely controlled by lithological and magmatic differentiation processes. Spatial integration of geochemical patterns with fault architecture highlights the importance of NW–SE and NE–SW structural corridors in focusing hydrothermal fluid circulation and associated metal dispersion. The identified Ag–As–Sb–Au associations are interpreted as epithermal-style hydrothermal geochemical enrichment and exploration-relevant geochemical footprints, rather than as evidence of confirmed or economic mineralization. Overall, Ataúro Island emerges as a compact natural analogue of post-arc geochemical system evolution in the eastern Banda Arc, where lithogenic background, hydrothermal fluid–rock interaction, and early supergene processes are superimposed. The integrated geochemical framework presented here provides a robust baseline for future targeted investigations aimed at distinguishing lithogenic from hydrothermal contributions and evaluating the potential significance of the identified geochemical enrichments. Full article

Accurate global mapping of lunar iron oxide (FeO) abundance is essential for understanding the Moon’s geological evolution and for supporting future in situ resource utilization (ISRU). While hyperspectral data from the Moon Mineralogy Mapper (M3) provide a unique combination of high spectral dimensionality, hectometre-scale spatial resolution, and near-global coverage, existing FeO retrieval approaches struggle to fully exploit the high dimensionality, nonlinear spectral variability, and planetary-scale volume of the Global Mode dataset. To address these limitations, we present an integrated machine learning pipeline for estimating lunar FeO abundance from M3 hyperspectral observations. Unlike traditional methods based on raw reflectance or empirical spectral indices, the proposed framework combines Discrete Wavelet Transform (DWT), deep autoencoder-based feature compression, and ensemble regression to achieve robust and scalable FeO prediction. M3 spectra (83 bands, 475–3000 nm) are transformed using a Daubechies-4 (db4) DWT to extract 42 representative coefficients per pixel, capturing the dominant spectral information while filtering high-frequency noise. These features are further compressed into a six-dimensional latent space via a deep autoencoder and used as input to a Random Forest regressor, which outperforms kernel-based and linear Support Vector Regression (SVR) as well as Lasso regression in predictive accuracy and stability. The proposed model achieves an average prediction error of 1.204 wt.% FeO and demonstrates consistent performance across diverse lunar geological units. Applied to 806 orbital tracks (approximately $3.5\times {10}^9$ pixels), covering more than 95% of the lunar surface, the pipeline produces a global FeO abundance map at 150 m per pixel resolution. These results demonstrate the potential of integrating multiscale wavelet representations with nonlinear feature learning to enable large-scale, geochemically constrained planetary mineral mapping. Full article

Groundwater–surface water interactions were investigated in the Highwood River (3952 km²) and Sheep River watersheds (1568 km²), originating in the Rocky Mountains headwaters of the South Saskatchewan River (Alberta, Canada), to improve understanding of hydrological processes that potentially influence water use and vulnerability to climatic change in representative, alpine-fed mixed-use watersheds. Similar to adjacent regions of the Bow, Red Deer and Oldman watersheds, the upper reaches of these watersheds are sparsely populated with significant seasonal glacier and snowmelt influence, while the lower watersheds are currently under increasing water supply pressure from competing agricultural–municipal interests, with notable risk of flooding during high-flow events and drought during the growing season. Investigations included mapping of hydrologic and hydrogeologic controls (aquifers, buried channels, colluvial deposits, etc.,) and synoptic geochemical and isotopic surveys (δ²H, δ¹⁸O, δ¹³C-DIC, ²²²Rn) to characterize evolution in water type and seasonal progression in streamflow sources and underlying mechanisms. Our findings confirm seasonal progression in streamflow water sources, characterized by a pronounced snowmelt-dominated spring freshet, but with a sustained recession fed by colluvial, moraine, fluvial, and fractured bedrock sources. Seasonal isotopic variations establish that shallow groundwater sources are actively maintained throughout the spring freshet, often accounting for a dominant portion of streamflow, which indicates active displacement of groundwater storage by snowmelt recharge during spring melt. The contrast in the proportion of alpine contributions in each watershed suggests these systems may respond very differently to climate change, which needs to be carefully considered in developing sustainable water-use strategies for each watershed. Full article

Machine learning (ML) algorithms are widely applied across various fields due to their ability to extract high-level features from large training datasets. However, their use in geochemical prospecting and mineral exploration remains limited because mineralization—a rare geological event—often results in insufficient training samples for supervised ML. Generating adequate training data is thus essential for applying supervised ML in this domain. In this study, we augmented training samples by utilizing adjacent samples centered around known mineral deposits and then employed random forest (RF) modeling to identify multivariate geochemical anomalies associated with mineralization. To evaluate the robustness of data augmentation and gain insights into the geochemical survey data, we applied interpretable ML techniques—feature importance and partial dependence plots (PDPs)—to clarify the data processing within mineral prospectivity mapping. The proposed methodology was tested in the Pangxidong Area, South China. The identified geochemical anomalies show strong spatial correlation with known mineral deposits, while feature importance rankings and PDPs validate the effectiveness of the proposed methodology. This practice enhances the applicability of supervised ML in geochemical prospecting and mineral exploration as well as the application of interpretable techniques for understanding data processing of multi-geoinformation. Full article

Sulfides are essential tracers for understanding the redox conditions, diffusion processes, and thermal mechanisms involved in the formation of ordinary chondrites. Their mineralogical and textural evolution provides valuable constraints on the metamorphic history of parent bodies. In this context, the Ksar El Goraane meteorite, which fell in Morocco in 2018 and is classified as an H5 ordinary chondrite, represents a particularly instructive case for investigating sulfur behavior during thermal metamorphism. Petrographic observations combined with geochemical data obtained by electron probe microanalysis (EPMA) and energy-dispersive X-ray spectroscopy (EDS) were used to characterize the main silicate and sulfide phases and to evaluate their degree of chemical equilibration. The compositions of olivine (Fa_18–20), Mg-Rich orthopyroxene, and sodic plagioclase (An_10–15) display limited analytical dispersion and well-recrystallized textures, confirming that Ksar El Goraane experienced an equilibrated metamorphic grade consistent with an H5 ordinary chondrite. The sulfide assemblage is dominated by troilite (FeS), iron-rich pyrrhotite (Fe_1−xS), and pentlandite ((Fe,Ni)₉S₈), with minor occurrences of pyrite (FeS₂). Textural relationships and chemical homogeneity observed in backscattered electron images and elemental maps indicate progressive re-equilibration during thermal metamorphism. Formation and transformation temperatures of the sulfide phases are inferred through comparison with experimental and empirical constraints reported in the literature. These results suggest early high-temperature crystallization of troilite, followed by sulfur depletion leading to pyrrhotite formation, subsequent low-temperature exsolution of pentlandite, and localized late-stage pyrite crystallization. Full article

This study investigates the coupled relationship between groundwater chemistry, lithology, and structural features in the dry zone of Netiyagama, Sri Lanka, within a fractured crystalline basement. Groundwater chemistry fundamentally reflects geological conditions determined by rock-water interactions, we hypothesized that the specific spatial patterns of groundwater chemistry in heterogeneous fractured systems are distinctly controlled by integrated effects of lithological variations, structurally driven flow pathways, aquifer stratification, and geochemical processes, including cation exchange and mineral-specific weathering. To test this, we integrated hydrogeochemical signatures with mapped hydrogeological data and applied multi-stage multivariate analyses, including Piper diagrams, Hierarchical Cluster Analysis (HCA), and Principal Component Analysis (PCA), and various bivariate plots. Piper diagrams identified five distinct hydrochemical facies, but these did not correlate directly with specific rock types, highlighting the limitations of traditional methods in heterogeneous settings. Employing a multi-stage multivariate analysis, we identified seven clusters (C1–C7) that exhibited unique spatial distributions across different rock types and provided a more refined classification of groundwater chemistries. These clusters align with a three-unit aquifer framework (shallow weathered zone, intermittent fracture zone at ~80–100 m MSL, and deeper persistent fractures) controlled by a regional syncline and lineaments. Further analysis through bivariate diagrams revealed insights into dominant weathering processes, cation-exchange mechanisms, and groundwater residence times across the identified clusters. Recharge-type clusters (C1, C2, C5) reflect plagioclase-dominated weathering and short flow paths; transitional clusters (C3, C7) show mixed sources and increasing exchange; evolved clusters (C4, C6) exhibit higher mineralization and longer residence. Overall, the integrated workflow (facies plots + PCA/HCA + bivariate/process diagrams) constrains aquifer dynamics, recharge pathways, and flow-path evolution without additional drilling, and provides practical guidance for well siting and treatment. Full article

This study conducts a comprehensive bibliometric analysis of literature from 2000 to 2025, aiming to map the intellectual landscape and evolving trends in research on heavy metal transport within watershed ecosystems. By leveraging the Citespace literature visualization tool, we analyzed publication trends, intellectual bases, and, most importantly, the dynamic shifts in research fronts through keyword co-occurrence and clustering analysis. The findings reveal a clear trajectory from basic geochemical theories to specific applications, characterized by three prominent themes: (1) the evolution of pollution source tracking from single-method tracing to coupled multi-method quantitative modeling; (2) the establishment of a comprehensive risk evaluation chain spanning regional assessments to targeted analyses of sensitive receptors; and (3) the analysis indicates that the current research on heavy metal transport in watershed environments remains somewhat fragmented, with limited cross-comparative synthesis across different metal species and watershed contexts, and uneven progress in applying advanced data-driven and multi-model approaches. Addressing these issues is crucial for enhancing the predictive power of models and formulating effective strategies. This study thus provides a detailed overview of the field’s development while highlighting critical pathways for future research to strengthen the scientific foundation for preventing and controlling heavy metal pollution in watershed ecosystems. Full article

The Hadamengou gold deposit, located on the northern margin of the North China Craton, represents one of the region‘s most significant gold mineralization clusters. However, exploration in its deeper and peripheral sectors is constrained by ecological protection policies and the structural complexity of the ore-forming systems. Multivariate analysis combined with multi-model integration provides an effective mathematical approach for interpretating geochemical datasets and guiding mineral exploration, yet, its application in the Hadamengou region has not been systematically investigated. To address this research gap, this study developed a pilot framework in the key Buerhantu area, on the periphery of the Hadamengou metallogenic cluster, applying and adapting a multivariate-multimodel methodology for mineral prediction. The goal is to improve exploration targeting, particularly for concealed and deep-seated mineralization, while addressing the methodological challenges of mathematical modeling in complex geological conditions. Using 1:10,000-scale lithogeochemical data, we implemented a three-step workflow. First, isometric log-ratio (ILR) and centered log-ratio (CLR) transformations were compared to optimize data preprocessing, with a reference column (YD) added to overcome ILR constraints. Second, principal component analysis (PCA) identified a metallogenic element association (Sb-As-Sn-Au-Ag-Cu-Pb-Mo-W-Bi) consistent with district-scale mineralization patterns. Third, S-A multifractal modeling of factor scores (F1–F4) effectively separated noise, background, and anomalies, producing refined geochemical maps. Compared with conventional inverse distance weighting (IDW), the S-A model enhanced anomaly delineation and exploration targeting. Five anomalous zones (AP01–AP05) were identified. Drilling at AP01 confirmed the presence of deep gold mineralization, and the remaining anomalies are recommended for surface verification. This study demonstrates the utility of S-A multifractal modeling for geochemical anomaly detection and its effectiveness in defining exploration targets and improving exploration efficiency in underexplored areas of the Hadamengou district. Full article

The Yixingzhai deposit is a giant gold system containing four cryptovolcanic breccia pipes, several of which host significant porphyry-type gold orebodies at depth. A key exploration target is the Tietangdong cryptovolcanic breccia pipe, characterized by skarn alteration in its upper zones. However, the evolution of early hydrothermal fluids and their implications for gold enrichment potential remain poorly understood. This study employs an integrated approach—combining petrography, electron probe microanalysis, laser ablation-inductively coupled plasma–mass spectrometry (LA-ICP-MS), and LA-ICP-MS elemental mapping—to analyze zoned garnets within the Tietangdong skarn, with the aim of deciphering changes in magmatic–hydrothermal composition and physicochemical conditions, as well as their influence on gold enrichment. Textural and compositional data reveal three distinct generations of garnets. Garnets from generations I and III consist of a grossular–andradite solid solution and commonly exhibits optical anisotropy. In contrast, generation II garnet is predominantly andraditic and optically homogeneous. LA-ICP-MS elemental mapping of generations I and III indicates that both generations contain significant Al and Fe, with their optical anisotropy attributed to a high degree of Fe³⁺/Al³⁺ cationic ordering. Compared to generations I and III, generation II garnet displays distinct geochemical characteristics, including enrichment in Fe, As, Sn, W, and U, patterns enriched in light rare earth elements, a positive Eu anomaly, and a wide range of Y/Ho ratios. Garnets from generations I and III crystallized under relatively high-pressure, high-temperature, and low-oxygen fugacity conditions, whereas generation II garnets formed under lower pressure–temperature conditions and higher oxygen fugacity. Moreover, concentrations of Co, Ni, and Cu increase systematically from generation I to generation III. We interpret the sharp compositional break at generation II as recording of the pulsed injection of magmatic–hydrothermal fluids, which enhanced the potential for gold mineralization. The zoning patterns in garnet provide a robust record of the temporal evolution of physicochemical conditions and fluid composition in the hydrothermal system. Full article

The traditional methods for classifying elemental concentrations such as the cumulative frequency method, the logarithmic interval method, and the mean–standard deviation method all have the limitation of depending on a specific dataset. An objective “ruler” that can measure the elemental concentration level regardless of the amount of data (even for a single sample) and enables comparisons among different elements and regions is highly necessary. Recently, the 19-level fixed-value method was proposed as a “ruler” to measure the elemental concentrations of Sn, Li, Mo, and Ni objectively and to facilitate comparisons across elements and regions. However, the method for Au has not been proposed until now. In this paper, we propose the “ruler” for Au, which objectively divides Au concentrations into 19 levels with 18 fixed values from the detection limit to the cut-off grade with easily understood numbers. The “ruler” for Au along with those for Mo and Sn was applied to geochemical survey data at 1:200,000 and 1:50,000 scales, respectively, in the Zhongchuan area of Western Qinling, China, to classify elemental concentrations and draw geochemical maps. The results show that elemental concentrations can be measured using the “ruler” to assess the background, anomaly, and mineralization levels objectively, and the levels can be compared across different elements, regions, and even different scales. Geochemical maps show that in the study area, known gold deposits are all associated with high anomalies or mineralization levels of Au, while the Mo and Sn concentrations are predominantly at background levels. These results are consistent with the known mineral resources in this area. When superimposing geochemical maps of larger scales onto those of smaller scales, the variation in the elemental concentration levels with different survey scales indicates valuable geochemical meanings for mineral exploration. Full article

Focusing on the West African Craton (WAC) as a test bed, this protocol-oriented scoping review synthesizes indicators for orogenic gold and translates them into an auditable, map-first checklist that separates Fertility and Preservation, while deliberately deferring any performance estimation to a blinded, out-of-sample evaluation. There is a need for a transparent, auditable, and field-ready framework that integrates geological, structural, geophysical, and geochemical evidence. We (i) synthesize the state of knowledge into a map-first, reproducible targeting checklist, (ii) formalize an indicator decision matrix that separates Fertility from Preservation factors, and (iii) specify a deferred, out-of-sample evaluation protocol to quantify performance. We conduct a Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR)-style scoping review (2010–2025) and codify commonly used indicators (e.g., transpressional jogs, lineament density, proximity to tonalite-trondhjemite-granodiorite (TTG)/tonalite contacts, Sr/Y proxies). Indicators are operationalized as auditable pass/fail rules and assembled into a decision matrix with explicit uncertainty handling and risk logging. We further define a deferred evaluation protocol using classification and ranking metrics (receiver operating characteristic (ROC) and precision–recall (PR) curves, odds ratios), ablation/sensitivity tests, and district-level threshold calibration. We deliver (1) a unified, auditable checklist with default (tunable) thresholds; (2) an indicator decision matrix that disentangles Fertility vs. Preservation signals; and (3) a deferred evaluation protocol enabling a reproducible, out-of-sample assessment without inflating apparent performance. All numerical thresholds reported here are explicit placeholders that facilitate transparency and auditability; they are not optimized. A properly blocked train/validation/test scheme, operating-point selection criteria, null models, and uncertainty procedures are prespecified for future evaluation. By publishing the checklist, data lineage, and audit-log schema now—without performance claims—we enable reproducible adoption and stress-test the framework ahead of calibration. Full article