Journal of Geochemical Exploration最新文献

Syenites are highly valued for economic and strategic exploration programs worldwide, along with associated rocks (e.g., carbonatites), as a primary source for several industrial minerals and strategic elements, such as phosphate, potash, rare earth elements (REE), and Nb. Rapid identification and mapping of syenite outcrops and their major geochemical signatures (i.e. potassic and sodic) over vast areas are crucial for exploration programs aimed at identifying new economic deposits. For this, remote sensing provides an interesting way to delineate these alkaline igneous rocks and predicts their mineralogical and geochemical characteristics. In the literature, few remote sensing studies have been devoted to syenite outcrops, and an effective predictive tool for their mapping and mineralogical-geochemical classification remains to be done. Accordingly, we explore in the present study the potential of using ASTER thermal emissivity data for prospectivity mapping and predicting the main alkaline mineralogical and geochemical affinities of syenite rocks. This approach was applied to the Moroccan High-Atlas Mountains (area ∼ 42,000 km²), known for the presence of several alkaline intrusions hosting different alkali-syenites. Hence, a spectral syenite index [SyI = (B10/B11 * B10/B13 * B14/B13)] without the use of in-situ field data, was suggested in the first stage to quickly highlight potential areas, reducing the initial exploration zone to only ∼1000 km²/42000 km² that include all well-known syenites in the studied area. Subsequently, several in-situ field missions were conducted in the identified zones to sample and obtain precise GPS points of well-exposed syenitic outcrops. For discrimination of mineralogical and geochemical endmembers (Na vs. K) of syenites, two new spectral indices were proposed [SpI-A = (B14-B12)/(B14 + B12) for K syenite signature and SpI-B = (B10-B11)/(B10 + B11) for Na syenite signature]. These indices highlight the two major geochemical affinities in the High-Atlas Mountains: the potassic syenite character (K-feldspar- and nepheline-rich) in the Midelt-Tamazeght Cenozoic complex and the sodic syenite character (albite-rich) in the Imilchil Mesozoic massifs. The results have significant implications for early exploration programs, aiming to cost-effectively discover favorable areas of alkali syenites, potassic against sodic affinities, and optimize fieldwork as well as preliminarily mineralogical and geochemical characterization.

In areas of contrasting geology, local but significant spatial changes in environmental conditions can occur suddenly and unexpectedly within aquifers, hampering accurate assessment of groundwater chemistry. Recently, the rare earth elements (REEs) have become extensively used in identifying geochemical processes in aqueous systems, due to their unique sensitivity to environmental changes. In this study, the REEs and Y (yttrium), combined with the chemical parameters of the main, minor and trace water components, and with the isotopic signatures of δ¹⁸O-H₂O, δ²H-H₂O, ³H-H₂O, δ³⁴S-SO₄, δ¹⁸O-SO₄, were investigated in order to gain a better understanding of the geochemistry of the groundwaters in the Holy Cross Mountains, which possesses a diverse hydrogeological system. The waters studied are ‘young’, meteoric-derived, of acidic to slightly alkaline pH (4.95–7.75) and TDS values of 38.97–2713.91 mg/L. They represent predominantly the HCO₃-Ca-Mg and less often the HCO₃-Ca-SO₄-(Mg) or SO₄-Ca-(Mg) types. The dissolved (<0.45 μm) concentrations of the REEs (5.55 to 13,857.35 ng/L) and Y (4.43 to 2450.22 ng/L) in the waters studied are the result of host rock dissolution, and tend to increase significantly, by up to several orders of magnitude, via interactions between the rocks and acidic waters. Speciation calculation reveals that dissolved REE + Y in neutral and alkaline waters are transported mainly as bicarbonate (CO₃)₂⁻ and carbonate CO₃⁺ complexes, while in a more acidic environment these elements occur preferably as free ions (REE³⁺+Y³⁺), and their abundance gradually increases along with decreasing pH value. The EUS (European Shale) normalized REE patterns of the waters studied show two distinct dominant types: (i) upwards-sloping with HREE-enrichment (LREEs<MREEs<HREEs), (ii) convex with MREE-enrichment (LREEs<MREEs>HREEs). The first pattern type reflects REE fractionation in alkaline and oxygenated waters, leading to preferential LREE adsorption onto mineral particles, accompanied by complexation of HREEs with carbonate and bicarbonate ions, while the second pattern type results from dissolution of the host rocks in more acidic conditions. The REE patterns in the waters studied are mostly different from the REE patterns characteristic of the host rocks, except for some water samples from carbonate aquifers. Ce and Eu anomalies were recorded in the waters studied. Some of the negative Ce and positive Eu anomalies were inherited from host rock dissolution, while other negative or positive Ce anomalies reflect oxygenic or more reducing conditions, respectively.

Dietary deficiency of selenium (Se) is a global health threat related to low Se concentrations in crops. Southern China has abundant Se-rich land resources, but the cadmium (Cd) pollution problem is prominent, which may lead to Cd exceeding the safety standard in Se-rich crops. Therefore, it is important to delineate Se-rich land without Cd pollution in order to develop green Se-rich agriculture. Based on soil/sediment geochemical survey data covering 2.3 million km² of southern China, this study analysed the concentration and spatial distribution of Se and Cd, discussed their enrichment mechanisms and proposed suggestions for the safe use of Se-rich land. The results showed that the soil/sediments in southern China were significantly enriched in Se and Cd, and the median values were 0.31 mg·kg⁻¹ and 221 μg·kg⁻¹, which were 1.8 times and 2.5 times the national soil background values, respectively. In addition, a significant positive correlation was observed between Se and Cd, indicating that Cd contamination in Se-rich soils frequently exceeded the pollution limit. According to statistics, Se-rich land accounted for 32.13 % of southern China. However, due to the co-enrichment of Se and Cd, areas without Cd pollution accounted for only one-third of the total Se-rich area. In particular, the areas with co-enrichment of SeCd are primarily distributed in Yunnan, Guizhou, Guangxi, western Hubei, northwestern Zhejiang, western Hunan, southern Hunan and northern Guangdong. The enrichment of Se is predominantly associated with parent rocks (black and carbonate rocks). At the same time, the enrichment of Cd is influenced by the parent rocks and PbZn mineralisation and mining activities. Three recommendations for managing Se-rich land were proposed: imposing restrictions on the utilisation of heavily contaminated Se-rich land for agricultural production, adopting a rational approach towards utilising lightly polluted Se-rich land and actively promoting the development of Se-rich agriculture in uncontaminated Se-rich areas. In the future, it is necessary to develop technologies that simultaneously enhance Se absorption while inhibiting Cd absorption in order to safely exploit Se-rich lands affected by Cd pollution.

Lithium (Li), as an essential element of green new energy technology, is a global strategic resource. Sedimentary Li is primarily associated with bauxite, with a local grade of >1000 ppm, and has a huge utilization prospect. However, fine particles limit the study of the occurrence of Li. The Danping bauxite deposit, located in northern Guizhou, China, which accompanying considerable Li resources. In this study, in situ elemental concentration analyses were conducted by laser ablation-inductively coupled plasma-mass spectrometry. The analysis results show that Li is mainly enriched at the bottom and top of the aluminiferous rock series, and the Li content at the top is higher (615.98–3289.98 ppm). Li content is positively correlated with Mg and Fe content, indicating that chlorite is a potential Li-bearing mineral. K content of <10,000 ppm, K content is positively correlated with Li content, indicating that illite may also be a Li-bearing mineral. Kaolinite, transformed from montmorillonite, may also have a high Li content. Ga content is always positively correlated with Al content, indicating that Ga mainly occurs in diaspores. Bauxite has similar Nb/Ta and Zr/Hf ratios to the underlying Hanjiadian Formation shale, as well as the same positive Ce anomalies (negative anomalies in Huanglong Formation), indicating that the ore-forming material of Danping is primarily derived from the underlying Hanjiadian Formation.

The Yaojialing Zn-Au‑Cu deposit is a porphyry-skarn-epithermal vein-type compound deposit that consists of epithermal vein-type lead‑zinc‑silver orebodies, skarn Zn-Cu-Au orebodies, and porphyry CuAu orebodies from shallow level to depth. We decipher the source and metallogenic mechanism by studying the trace element and S isotopic compositions of sulfides (pyrite, sphalerite, chalcopyrite, and galena) from three types of orebodies. The collected pyrite can be divided into two types. PyI coexists with chalcopyrite, and PyII coexists with sphalerite or galena. In addition, PyI was further divided into PyIa (collected from porphyry copper bodies) and PyIb (collected from skarn copper bodies). PyII can be further divided into PyIIa (collected from skarn-type lead‑zinc ore body) and PyIIb (collected from vein lead‑zinc ore body in strata). Sphalerite and galena from skarn-type PbZn ore bodies and shallow vein-type PbZn ore bodies are named SpI and GnI, and SpII and GnII, respectively.

Pyrite and sphalerite trace element thermometers revealed that the temperature of the ore-forming fluids decreased from 500 to 600 °C in the porphyry ore body to 300– 360 °C in the skarn ore body and then to 240– 280 °C in the shallow vein ore body. The decrease in the Co and Ni contents of pyrite collected from deep to shallow depths may indicate that meteoric water precipitated in the late ore-forming hydrothermal system. Rapid crystallization and variations in the physicochemical states (such as temperature, pH, fO₂, and geochemical composition) of the fluids resulted in an obvious oscillating zone of euhedral PyI pyrite particles. It also affects the solubility of trace metal elements and leads to the selective entry of these elements into pyrite. PyII also shows obvious zonation characteristics rather than oscillating zonation, indicating that the growth rate of pyrite is relatively slow. Moreover, the relationships between the Au and As contents in the two types of pyrite are different. PyI is coupled, while PyII shows decoupling. We believe that this phenomenon is due to the high content of As in ore-forming fluid systems, which may inhibit the absorption of Au on the surface of pyrite rather than the decoupling of Au and As caused by rapid crystallization, based on the rapid increase in As content and non-oscillating zonation in PyII. According to the analysis of the sulfur isotopes of various sulfides, the solid evidences suggest that the ore-forming materials of each type of orebody in the Yaojialing deposit were mainly derived from magmatic-hydrothermal processes and that the fractionation of sulfur isotopes was the result of variations in physicochemical conditions caused by magma-hydrothermal evolution rather than the addition of foreign sulfur sources.

The physics-driven dynamics simulation (DS) and data-driven machine learning (ML) are two general approaches to predict complex systems whose complexity is a hardship impediment to prediction. Based on the 3D geological modeling (GD), we embedded the DS into ML to predict high potential targets and to evaluate ore-controlling and ore-indicating factors in the Tongguangshan (TGS) skarn orefield that has undergone intensive exploration and 4 Cu and Au deposits discovered. The 3D geological models show that the heterogeneous distribution of orebodies around intrusions is associated with the wall rock lithology and contact zone (CZ) characteristics of intrusions, and the resistivity can only provide some ambiguous clues for interpretation of underground geological architectures rather than a direct ore-indicator. The DS results show heterogeneous distribution of temperature, pore pressure, differential stress, volume strain and shear strain, among which the volume strain is closest associated with ore formation. Based on the prediction of Random Forest (FR) model of which the feature variables are combination of DS and 3D modeling results, the SHAP valuing results show a descending importance rank of ore-controlling factors and ore-indicators as lithology, volume strain, distance to CZ, distance to Devonian-Carboniferous interface, curvature of CZ, pressure, temperature, CZ azimuth, resistivity, differential stress, shear strain and CZ dip. The DS results are more important than the resistivity. We have run 6 RF models, consisting of different feature variables which were assigned by DS and 3D modeling, to predict ore-formation favor spaces. The prediction performances on test data sets suggest that, integrating of geological features with dynamics features can enhance performance of RF prediction, the RF model consisting of pure dynamics features can predict mineralization different from the training samples. All RF models' predictions support that there are no significant high potentials at the depth of the orefield, except one small target at its eastern south corner.

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.

Pegmatites occur widely in the Ke'eryin rare metal orefield. The genesis and evolution of the Ke'eryin pegmatites are still in dispute, and morphological and geochemical studies on tourmalines from the Ke'eryin pegmatites are limited. In this study, in-situ analyses of major and trace elements and B isotope were conducted to uncover the origin of tourmaline and the evolution of related pegmatites. Three types of tourmaline from the Ke'eryin barren pegmatite were identified: elongated columnar or needle-columnar tourmaline (Tur-1 type), isolated, disseminated, irregular, and massive tourmaline (Tur-2 type), and long columnar tourmaline (Tur-3 type). Petrographically, the Tur-1 type crystallized at the early stage of pegmatitic crystallization sequence, the Tur-2 type possibly formed at the early- and/or syn-pegmatitic crystallization sequence, whereas the Tur-3 type likely formed at the relatively late crystallization sequence. Compositionally, most tourmalines belong to the alkali group with a few falling in the vacancy group. All the tourmalines show a schorl composition and are of magmatic origin. Chemical variations from the Tur-1 to Tur-3 tourmalines are controlled by magma fractionation and melt compositions rather than crystal chemical effects. Most tourmalines follow the (Na, Mg)(X_vac, Al)₋₁, (Mg, OH)(Al, O)₋₁, and (Ca, Mg₂)(X_vac, Al₂)₋₁ exchange vectors. The higher contents of Zn, Sn, Li, Be, Nb, and Ta and negative Eu anomalies in the Tur-3 type indicate that it was likely crystallized at a more evolved stage. In combination with textural evidence and tourmaline chemistry, we suggest that the Tur-1 and Tur-2 types were formed at the relatively earlier stage of pegmatite-forming magma and the Tur-3 type was likely formed closer to the end-stage of barren pegmatite crystallization. The B isotopic compositions are relatively homogeneous and display slightly higher in the Tur-3 type, which were likely caused by fractional crystallization during B-rich magma evolution. It can be inferred that the tourmaline in more evolved and/or Li-mineralized pegmatite with magma evolution should have higher Li, Be, Nb, Ta, and Sn contents, implying that tourmaline chemistry may be used as a potential exploration indicator for rare metal mineralization.

Pyrite geochemistry has been extensively used to reveal ore-forming processes in diverse ore deposits, but its application in skarn systems is not well understood. The Huangshaping deposit in the Nanling Range (South China) uniquely develops W–Sn–Pb–Zn and Cu–Pb–Zn skarn mineralization systems, and both two systems have formed multi-types of pyrite, which provides a good window to reveal the mineralization histories of different skarn systems using pyrite trace element geochemistry. In the Cu–Pb–Zn system, texturally homogeneous Py1 mainly occurs in calcite veins within the host rock, whereas texturally homogeneous Py2 in the calcite-sulfide stage mainly occurs in skarn orebodies. Py3 in the siderite-sulfide stage replaces Py2 and commonly develops abundant pores or fractures, resembling the “bird's eye” texture. In the W–Sn–Pb–Zn system, Py4 in calcite veins can be divided into the oscillatory-zoned Py4a and irregular Py4b under BSE, and Py4b commonly replaces Py4a as veins or overgrowth. Texturally homogeneous Py5 in the calcite-sulfide stage occurs in skarn orebodies and is replaced by Py6 with a “bird's eye” texture in the siderite-sulfide stage.

In the Cu–Pb–Zn system, Py1 may have formed by fluid cooling during its ascent along the hydraulic fractures indicated by its enrichment of Co, Ni, As, Sb, and Tl, whereas Py2 is likely formed under higher temperature and pH conditions caused by intense fluid-rock interactions evidenced by its depletion of Co, Ni, As, Sb, and Tl as well as its enrichment of Zn and Ag. In the W–Sn–Pb–Zn system, Py4b has higher contents of Co, Ni, As, Sb, and Tl than Py4a and similar contents of Ag, Zn, and Mo with Py4a, suggesting that decreasing temperature may have controlled the formation of Py4b. Py5 is featured by the depletion of As, Sb, Tl, and Mo as well as the enrichment of Zn and Ag, indicating that Py5 is likely formed under higher temperature and pH conditions resulting from the intense fluid-rock interactions. Marcasite replaces pyrrhotite and then is replaced by pyrite may be an important precipitation mechanism for pyrite with a “bird's eye” texture (Py3 and Py6) in both two skarn systems at Huangshaping. This study demonstrates that fluid-rock interaction is an important mechanism for sulfide precipitation at Huangshaping, which shows that pyrite geochemistry has good potential to reveal mineralization histories in skarn systems.

Previous studies on the mineralogical differentiation of Pleistocene loess/palaeosol sections focused on the description and source material of four loess/palaeosol sections located on the eastern border of Croatia along the Danube: Zmajevac, Zmajevac I, Erdut and Šarengrad. The authors demonstrated the decreasing influence of the Danube and the increasing influence of the rivers draining the Central Bosnian Mountains of the Dinaric Ophiolite Zone both important source areas for aeolian sediments at the southern edge of the Carpathian Basin that transport material from the Central Bosnian Mountains. The aim of this research is to identify the palaeoclimatic factors that influenced the pedogenetic development of the studied palaeosols. The model was created based on the research results of the same four loess/palaeosol sequences in Eastern Croatia. This model can also be applied in other locations to determine the influence of certain climatic factors on the degree of pedogenetic development of individual palaeosols. The loess/palaeosol sequences were divided into eight comprehensive groups (horizons) based on their genesis, degree of pedological development and/or position in the soil profiles. The explanation of the typical patterns occurring between the studied horizons is based on the construction of a Discriminant Function Model (DFM) resulting from the analysis of the compositional data (CoDa) of the geochemical (major and trace elements) and granulometric (grain size) data of the loess/palaeosols in combination with external variables such as weathering coefficients and chemical soil properties. In the final phase, the DFM was transformed from structural (mathematical) to functional (process) terms. This revealed that three main themes dominate the formation of Pleistocene loess/palaeosol sequences: 1) the separation of well-developed palaeosols from parent material; 2) the separation of automorphic palaeosols from hydromorphic soils exposed to post-pedogenic waterlogging conditions; and 3) the differentiation of horizons (soils and alluvium) formed by the redeposition (by water or mudflows) of previously deposited aeolian material, regardless of whether and to what extent it was exposed to post-sedimentary pedogenesis.