Applied Geochemistry最新文献

We carried out density functional computations to investigate experimentally suggested ternary Ca–Am(III)–OH and possible Mg–Am(III)–OH complexes in water. We confirmed the experimental stoichiometry for the Ca complexes and their relative stability. For the Mg complexes, we find comparable or weaker complexation. This finding is in agreement with experimental observations. We demonstrate that explicit solvation of counterions is important when comparing Ca and Mg species. For the Ca complexes this has a minimal effect on their relative stability. Contrariwise, Mg complexes exhibit a lower stability and are highly sensitive to explicit short-range solvation effects. Explicit Mg²⁺ solvation significantly altered both absolute and relative formation energies compared to a simpler model. These findings highlight the crucial role of incorporating explicit short-range solvation effects in accurate computational modeling when small and highly charged ions are treated.

Rice and wheat, being major food crops worldwide, are susceptible to pollution risks associated with potentially toxic elements (PTEs). However, the accumulation and transfer patterns of different PTEs within rice and wheat systems remain a topic of debate. In this study, we conducted a holistic investigation of the risk flow of seven PTEs (As, Cd, Cr, Cu, Ni, Pb, and Zn) in the soil-root-straw-grain continuum of a typical rice-wheat rotation system. Laboratory analyses were performed on a total of 72 samples, comprising complete rice and wheat plants as well as paired soil samples. These samples were collected from nine cropland sites located in the Yangtze River Delta (YRD), a highly industrialized region in China. Our results revealed that Cd and Pb levels in the soils exceeded acceptable limits. Additionally, Cd, Cr, Ni, Pb, and Zn levels in wheat grains, as well as Cd in rice grains, exceeded food safety standards. Based on their behaviors within the soil-root-straw-grain continuum of rice and wheat, the seven PTEs can be classified into three categories: (1) The siderophile elements, Cr and Ni, exhibited higher concentrations in wheat roots, straws, and grains than in rice. (2) The chalcophile elements, Cd, Cu, Zn, and Pb, showed higher contents in rice roots and straws but lower contents in rice grains than in wheat. (3) The metalloid element, As, exhibited significantly higher concentrations and uptake capacity in rice than in wheat. Our findings suggest that wheat has a greater internal translocation capacity for PTEs than rice, leading to higher contamination levels and lower risk resistances for wheat crops. This study provides insights into agronomic regulations of different PTEs in rice and wheat cultivation areas.

The mineralogy, bulk geochemical composition, chemistry and U–Pb ages of detrital zircons in sediments from the La Pesca (LP) and Tesoro Altamira (TA) beaches, NW Gulf of Mexico are analyzed. The aim of this study is to infer the weathering history and provenance of sediments, and to identify the potential source terranes that are contributing sediments to the LP and TA beach areas. The beach sediments are rich in quartz and aluminosilicates. The Chemical Index of Weathering (CIW') and trace elements such as Th, Sr, U, and Ba reveal high weathering intensity for the LP and TA beach sediments. Major-element based diagrams and trace elemental ratios based on Co, Cr, Sc, La, and Th contents in sediments indicate felsic provenance, which is further supported by a negative europium anomaly and rare earth element (REE) patterns. The Th/U ratios (>0.3) together with positive cerium and negative europium anomalies of zircons in the LP and TA beaches indicate igneous origin. The comparison of zircon U–Pb ages of this study with ages reported from the adjacent terranes revealed that the Proterozoic (Paleoproterozoic: 1607.07–1943.45 Ma and Mesoproterozoic: 1021.19–1586.52 Ma) zircons are derived from the Oaxaquia, Mesa Central, Sierra Madre Oriental Provinces of Mexico and Mazatzal–Yavapai Province of the USA. On the other hand, Mesozoic (Jurassic 146.49–199.43 Ma and Cretaceous 68.46–136.82 Ma) and Cenozoic (Eocene 33.97–51.46 Ma and Oligocene 23.39–33.86 Ma) zircons are contributed by the Mexican volcanic rocks, Mesa Central and Sierra Madre Oriental Provinces in Mexico, and Mogollon-Datil Volcanic field and Colorado Plateau in USA. The rivers and their tributaries draining from the source areas are considered as a carrier and agent of distributing sediments along the northwestern Gulf of Mexico coastal areas, which are subsequently mixed by littoral currents.

Rare earth elements (REEs), a significant subset of critical minerals, play an indispensable role in modern society and are regarded as “industrial vitamins,” making them crucial for global sustainability. Geochemical survey data proves highly effective in delineating metallic mineral prospects. Separating geochemical anomalies associated with specific types of mineralization from the background reflecting geological processes has long been a significant subject in exploration geochemistry. The processing of high-dimensional, non-linear geochemical survey data necessitates a systematic framework to address common issues, including missing values, the closure effect, the selection of appropriate multivariate analysis methods, and anomaly detection techniques in order to detect geochemical anomalies associated with mineral occurrences. The Curnamona Province in South Australia is considered an emerging REE province with significant REE mineralization potential. In this study, we use data from this region to evaluate the performance of a novel machine learning-based framework that incorporates data pre-processing, multivariate statistical analysis, and anomaly recognition to address challenges such as missing data, noise interference, data imbalance and high non-linearity. We utilize lithogeochemical data to map potential greenfield regions of REE mineralization. The primary advantages of our framework lie in its provision of an effective random forest-based data imputation method, utilization of isometric log-ratio transformation to eliminate the closure effect, and reduction of the impact of outliers on data interpretation through robust principal component analysis. Additionally, the framework utilizes a deviation network to learn anomaly scores from complex, non-linear data under imbalanced data conditions, identifying geochemical anomalies associated with REE occurrences by leveraging prior knowledge rather than those caused by data noise or anthropogenic factors. The anomalous areas identified by this framework delineate all known REE deposits and extend to the surrounding regions. Furthermore, a close spatial coupling relationship exists between these strongly anomalous areas and the felsic granite intrusions. The comprehensive workflow for processing geochemical data proposed in this study can effectively address common challenges in the geochemical exploration of critical minerals. The identified geochemical anomalies can provide important clues for subsequent exploration.

Claystone formations are candidate host rocks for high-level heat-emitting nuclear waste (HLW). Temperatures from 90 to 150 °C at the canister surface are discussed internationally as potential emplacement and storage conditions. The thermal energy emitted from waste containers will be transported into the host rock formation, accelerating chemical reactions including the release of sorbed and dissolved gases and the generation of new gases. This study investigated gas release and generation in Opalinus Clay from Mont Terri (Switzerland) at elevated temperature and pressure conditions relevant for HLW storage and beyond. Hydrous pyrolysis experiments were conducted in Dickson-type flexible gold-titanium reaction cells and gold capsules in the temperature range of 80–345 °C and at 20 MPa. CO_2(g) was the predominant product, followed by C₁–C₄ hydrocarbons, which decrease in abundance with increasing carbon atom number. Neither CO nor H₂S was detected. H₂ was generated only in high temperature experiments at 315 °C and 345 °C, respectively. A combination of CO_2(g) quantification, stable carbon isotopic composition data, thermodynamic calculations and aqueous fluid composition (dissolved ions, pH) demonstrated that ≥80 % of the measured CO_2(g) originated from carbonate mineral dissolution. The model calculations also suggest that the fraction of CO_2(aq) in DIC increases from ∼50 % at 80 °C to nearly 100 % at higher temperatures. Thermal transformation of organic matter represented an additional source for CO_2(g) and was the predominant process yielding the C₁–C₄ hydrocarbons. Our findings stress the importance of quantitative geochemical data for the safety assessment of potential host rocks for HLW storage. We demonstrated that two sources are involved in gas release and generation at temperatures relevant for HLW storage, e.g., in the Opalinus Clay – organic matter and carbonate minerals. Our data will contribute to numerical modelling studies and the refinement of feature, events, and processes (FEP) catalogues.

The germanium content and its isotope ratio in thermal waters, aquifer rocks and main silicate minerals in a terrestrial groundwater system located in a granitic pluton (Karkonosze granitoid, Sudetes, Poland) have been investigated. This is the first extensive Ge isotope study carried out in both groundwater and aquifer rocks to better understand previously the identified enrichment of groundwater relative to rocks. This research also provides the first data on δ^74/70Ge for hybrid acid rocks formed by mixing magmas from two different sources (mantle- and crustal-derived) and main silicate minerals. The Ge isotopic composition in different facies of granite (porphyritic, equigranular) is comparable (δ⁷⁴/⁷⁰Ge of 0.43–1.23‰) to its hybrid rocks (quartz diorite–granodiorite, microgranular magmatic enclaves, composite dykes) – 0.79–1.27‰. However, the range of variability of this feature is quite wide. The minerals have δ^74/70Ge values of 1.01–1.04‰ in quartz, 0.84–0.90‰ in alkali feldspars, 0.76–0.88‰ in plagioclase, and 0.36–0.39‰ in biotite. The thermal waters are enriched in heavy Ge isotopes (δ^74/70Ge of 1.21–2.78‰) relative to the aquifer rocks (δ^74/70Ge of 0.43–1.27‰). Currently, the most likely explanation for this is the influence of secondary mineral phases formed in the geothermal granitic system. This comprises the preferential incorporation and adsorption of light Ge isotopes in/onto iron oxide/hydroxides and clay minerals. The other theoretical explanation, i.e., sulfide formation, is unlikely due to the unfavourable hydrogeochemical conditions in the studied system. The δ^74/70Ge values of thermal waters are similar to those of previously studied continental geothermal waters (1.65–3.29‰; Siebert et al., 2011) and fresh groundwater (2.24–4.02‰; Baronas et al., 2020), confirming that groundwater enrichment in heavy Ge isotopes relative to aquifer rocks may be widespread in the upper continental crust. Variation in the isotopic composition of the studied thermal waters is a result of the aquifer rock mineralogy and, in some cases, mixing of the old deep-circulating thermal water with the shallow modern cold groundwater. The general similarities in the chemical composition of the studied waters are due to the influence of porphyritic granite, which is the dominant rock type in this aquifer system. Some differences in chemical composition, including differences in the Ge isotopic composition, are related to the local distribution of hybrid rocks and sulfides. The δ^74/70Ge and Ge/Si ratios have been shown to be sensitive indicators of local hydrogeochemical conditions in an alimentation zone and a near-borehole zone of particular water intakes.

This study combines geochemical anomaly separation with geostatistical approaches and compositional data analysis. To have a reasonable model for abnormal areas, suggesting the optimal drilling coordinates, one needs to consider some effective geological controllers on the mineralization such as lithology, alteration, and tectonic processes. The lithogeochemical samples at 608 locations were processed from the copper porphyry mineralization area of Kuh Panj, Iran, to illustrate the proposed approach. The heterogeneity of rock type domains was detected using contact analysis. Based on this, plurigaussian simulation made it possible to model the uneconomic dykes of the area. Copper-molybdenum grades and filler as geochemical components were transformed into multivariate normal data using isometric logarithmic ratio-flow anamorphosis. Hierarchical rock type-grade simulation reproduced the grade behavior at hard rock type boundaries. Selection of a dense and regular simulation grid minimized the smoothing effect caused by interpolation of the singularity index values. Finally, unsupervised machine learning identified the anomaly zone by clustering the results of the singularity analysis. Validation using drilling data and the geological map shows that the anomaly separation, considering the geological conditions and the compositional nature of the geochemical data, can provide a reliable model of the geochemical anomalies in the Kuh Panj deposit.

The uptake of formate and gluconate by C–S–H, AFm phases, ettringite and hydrated Portland cement (PC) was studied at pH 13 by batch sorption experiments. The formation of gluconate and formate-AFm phases was observed in pure systems, but not in hydrated cement. Gluconate sorbs more strongly on AFm phases and ettringite than formate. Higher calcium concentrations increase the gluconate sorption on C–S–H and hydrated Portland cements due the formation of Ca-gluconate surface complexes on C–S–H. Measured R_d values for gluconate sorption on C–S–H increase from 2.0 dm³‧kg⁻¹ for C–S–H with Ca/Si = 0.8 to 34 dm³‧kg⁻¹ for Ca/Si = 1.4 at pH 13. They are a factor 5 to 10 higher at lower pH values, and higher Ca-concentrations. Calcium concentration does not significantly affect the uptake of formate by C–S–H. Formate sorbs on hydrated PC with R_d values in the range of 3–33 dm³‧kg⁻¹.

The identification of geochemical anomalies is crucial in mineral exploration. However, the limited sample size, high-dimensional features, and mixed geochemical information make identifying geochemical anomalies a significant challenge. Machine learning algorithms (MLAs), especially those with spatial and spectrum branches, have been proven to be a high efficiency tools for detecting geochemical anomalies related to mineralization. The spatial branch MLAs take two-dimensional images (pixel-patches) as input and mainly capture the spatial characteristics of geochemical patterns. The spectrum branch MLAs take one-dimensional sequence data (pixels) as input and mainly consider the elemental concentration and assemblies. Simultaneously considering the spatial patterns and geochemical concentrations of the geochemical survey data can mitigate geochemical concentration variations arising from objective factors and amplify subtle mineralization anomalies. This study proposes an unsupervised spatial-spectrum autoencoder (AE), namely dual-AE, which consists of a graph convolutional autoencoder (GCN-AE) and a long short-term memory network autoencoder (LSTM-AE) for geochemical anomalies identification. The spatial branch is constructed using the GCN-AE, which can effectively capture spatial geochemical patterns and extract spatial relationships between neighboring pixels. The spectrum branch consists of an LSTM-AE that can study geochemical elemental assemblies within a single pixel. A key ore-controlling factor was added into the dual-AE as a soft constraint to construct a geologically constrained dual-AE. A case study was conducted to recognize geochemical anomalies associated with iron polymetallic mineralization in Southwest Fujian Province, China. The obtained results demonstrated that (1) the unsupervised spatial-spectrum deep learning algorithm serves as a potent method for detecting geochemical anomalies related to mineralization, (2) the geologically constrained unsupervised spatial-spectrum dual-branch model can improve the accuracy and interpretability of geochemical anomaly identification, and (3) the identified anomalous areas can provide essential clues for further mineral exploration.

This study focuses on the adsorption and transport of Cr (VI) on natural sediments from Qiqihar, China. Through batch and column experiments, we assessed the adsorption capacities influenced by factors such as contact time, initial concentration, pH, ionic strength, solid-to-solution ratio, coexisting ions in groundwater, sediment characteristics and flow rate. The adsorption kinetics of Cr (VI) follow the pseudo-first-order model well, while the isotherms of all three sediments are accurately represented by the Freundlich model. The adsorption edges reveal a strong pH dependence in Cr (VI) adsorption: the stronger the acidity, the more favorable it is for adsorption. The adsorption capacity decreases with an increasing solid-to-solution ratio, stabilizing at higher ratios. Coexisting ions in groundwater reduce Cr (VI) adsorption in loam under neutral pH. Additionally, Fourier transform infrared spectroscopy (FTIR) results indicate that the hydroxyl group is the primary reactive functional group in all three sediments. X-ray photoelectron spectroscopy (XPS) results further show partial adsorbed Cr (VI) was reduced to Cr (III) by organic matters. However, surface complexation reactions dominate the removal of Cr (VI). On the base above, we introduced a surface complexation model, optimizing equilibrium complexation constants by fitting adsorption edges. Subsequently, reactive transport models incorporating both surface complexation and reduction processes for Cr (VI) were established to simulate column experiments. As the flow rate decreases, the adsorption capacity and the amount of reduction reaction for Cr (VI) increase, while the reduction rate decreases. Specifically, the reduction for Cr (VI) was found to be more significant in loam compared to sand, correlating with the organic matter content. The results emphasize the existence of surface complexation reactions and the role of organic matters in electron transfer. Our study provides significant information for understanding Cr (VI) adsorption and transport behavior in natural aquifer sediments.