Applied Geochemistry最新文献

Soil organic carbon (SOC) plays an important role in global carbon cycle which is influenced by multiple factors. Elevation, as one of these factors, has a close but complex relationship with SOC concentration. The traditional ‘global’ statistical models cannot capture the spatial variation thus are inefficient in revealing the relationships between SOC and elevation at the local scale. In this study, a ‘local’ model of geographically weighted regression (GWR) was used to explore the complex relationships between SOC and elevation in the topsoil of Ireland based on the dataset from National Soil Database of Ireland. The results indicated SOC and elevation exhibited the spatially continuously varying relationships across the study area. Positive relationships in the mountainous areas suggested SOC concentration increased with the increasing elevation. Negative relationships were observed in the midlands where SOC concentration decreased with the increasing elevation. Such varying relationships between SOC and elevation in Ireland were related to the two different main types of peat: blanket peat and raised peat. These two types of peat have different formation processes, thus are distributed at different elevations. In the mountainous areas, low temperature and high humidity create cool and anoxic environment that mitigates SOC mineralization, promoting the accumulation of blanket peat at a high elevation. In the midlands, the low-lying lakes and wetlands provide anoxic environment where raised peat is developed and located at a low elevation. The findings of the spatially varying relationships between SOC and elevation in Ireland have demonstrated the importance of modelling SOC at the ‘local’ level. Attention is required for soil mapping using a global algorithm and it is recommended that localized algorithms are considered in modelling SOC, taking the feature of continuous variation into consideration.

Monitoring and managing dust (i.e., particulate emissions) remains a ubiquitous challenge to the mining industry resulting in outstanding questions regarding the nature and spatial-temporal distribution of fugitive dust emissions to the near-mine environment. In this study, fugitive dust samples were captured up to 1 km from the mine perimeter over a ∼2-year study period using passive dry deposition samplers (PAS-DD) deployed around an active open-pit gold mine in Northwestern Québec, Canada. This study demonstrates the utility of the recently developed PAS-DD for long-term (84–285 days) dust sampling under a wide-range of weather conditions (−37 to 32 °C), allowing for measurement of the mine-dust footprint, the flux of dust-transported metal to the near-mine environment, and the micro-characterization of dust including its mineralogy. The results show that net dust deposition is highest near mine operations occurring near the open pit and the mine-access road, and that dust deposition reaches reference-site levels between 200 and 1000 m from the mine perimeter. Captured dust comprised 87–99 vol% silicates (primarily chlorite, quartz, muscovite, plagioclase, and amphibole), 1–9 vol% carbonates (calcite, ankerite, and dolomite), and <2 vol% sulfides (pyrite, pyrrhotite, sphalerite and arsenopyrite). Trace amounts (<0.2 vol%) of arsenopyrite in the dust is primarily responsible for the atmospheric deposition of As to the near-mine environment. The highest flux of As to the near-mine environment (<0.003 mg/dm²day) was recorded by samplers north of the open pit and mine access road, where net dust deposition is highest. In contrast, south of the mine dust has much lower net deposition rates (comparable to reference site levels), but delivers a higher concentration of As to the environment, resulting in As deposition rates up to 0.001 mg/dm²day (∼300x reference site levels). Dust captured south of the mine was enriched in arsenopyrite and is interpreted to reflect increased particulate input from the adjacent tailings storage area. The higher concentration of As in dusts reaching the southern near-mine environment correlates with As-enrichment in the organic layer of soils characterized in an earlier study. Overall, this study demonstrates how the geochemical and mineralogical characterization of dust captured by PAS-DD can be used to understand the role of fugitive mine dust in the transport of environmental contaminants to the near-mine environment.

Sinkholes play a critical role in groundwater systems by facilitating both recharge and discharge of groundwater, serving as indicators of underlying geologic processes, shaping subsurface hydrology, and influencing water quality. Therefore, studying karst groundwater systems is essential for effective groundwater management, especially in areas with limestone sequences. Spatial variations of water isotopes (δ²H, δ¹⁸O), dissolved inorganic and organic carbon (DIC and DOC), including their isotopes alone with pH, EC, alkalinity and chloride were determined in surface- and groundwater of the Mulankavil karst aquifer basin in the northwest of Sri Lanka. Twenty-seven groundwater wells, one offshore spring and two sinkholes were selected for sampling. The contribution of sinkhole water and seawater to karst aquifers was calculated using δ¹⁸O and chloride as tracers. In addition, deuterium excess (d-excess) values were used to determine groundwater evaporative loss before infiltration. Near the Mulankavil sinkhole area, the mixing of surface water and infiltrating rainwater was found to vary between 26 and 60%, with an average of 56%. In contrast, surface water mixing in the Nagapadduvan and Vellankulam sinkholes was about 41–59% and 33–70%, respectively. In near coastal wells, these values fell to 20% due to the influence of seawater intrusion. During the dry season, groundwater d-excess varied between −5.0 and + 10.8‰, while surface water in sinkholes showed values between +1.8 and −9.4‰. Groundwater wells near the Mulankavil sinkhole showed lower DIC (<5.5 mmol/L) with enriched δ¹³C_DIC (>-14‰). The karst aquifer systems in northern Sri Lanka exhibit two main recharge mechanisms: (a) selective recharge by surface water at sinkholes and (b) diffuse recharge by direct rainfall over the study area. Seawater intrusion near the coast can be prevented by artificially recharging rainwater during the monsoon season.

This study presents updated chemical, thermodynamic, and activity models for the system U⁴⁺–Na⁺–Mg²⁺–Ca²⁺–H⁺–Cl^––OH^––H₂O(l) derived using the Pitzer formalism and a strict ion interaction approach. The models build on comprehensive solubility datasets in dilute to concentrated NaCl, MgCl₂, and CaCl₂ solutions. The Nuclear Energy Agency-Thermochemical Database (NEA-TDB) selection of solubility and hydrolysis constants in the reference state were taken as anchoring point, and were extended further with the solid nanocrystalline phase UO₂∙H₂O(ncr) and the ternary complex Ca₄ [U(OH)₈]⁴⁺. The former was identified in long-term solubility experiments at ambient conditions, whereas the latter has been selected in analogy to Th(IV), Np(IV), and Pu(IV) considering experimental evidences available for these An(IV) in alkaline, concentrated CaCl₂ solutions. These models represent an improved tool for the calculation of U(IV) solubility and aqueous speciation in a variety of geochemical conditions including concentrated brine systems relevant in salt-based repositories for nuclear waste disposal.

Soil carbon pools play a crucial role in the Earth's ecosystem, acting as significant carbon sinks and sources. Through a detailed analysis of soil carbon content using data from the Huangpi District in Wuhan, China, this research employs geochemical survey data, field replicates, and spatial autocorrelation information to establish an assessment model for soil carbon stocks. The model addresses the sources of errors and their effects on carbon pool changes, using both traditional statistical theories and geostatistical models to detect changes in carbon density and estimate carbon sources and sinks with minimized error ranges. Key findings indicate that sampling errors, influenced by small-scale spatial variability, are the primary source of observational inaccuracies in assessing total soil carbon and organic carbon, accounting for over 90% of the variation. Meanwhile, analytical errors are more significant when quantifying soil inorganic carbon content due to its lower concentrations. From 2001 to 2022, no significant changes were observed in the soil organic carbon stock in Huangpi District, while a modest increase in inorganic carbon was noted. The study highlights that increasing sample density beyond a certain threshold does not significantly affect carbon stock estimates or their error ranges, emphasizing the stability of the block kriging method in estimating regional carbon stocks.

Coal fly ashes (CFAs) are the low-density byproducts of the coal combustion process. Improper or uncontrolled CFA disposal poses significant environmental and health concerns due to the potential leaching of toxic heavy metals such as arsenic (As). Previous studies have investigated the content and speciation of As in different CFA samples, yet systematic information on As speciation in CFA with representative coal source and combustion conditions is still missing. Based on a recent survey study on the typical coal sources and combustion conditions across the U.S., this study selected 19 representative CFA samples to systematically investigate As speciation and potential correlations with these parameters. The composition, morphology, mineralogy, and As speciation of these CFA samples were characterized by complementary analytical, microscopic, and spectroscopic techniques. Synchrotron X-ray spectroscopy and microscopy analyses revealed the dominant As oxidation state to be As(V) and with strong associations to Ca, with the exception of 3 samples that had 19–51% As(III), likely due to the use of selective catalytic reduction (SCR) process. Principal component analysis was conducted to identify potential correlations of As concentration and oxidation state with parameters such as major element content, loss on ignition (LOI), average particle size, coal source, and combustion condition. Al₂O₃ and FeO content were found to capture a majority of the variability. Results from this study provide fundamental basis for understanding the correlations between coal source, combustion conditions, CFA characteristics, and As speciation, and providing insights for downstream beneficial utilization or disposal management.

Combining traditional geochemical methods with advanced analytical techniques is a hallmark of contemporary exploration efforts. This study explores the intricate geological dynamics of the Dayu gold deposit, located in the Dayao Uplift of the South China Block. Using a multidisciplinary approach that includes soil geochemistry, conventional geochemical methods and advanced computational techniques such as machine learning and Discriminant Projection Analysis (DPA), we aim to uncover the deposit formation information. Our results reveal a complex pattern of element anomalies, which serve as a geochemical fingerprint of the Au mineralization processes that shaped the deposit over geological time. Principal Component Analysis (PCA) and cluster analysis on soil samples highlight significant correlation among Au and its pathfinder elements. By leveraging the predictive capabilities of machine learning algorithms, particularly Convolutional Neural Networks (CNN), we improve exploration strategies, enhance the precision of target delineation and guide sampling efforts. DPA further identifies distinct discriminant functions, aiding in group differentiation and providing insights into prospective mineralization zones. This study exemplifies the integration of traditional and innovative methodologies, offering a pathway to a deeper understanding of mineralization processes and improving the effectiveness of exploration in complex geological terrains. The findings advance our knowledge of the Dayu gold deposit and demonstrate the potential of these integrated approaches in similar geological settings.

Groundwater is a key medium for the migration and enrichment of elements into ore bodies in sandstone-type uranium deposits, with anomalies of uranium elements and their associated components in water serving as indicators for exploring such deposits. The Erlian Basin, located in central-northern Inner Mongolia, is a crucial production area for sandstone-type uranium deposits in China. The groundwater flow system in the basin plays a significant role in the formation of uranium deposits. To study the hydrogeochemical characteristics and enrichment regularities of groundwater uranium in the Erlian Basin, 269 groundwater samples were collected. Hydrogeochemical analysis methods, such as Piper diagrams, Gibbs diagrams, and contour maps, were employed to determine the distribution characteristics and occurrence forms of groundwater uranium in the study area. The primary water chemistry types in the study area were HCO₃–Ca•Na, HCO₃–Na, HCO₃•SO₄–Na, and SO₄•HCO₃–Na•Ca. The distribution range of uranium content in groundwater in the study area was 0.1–453 μg/L (average of 53.08 μg/L). A comprehensive analysis, based on the direction of groundwater flow and changes in the redox environment, suggested that the higher uranium values in groundwater were distributed in the runoff and discharge areas, with uranium anomaly points existing in areas with alternating oxidation and reduction zones. These uranium anomaly points were in good agreement with the known large uranium deposits of Nuheting, Qiharigetu, Daoersu, and others, thereby predicting six other uranium hydrochemical anomaly points as prospective areas for uranium mineralization. The pH value distribution range in the study area's groundwater was 6.8–9.1, and the redox potential (Eh) value range was -126–52 mV, indicating that uranium exists in groundwater in the form of UO₂(CO₃)₃⁴⁻ and UO₂(CO₃)₂²⁻. An increase in bicarbonate (HCO₃⁻) is conducive to uranium dissolution. The enrichment and occurrence forms of uranium in groundwater are influenced by the concentrations of Fe and (Ca²⁺+Mg²⁺), with uranium precipitation and enrichment occurring as the groundwater evolves and changes in the redox environment. The uranium content in deep wells is higher than in nearby shallow wells, indicating that deep water circulation is beneficial for mineralization. The pH, Eh, HCO₃⁻, Fe, and other hydrogeochemical indicators are indicative of uranium enrichment; thus, they can be considered as reference bases when exploring for potential uranium resources.

Radionuclide transport in smectite clay barrier systems used for nuclear waste disposal is controlled by diffusion, with adsorption significantly retarding transport rates. While a relatively minor component of spent nuclear fuel, ⁷⁹Se is a major driver of the safety case for spent fuel disposal due to its long half-life (3.3 × 10⁵ yr) and its low adsorption to clay (K_D < 10 L/kg), thus a thorough understanding of Se diffusion through clay is critical for understanding the long-term safety of spent fuel disposal systems. Through-diffusion experiments with tritiated water (HTO, conservative tracer) and Se(VI) were conducted with a well-characterized, purified montmorillonite source clay (SWy-2) under a constant ionic strength (0.1 M) and three different electrolyte compositions: Na⁺, Ca²⁺, and a Na ⁺ -Ca²⁺ mixture at pH 6.5 in order to probe the effects of electrolyte composition and interlayer cation composition on clay microstructure, Se(VI) aqueous speciation, and ultimately diffusion. The results were modeled using a reactive transport modeling approach to determine values of porosity (ε), D_e (effective diffusion coefficient), and K_D (distribution coefficient for adsorption). HTO diffusive flux was higher in Ca-montmorillonite (D_e = 1.68 × 10⁻¹⁰ m² s⁻¹) compared to Na-montmorillonite (D_e = 7.83 × 10⁻¹¹ m² s⁻¹). This increase in flux is likely due to a greater degree of clay layer stacking in the presence of Ca²⁺ compared to Na⁺, which leads to larger inter-particle pores. Overall, the Se(VI) flux was much lower than the HTO flux due to anion exclusion, with Se(VI) flux following the order Ca (D_e = 1.03 × 10⁻¹¹ m² s⁻¹) > Na–Ca (D_e = 2.12 × 10⁻¹² m² s⁻¹) > Na (D_e = 1.28 × 10⁻¹² m² s⁻¹). These differences in Se(VI) flux are due to a combination of factors, including (1) larger accessible porosity in Ca-montmorillonite due to clay layer stacking and smaller electrostatic effects compared to Na-montmorillonite, (2) larger accessible porosity for neutral-charge CaSeO4 species which makes up 32% of aqueous Se(VI) in the pure Ca system, and (3) possibly higher Se(VI) adsorption for Ca-montmorillonite. Through a combination of experimental and modeling work, this study highlights the compounding effects that electrolyte and counterion compositions can have on radionuclide transport through clay. Diffusion models that neglect these effects are not transferable from laboratory experimental conditions to in situ repository conditions.