Climate change is intensifying drought and altering nutrient dynamics in vineyards, yet management within a single terroir remains largely uniform, ignoring the soil geochemical heterogeneity that governs water and nutrient supply. Mapping this heterogeneity is therefore a pressing but underexplored need. This study introduces a reproducible workflow that delineates soil geochemical domains from pre-existing geochemical data and links them to soil quality, turning a static database into an actionable tool for site-specific vineyard management in the Taurasi terroir (southern Italy), renowned for its high-quality wines. Compositional data analysis, robust principal component analysis, and K-means clustering were applied to 102 topsoil samples (10 elements) to identify domains, which were mapped using Thiessen polygons. New samples collected from the same sites provided data on pH, organic carbon, and grain size, which were integrated into a weighted Soil Quality Index (SQI). Three domains were identified: carbonate (49% of samples; 132 km2), volcanic (39% of samples; 109.4 km2) and weathered (12% of samples; 33.3 km2). Volcanic soils showed the highest levels of organic carbon (median 3.51%), K (13,400 mg/kg), P (1205 mg/kg), and B (16 mg/kg), a coarse texture, and a near-optimal pH (median 6.68), resulting in the highest SQI (median 0.40). Carbonate soils, despite their high Ca content (60,600 mg/kg), had an alkaline pH (median 8.07), which limited the availability of P and K (SQI 0.22), whereas weathered soils were nutrient-poor and fine textured (SQI 0.18). These differences imply different potential nutrient supply and drought resilience across the various domains. We conclude that mapping geochemical domains is a fundamental tool for sustainable viticulture and recommend prioritizing the planting of new vineyards on volcanic soils to reduce fertilizer inputs and mitigate water stress under climate change.

This study presents a multidisciplinary investigation of the Bolle della Malvizza mud volcanoes, located in the southern Apennines fold-and-thrust belt (Italy), aimed at characterizing these structures and constraining processes and sources of mud and gas leakage. Twelve main vents are present, continuously and slowly ejecting mud, saltwater, and gases, including CH4 and CO2. We carried out different investigations, including (i) stratigraphic and structural surveys, (ii) topographic and morphometric evaluations using a digital elevation model obtained by drone photogrammetry, (iii) geochemical measurements of CO2 flux, radioactivity and soil pH and (iv) geophysical surveys including electrical resistivity tomography, induced polarization and self potential. Nine main groups of mud volcanoes are present in the area, varying in size (from a few centimeters to 13 meters) and height (from ∼3 to 15 cm). These mud eruptive vents are aligned along the ENE-WSW and N-S directed normal faults. The geogenic CO2 flux is low when compared to other non-volcanic emissions in the southern Apennines. The electrical resistivity tomography reveals conductive volumes interpreted as clay-rich layers alternating with resistive bodies of clay-marly rocks, and conductive layers corresponding to shallow and deep aquifers. The induced polarization data highlights high-chargeability zones linked to clay-rich bodies and a narrow vertical conduit connecting deeper conductive zones to shallow levels. Self-potential data show a pronounced negative anomaly aligned with the main vents, spatially matching the high-chargeability conduit and a resistivity inflexion in the electrical section. Ground deformation modelling and Monte Carlo simulation suggest a source at ∼110 m depth, with a negative volume change of ∼5 × 105 m3. We propose a conceptual model in which deep fluids slowly ascend along damage zones of two major faults, interacting with the surficial aquifer and the clayey host rock, and accumulate in a shallow reservoir that gradually releases muddy fluids to the surface, forming mud volcanoes that are continuously eroded during rainfall events.

This research investigates the uptake of potentially toxic elements (PTEs) by Brassica rapa L. grown in volcanic and clay soils with high natural background levels of these elements, and assesses related human health risks. The study was conducted in two Italian regions that produce B. rapa L. for food use (Campania and Sicily). The results of this exploratory research indicate that the naturally elevated concentrations of PTEs in soils lead to correspondingly high levels of these elements in B. rapa L. The investigated soils exhibited marked chemical differences. Volcanic soils had higher Total Organic Carbon (TOC) and PTEs concentrations alongside lower pH and Cation Exchange Capacity (CEC) than clayey soils. In the investigated plants, PTEs accumulated mainly in roots and stems, with notable Hg levels in leaves. While As exceeded safety limits in only one edible sample from volcanic soil, Cd, Hg, and Pb frequently surpassed them. Health risk assessments revealed significant carcinogenic and non-carcinogenic risks from plants grown on volcanic soils, with levels that remain unacceptable even at low consumption rates. In contrast, lower risk levels are associated with the consumption of Brassica rapa grown in clay soils, with values that are generally considered tolerable at low consumption rates. The preliminary findings of this study highlight that natural soil enrichment can cause PTE levels in B. rapa L. that often exceed safe consumption thresholds. These results provide a foundation for future research aimed at more thoroughly investigating the mechanisms of metal uptake by edible plants in areas naturally enriched with PTEs in order to enhance the safety and sustainability of our food.

Accurate determination of natural background levels (NBLs) of groundwater hydrochemistry is critical for setting water quality standards, yet traditional approaches often fail to capture spatial heterogeneity, particularly in large-scale regions with uneven monitoring networks and human activities. To bridge the gap, this study proposes a novel framework that integrates machine learning models (TabPFN and XGBoost) with spatial grid resampling to model NBLs and their controlling factors (strata, land use/land cover, topographic slope, population, and nitrogen fertilizer use), thereby generating high-resolution NBL maps. A total of 1250 groundwater samples from the northwest Sichuan Basin, China, were used to validate this framework. The results showed that TabPFN outperformed XGBoost in NBL prediction across all parameters, yielding higher R2 (0.933–0.979) and reduced uncertainty by 15%–44%. The high-resolution NBL maps revealed that, although lithology remained the primary control on geogenic indicators (e.g., Ca2+, Mg2+), anthropogenic drivers reshaped the baseline patterns of hydrochemical parameters (e.g., NO3-N, Cl−, and Na+). The dissolution of mirabilite, dolomitic strata (Cretaceous), and calcareous formations (Jurassic) explained the elevated SO42−/Na+ in the groundwater environmental unit (GEU) Ⅰ, Mg2+ in GEU Ⅱ, and Ca2+ in GEUs Ⅲ–Ⅵ, respectively. Slow groundwater runoff increased hydrochemical concentration in GEUs Ⅰ and Ⅲ–Ⅵ. Domestic sewage and nitrogen fertilizer application were identified as the primary sources of elevated Na+/Cl− and NO3-N levels, respectively, which notably affected GEUs Ⅰ and Ⅲ–Ⅴ. The maps characterized the spatial heterogeneity of NBLs, thereby enhancing the understanding of baseline hydrochemistry. Contemporary NBL should be regarded as a present-day baseline modified by modern human activities. These findings provide an effective approach for determining groundwater NBLs across large, unevenly sampled areas.

In this study, the Campania region (Italy) was selected to test a novel approach for identifying the geochemical signature of volcanic material in distal soils using their chemical composition. The Campania soil database comprises analyses of 48 elements for 5553 samples. Previous studies allowed us to confidently label 1277 samples as volcanic soils and 353 as non-volcanic soils. These labeled samples were used to train three machine learning algorithms to classify 3903 uncertain samples. Three different soil types were effectively identified with 98 % accuracy: volcanic, non-volcanic, and mixed. Subsequently, regional geochemical background values for each element in the various identified soil types were determined using ProUCL software. The results show that volcanic soils have background values of some key macronutrients (K, Na) and potentially toxic elements (As, Be, Hg, Pb, U, Tl) up to 18 times higher than non-volcanic soils. On the contrary, non-volcanic soils show the geochemical signature of materials of carbonate and clay origin, with enrichments of Ca, Mg, Co, Mn, Ni up to 4 times higher than volcanic soils. All these findings are fundamentally important for accurately establishing local reference background concentration values, which are crucial for promoting sustainable soil management practices. Moreover, the geochemical information generated by this study also yielded valuable insights into the geographic distribution of pyroclastic fallout from ancient eruptions, which is essential for understanding the historical dynamics of volcanic activity in the region.

Assessing the geochemical background is critical for addressing soil contamination, particularly in regions with complex interactions between the natural geological context and anthropic activities. Traditional methods for distinguishing geochemical backgrounds from anthropogenic anomalies often struggle to account for overlapping signals in such areas, leading to limitations in accurately identifying contamination sources. This study introduces the “anthropigene” method, an adaptation of the “geochemical gene” method initially developed for mining applications in the environmental context. By classifying geochemical indicators (“genes”) associated with urban and agricultural contamination, the anthropigene provides a robust framework for distinguishing anthropogenic anomalies from natural geochemical signals. Applied to approximately 3000 topsoil samples from the Campania region in Italy, the method allowed the determination of multivariate geochemical patterns linked to urban and agricultural sources of contamination. Samples considered contaminated were eliminated from the original dataset, and the remaining data were used to assess geochemical backgrounds.Results showed that the background values determined through the proposed approach significantly differed from those generated by applying Italian guidelines; they are also generally more conservative if used as a reference for a tier-one human health risk assessment and environmental restoration. Using the proposed method could have favorable practical implications for unveiling the presence of large-scale diffuse contamination processes that could be easily mistaken for natural enrichments due to their spatial extension.The method certainly has wide margins for improvement, and future studies will focus on identifying specific indicators of anthropic processes not considered in this paper and improving the techniques for estimating background values at a regional scale.

The main objective of this study is to propose a method to determine, as accurately as possible, the natural background content of a chemical element in urban soils, identify potential sources, and quantify emissions from human activities. To achieve this, 156 topsoil samples were taken from the surface horizon of the soil (first 20 cm) and analysed for 25 elements using a combination of inductively coupled plasma atomic emission spectrometry (ICP-AES) and inductively coupled plasma mass spectrometry (ICP-MS), after aqua regia digestion. The concentration data obtained were rigorously analysed using multivariate statistical analysis methods, including compositional data analysis (CoDA), clustering and dimension reduction techniques. This analysis separated the data into distinct populations, each characteristic of a natural or anthropogenic phenomenon. The ProUCL 5.2.0 software package was then used to calculate the natural background levels of each element for each data population. The background of some elements, including Co and Tl, exceeds the threshold values imposed in Italy by environmental law in some areas. These findings, together with the use of specific indices, allowed us to precisely define the degree of potentially toxic elements enrichment and the potential ecological risk of the studied area, thus providing valuable information for decisions on urban planning and environmental policy and potentially influencing future strategies for managing urban soil health.

Soil contamination by potentially toxic elements (PTEs) poses a major environmental concern. The distribution and concentration of these elements can vary significantly in polluted areas, making detailed assessments crucial. A comprehensive analysis is essential to accurately characterise contamination patterns, as a foundation for effective site evaluation and remediation efforts. This study evaluates the effectiveness and reliability of X-ray fluorescence (XRF) and inductively coupled plasma mass spectrometry (ICP-MS) for determining PTEs in soil samples. Statistical analyses reveal significant differences between the two techniques for Sr, Ni, Cr, V, As, and Zn, likely due to variations in detection sensitivity, calibration methods, or matrix effects. Pb exhibits a weaker difference, suggesting a potential, yet statistically insignificant, difference between methods. Correlation analyses indicate a strong linear relationship for Ni and Cr, while Zn and Sr display high variability, limiting direct comparability. Bland–Altman plots highlight systematic biases, particularly for V, where XRF consistently underestimates concentrations compared to ICP-MS. These findings underscore the importance of selecting the appropriate analytical technique based on detection limits, sample characteristics, and measurement reliability. While both methods provide valuable insights for environmental monitoring, carefully considering their limitations is crucial for accurate contamination assessment.

The southern Apennine chain ranks among Europe's regions with the highest historical seismicity, yet its seismogenic structures remain poorly defined or completely unknown, including those of highly destructive Mw similar to 7.0, 1456 and 1688 Sannio earthquakes, which are examined in this study. Using a multi-scale, interdisciplinary approach - combining detailed field investigations (stratigraphic, geomorphological, structural, and paleoseismological analyses), tephrochronological and OSL dating, and reassessment of macroseismic intensity distribution from archival sources - this study identifies a possible source for these earthquakes. It corresponds to a similar to 45 km normal fault system composed by two main branches (Eastern Calore Fault and Western Calore Fault) with primary segments trending E-W to ESE-WNW and dipping N- to NNE. Segments extend along the southern border of both eastern and western Calore River sub-basins and are partially connected by NNW-SSE to N-S trending, east-dipping, transfer zone fault splays. Although the morphostructural evidence of Quaternary tectonic activity is unevenly expressed in both sub-basins, they share a similar Middle Pleistocene-to-Holocene morpho-sedimentary evolution, suggesting a common driving factor, ascribable to the sub-coeval activity of the fault segments delimiting both sub-basins. On a short-time scale, this study provides the first evidence of a post-14 ka occurrence of a paleoearthquake with a surface displacement greater than or similar to 0.7 m, as well as of a decametric off-set affecting post-9 ka sediments. These coseismic surface ruptures have an estimated recurrence time of approximately 1400 years, with the two more recent events likely corresponding to the Mw similar to 7.0, 1456 and 1688 Sannio earthquakes. Further detailed paleoseismological investigations are recommended to uncover direct evidence of co-seismic displacement linked to the 1456, 1688, and earlier earthquakes.

We present a multidisciplinary study on natural non-volcanic CO2 degassing vents in the southern Apennines, aiming to investigate gas leakage mechanisms related to tectonic structures. The studied degassing areas are located in the Sele River Valley, north and east of Oliveto Citra town. The Sele River Valley features multiple cold and hot springs and frequently aligned gas vents emitting CO2 and noble gases. We performed structural-geological mapping and geochemical investigations (soil pH and CO2 mapping) in three key areas of the Sele River Valley. These were implemented by geophysical surveys, including 2D Electrical Resistivity Tomography (ERT), Induced Polarization (IP) Tomography, 2D Seismic Refraction Tomography (SRT), Magnetometry (MAG), and Self Potential (SP) mapping in a single sector (area 1) included in the Mofeta del Vecchio Mulino vents north of the Oliveto Citra town. The results of this multidisciplinary study indicate that most of the gas emissions are along the intersection between the major faults that crosscut a tectonic pile formed by limestones tectonically covered by an oceanic succession made of clays and marls. In area 1, ERT, IP, and SRT profiles mark a vertical conduit where the fluids migrate upward, corresponding to a major fault zone that lowered the tectonic pile to the north. The MAG and SP maps also show anomalies highlighting uprising fluids along the intersection between major faults. CO2 flux maps of three areas embedding the major vents show that the geogenic emissions are widespread, with the highest values reaching 2256 gm2d- 1. Generally, the degassing vents form about circular areas of 10 m in diameter. Also, the pH map indicates acid soil anomalies close to the major emission vents. The novelty of this work is the multidisciplinary approach, which uses different methodologies to reconstruct the buried tectonostratigraphic architecture and the articulated pathways for fluid migration, highlighting that once fluids move toward the surface, they follow the main fault zones. Furthermore, their migration and leakage are controlled mainly by the surficial segmentation of faults and local permeability paths. The procedures applied in this study can be helpful for investigations in other natural degassing areas or the CO2 storage industry to investigate the seeping and leakage processes and mitigate the gas migration.

Application of advanced data mining methods to various types of geochemical data is able to fingerprint valid signatures of mineralization, thus unveiling ore genesis and discovering new minerals. But individual studies that apply data mining methods to both local- and regional-scale, both sediment and whole-rock multi-element geochemical data sets are relatively scarce. Here, we applied data mining methods, including multivariate statistical analysis (principal component analysis), spatial analysis (trend surface analysis), unsupervised machine learning algorithm (K-means clustering), supervised algorithms (random forest and deep neural network) to both regional sediment geochemical and local lithogeochemical data from the Duolun-Guyuan prospect, in order to determine the geochemical signatures of volcanic-type uranium mineralization through characterizing: (1) representative element associations; (2) axial zonation of primary haloes; (3) element distribution patterns; and (4) crustal structures (via deep learning-based predictive hafnium (Hf) isotopic mapping). Results of principal component analysis and random forest show that samples from known ore districts (e.g., Zhangmajing and Daguanchang) exhibit a distinct combination of major ore-forming elements (U and Mo), chalcophile elements (Ag, Hg, Pb, Sb and As), rare and rare earth elements (Be, Li, La, Nb and Y), tungsten (W), bismuth (Bi), and rockforming elements (SiO2, K2O, Na2O and Al2O3), differing from samples of both the mineralized and barren areas. The axial zonation of primary haloes in Daguanchang is comprised of supra-ore haloes (rare earth elements, Th, Nb, Zr, Hf, Ga and Rb), near-ore haloes (U, Mo, Pb, Zn, Cd and Sb), and sub-ore haloes (Li, Be, Sc, V, Cu, Sr, Cs, Ba, W and Bi). Moreover, trend surface analysis shows that in the study area, the spatial distribution pattern of the supra-, near-, and sub-ore elements forms a northwesterly alignment, with the supra-ore elements concentrated in the southeast, the sub-ore elements in the northwest, and the near-ore elements in between. Finally, deep learning-based predictive hafnium (Hf) isotopic mapping reveals that the Duolun-Guyuan prospect is dominated by negative mean zircon epsilon Hf(t) values ranging from -17 to 0, except for some local areas in the west and southwest of Duolun and the north of Weichang. The above results may indicate critical signatures of volcanic-type U mineralization, consisting of meta- or pera-luminous, alkaline rhyolite resulted from crustal reworking, surrounding mantle-derived igneous rocks, proximal heat source, accompanying epithermal deposits (e.g., Ag, Au, etc.), and anomalous concentrations of U, Mo and relevant elements particularly Th, W, Bi, Ag and Sb etc. Our study will effectively provide new exploration geochemical indicators of volcanic-type U deposit.

This study reviewed scientific literature on inhalation exposure to heavy metals (HMs) in various indoor and outdoor environments and related carcinogenic and non-carcinogenic risk. A systematic search in Web of Science, Scopus, PubMed, Embase, and Medline databases yielded 712 results and 43 articles met the requirements of the Population, Exposure, Comparator, and Outcomes (PECO) criteria. Results revealed that HM concentrations in most households exceeded the World Health Organization (WHO) guideline values, indicating moderate pollution and dominant anthropogenic emission sources of HMs. In the analyzed schools, universities, and offices low to moderate levels of air pollution with HMs were revealed, while in commercial environments high levels of air pollution were stated. The non-carcinogenic risk due to inhalation HM exposure exceeded the acceptable level of 1 in households, cafes, hospitals, restaurants, and metros. The carcinogenic risk for As and Cr in households, for Cd, Cr, Ni, As, and Co in educational environments, for Pb, Cd, Cr, and Co in offices and commercial environments, and for Ni in metros exceeded the acceptable level of 1 x 10-4. Carcinogenic risk was revealed to be higher indoors than outdoors. This review advocates for fast and effective actions to reduce HM exposure for safer breathing.

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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.

Total alpha and beta activities and Rn-222 concentrations were determined in water from different sections of seven aqueducts belonging to the water supply system of Campania region (Italy), known worldwide for its volcanism. Statistical analysis was performed on data to account for their variability across the aqueduct sections, and results were discussed considering the geology of reservoirs, the potential mixing processes occurring along the pipe network, the building/constituting materials of the aqueduct sections, and the integrity of the infrastructure. Guidelines proposed by Italian and international regulation entities were considered to determine if total alpha and beta activities and Rn-222 concentrations found at the taps of the different aqueducts should be considered detrimental to public health. Based on a deterministic and a stochastic approach, a health risk assessment was also tested for Rn-222, assuming direct ingestion and showering as potential exposure pathways. Results showed that applying guidelines returned an absence of hazard, whereas risk assessment returned a high probability of exposure to unacceptable Rn-222 doses for some aqueducts. Beyond the usefulness of obtained results to plan actions to improve the safety of drinking water in Campania, our outcomes represent a warning for bodies dealing with public health at any level: the use of guidelines can bring an underestimation of the risks exerted by the exposure to Rn-222 on human health. Further, using a probabilistic approach in risk assessment accounting for uncertainty can favor risk forecasts based on more "realistic" scenarios.

When dealing with environmental problems, it is of fundamental importance to establish reference values (geochemical baselines) against which to determine the presence or absence of active contamination processes.In the effort to develop a method to assess the geochemical baselines for territories featuring complex geological settings and a well-established anthropic environmental pressure, we combined compositional data analysis (CoDA) with geolithological information to reduce the degree of uncertainty possibly affecting the results. The proposed approach comprises (1) a knowledge-driven step to select a number of sample subsets from a geochemical dataset each with a high probability of having its composition strongly influenced by only one of the lithologies outcropping in the study area; (2) a data-driven step to compute compositional principal balances and define geochemical indicators to be used to assign each of the observations in the dataset to one of the geochemical domains associated to a mayor lithologies outcropping in the study area; (3) the determination for each geochemical domain of baseline values based on the samples assigned to them by the data-driven step.The method was tested using the geochemical data referring to 887 stream sediment samples collected across the Volturno River catchment basin (Southern Italy), featuring a relevant lithological heterogeneity.The results obtained were easily interpretable as they fitted well with the geomorphological, geochemical, and geodynamic processes characterizing the study area.Despite the use of stream sediments for the specific case study presented, the application principles of the method hold for any environmental media and for any territory for which there is a need to define baseline values. However, for a successful application of the method, it is crucial to have a fair knowledge of the geological settings of the study area.

The south-eastern sector of the Matese Massif (southern Apennines, Italy) includes several nonvolcanic gas (mainly CO2) vents. The gas emissions in the northern part (Ciorlano-Ailano sector) have been associated with the Southern Matese Fault system, whereas a similar relationship is not evident in the southern part (Telese-Solopaca sector). Hence, we investigated the latter area (hills north of Solopaca town) through a multidisciplinary study of the principal CO2-degassing vent (Santantuono spring). The main goal is to reconstruct the structural architecture of the area and study the role of the fault array in conveying the gas migration to the surface. In particular, an integrated approach that combines structural and stratigraphic investigations with CO2 flux and geoelectrical surveys is proposed to shed light on the relationships between near-surface faults and gas rising. The main results from the geological-structural investigation suggest that thrust faults are the oldest structures, mainly verging to NNW, crosscut by high-angle N-S and younger NW-SE normal faults. This understanding is supported by the results of the CO2 flux survey, which records the highest flux values in correspondence with the mapped young normal faults, especially at their intersections. Moreover, the hypothesized tectonic and stratigraphic structure at depth is entirely consistent with the 3D geoelectrical model of the survey area provided by a 3D electrical resistivity tomography investigation, which also identifies the main NW-SE striking fault as the preferential pathway for gas migration. Finally, we suggest that the reconstructed NW-SE faults are the prolongation of the active Southern Matese Fault system bounding the SW Matese Massif margin defined by different segments with dominant normal kinematics and several gas vents.

When dealing with environmental problems, identifying areas with common geochemical characteristics and assessing reference concentration values for potentially toxic elements is critical to discriminating anthropogenic from geologic contribution. Statistics can favor the process, but results can be inaccurate if the data used are not adequately subsetted. This paper combines compositional data analysis (CoDA) with geolithological information to reduce the uncertainty in determining geochemical background reference values. For this purpose, we used geochemical data referring to 887 stream sediment samples collected across the Volturno River catchment basin (Southern Italy) that features a relevant lithological heterogeneity.The proposed approach comprises a) a knowledge-driven step to select subsets of samples (end-members) with a high probability of having their composition strongly influenced by only one lithology and b) a data-driven step (based on unsupervised statistical learning techniques) to derive compositional principal balances and define geochemical indicators to be used to group samples under common geochemical domains.Four geochemical domains (i.e., predominant components influencing the geochemistry of sediments) were determined for the Voulturno River catchment basin: a) Carbonatic (PCC), b) siliciclastic (PSC), c) pyroclastic (PPC), and d) volcanic (PVC). The PCC features sediments enriched in Ca, Mg, and Sr and depleted in Th, La, Ba, Ga, K, Na, and Al. A relative enrichment in Co, Ni, Fe, and Mn characterizes the PSC. The PSC and PVC include sediments generally enriched in Th, La, Ba, Ga, K, Na, and Al, with pyroclastic deposits enriched in high mobility elements (K, Na, Mg, Ca) and older volcanic rocks enriched in low mobility elements (Th, La, Ti, Ga, Mn), respectively.The overall extension of each geochemical domain was spatially defined, joining the catchment basin' areas of the samples belonging to it. The reference values for the geochemical background were calculated and assigned to samples based on geochemical domains.

The Reshui area, located to the northeast of the Qinghai–Tibet Plateau, exhibits complex geological conditions, well-developed structures, and strong hydrothermal activities. The distribution of hot springs within this area is mainly controlled by faults. In this paper, five hot springs from the area were taken as the research object. We comprehensively studied the geochemical characteristics and genetic mechanism of the geothermal water by conducting a field investigation, hydrogeochemistry and environmental isotopic analysis (87Sr/86Sr, δ2H, δ18O, 3H). The surface temperature of the geothermal water ranges from 84 to 91 °C. The geothermal water in the area exhibits a pH value ranging between 8.26 and 8.45, with a total dissolved solids’ (TDS) concentration falling between 2924 and 3140 mg/L, indicating a weakly alkaline saline nature. It falls into the hydrochemical type CI-Na and contains a relatively high content of trace components such as Li, Sr, B, Br, etc., which are of certain developmental value. Ion ratio analysis and strontium isotope characteristics show that the dissolution of evaporite minerals and carbonate minerals serves as a hot spring for the main source of solutes. Hydrogen and oxygen stable isotope characteristics findings indicate that the geothermal water is primarily recharged via atmospheric precipitation. Moreover, the tritium isotopic data suggest that the geothermal water is a mixture of both recent water and ancient water. Moreover, the recharge elevation is estimated to be between 6151 and 6255 m. and the recharge area is located in the Kunlun Mountains around the study area. The mixing ratio of cold water, calculated using the silicon enthalpy equation, is approximately 65% to 70%. Based on the heat storage temperature calculated using the silicon enthalpy equation and the corrected quartz geothermal temperature scale, we infer that the heat storage temperature of geothermal water in the area ranges from 234.4 to 247.8 °C, with a circulation depth between 7385 and 7816 m. The research results are highly valuable in improving the research level concerning the genesis of high-temperature geothermal water in Reshui areas and provide essential theoretical support for the rational development and protection of geothermal resources in the area.