Stream sediments integrate the geochemical and mineralogical signals of entire drainage basins, reflecting both bedrock lithology and anthropogenic inputs. This study applies knowledge-driven Sequential Binary Partitions (SBPs) of isometric log-ratio (ilr)-transformed data to unravel relationships among geochemistry, mineralogy, and mass-specific magnetic susceptibility (chi), with an approach tested on a representative river basin (i.e., Ombrone Grossetano River Basin, Southern Tuscany, Italy), lithologically diverse and impacted by past mining activities. The method aims to improve the understanding of natural and anthropogenic influences on sediment composition. Geochemical data (X-ray fluorescence) were transformed through ilr-balances, whereas mineralogical compositions (X-ray diffraction), lithological information, and chi measurements were used to support the interpretation of sediment sources. Strong correlations between ilr-balances and mineral phases confirm that the geochemical signals reliably reflect sediment mineralogy and the basin's lithological variability. Comparisons between chi and ilr-balances detect localized anthropogenic inputs, notably Fe-enrichments linked to historical mining in a specific sub-basin (Farma-Merse). The combined use of compositional data analysis, mineralogical constraints and magnetic susceptibility provides a transferable framework to investigate sediment provenance and anthropogenic legacy in complex river systems. Beyond the case study, the results highlight the importance of considering whole-composition geochemical relationships to correctly interpret element distributions in fluvial sediments.

Over the last decades, the use of boron stable isotopes has steadily increased in the Earth Science literature, including hydrological studies. This paper presents "IsoBorDat", a global open-access database containing boron stable isotope ratios (expressed as permil delta 11B) measured in various hydrologic reservoirs such as groundwaters, surface waters, and rainwaters. The repository includes B contamination-related samples that have been (i) characterized in their isotopic signature as raw material or (ii) identified as potential sources of pollution in hydrological systems. IsoBorDat provides information on B content and B isotope ratios, water type, analytical methods, sampling time, and location. Data are available in open, structured.ods format, adhering to the FAIR principles. The database is hosted by the National Research Council of Italy (CNR) and is openly accessible at https://isobordat.cnr.it. We also present a quantitative and qualitative explorative approach applied to the statistical distribution of boron concentrations and isotope compositions across the four water types (meteoric, river, lake, and groundwater) and diverse water contamination sources of IsoBorDat. The statistical analysis reveals general distribution patterns and highlights differences among reservoirs, offering insights into geochemical processes influencing boron behaviour. This work supports the integrated use of isotopic data to better understand natural and anthropogenic influences on hydrological systems. IsoBorDat will be integrated within the ISOTOPE VRE, a Virtual Research Environment dedicated to environmental isotopes.

Understanding compositional changes is the key to investigate how complex natural systems evolve. Traditional geochemical approaches, such as univariate, bivariate, or multivariate analyses, usually focus on variability around a central composition. However, they do not provide insights into evolutionary paths or changes from benchmark states. In this work, we propose a comprehensive conceptual and methodological discussion of a holistic approach that addresses these limitations. We combine compositional data with metrics tailored to the simplex structure, specifically the robust Mahalanobis distance (MD) and perturbation analysis. Two large-scale datasets were analyzed: the Abyssal Volcanic Glasses Database (AVGD) with primitive compositions (chondrites and MORBs) as benchmarks, and the FOREGS repository of European stream and alluvial sediments, with crustal averages and diluted waters as reference states. By calculating MD from benchmark compositions and examining the frequency distribution, skewness, kurtosis, and multimodality, we identify patterns of compositional change, resilience, and potential instability. This work provides a data-driven perspective on how compositional metrics can enhance the understanding of Earth system dynamics. In particular, the proposed framework enables the detection of early-warning signals and tipping points. This offers a powerful tool for multi-scale assessment of geochemical system dynamics and resilience.

A critical review of studies concerning the attribution of the provenance of marble from the Apuan Alps (Italy) (AAM) used for historical–monumental buildings and artefacts is proposed based on its O/C isotopic and EPR signature. First, a summary of the geological origin of AAM and its geo-structural evolution and setting is presented. A review of the exploitation history of AAM is then discussed. This geological and historical information is used as categorical information to better constrain the literature multimethodic database, containing numerous data, including O/C isotopic and EPR spectroscopic parameters. A robust multivariate statistical analysis of the combination of all these data is performed. The results point to the fact that the O/C isotopic and EPR signature can help in attributing an analysed AAM sample to a marble extraction district, and to a certain extent also to a site, whereas the discrimination of the individual quarry appears to not yet be achievable.

The chemistry of rivers plays a crucial role in comprehending the evolution of weathering processes, especially in the context of climate change and human activities. As weathering proceeds within river catchments, chemical concentrations tend to move towards saturation, or thermodynamic equilibrium. However, thermodynamic equilibrium is extremely difficult to achieve in an open system where matter and energy are continuously exchanged. The speed of weathering processes and the associated probability distributions of concentrations values differ among geochemical species. We demonstrate that these differences are characterized by the rate of entropy production associated with the mixing of groundwater enriched with weathering products with the less saturated river water. Based on river chemistry and discharge data observations in the Arno River basin in central Italy, we distinguish two groups of chemical variables, reflecting different levels of dissipative behavior. We show that Calcium (Ca2+) and Bicarbonate (HCO3-) concentrations are close to saturation along most of the downstream length of the Arno River, with decreasing dissipation rates and a (log)normal distribution, while Sodium (Na+) and Chlorine (Cl−) concentrations increase substantially downstream, showing increased dissipation rates and being power-law distributed. This supports our hypothesis that power law distributions appear to be indicative of dissipative systems far from thermodynamic equilibrium, while (log)normal distributions indicate weakly dissipative systems close to equilibrium. This suggests that the frequency distributions of environmental variables are intricately connected to their thermodynamic state, and the degree of disequilibrium constrains the range over which power-law scaling can be observed. These results should contribute to a more comprehensive understanding of the characteristics and underlying mechanisms that lead to these types of distributions, allowing to better classify variability in systems based on how dissipative they are.

John Aitchison revolutionised in 1982 our way of approaching geochemical data focusing on their relative nature. In this perspective, the investigation of single variables is meaningless due to the entangled structure that links all the parts of a composition. Starting from that time, several developments have characterized the debate within the scientific community, both from the applied and the theoretical point of view. The consequence was that the number of papers where compositional data are consistently and coherently managed increased exponentially. The exploratory phase of compositional data is a very important step in data analysis and modeling. It not only helps to clarify the available sample data structure but also determines the base to develop models to predict time and space changes. Real chemical data along the course of the river Tevere (Tiber) (Italy) and its tributaries are taken to illustrate how compositional techniques help explore compositions and detect patterns and outliers in the data.

This study introduces a robust method for analyzing the geochemical behavior of chemical species in river catchment water. It focuses on isometric log-ratio coordinates obtained from a sequential partition method that successively maximizes the explained variance in the data set. Robust orthonormal coordinates are created based on hierarchical clustering and robust estimation of the variation matrix. Applying this to the water chemistry of Italy's Arno and Tiber basins, the research reveals the associations of variables in data structure and processes across varying geological and climatic conditions. The method uncovers key contrasting geochemical processes and suggests that the behavior of simple balances characterized by lower variances (i.e., Ca2+/HCO3− and Na+/Cl−) are mainly influenced by random fluctuations with no differences between classical or robust methods. However, when balances describe more complex geochemical processes resulting in frequency distributions affected by the presence of bimodality or outliers, significant differences among the two approaches emerge, compromising the data interpretation. The proposed metodology offers more insights into the investigation of catchment geochemistry's resilience to hydroclimatic changes, marking a significant step in understanding large-scale environmental dynamics.

The distribution of geochemical species are typically either (log)normally distributed or follow power laws. Here we link these types of distributions to the dynamics of the system that generates these distributions, showing that power laws can emerge in dissipative systems far from equilibrium while (log)normal distributions are found for species for which the concentrations are close to equilibrium. We use observations of the chemical composition of river water from the sampling space in central Italy as well as discharge data to test this interpretation. We estimate the dissipation rate that results when groundwater drains into the river and the dissolved chemical species mix with the river water. We show that calcium (Ca2+) and bicarbonate (HCO3−) concentrations are close to saturation along most of the downstream length of the Arno river, with decreasing dissipation rates and a lognormal distribution, while sodium (Na+) and chloride (Cl−) concentrations increase substantially downstream, show increased dissipation rates, and are power-law distributed. This supports our hypothesis that power law distributions appear to be indicative of dissipative systems far from thermodynamic equilibrium, while (log)normal distributions indicate weakly dissipative systems close to equilibrium. What this implies is that probability distributions are likely to be indicative of the thermodynamics of the system and the magnitude of disequilibrium constrains the range over which power-law scaling may be observed. This should help us to better identify the generalities and mechanisms that result in these common types of distributions and to better classify variability in systems according to how dissipative these are.

The chemical composition of river waters represents an important matter of investigation to understand environment modifications in response to climate changes and global warming. Prolonged dry periods, heavy flood events, degradation of the lands and ice thawing, modify the chemical composition of river waters influencing the drivers governing the complex dynamics of river catchments where everything comes together. In this framework, Compositional Data Analysis (CoDA) offers methods in which the complex structure of the river water composition and the interrelationships among the various components are put into the proper context for their statistical analysis. In this research, we propose a new CoDA approach combining the robust Mahalanobis distance (D) calculus of ilr-transformed chemical variables and the perturbation difference, both with respect to a pristine compositional benchmark. The aim was to trace the change in the chemical composition of the Eastern Siberian River Chemistry Database where degradation of the permafrost for global warming produces important effects on natural waters. The findings indicate complex multiplicative laws and feedback mechanisms governing solutes in Eastern Siberian rivers, with high values of D found where permafrost is more discontinuous. Perturbations clearly discriminate chemical components more resilient to stresses induced by global changes (Ca2+, Mg2+ and HCO3-) from those whose variability is not maintained under control (Cl-, Na+, SO42-). These outcomes open up a new scenario in searching for spatiotemporal resilience metrics to reveal rivers response to environmental changes.

The analytical and spectroscopic discrimination of marbles coming from quarries used in historical times is a task object of a wide interest in archaeometric investigations. This task is even more difficult, when the goal of the provenance assessment is focused on marbles coming from historical quarries located in a close geographic area. In this paper, we present the results of a systematic Electron Paramagnetic Resonance spectroscopy study aimed at assessing the discrimination criteria among 5 quarries located in the Denizli region (Anatolia, Turkey) that were benefited in Hellenistic and Roman period to provide materials for the buildings in the nearby city of Hierapolis of Phrygia (Turkey). The resulting EPR characterisation is used, in combination with the results of isotope geochemistry and petrological observation, to define criteria able to discriminate the provenance of marble samples from the considered quarries. The criteria arose from the analysis operated through robust compositional statistical techniques over the results of the experimental investigation. In this approach, the internal structure of the multimethodic dataset was unravelled. The results here presented provide evidence of a good discriminating ability of the proposed approach.

A more sustainable global mobility system in which Internal Combustion Engine (ICE) vehicles are replaced by electric vehicles (EVs) powered by lithium-ion batteries (LiBs), taking into account the existing, or inferred, resource, is still possible? The present study aims at providing an answer to this question, through the design of an innovative compartmental model. Model scenarios have been considered accounting for three different estimates of the resource, i.e. the declared reserves, the hypothesized resources, and the full beneficiation of dissolved Li in the oceans. Input data were provided from the historical data of Li primary production, EVs production and recycling rates. The replacement of the ICE vehicles fleet appears possible only under extreme, unrealistic situations, unless the Li "stored" in the oceans is considered exploitable. The main viable policies, i.e. the optimisation of the resource share (almost entirely devoted to mobility issues) and of recycling strategies (pushed up to >90 %) have a modest effect on the achievement of fleet replacement. The total amount of geological lithium resources results as the main limiting factor for the complete transition to EVs. According to the developed model, the peak of production would occur between 2078 and 2130, unless seawater Li is accounted for. The future of the global mobility in a resource-constrained world should be driven toward a model based on the service rather than the individual property of vehicles. Planning a total number of electric vehicles able to assure long term sustainability will be also highly relevant.

The Langelier-Ludwig square diagram is a commonly used diagnostic tool in groundwater chemistry. Suitable groupings of cations and anions are selected and plotted as percentages of milliequivalents with the sums of the selected cations and anions plotted on the y-and x-axes, respectively. It displays relative ratios rather than absolute concentration whereby each axis ranges from 0 to 50 meq%. However, the sample space in which data are represented in a Langelier-Ludwig square diagram is indeed given by the simplex. Incorrect conclusions may be drawn when the compositional nature of compositional data is not taken into account, i.e., a change in one value in one component changes all other values due to due to the constant sum constraint of the measured chemical elements. Correlations are thus influenced by the presence of negative bias in the covariance structure and linear or nonlinear patterns on the square diagram can be misinterpreted. A new version of the Langelier-Ludwig square diagram based on a well-chosen coordinate representation of cations and anions is proposed. The advantage of the revised diagram is that all the information is contained in the log-ratios describing the intricate relationship between chemical species in aqueous solutions. It is shown that the geochemical inter-pretation of this new diagram - based on the relative dominance of major ions and distance from the (robust) barycenter of the data - provides a better and unbiased understanding of water-environment interactions. To further aid interpretation, (robust) tolerance ellipses show the correlation structure in the new version of the Langelier-Ludwig square diagram, and clustering algorithms can be applied to divide the data into groups be-forehand. A bunch of different plotting options and interactive representations complete the implementation in free open-source software. It is recommended to replace the classic Langelier-Ludwig diagram with the new version.

The concept of natural background level (NBL) aims at distinguishing the natural and anthropogenic contributions to concentrations of specific contaminants, as groundwater management and protection tools. This is usually defined as a unique value at a regional scale, even when the hydrogeological and geochemical features of a certain territory are far from homogeneous. The concentration of target contaminants is affected by multiple hydrogeochemical processes. This is the case of arsenic in the Calabria region, where concentrations are definitely variable in groundwater. To overcome the limitation of a traditional approach and to include the intrinsic hydrogeological and geochemical heterogeneity into the definition of the natural contribution to As content in groundwater, an integrated probabilistic approach to the NBL assessment combining aquifer-based preselection criteria and multivariate non-parametric geostatistics was proposed. In detail, different NBL values were selected, based on the aquifer type and/or hydrogeochemical features. Then, these aquifer-based NBL values of arsenic were used in the Probability Kriging method to map the probability of exceedance and to provide contamination risk management tools. This multivariate geostatistical approach that takes advantage of the physico-chemical variables used in the aquifer-based NBL values definition allowed mapping the probability of exceedance of As in a physically-based way. The hydrogeochemical diversity of the study area and all the processes affecting As concentrations in the aquifers have been considered too. As a result, the obtained map was characterized by a short-range and long-range variability due to local hydrogeochemical anomalies and water-rock interaction and/or atmospheric precipitation. By this approach, the NBL exceedance probability maps proved to be less “noisy”, because the local hydrogeochemical conditions were filtered, and more capable of pointing out anthropogenic inputs or very anomalous natural contributions, which need to be investigated more in detail and properly managed.

•A novel method based on EPR spectroscopy and statistical analysis is presented.•Samples consist of CaCO3 layer in a highly complex, multi-layered material.•Identification of the mineralogical nature of a carbonate layer is obtained.•Clues to the assessment of the geographical provenance of CaCO3 were provided.•This microinvasive method is reliable for future applications in cultural heritage studies.

Assessing geochemical baseline and threshold values of potentially toxic elements at adequate scales is funda-mental for distinguishing geogenic contamination from anthropogenic pollution in groundwater. This study was aimed to estimate the regional threshold values of Li, Be, B, Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Rb, Sr, Mo, Ag, Cd, Sb, Te, Ba, Hg, Tl, Pb, Bi, and U (elements listed according to atomic numbers) in groundwater, compare results to guidelines established for drinking water and the protection of groundwater from contamination, investigate the geographical distribution of trace elements, and assess the potential influence of water-rock interaction.A pre-selection aimed at excluding groundwater samples affected by known anthropogenic activities was carefully carried out based on hydrogeochemical characteristics of waters and considering the potential sources of contamination. The resulting dataset was comprised of 1227 groundwater sampling sites located in Sardinia (Italy). Undetected values were treated using the Regression on Order Statistics method. For elements containing >75 % of undetected values and/or a limited number of samples in the dataset (Li, Rb, Sr, Mo, Ag, Te, Tl, Sb, Hg and Bi), the threshold values were estimated using either the 95th or 97.7th percentiles. For the other elements the mean + 2SD (Standard Deviation), the median + 2MAD (Median Absolute Deviation), and the TIF (Tukey Inner Fence) estimators were also calculated.Geochemical maps allowed to recognize the threshold value of each element at different scales. Regional threshold values of the regulated elements B, Al, V, Cr, Cu and Cd in groundwater were below the Italian and World Health Organization drinking water guidelines, whereas Mn and As were above them. Regional threshold values estimated with TIF exceeded the drinking water guidelines for Ni, Se, Pb and U.Results of this study showed that high concentrations of trace elements in groundwater were primarily dependent on the corresponding amount in parent materials with which the groundwater came into contact. Physical-chemical parameters and geochemical characteristics may contribute to enhancing concentrations of some trace elements in groundwater, e.g. As via reductive dissolution of Fe(III)-Mn(IV) hydroxides/oxides, Pb via formation of stable aqueous complexes, and other elements via adsorption onto fine particles with size below 0.4 mu m (i.e. the pore size of filters used).Maps drawn on the centered log-ratio (clr) transformation of hydrogeochemical data, following the CoDA (Compositional Data Analysis) approach, allowed to pinpoint critical areas to be investigated in more detail. For each geological complex, groundwater samples likely representing nearly pristine conditions were identified. The monitoring of these representative groundwater samples may help to pinpoint eventual changes in environ-mental conditions.

In geochemical data analysis, assessing the potential of new techniques to identify compositional time–space changes is of great interest for monitoring purposes. This work aims to evaluate, in the light of the compositional data analysis perspective, the performance of different statistical indices in tracing the evolution of a geochemical composition and the relationships among its parts. To reach this goal, source-to-sink chemical changes in water and stream sediment composition of the Tiber river (central Italy) are analyzed using three indices: (i) the cumulative sum of unclosed perturbation factors of each composition (row sum) with respect to a reference composition; (ii) the robust Mahalanobis distance, describing the compositional differences from the same reference and, (iii) the geometric mean of each composition as a measure able to capture the interactions among the parts. The results highlight the major compositional changes downriver, allowing to explore geochemical footprints’ propagation and their natural or anthropogenic origin. The tested indices are consistent in most cases, particularly if high-variability species are treated separately and low values are rare. Under this latter condition, the geometric mean of the composition shows a close connection with the cumulative sum of unclosed perturbation factors. This indicates that both indices inherit the complex history of the changes, well capturing the interactions among the parts under the influence of environmental drivers. With this awareness, the application of these methods in monitoring and applied geochemical studies could offer new insights into the inner workings of river systems and their resilience to environmental pressures.