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Research on magmatic Cl has proven useful for understanding melt evolution, degassing, and other igneous processes. Magmatic Cl behavior varies strongly with its solubility in melt, and Cl solubility and its partitioning between melts and fluids vary with the Cl content of the system, melt composition, pressure, and the abundance of oxidized magmatic sulfur. Given these relationships and given that they differ from other magmatic volatiles, Cl can provide unique insights on magma evolution. We present a new method of interpreting melt Cl concentrations that are normalized to their calculated Cl solubilities, and the most accurate results apply to solubilities computed at 200 MPa due to insufficient experimental data for other pressures. We apply the new method to compositional data for more than 3500 dacitic to rhyolitic melt inclusions and matrix glasses, representing 64 felsic igneous systems, to demonstrate how the behavior of Cl during magmatic, magmatic-hydrothermal, and degassing processes can be more accurately interpreted. Variations in Cl for most of the 64 systems agree with modeled Cl behavior indicative of melt evolution dominated by fractional crystallization of fluid(s)-saturated melts, and the majority of these systems were apparently saturated in fluid(s) well before melt inclusion entrapment. Comparison of Cl solubility-normalized Cl concentrations of these glasses with modeled results identifies magmas saturated in hydrosaline liquid ± vapor at pressures as high as 600 MPa. Modeling of pressure reductions from 600 down to 20 MPa distinguishes other magmas that exsolved hydrosaline liquid as magmas ascend to shallower depths. This new approach also supports computation of Cl concentrations of magmatic fluids at 200 MPa, for each of the >3500 glasses, and shows how the Cl contents of fluids vary with the (fluid/melt) mass ratio. For example, Cl contents of magmatic fluids range from 0.3 to nearly 70 wt.% at fluid/melt mass ratios of 2 × 10−3, and from 0.3 to a maximum of only 11 wt.% Cl for fluid/melt mass ratios of 4.2 × 10−2. Compositional trends in the glass data show either increasing Cl contents of residual melt, essentially no change of Cl in melt, or decreasing Cl contents of aliquots of residual melt with progressive melt evolution. This method identifies melts that have assimilated magmatic or externally sourced hydrosaline liquids. Plots of (measured Cl in melt/modeled solubility of Cl in melt; Cl[Me/Mo]) versus the Larsen melt differentiation index show minimal dispersion for the least-evolved dacitic melts and increasing dispersion with melt evolution to rhyolitic compositions. Increased dispersion may be a consequence and indication of equilibrium or non-equilibrium degassing and/or assimilation of hydrosaline liquid.

Iron slags and ores were collected from 22 sites (A to V) in Preah Khan of Kompong Svay, the area surrounding Phnom Daek, and the Angkor monuments. Iron ores were taken from two outcrops in Phnom Daek. The chemical compositions of fayalite and w&uuml, stite in the iron slags and magnetite in the iron ores were determined using a scanning electron microscope equipped with an energy dispersive spectrometer. Cluster analysis and principal component analysis using averaged chemical compositional data for fayalite allowed for the investigated slag dumps to be classified into two main groups: Groups 1 and 2. The slag dumps in the area surrounding Phnom Daek and those in the Angkor monuments were classified as Group 1, and those in Preah Khan of Kompong Svay were classified as Group 2, except for sites C and U, which were classified as Group 1. Radiocarbon dating was carried out on 10 charcoal fragments from slag dumps outside the Angkor area. The dating results indicate that iron making in Preah Khan of Kompong Svay was conducted in and after the 13th century except for sites C and U, where iron ores may have been supplied from Phnom Daek before the 13th century.

Geochemical studies that focus on environmental applications tend to approach the chemical elements as individual entities and may therefore offer only partial and sometimes biased interpretations of their distributions and behaviour. A potential alternative approach is to consider a compositional data analysis, where every element is part of a whole. In this study, an integrated methodology, which included compositional data analysis, multifractal data transformations and interpolation, as well as enrichment factor analysis, was applied to a geochemical dataset for the Campania region, in the south of Italy, focusing in particular on the behaviour, footprints and sources of a smaller pool of elements: Al, Na, K and P. The initial dataset included 3669 topsoil samples, collected at an average sampling density of 1 site per 2.3 km(2), and analyzed (after an aqua regia extraction) by a combination of ICP-AES and ICP-MS for 53 elements. Frequency based methods (Clr biplot, Enrichment Factor computation) and frequency spatial-method (fractal and multifractal plots) allowed identifying the relationships between the elements and their possible source patterns in Campania soils in relation to a natural occurring concentrations in geogenic material (rocks, soils and sediments) or human input. Results showed how the interpretation of concentration and behaviour of Al, Na, K and P was enhanced thanks to the application of data log-ratio transformation in univariate and multivariate analysis compared to the use of raw or log-normal data. Multivariate analyses with compositional biplot allowed the identification of four element associations and their potential association with the underling geology and/or human activities. When focusing on the smaller pool of elements (Al, P, K and Na), these relationships with the unique geology of the region, were largely confirmed by multifractal interpolated maps. However, when the local background was used for the calculation of the enrichment factor, the resulting interpolated maps allowed to identify smaller areas where the greater concentrations of P could not be possibly associated to a mineralisation (e.g., ultrapotassic rocks) but were more likely to be associated to anthropogenic input such as agriculture activities with potentially extensive use of phosphate fertilizers. The integrated approach of this study allowed a more robust qualitative and quantitative evaluation of elemental concentration, providing in particular new and vital information on the distribution and patterns of P in soils of the Campania region, but also a viable, more robust, methodological approach to regional environmental geochemistry studies.

Determining the viscosity of heavy crude oil is important in the field of petroleum science, and reservoir simulators are routinely used to achieve this goal. In this study, a new empirical model for predicting heavy-oil viscosity is presented. The model was developed using the compositional data of 28 heavy crude oil samples from the Middle East. Viscosity measurements from 196 data points in the 20–80 °C temperature range were used during model development, and another 47 viscosity measurements were used to validate the model. The compositional and viscosity measurements were also used to evaluate the accuracy of previously published methods for predicting heavy-oil viscosities. These methods include corresponding-states models, residual viscosity models, and equations-of-state-based models. The study reveals that none of the previously published methods adequately predict the viscosities of heavy crude oils. On the other hand, it shows that the new empirical model is able to predict the viscosities of heavy oils with an average relative error of 3.8%. The proposed model is much simpler and easier to use than existing methods.

Accelerated glacier melt and runoff may lead to inputs of labile dissolved organic matter (DOM) to downstream ecosystems and stimulate the associated biogeochemical processes. However, still little is known about glacial DOM composition and its downstream processing before entering the ocean, although the function of DOM in food webs and ecosystems largely depends on its composition. Here, we employ a set of molecular and optical techniques (UV-vis absorption and fluorescence spectroscopy, 1H NMR, and ultrahigh-resolution mass spectrometry) to elucidate the composition of DOM in Antarctic glacial streams and its downstream change. Glacial DOM consisted largely of a mixture of small microbial-derived biomolecules. 1H NMR analysis of bulk water revealed that these small molecules were processed downstream into more complex, structurally unrecognizable molecules. The extent of processing varied between streams. By applying multivariate statistical (compositional data) analysis of the DOM molecular data, we identified molecular compounds that were tightly associated and moved in parallel in the glacial streams. Lakes in the middle of the flow paths enhanced water residence time and allowed for both more DOM processing and production. In conclusion, downstream processing of glacial DOM is substantial in Antarctica and affects the amounts of biologically labile substrates that enter the ocean.

The distribution of six common metal contaminants (Cd, Cr, Cu, Ni, Pb, Zn) in the bulk (&lt, 2 mm) and fine fractions (&lt, 63 µm) of freshwater sediments was compared to conclude on the long-existing dilemma which fraction should be used in the investigation of the metal contamination. The environments included in the study (24 rivers, 8 lakes) were very different with respect to sediments origin and composition and they provided a good review of the possible scenarios. For the river sediments, particularly those having &gt, 40% of sand fraction, metal concentrations were up to seven times higher in the fine fraction, implying the necessity for considering sand dilution effect in compositional data analysis. The same samples were also characterized with higher organic matter content (OM) in the fine fraction. Lake environments were characterized by fine-grained sedimentation and the difference between metal concentrations in the bulk and fine fraction was not so expressed. The preparation of samples for the geochemical and compositional data mining should be carried out in accordance with the sedimentological characteristics of the investigated environment. It implies that the insight into geological setting and determination of sedimentological characteristics should be an obligatory part of monitoring/investigating metal contamination in freshwater sediments. For river sediments, the analysis of the fine sediment fraction or correction for sediment lithology are advisable.

21 Pa´ginas.-- 10 Figuras.-- 3 Tablas, Table olives can suffer different types of spoilage during fermentation. In this work, a multi-statistical approach (standard and compositional data analysis) was used for the study of the volatile organic compounds (VOCs) associated with altered (butyric, sulfidic, and putrid) and non-altered (normal) Manzanilla Spanish-style table olive fermentations. Samples were collected from two industrial fermentation yards in Seville (Spain) in the 2019/2020 season. The VOC profiles of altered (n = 4) and non-altered (n = 6) samples were obtained by headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME-GC-MS). Ninety-one VOCs were identified and grouped into alcohols (30), esters (21), carbonyl compounds (12), acids (10), terpenes (6), phenols (6), sulfur compounds (2), and others (4). The association of the VOCs with spoilage samples depended on the standard or compositional statistical methodology used. However, butyric spoilage was strongly linked by several techniques to methyl butanoate, ethyl butanoate, and butanoic acid; sulfidic spoilage with 2-propyl-1-pentanol, dimethyl sulfide, methanol, 2-methylbutanal, 2-methyl-2-butenal, ethanol, 2-methyl-3-buten-2-ol, and isopentanol, while putrid was mainly related to D-limonene and 2-pentanol. Our data contribute to a better characterisation of non-zapatera spoiled table olive fermentations and show the convenience of using diverse statistical techniques for a most robust selection of spoilage VOC markers., This research was funded by Spanish Government (TOBE Project: grant number RTI2018-100883-B-I00).

New lithological and whole rock compositional data show that the main platinum-group element (PGE) horizons of the Flatreef succession show strong compositional similarities to the Merensky and Bastard reefs of the western Bushveld Complex (WBC), notably in terms of many immobile and incompatible minor and trace elements such as TiO2, Zr, Y, and REE. However, Al2O3, CaO, and Na2O contents are markedly lower in the Flatreef, whereas MgO contents are higher. In view of broadly similar silicate mineral compositions in the Flatreef and the WBC reefs, we suggest that the major element compositional differences between the rocks are largely due to higher modal proportions of orthopyroxene and olivine and lower proportions of plagioclase in the Flatreef. The thickness of the mineralised interval is much greater in the Flatreef than in the WBC (several 10 s of m vs ~ 1 m) and the abundance of sulfides in the Flatreef is typically somewhat higher (on average ~ 1.5% vs ~ 1%). These data, complemented by textural observations, are interpreted to reflect enhanced hydrodynamic crystal sorting accompanied by percolation of sulfide melt through incompletely solidified cumulates. Further genetic constraints are provided by metal data: The concentration of Ni (~ 3000 ppm) in the Flatreef is broadly similar to that in the Merensky Reef of the WBC, but Cu contents are markedly higher (average ~ 1500 ppm vs 700 ppm in the WBC). The concentrations of most PGE are slightly lower (Flatreef ~ 1.5–2 ppm Pt, ~ 100–150 ppb Rh; WBC MR 3.7 ppm Pt, 240 ppb Rh), but Pd has broadly similar contents (Flatreef ~ 1.2–2 ppm; WBC MR 1.54 ppm). The relatively high Cu content of the Flatreef is interpreted as a result of assimilation of Cu sulfides from the sedimentary floor rocks. The reason for the enrichment of Pd relative to Pt, especially in the basal rocks, remains unclear. It could reflect mobilisation of Pd via a fluid phase from the country rocks or the interior of the intrusion, relatively enhanced partitioning of Pd into the sulfides, or relative Pt depletion of the earliest magma pulses in response to Pt alloy fractionation triggered by contamination with reducing country rocks.

Chemically, petroleum is an extraordinarily complex mixture of different types of hydrocarbons that are now possible to isolate and identify because of advances in geochemistry. Here, we use biomarkers and carbon isotopes to establish genetic differences and similarities among oil samples. Conventional approaches for evaluating biomarker and carbon isotope relative abundances include statistical techniques such as principal component and cluster analysis. Considering that proportions of the different hydrocarbon molecules are relative parts of a laboratory sample, the data are compositional in nature, thus requiring the use of log-ratio approaches for adequate mathematical modeling. We apply both traditional and compositional modeling approaches to crude oil samples from an onshore area of about 50,000 square miles in southeast Texas. The data comprise 177 crude oil samples from producing oil fields that include key biomarkers, elemental, and isotopic values commonly used in source rock correlation studies. Our results indicate that compositional modeling has higher discriminating power and lower uncertainty than the traditional approach, allowing the identification of up to 16 clusters. Each cluster represents one oil family from a source rock organofacies ranging from Carboniferous to Paleogene. The families provide new insights into important petroleum systems in the Texas onshore region of the Gulf of Mexico sedimentary basin.

A series of quantitative micro X-ray fluorescence (μ-XRF) analyses was performed on a) corroded surface, b) stripped-patina area and c) polished cross section of twenty-five archaeological copper alloys from Iran in order to check the viability of quantitative XRF data for the classification of ancient copper alloys. The limits of detection and quantification and, also, the precision and accuracy of the analytical data were measured using twelve certified reference materials (CRM). The compositional data obtained through these three approaches were statistically evaluated comparing with the compositional data on the same samples obtained by the inductively coupled plasma – optical emission spectroscopy (ICP-OES). We demonstrated that the corroded surfaces are depleted in Ni and Zn and enriched in Pb, Sn and As. Also, we suggest that although μ-XRF quantitative compositional data collected from the corroded surfaces may result in misleading information, the areas with the lowest Sn concentration may represent the closest compositional data to the absolute quantity of Cu, Zn, As and Pb in ancient copper alloys. Moreover, it is shown that the quantitative μ-XRF data obtained from the stripped-patina surface and those from the polished cross sections are comparable with the ICP-OES compositional data and can be confidently used for determining the diversity and technology of ancient copper alloys.

International audience; This work investigated the influence of grape variety, vineyard location, and grape harvest maturity, combined with different oxygen availability treatments, on red wine composition during bottle aging. Chemometric analysis of wine compositional data (i.e., wine color parameters, SO 2 , metals, and volatile compounds) demonstrated that the wine samples could be differentiated according to the different viticultural or bottle-aging factors. Grape variety, vineyard location, and grape maturity showed greater influence on wine composition than bottle-aging conditions. For most measured wine compositional variables, the evolution patterns adopted from the viticultural factors were not altered by oxygen availability treatment. However, contrasting evolution patterns for some variables were observed according to specific viticultural factors, with examples including dimethyl sulfide, phenylacetaldehyde, maltol, and β-damascenone for vineyard locations, 2-methylbutanal, 1,4-cineole, and linalool for grape variety, and methanethiol, methional, and homofuraneol for grape maturity.

Understanding geochemical provenances and their respective geochemical background values is crucial to sustain a proper comprehension of a tropical ecosystem and provides a compatible evaluation for further environmental policy and monitoring. In this research, the concentrations of Mg, Al, Ca, Cr, Fe, Co, Cu, Cd, Ti, Mn, Ni, Zn, Ba, Pb, and organic matter were measured in 78 samples of bottom sediments in order to evaluate the influence of geogenic and anthropogenic chemical sources in the Tres Marias reservoir. Data exploration analysis, multivariate techniques using compositional data, multielemental mapping, geochemical background based on land-use management and geological domains, and enrichment factors were applied to understand the environmental dynamics. Geochemical signatures highlight three pronounced geological structures that control the sediment supply in the Tres Marias reservoir: ultramafic rocks from the Mata da Corda Formation, carbonates from the Tres Marias Formation, and pedogenic cover formed by tropical Latossoils. The median values of Cu, Ti, and Pb are 28.83 mg/kg, 20.36 mg/kg, and 24.92 mg/kg, respectively, all of which exceed the average upper continental crust concentrations. Pb and Cu ratios reach the threshold effect level, whereas Cr reaches the probable effect level proposed in the CONAMA 454/2012 (Brazilian environmental guidelines). This research conjugates multielemental mapping, background evaluation, and enrichment factors to elucidate the geochemistry dynamics of the Tres Marias reservoir in the sense of understanding the behavior of the bottom sediments and to define geochemical reference values for the upper Sao Francisco basin.

Fatty acid (FA) compositions provide insights about storage and feeding modes of marine organisms, characterizing trophic relationships in the marine food web. Such compositional data, which are normalized to sum to 1, have values—and thus derived statistics as well—that depend on the particular mix of components that constitute the composition. In FA studies, if the set of FAs under investigation is different in two separate studies, all the summary statistics and relationships between the FAs that are common to the two studies are artificially changed due to the normalization, and thus incomparable. Ratios of FAs, however, are invariant to the particular choice of FAs under consideration—they are said to be subcompositionally coherent. Here, we document the collaboration between a biochemist (M.G.) and a statistician (M.J.G.) to determine a suitable small set of FA ratios that effectively replaces the original data set for the purposes of univariate and multivariate analysis. This strategy is applied to two FA data sets, on copepods and amphipods, respectively, and is widely applicable in other contexts. The selection of ratios is performed in such a way as to satisfy substantive requirements in the context of the respective data set, namely to explain phenomena of interest relevant to the particular species, as well as the statistical requirement to explain as much variance in the FA data set as possible. Benefits of this new approach are (1) univariate statistics that can be validly compared between different studies, and (2) a simplified multivariate analysis of the reduced set of ratios, giving practically the same results as the analysis of the full FA data set.

Despite the common exploitation of quartzites as raw materials during the African Stone Age, petrographic and geochemical characterization studies have been rarely undertaken. The Naibor Soit outcrop at Oldupai Gorge (Tanzania), considered the main source for quartzite procurement in the area, probably represents the exception to this analytical scarcity. Previous studies have determined variability among quartzites and the existence of singular mineral assemblages and geochemical compositions. In this study, we present the first systematic survey and EDXRF characterization of 86 samples from the two inselbergs that conform Naibor Soit. Samples are classified into nine macroscopic varieties and are mineralogically composed of quartz, muscovite, occasional hematite, rutile, magnetite, anhydrite, and fuchsite. Geochemical analyses, which include previously published data, confirm the existence of inter-/intra-outcrop variability and suggest compositional similarities among some areas of both inselbergs. Our study contributes compositional data and elevated predictive values for future archeological sourcing studies at Oldupai. Our results emphasize the necessity of systematic surveying and sampling to fully understand raw material variability and the factors that may have influenced their selection and exploitation. Introduction - Naibor Soit (Oldupai Gorge, Tanzania) Materials and methods - Field survey and samples classification - EDXRF Results - Macroscopic classification and petrographic analysis - EDXRF Discussion Conclusions

22 Páginas; 5 Figuras; 3 Tablas, Food nutritional labeling is compulsory in the European Union since 13 December 2016. The olive oil fatty acid composition shows high variation depending mainly on the variety. Thus, olive oil nutritional labeling is problematic for the industry. Besides, the analysis of all batches of olive oil using the official methods is expensive. Therefore, the olive oil industry is seriously concerned about solutions for nutritional labeling. In this study, a new rapid technique to measure the nutrients for the olive oil nutritional labeling, is assessed. A novel partial least squares (PLS) calibration model using log-ratio coordinates has been formulated and successfully tested for predicting the percentages of monounsaturated, saturated, and polyunsaturated fatty acids based on visible and near infrared spectroscopy. The model provided accuracy suitable for labeling, under the rules in force in the European Union. The error was generally much lower than the tolerance., J. A. Cayuela expresses gratitude to the European Regional Development Fund, aswell to the Ministry of Economy and Competitiveness of Spain for funding parts of this study, which was developed within the project Recupera 2020 1.4.4., and to the Spanish Council for Scientific Research, for co-funding the grant 20137R065 corresponding to this project. J. Palarea-Albaladejo was partly supported by the Scottish Government's Rural and Environment Science and Analytical Services Division (RESAS) and by the Spanish Ministry of Economy and Competitiveness under the project CODA-RETOS MTM2015-65016-C2-1(2)-R.

Combined analyses of the surface elemental composition and mineralogy of Vesta and Ceres provide insights into their interior evolution, crustal formation, and regolith processes. Compositional data acquired by Dawn's Visible to Infrared Mapping Spectrometer (VIR) and Gamma Ray and Neutron Detector (GRaND) are sensitive to different depths and spatial scales. To compare these data sets, high-resolution maps of absorption band strengths from VIR are degraded to the broad spatial scales sampled by GRaND using a physics-based smoothing algorithm that accounts for the shape and topography of Vesta and Ceres. On Vesta, the distributions of elemental hydrogen and hydroxyl are similar, which implies that hydrogen is primarily in the form of hydroxyl, likely as phyllosilicates delivered by the infall of carbonaceous chondrite impactors. Small differences in the spatial patterns of hydroxyl and hydrogen imply that hydrogen is layered in some locations. In Vesta's dark hemisphere, hydrogen deposits are more extensive than hydroxyl, which indicates higher concentrations of hydrated minerals at depth. In contrast, the distributions of elemental hydrogen and hydrogen-bearing species (OH and NH_4^+) on Ceres are dissimilar. High concentrations of hydrogen in the Ceres’ polar regions (approaching 30 wt.% equivalent H_2O) indicate the presence of subsurface ice as predicted by ice stability theory. The concentration of iron follows a water-dilution trend when plotted as a function of regolith hydrogen content, consistent with the presence of subsurface water ice. The VIR and GRaND data jointly constrain aspects of Ceres’ surface chemistry and evolution. GRaND iron measurements place a firm upper bound on magnetite content, which supports graphitized carbon as an alternative to magnetite as a darkening agent. Lower-bounds on the concentration of carbon in carbonates implied by VIR, together with the ratio of carbonates to organics in carbonaceous chondrite meteorite analogs suggest high concentrations of carbon within Ceres’ regolith. GRaND neutron measurements permit elevated carbon concentrations, equal to or in excess of that found in CI chondrites (greater than a few wt.%). Organic matter, detected by VIR at Ernutet crater, might be widespread and may have been converted to graphite, e.g. via UV exposure, elsewhere on the surface. Furthermore, elevated concentrations of carbonaceous material can explain the difference between iron and hydrogen concentrations measured by GRaND and the CI carbonaceous chondrites, which are representative of the materials from which Ceres accreted. The elemental measurements indicate that ice and rock fractionated during Ceres’ evolution producing a crust that differs in composition from the whole body.

Water-soluble organic matter (WSOM) in air particles has profound effects on climate and human health. At the heart of this environmental significance of WSOM lies a complex set of compounds, of which a major fraction still often remains undeciphered. Yet, not all environmental problems require delving into the molecular-level identification of WSOM constituents. Understanding the contribution of different functional groups to whole aerosol WSOM composition offers a highly important structural dataset that enables a better representation of WSOM in climate studies. For the first time, advanced solid-state 13C nuclear magnetic resonance (NMR) techniques, including nearly quantitative 13C multiple cross polarization/magic angle spinning (multiCP/MAS), multiCP/MAS with dipolar dephasing, multiCP/MAS with 13C chemical shift anisotropy filter, and two-dimensional 1H−13C heteronuclear correlation (2D HETCOR), are applied to acquire an accurate quantitative structural description of whole aerosol WSOM collected in an urban atmosphere. Two urban aerosol WSOM samples collected in two short periods of time, under different wintry weather conditions, were investigated. NMR data successfully pinpointed the variability of whole aerosol WSOM composition, allowing to suggest source-specific structural characteristics for each sample in two short periods of time. A new structural model of urban aerosol WSOM was build based on this compositional data, showing the presence of three independent classes of compounds that vary both in content and molecular diversity within short periods of time: heteroatom-rich aliphatic (either chain or branched), carbohydrate-like moieties, and highly substituted aromatic units. These findings establish advanced solid-state NMR as a promising tool for probing the chemical structures of inhomogeneous aerosol WSOM in rapidly changing atmospheric conditions, allowing to resolve discrepancies between modeled and measured aerosol WSOM. Fulbright Scholar Program; NSF (Award No. 1726346). published

Several studies have investigated the wax precipitation process, focusing on the equations of state, correlations for fusion properties, and calibration of parameters. In most of them, the impact of the fluid characterization on the wax properties has not been addressed widely. In this study, we show that a single characterization scheme is not applicable to all crudes with wax precipitation. However, it is possible to categorize the crudes based on the compositional data and wax parameters to have a primary understanding of the fluid description for modeling. We employed the PC-SAFT equation of state for modeling of liquid phase behavior and the multi-solid framework to describe solid phase. The heptane plus fraction of the studied fluids is defined by the three-parameter gamma distribution of Whitson, et al. [1] , and the continuous description of the plus fraction is discretized by the pseudoization method of Whitson, et al. [2] . We also show the significance of binary interaction parameters on calculating wax appearance temperature and wax weights. The critical volumes of the precipitating hydrocarbons are adjusted to find the best binary interaction parameters values for the WAT and wax weight determination. The WAT and wax weight of eleven crude oil samples are calculated and compared to experimental and modeling results of previous studies. Our model shows considerable improvements in estimating fluid description, WAT, and wax weight compared to other available models. Moreover, we demonstrated that the number of pseudo-components and the heaviest molecular weight in the description of plus fraction highly depend on the compositional data of the heavy end and wax properties. According to our results, 15 pseudo-components with the highest molecular weight of 1200 g/mol would result in the accurate presentation of WAT and wax weight for crudes with WAT higher than 310 K and high wax weights.

We present a new approach to laser ablation inductively coupled plasma mass spectrometry (LA‐ICP‐MS) U‐Pb dating of carbonates based on selection and pooling of pixels from 2‐D elemental and isotopic ratio maps. This image mapping technique is particularly useful for targeting subdomains in samples with complex geological histories. Key major and trace elements that are sensitive to detrital components, postformational fluid ingress, mineralogical changes, or diagenetic overprinting are measured along with the Pb and U isotopic data. Laser sampling is undertaken along successive linear rasters that are compiled into maps using the Monocle add‐on for Iolite, with one pixel in the map corresponding to one time slice of the time‐resolved signal. These element, element ratio, and isotope ratio maps can be overlain over photomicrographs or scanning electron microscopy images to spatially link compositional data to textural and structural features. The pixels corresponding to likely homogeneous age domains can be isolated by applying appropriate selection criteria (e.g., Th < 0.3 ppm, Mg/Ca < 0.004) and pooled into pseudo‐analyses using a proxy for the parent/daughter ratio (e.g., 207Pb/235U, 238U/208Pb) to retrieve the largest possible spread of the data points on isochron diagrams. The approach is best suited for analytical setups capable of rapidly or simultaneously scanning over a large mass range and can yield a precision of ±1% or better on quadrupole instruments depending on U concentration, 238U/204Pb, and age of the sample. The sample‐specific filtering criteria for selection and rejection of data and their rationale can be reported, resulting in more transparency with regard to data processing.

Various genesis of epithermal veins as well as host rock cause complication in the modeling process. Thus LINEST and controlling function were applied to improve the accuracy and the quality of the model. The LINEST is a model which is based on multiple linear regression and refers to a branch of applied statistics. This method concerns directly to the application of t-test (TINV and TDIST to analyses of variables in the model) and F-test (FDIST, F-statistic to compare different models) analysis. Backward elimination technique is applied to reduce the number of variables in the model through all the borehole data. After 18 steps, an optimized reduced model (ORM) was constructed and ranked in order of importance as Pb>Ag>P>Hg>Mn>Nb>U>Sr>Sn>As>Cu, with the lowest confidence level (CL) of 92% for Cu. According to the epigenetic vein genesis of Glojeh polymetallic deposit, determination of spatial patterns and elemental associations accompanied by anomaly separation were conducted by K-means cluster and robust factor analysis method based on centered log-ratio (clr) transformed data. Therefore, 12 samples (cluster 2) with the maximum distance from centroid, indicates the intensity of vein polymetallic mineralization in the deposit. In addition, an ORM for vein population was extracted for Sb>Al>As>Mg>Pb>Cu>Ag elements with the R2 up to 0.99. On the other hand, after 23 steps of optimization process at the host rock population, an ORM was conducted by Ag>Te>Hg>Pb>Mg>Al>Sb>As represented in descending order of t-values. It revealed that Te and Hg can be considered as pathfinder elements for Au at the host rock. Based on the ORMs at each population Ag, Pb, and As were often associated with Au mineralization. The concentration ratio of (tSb × tAl)vein/(tSb × tAl)background as an enrichment index can intensify the mineralization detection. Finally, Glojeh deposit was evaluated to be classified as a vein-style Au (Ag, Pb, As)-polymetallic mineralization.

The multi-element aqua regia National Geochemical Survey of Australia (NGSA) database is used to demonstrate an improved method for quantifying the degree of geochemical similarity (DOGS2) between soil samples. The improvements introduced here address issues relating to compositional data (closure, relative scale). After removing the elements with excessive censored (below detection) values, the rank-based Spearman correlation coefficient (rs) between samples is calculated for the remaining 51 elements. Each element is given equal weight through the rank-based correlation. The rs values for pairs of samples of known similar origin (e.g. granitoid-derived) are significantly positive, whereas they are significantly negative for pairs of samples of known dissimilar origin (e.g. granitoid- v. greenstone-derived). Maps of rs for all samples in the database against various reference samples are used to obtain correlation maps for lithological derivations. Likewise, the distribution of soils having a geochemical fingerprint similar to established mineralized provinces can be mapped, providing a simple, first order mineral prospectivity tool. Sensitivity of results to the removal of up to a dozen elements from the correlation indicates the method to be extremely robust. The new method is compliant with contemporary compositional data analysis principles and is applicable to various digestion methods.

The [MnO|SiO2,Al2O3,FeO,MgO] balanced ratio (i.e. the isometric log-ratio of the MnO concentration relative to the concentration of SiO2, Al2O3, FeO and MgO) of chlorite and of whole-rock composition is an effective discriminant between Mesozoic stratigraphic formations in the Magallanes Basin (Chile). The MnO content in chlorite is only controlled by the host rock chemistry and is dependent on the geological environment. The MnO content in chlorite remains unchanged at low-grade metamorphic conditions. Single-grain chlorite analysis (n = 1042, electron microprobe) and whole-rock analysis (n = 40, X-ray fluorescence) were used to discriminate stratigraphic formations and to decipher differences in the depositional environment in the Magallanes Basin. The samples are from one Upper Jurassic and three Cretaceous sedimentary units that were affected either by low-grade regional metamorphism or by Miocene contact metamorphism. The highest [MnO|SiO2,Al2O3,FeO,MgO] values are recorded in the upper Zapata Formation. The Punta Barrosa, Cerro Toro and Tobífera Formations show slightly lower [MnO|SiO2,Al2O3,FeO,MgO] values. Elevated [MnO|SiO2,Al2O3,FeO,MgO] values at the transition between Zapata and Punta Barrosa Formations record an oxygenated shallow marine environment that can be linked to the closure of the Rocas Verdes Basin and the onset of fold-and-thrust belt formation. Decreasing [MnO|SiO2,Al2O3,FeO,MgO] values from the Punta Barrosa towards the Cerro Toro Formation indicate gradually increasing water depths during the Upper Cretaceous that correlate well with the global sea level.

Wastes from the world's largest manufacturer of DDT (1-chloro-4-[2,2,2-trichloro-1-(4-chlorophenyl)ethyl]benzene) were released into the Los Angeles County municipal sewer system from 1947 to 1971. Following primary treatment, the effluent was discharged through a submarine outfall system whereupon a portion of the DDT and associated degradation products were deposited in sediments of the Palos Verdes Shelf (PVS). Parent DDT is present only in trace amounts in the sediments today, the vast majority having been transformed to DDE (1-chloro-4-[2,2-dichloro-1-(4-chlorophenyl)ethenyl]benzene) shortly following deposition. Previously believed to be inert, DDE is slowly being converted to DDMU (1-chloro-4-[2-chloro-1-(4-chlorophenyl)ethenyl]benzene) and DDMU to DDNU (1-chloro-4-[1-(4-chlorophenyl)ethenyl]benzene) via microbially-mediated reductive dechlorination (RDC). Kinetic and compositional data suggest that this process began sometime in the mid- to late 1970s. Rates of DDE RDC in shelf sediments are spatially variable and have proven difficult to determine accurately. This limits our ability to understand the factors controlling RDC rates and to predict the course of natural recovery. In the present study, concentrations of ten DDT compounds and twelve PCB (polychlorinated biphenyl) congeners were determined in cores collected at two locations on the PVS (stations 3C, 6C, ~ 7 km and ~ 2 km downcurrent from the outfalls, respectively). DDE inventories, normalized to those of non-degrading PCB congeners having similar physico-chemical properties , were modeled to yield first-order RDC rates for the period 1981–2010. Average rates at stations 3C and 6C were 0.044 ± 0.004 and 0.008 ± 0.002 yr− 1, respectively, with depth-dependent RDC rates at station 3C (1992–2003) ranging from 0.0025 to 0.102 yr− 1. Comparison of RDC and total loss (i.e., RDC + physical loss) rates suggests that the average per cent loss of DDE due to RDC is ~ 90% at station 3C (1981–2010) and ~ 57% at station 6C (1992–2010). Trajectories of adjusted molar inventories of DDE, DDMU, and DDNU were forecast using a first-order multi-step reaction series (M-SRS) model. The results for DDE are consistent with the normalization procedure; RDC rates at stations 3C and 6C were 0.036 ± 0.002 yr− 1 and 0.010 ± 0.001 yr− 1, respectively. At station 6C, the DDE to DDMU transformation appears to be the rate limiting step in the reaction sequence, DDE k 1 → DDMU k 2 → DDNU k 3 → unidentified compound(s), whereas at station 3C RDC rates for DDE and DDMU are roughly equivalent. At both locations the transformation rate of DDNU is 7–20 times that of the other steps. Estimated half-lives of DDE at stations 3C and 6C based on the M-SRS model results are ~ 19 and 72 years, respectively.

A 157-cm-long sediment core from Longemer Lake in the Vosges Mountains of France spans the past two millennia and was analyzed for trace metal content and lead isotope composition. Trace metal accumulation rates highlight three main input phases: Roman Times (cal. 100 BC–AD 400), the Middle Ages (cal. AD 1000–1500), and the twentieth century. Atmospheric contamination displays a pattern that is similar to that seen in peat bogs from the region, at least until the eighteenth century. Thereafter, the lake sediment record is more precise than peat records. Some regional mining activity, such as that in archaeologically identified eighteenth-century mining districts, was detected from the lead isotope composition of sediment samples. Compositional data analysis, using six trace metals (silver, arsenic, cadmium, copper, lead and zinc), enabled us to distinguish between background conditions, periods of mining, and of other anthropogenic trace metal emissions, such as the recent use of leaded gasoline.

Modelling of topsoil geochemical data using discriminant function analysis, along with a set of corresponding geochemical maps, portray a legacy of environmental contamination in the city of Sisak. Based on centred log-ratio (clr) transformed compositional data from topsoil samples collected on Kupa-Odra and Sava River floodplain sediments and loess, underlying the Sisak urban area, and regrouped according to their land use characteristics (urban, industrial and agricultural areas), a few element clusters emerged accounting for discrimination between the defined groups. The most prominent feature of the lithological model, as suggested by the first discriminant function, is the carbonate group (Mg, Ca, Sr) versus anthropogenic sourced elements/transition metals (e.g., Sn, Zn, Ba, Mn, Pb, U, Ag, Cr, V) dichotomy separating soil developed on floodplain sediments of Sava and Kupa-Odra Rivers from those evolved on loess. The major attribute of the land use model, according to the main discriminant function, is differentiation between urban/industrial and rural (agricultural) samples based on contrast provided by the carbonate component and other anthropogenic sourced element clusters (predominantly alkaline and concentrated over the loess substrate), in contrast to fertiliser trace and transition element clusters (predominantly acid and disseminated over Kupa-Odra and Sava River floodplain sediments). In both cases, the second discriminant function provides additional information on the secondary level, i.e., in the lithology model the Kupa-Odra sediment group is distinguished from other lithological groupings owing to its predominantly transition element signature. In the land use model, urban soil samples are separated from industrial ones based on the characteristic Na-Sr-Ca-pH(KCl) element association (urban waste) against a typical ‘industrial’ element signature (Zn-Cd-Mn-Pb-Mo).

Different features of geochemical information were studied by comparing spatial distribution of concentration values and compositional data values. Geochemical data are compositional and should be treated as such to avoid spurious correlations and misleading interpretations. However, geochemists are also interested to discuss in terms of elemental concentrations. In this work the spatial distribution of Fe, Mn, Ti, Co, Cr, Ni and V based on 3535 topsoil samples collected in Campania region (Southern Italy) and analysed by ICP-MS after aqua regia digestion, is studied. Unielement maps and CoDA based maps, namely of ilr-transformed data and of two subcompositions of 3 components have been produced and interpreted. Results show that the ilr maps often show different geochemical patterns from those provided by the maps based on raw concentrations, namely for V, Fe and Co. This is not surprising as each studied ilr is a (log)ratio of an element against the others and account for the compositional variability. Nevertheless, the geochemical patterns of both raw and ilr based maps relate mostly with the geolithological features of the region: (1) (Ti, Ni, Cr)log-ratio variables are the best pathfinder in differentiating between volcanic (relative enrichment in Ti) and non-volcanic (relative enrichment in Ni and Cr) areas. (2) Soil alteration phenomena could locally enhance log-ratios of Ti due its high geochemical stability. (3) The spatial analysis of ilr-Fe and ilr Mn variables amplifies their relative degree of enrichment in correspondence of silici-clastic formations suggesting that Mn-Fe oxides of clay minerals mainly dominate the geochemical composition of the soils of the survey area. (4) Local enrichments of Cr and Ni at the main rivers' mouths and in the metropolitan areas of Naples and Salerno, possibly of anthropogenic origin, are highlighted in the 3-part subcomposition analysis. The developed exploration methodology of uni-element geochemical data under a compositional perspective leads to deeper insight and the gain is a more accurate interpretation of processes controlling soils geochemical variability.

A simulation model is developed for pulsed laser remelting that captures the homogenization of surface chemical composition and height variations that occur due to silicon (Si) precipitates in a hypereutectic aluminum-silicon (Al-Si) casting alloy. The model simulates remelting pulse-by-pulse with two sequential and repeated steps: it first predicts surface homogenization by areal averaging within a laser spot and then generates and adds a surface feature, due to thermocapillary flow, whose size depends on the concentration of Si within the homogenized spot. Compositional data of remelted lines was collected with energy-dispersive x-ray spectroscopy and used to verify the homogenization step of the simulation model. It was found that Si precipitates get redistributed by the laser with the peak in Si concentration occurring in the direction opposite that of beam travel. Height data from remelted lines were measured using white light interferometry to verify the accuracy of the remelting model in simulating surface topographical modifications. It was found that variations of approximately ± 1 μm are induced in the Al-Si alloy during pulsed laser remelting due to the Si proeutectic precipitates. This is attributed to differences in laser absorption of Si and Al. Because the Si precipitates absorb more energy from the laser, they experience higher temperatures and temperature gradients, which cause larger thermocapillary flow. The results provide insights into approaches to model surface compositional homogenization that occurs during laser remelting and provides an understanding of surface microstructural and topographical features often seen in laser polished Al-Si casting alloys.

The data represent the first available data set on platinum group element (PGE) levels in Berlin topsoil. In 2013, over 100 topsoil samples (0–20 cm) were collected in the inner city of Berlin. The PGEs in topsoil samples were analysed by ICP-MS after a trace-matrix separation. The results were compared to analyses of PGEs in Berlin topsoil collected at the same sample sites in 1992. The data show an increased accumulation of PGE concentrations in Berlin topsoil during this two-decade interval as a result of gradual increase in the use of vehicles with catalytic converters. A comparison of PGE median concentrations show an increase by a factor of 1.5 for Pt, 3.0 for Pd, 4.3 for Rh, and 3.1 for Au, over the 20-year period. The single element distribution maps of PGEs from 2013 confirm a clear correlation with traffic density. The PGE ratios (Pt/Pd, Pt/Rh, Pd/Rh) were consistent with known catalytic converter compositions, and indicate catalytic exhausts as the main source of these elements. A comparison of the maps of measured raw PGE data with the clr-transformed maps reveals identical distribution patterns (including PGE anomalies). Principal component analysis (PCA) results obtained from the classical statistical approach (standardised) are quite similar to those from PCA carried out using the compositional data analysis (CoDA) approach. Grouping of the PGEs, based on hierarchical cluster analysis, provides a complementary treatment and confirms the PCA results, indicating that the PGE concentrations in Berlin topsoil from 2013 are mainly caused by vehicle emissions.

8 Páginas; 3 Tablas; 2 Figuras, This article contains processed data related to the research published in “Tentative application of compositional data analysis to fatty acid profiles of green Spanish-style Gordal table olives” (Garrido-Fernández et al., 2018) [1]. It provides information on the implementation of compositional data analysis (CoDa) to the fatty acid profiles of Spanish-style Gordal table olives vs the use of conventional statistical analysis (data composition expressed in percentages). Particularly, it includes: i) the matrix of the sequential binary partition used for the balance estimation and the isometric log-ratio transformation (ilr) of the fatty acid profiles, ii) correlation among the diverse fatty acids expressed in percentages and their significances, iii) the ilr transformed values (coordinates in the Euclidean space) obtained following the sequential binary partition previously detailed, iv) the graphical presentation in the Simplex (ternary centred plot) of the treatments as a function of the four fatty acids with the higher log-ratio variances, and v) segregation of treatments based on Cluster Analysis., This work was supported by the Spanish Government under project (AGL2010-15494/ALI, partially financed by European Regional Development Funds, ERDF) and Junta de Andalucía through financial funding to group AGR-125. We also thank Elena Nogales Hernández for technical assistance.

The Zarshuran gold deposit as sediment-hosted Carlin-type has a total reserve of 120 million metric tonnes and an average grade of 3.5 g/t Au. The dominant hydrothermal alterations associated with gold mineralization are argillic and silicic as well as decalcification of the carbonate host rocks. The exploration geochemistry was applied to characterize the mineralization in the subsurface and peripheries of the open-pit mine at Zarshuran in order to enhance the proved reserves of the gold ores. A sampling network of a 10 × 10 m grid (n = 1720) was applied to almost unweathered surface outcrops to determine the primary geochemical haloes in the study area. Initially, the cut-off grades utilized in the exploratory data analysis were applied to identify the threshold values of the trace elements with lognormal distribution. Then, the central log ratio transformation was used to determine the robustness against outliers to characterize the closure problems with compositional data during Principle Component Analysis (PCA). The supra-ore and near-ore geochemical haloes are recognized by the indicator elements like As-Sb-Hg-Te-Au-Ag-Fe-Mn-Ba-F which are associated with mineral assemblages such as arsenical pyrite, orpiment, realgar, cinnabar, barite, and fluorite. The sub-ore geochemical haloes are characterized by index element association like Cu-Mo-Bi-W-Sn-Co-Ni-V-Cr. The ores at Zarshuran are enriched in Au, As, Sb, Ag, Te, Tl, Zn, Pb, and F but depleted in Cu, W, and Sn, as were observed in many other Carlin-type gold deposits. The enrichment factor of indicator elements (except S, Ag, and Sb) gradually decreases in value from the highly altered and mineralized zones (in proximity of the mine) toward the zones with least alteration and mineralization (in the distal parts of the mine). According to PCA analysis, two main types of ore mineralization occurred at Zarshuran, (1) Au mineralization associated with As, Sb, and Hg, and (2) Cu-Zn-Pb base-metal mineralization related to Ag. The ore-forming index was used to determine the primary axial haloes in both shallow ( −120 m) levels. The results of this study show that the main ore body may extend eastwardly and downwardly to greater depths, as was verified by the data obtained from diamond drill cores in the eastern part of the mine.

The CO2-rich spring water (CSW) occurring naturally in three provinces, Kangwon (KW), Chungbuk (CB), and Gyeongbuk (GB) of South Korea was classified based on its hydrochemical properties using compositional data analysis. Additionally, the geochemical evolution pathways of various CSW were simulated via equilibrium phase modeling (EPM) incorporated in the PHREEQC code. Most of the CSW in the study areas grouped into the Ca-HCO3 water type, but some samples from the KW area were classified as Na-HCO3 water. Interaction with anorthite is likely to be more important than interaction with carbonate minerals for the hydrochemical properties of the CSW in the three areas, indicating that the CSW originated from interactions among magmatic CO2, deep groundwater, and bedrock-forming minerals. Based on the simulation results of PHREEQC EPM, the formation temperatures of the CSW within each area were estimated as 77.8 and 150 °C for the Ca-HCO3 and Na-HCO3 types of CSW, respectively, in the KW area; 138.9 °C for the CB CSW; and 93.0 °C for the GB CSW. Additionally, the mixing ratios between simulated carbonate water and shallow groundwater were adjusted to 1:9-9:1 for the CSW of the GB area and the Ca-HCO3-type CSW of the KW area, indicating that these CSWs were more affected by carbonate water than by shallow groundwater. On the other hand, mixing ratios of 1:9-5:5 and 1:9-3:7 were found for the Na-HCO3-type CSW of the KW area and for the CSW of the CB area, respectively, suggesting a relatively small contribution of carbonate water to these CSWs. This study proposes a systematic, but relatively simple, methodology to simulate the formation of carbonate water in deep environments and the geochemical evolution of CSW. Moreover, the proposed methodology could be applied to predict the behavior of CO2 after its geological storage and to estimate the stability and security of geologically stored CO2.

The analysis of organic materials such as phenyl-C61-butyric acid methyl ester (PC61BM) by depth profiling is typically fraught with difficulty due to the fragile nature of the sample. In this work we utilise a gas cluster ion source for the controlled depth profiling of organic materials that would historically have been too fragile to analyse and obtain quantitative compositional data through the whole thickness of the film. In particular we examine the oxygen diffusion and photo-oxidation kinetics of one of the most commonly used electron acceptor materials for many organic optoelectronic applications, namely PC61BM, in both neat films and in blends with polystyrene. Exposure to AM1.5G light and air under ambient conditions, results in a higher level of surface oxidation of blended PC61BM:polystyrene than is observed for either pure control film. Gas cluster ion source depth profiling further confirms that this oxidation is strongest at the extreme surface, but that over time elevated oxygen levels associated with oxidised organic species are observed to penetrate through the whole blended film. The results presented herein provide further insights on the environmental stability of fullerene based organic optoelectronic devices.

Quantitative allochem compositional trends across the Lochkovian-Pragian boundary Event were examined at three sections recording the proximal to more distal carbonate ramp environment of the Prague Basin. Multivariate statistical methods (principal component analysis, correspondence analysis, cluster analysis) of point-counted thin section data were used to reconstruct facies stacking patterns and sea-level history. Both the closed-nature allochem percentages and their centred log-ratio (clr) coordinates were used. Both these approaches allow for distinguishing of lowstand, transgressive and highstand system tracts within the Praha Formation, which show gradual transition from crinoid-dominated facies deposited above the storm wave base to dacryoconarid-dominated facies of deep-water environment below the storm wave base. Quantitative compositional data also indicate progradative-retrogradative trends in the macrolithologically monotonous shallow-water succession and enable its stratigraphic correlation with successions from deeper-water environments. Generally, the stratigraphic trends of the clr data are more sensitive to subtle changes in allochem composition in comparison to the results based on raw data. A heterozoan-dominated allochem association in shallow-water environments of the Praha Formation supports the carbonate ramp environment assumed by previous authors.

The aim of the study was to investigate the association of methane (CH) yields (g/kg DMI) with rumen VFA molar proportions and animal and diet-related covariates from individual animals and multiple experiments. The dataset available consisted of 284 measurements of CH yields for beef cattle from 6 experiments measured in indirect respiration chambers. A compositional modeling approach was employed where VFA measurements were considered as a whole, instead of in isolation, emphasizing their multivariate relative scale. The analysis revealed expected close groupings of acetate and butyrate; propionate and valerate; iso-butyrate and iso-valerate. Linear mixed models were then fitted to examine relationships between CH yield and VFA, represented by meaningful log-contrasts of components called compositional balances, while accounting for other animal and diet-related covariates and random variability between experiments. A compositional balance representing (acetate × butyrate)/propionate best explained the contribution of VFA to variation in CH yield. The covariates DMI, forage:concentrate proportion (expressed as a categorical variable diet type: high concentrate, mixed forage:concentrate or high forage), and diet ME were also statistically significant. These results provided new insights into the relative inter-relationships among VFA measurements and also between VFA and CH yield. In conclusion, VFA molar proportions as represented by compositional balances were a significant contributor to explaining variation in CH yields from individual cattle.

The liquid–liquid equilibria of ternary systems composed of water, butane-2,3-diol, and alcohols such as 2-methylbutan-1-ol, 2-ethylbutan-1-ol, and 4-methylpentan-2-ol were studied at two different temperatures (298.15 and 308.15 K). The experimental tie-line data were compared with the compositional data predicted by the NRTL and UNIQUAC models. The distribution ratio and separation factors were calculated to evaluate the extraction efficiencies. Among the three different branched-chain alcohols selected as extractants, 2-methylbutan-1-ol, which has the shortest chain and branch, provided the highest distribution ratios of 0.55–0.67. The root-mean-square deviation (RMSD) values were calculated for each ternary system, and the average RMSD value was 0.0058, which assures good reliability.

This study presents geochemical data on organic-rich rock samples collected from Riphean—Lower Paleozoic strata (potential source rocks) of the southern Siberian Platform and compositional data on hydrocarbon biomarkers (steranes, terpanes, n-alkanes, 12- and 13-methylalkanes, isoprenanes) and diamondoid hyrocarbons from core samples collected from the Kulindinskaya-1 well, which was drilled by RN-Exploration in 2012 within the Katanga saddle.

The area east of Varanasi is one of numerous places along the watershed of the Ganges River with groundwater concentrations of arsenic surpassing the maximum value of 10 parts per billion (ppb) recommended by the World Health Organization in drinking water. Here we apply geostatistics and compositional data analysis for the mapping of arsenic and iron to help in understanding the conditions leading to the occurrence of elevated level of arsenic in groundwater. The methodology allows for displaying concentrations of arsenic and iron as maps consistent with the limited information from 95 water wells across an area of approximately 210 km2; visualization of the uncertainty associated with the sampling; and summary of the findings in the form of probability maps. For thousands of years, Varanasi has been on the erosional side in a meander of the river that is free of arsenic values above 10 ppb. Maps reveal two anomalies of high arsenic concentrations on the depositional side of the valley, which has started seeing urban development. The methodology using geostatistics combined with compositional data analysis is completely general, so this study could be used as a prototype for hydrochemistry mapping in other areas.

Concern about health effect of Potentially Toxic Elements (PTEs) has led to an increasing global attention about their concentration levels in the environment. Soil geochemistry has been widely used as a tool for environment monitoring. This study investigates topsoil geochemistry of Campania region (Southern Italy) and (i) allows a reliable overview of the PTEs (As, Be, Cd, Co, Cr, Cu, Hg, Ni, Pb, Sb, Se, Sn, Tl, V and Zn) concentration in soils, (ii) enable the investigation of the main factors governing PTEs geochemical variation on a regional scale. Over 7300 topsoil samples were collected from the survey area, which occupies an area of about 13.600 km2. Samples were analyzed for pseudo-total content of 53 elements (major and trace elements) by ICP-MS after aqua regia digestion. Data analysis was performed taking into account both raw data and their compositional nature as a tool for the PTEs environmental evaluation and origin investigation. As, Be, Cu, Pb, Sn, Tl, V and Zn in soils of Campania region show higher median concentration levels than Italian and European ones. In addition, all PTEs exceed the residential/ recreational intervention limit (CSCA) set by Italian legislation. The variation structure of compositional data had been visualized using compositional (clr) biplots and displaying the individual sample observations according to their parent rock. Clr-biplot analysis allowed us to recognize geochemical processes controlling most of soil chemical signatures. Multivariate analysis has been performed and three principal components were determined. PC1 is controlled by enrichment of elements deriving from dominant parent rocks of the area (siliciclastics and volcanoclastics). On the other hand, PC1 reveals the presence of an elemental association dominated by Na, K, U, Th, Zr, Ti, Tl and Be (clr variables), which are pathfinder element of soils developed from volcanic parent material. The second (PC2) component well discriminates the geochemical mobility of the elements in soils. The third (PC3) component reveal the presence of an anthropogenic association (Hg, Sb, Pb, Sn, Au, Ag) which depict a marginal contribution in soil geochemistry of the study area. The generation of clr-biplot helped us in a deeper interpretation of single element spatial distribution patterns. As, Be, Sn, Tl and V spatial distribution shows dominance in soil developed from volcanic products of the main volcanic complexes. Our study showed that element such as Be, Sn and Tl naturally exceed the contamination thresholds in almost the entire territory, due to a quite elevated background concentration values. Hence, Campania region con not be considered entirely contaminated (at this scale) by such elements. Co, Cd, Cr and Ni are more abundant where siliciclastic parent rocks occur.

The application of a novel UV fs Laser Ablation Ionization Mass Spectrometry approach for chemical depth profiling of low-melting point, high surface roughness SnAg solder bump features is presented. The obtained submicrometer resolved three-dimensional compositional data reveal unprecedented information on the distribution of individual elements inside the solder bump matrix. Moreover, the determination of matrix-matched relative sensitivity coefficients allows the first report on quantitative assessment of the SnAg alloy composition. These results significantly contribute to an in-depth understanding of the SnAg plating process. This experimental procedure may find application in future additive performance screening.

A detailed and critical comparative survey is made of the published elemental oxide analytical data which has been obtained for many of the English and Welsh porcleian manufactories discussed earlier in the text. The use of replicate specimens or sampling to establish the experimental errors in the data is discussed and the pitfalls awaiting incomplete data interpretation are highlighted. The selection of multiple component analytical data is merited and several experimental protocols are suggested for the evaluation of porcelain type compositions and the establishment of a factory attribution, including the phosphorus pentoxide, magnesia and lead oxide protocols.

The aim of this study is to estimate the uncertainty of a portable X-ray fluorescence (p-XRF) instrument for the (semi-quantitative) analyses of tiles with underglaze decoration. Before starting the campaign of on-site measurements, the optimum acquisition time and the most accurate calibration mode were selected. For this purpose, the elemental composition of two glass standards of NIST (SRM610 and SRM612) and a Corning A standard were measured with varied times (5-360 s) and in different calibration modes (Mining, Mining Light Elements, Soil, and Rare Earth Elements). Afterwards, a set of blue-and-white tiles that was unearthed at Iznik Tile Kilns Excavation between the dig seasons of 2015 and 2019 was examined with p-XRF by selecting ten points of measure from each layer (body, transparent glaze, and blue coloured areas). The elemental composition of different layers was evaluated by means of the intragroup and intergroup data. They were also compared to the previous studies and found that the corrosion-free, homogeneous, and non-porous surfaces decrease the relative standard deviation (RSD) by increasing the consistency of the compositional data. The major elements found in the matrix of each layer (Al and Si for the body, Pb and Sn for the glaze) have the lowest value of RSD, as expected. However, the comparison of the data with the analysis of the reference materials showed that the content of Mg and also Si, which belong to the low-Z elements group, is shifted relatively towards the higher compositional values. The impossibility of measuring the elemental composition of sodium does not hinder the classification of the samples. Although the transition metals have very low concentrations, p-XRF measurements appear rather consistent and the intrinsic scattering of the data observed for a single artefact is largely smaller than those observed for the tiles of different historical buildings. Thus, it allows the classification to be made related to the different techniques used., İstanbul University Scientific Research Projects Coordination Unit

The quality traits of peanuts (Arachis hypogaea L.) are fundamental to the whole peanut industry. However, many common analyses require the sample to be brought to the laboratory. Therefore, this research explores the feasibility of portable near-infrared spectroscopy combined with a single detection accessory to analyse the composition of peanuts in a single seed level quantitatively. The single detection accessory was specifically designed for spectral data collection considering the internal and external characteristics of single peanuts. Confocal laser scanning microscopy revealed that the oil body and protein body were randomly distributed at cell of single peanuts. The external characteristics of single peanuts were also determined and considered length (11.32–24.25 mm) and width (7.49–12.25 mm). The chemical compositional data (i.e. fat, sucrose, protein, and 16 amino acids) were determined by conventional wet-chemical methods and showed large variation. Principal component analysis on the compositional data showed that peanuts with higher fat contents usually have higher hydrophobic amino acids contents, lower sucrose contents, and lower protein contents. The composition prediction models of single peanuts were estimated using partial least squares regression models that were integrated with different spectral pre-treatments and validated by external sets. The results showed that the prediction models have good performance with a correlation coefficient above 0.88 (calibration) and 0.83 (prediction) and a residual prediction deviation above 1.5 except for a few indicators. Overall, the portable near-infrared spectroscopy offered reliable methods to assess the major components and amino acids quantitatively in a single peanut, which will improve the raw material quality in the peanut industry through the simultaneous and short-term determination of multiple indicators.

International audience; The extraction of palaeoenvironmental (palaeoclimatic) signals from the chemical composition of siliciclastic sediments is valuable for the reconstruction of past environments, particularly in continental basins. Here we test novel weathering proxies, which are less sensitive to lithological control than the previously used raw element ratios K/Al, K/Ti, and K/Rb: (1) local enrichment factors of K/Al, Mg/Al, and K/Rb, i.e., the element ratios corrected for grain size- and matrix composition using local background functions (Al/Si, Fe, and Ca as explanatory variables) and ordinary regression and (2) robust regression residuals of those element ratios based on isometric log-ratio coordinates of the most relevant “lithogenic” elements (Ca, Fe, Rb, Si, Zr) in the chemical composition. Chemical weathering proxies can be obtained from departures of chemical composition of sedimentary profiles from relationships with other chemical elements, in particular those with grain-size control. The resulting weathering proxies were examined for the Miocene deposits from the Most Basin, the Czech Republic, which recorded one of the major warm episodes of the Cenozoic time – the Miocene Climatic Optimum. The performance of weathering proxies has been checked by (1) comparison of individual proposed proxies in one drill core HK930, (2) detailed analysis of orbital signals in the relevant compositional functions in HK930; and (3) lateral correlation of three cores HK930, DU7, and DO565 of the same basin. The novel proxies show lateral stability and orbital signatures of short eccentricity, obliquity, and precession, confirming their usefulness in palaeoenvironmental studies. Corrections for grain-size and carbonate contents should help to isolate climatic content from the weathering proxies, although in the studied sediments it weakened the precession component in the orbital signal, as grain-size proxies and other compositional data also carried orbital signals. We propose to consider these proxy ideas in palaeoclimatic reconstructions based on chemical weathering proxies.

The aims of this study were to investigate the occurrence and distribution of total mercury (Hg) and other trace elements of environmental concern, such as arsenic (As), copper (Cu), chromium (Cr), manganese (Mn), nickel (Ni), lead (Pb), zinc (Zn) and vanadium (V), in soils from the abandoned Mernik cinnabar mine in eastern Slovakia. For this purpose, thirty soil samples from two depth intervals within the mine area (n = 60 soil samples) and additional sixteen soil samples from adjacent areas (n = 25 soil samples) were collected. Total Hg was measured by atomic absorption spectrometry, while As and other metals were analyzed using inductively coupled plasma atomic emission spectrometry. High mercury concentrations (> 100 mg/kg with a maximum of 951 mg/kg) were observed only in surface soils close to mine waste heaps and adits. Otherwise, Hg concentrations in the majority of surface soils were lower (0.14–19.7 mg/kg), however, higher than Hg in soils collected from sites outside the mine area (0.19–6.92 mg/kg) and even considerably higher than Hg in soils at sites not influenced by the Mernik mine. Elevated Cr and Ni concentrations in soils regardless of their sampling sites (mean of 276 mg/kg and median of 132 mg/kg for Cr and 168 mg/kg and 81 mg/kg for Ni, respectively) were attributed to the lithology of the area; the soils are underlain by the sediments of the Central Carpathian Palaeogene, containing a detritus of ultrabasic rocks. As our geochemical data are compositional in nature, they were further treated by compositional data analysis (CoDA). Robust principal component analysis (RPCA) applied on centred (clr) log-ratio-transformed data and correlation analysis of compositional parts based on symmetric balances distinguished very well different sources of origin for the chemical elements. The following three element associations were identified: Hg association with the main source in mining/roasting, Cr–Ni association derived from bedrock and As–Cu–Mn–Pb–Zn–V association (natural background and minor sulphides/sulfosalts in mineralized rocks). The values of geoaccumulation index and enrichment factor suggested that concentrations of Hg in the soils were influenced by human industrial activities.

Coal mine gas originates from the gas emission zone (GEZ) of the mine, as well as the longwall face and pillars. Gas emissions are controlled directly at the sources using horizontal or vertical boreholes drilled from surface or from the entries in advance of mining, or it is captured from the fractured and caved zones (gob) using ventholes during mining. The rest of the gas, especially that gas that originates from the longwall face and caved zone, mixes with the ventilation air and travels through bleeder and return entries before being exhausted to atmosphere from air shafts. Although the gas associated with mining mostly focuses on methane, the gas is not pure methane but is a mixture (where both the components and their quantities vary depending on the sampling location). Understanding the evolution of the composition of the gas from source to different sampling and evaluation points in mines using proper statistical analysis and interpretation methods can lead to better designed degasification and ventilation systems and the selection of the most adequate utilization method for generating energy from the gas. In this work, we present the results of compositional data analysis (CoDa) of gases sampled at different locations in a longwall mine operating in Pennsylvanian coal-bearing strata in the Northern Appalachian coal basin. Sampling locations were from accessible parts of the bleeder entries, returns, bleeder evaluation points and shafts within the mine, and also from gob gas ventholes (GGV) and coal degasification boreholes drilled in the panel areas. In addition, desorbed gas samples from seams that are important for the mine were included in the analyses for comparison. The compositional data analysis showed that the gas composition shifts based on the sampling location, putting in-mine and pure coalbed gases on the opposite ends. Removal of air from the samples did not change this observation suggesting that oxygen is depleted especially for in-mine samples, which is due to oxidation. Results also suggested that desorbed gas samples may not represent the composition of the coal seam gas.