57 research outputs found
EuroGeoSurveys geochemical mapping of agricultural and grazing land soil of Europe (GEMAS). Field manual.
REACH (Registration, Evaluation and Authorisation of Chemicals), the new European Chemicals Regulation was adopted in December 2006. It came into force on the 1st June 2007. REACH, as well as the pending EU Soil Protection Directive, require additional knowledge about "soil quality" at the European scale. The GEMAS (geochemical mapping of agricultural soils and grazing land of Europe) project aims at providing harmonized geochemical data of arable land and land under permanent grass cover at the continental, European scale. Geological Surveys in 34 European countries, covering an area of 5.6 million km2, have agreed to sample their territory at a sample density of 1 site each, arable land (0-20 cm) and land under permanent grass cover (0-10 cm), per 2500 km2. Sampling will take place during 2008, following a jointly agreed field protocol which is presented in this report. All samples will be prepared in just one laboratory, a strict quality control procedure has been established and all samples will always be jointly analyzed in just one laboratory for any one chemical element/parameter
Geochemical Atlases of Europe Produced by the EuroGeoSurveys Geochemistry Expert Group: State of progress and potential uses
U-Th signatures of agricultural soil at the European continental scale (GEMAS): Distribution, weathering patterns and processes controlling their concentrations
Agricultural soil (Ap-horizon, 0–20 cm) samples were collected in Europe (33 countries, 5.6 million km2) as part of the GEMAS (GEochemical Mapping of Agricultural and grazing land Soil) soil-mapping project. The GEMAS survey area includes diverse groups of soil parent materials with varying geological history, a wide range of climate zones, and landscapes. The soil data have been used to provide a general view of U and Th mobility at the continental scale, using aqua regia and MMI® extractions. The U-Th distribution pattern is closely related to the compositional variation of the geological bedrock on which the soil is developed and human impact on the environment has not concealed these genuine geochemical features. Results from both extraction methods (aqua regia and MMI®) used in this study support this general picture. Ternary plots of several soil parameters have been used to evaluate chemical weathering trends. In the aqua regia extraction, some relative Th enrichment-U loss is related to the influence of alkaline and schist bedrocks, due to weathering processes. Whereas U enrichment-Th loss characterizes soils developed on alkaline and mafic bedrock end-members on one hand and calcareous rock, with a concomitant Sc depletion (used as proxy for mafic lithologies), on the other hand. This reflects weathering processes sensu latu, and their role in U retention in related soils. Contrary to that, the large U enrichment relative to Th in the MMI® extraction and the absence of end-member parent material influence explaining the enrichment indicates that lithology is not the cause of such enrichment. Comparison of U and Th to the soil geological parent material evidenced i) higher capability of U to be weathered in soils and higher resistance of Th to weathering processes and its enrichment in soils; and, ii) the MMI® extraction results show a greater affinity of U than Th for the bearing phases like clays and organic matter. The comparison of geological units with U anomalies in agricultural soil at the country scale (France) enables better understanding of U sources in the surficial environment and can be a useful tool in risk assessments
GEMAS: Spatial analysis of the Ni distribution on a continental-scale using digital image processing techniques on European agricultural soil data
This study demonstrates the use of digital image processing for the spatial pattern recognition and characterisation of Ni concentrations in topsoil in Europe. Moving average smoothing was applied to the TIN-interpolated grid model to suppress small irregularities. Digital image processing was applied then to the grid. Several NE-SW, E-W and NW-SE oriented features were revealed at the continental scale. The dominant NE-SW linear features follow the Variscan and Alpine orogenies. The highest variability zones are in the Alps and the Balkans where mafic and ultramafic rocks outcrop. A single major E-W oriented north-facing feature runs along the last continental glaciation zone. This zone also coincides with a series of local maxima in Ni concentration along the glaciofluvial deposits. The NW-SE elongated features are located in the Pyrenees, northern Italy, Hellas and Fennoscandia. This study demonstrates the advantages of digital image processing analysis in identifying and characterising spatial geochemical patterns unseen before on conventional colour-surface maps
Mercury in European agricultural and grazing land soils
Agricultural (Ap, Ap-horizon, 0–20 cm) and grazing land soil samples (Gr, 0–10 cm) were collected from a large part of Europe (33 countries, 5.6 million km2) at an average density of 1 sample site/2500 km2. The resulting more than 2 x 2000 soil samples were air dried, sieved to <2 mm and analysed for their Hg concentrations following an aqua regia extraction. Median concentrations for Hg are 0.030 mg/kg (range: <0.003–1.56 mg/kg) for the Ap samples and 0.035 mg/kg (range: <0.003–3.12 mg/kg) for the Gr samples. Only 5 Ap and 10 Gr samples returned Hg concentrations above 1 mg/kg. In the geochemical maps the continental-scale distribution of the element is clearly dominated by geology. Climate exerts an important influence. Mercury accumulates in those areas of northern Europe where a wet and cold climate favours the build-up of soil organic material. Typical anthropogenic sources like coal-fired power plants, waste incinerators, chlor-alkali plants, metal smelters and urban agglomerations are hardly visible at continental scales but can have a major impact at the local-scale
GEMAS: Indium in agricultural and grazing land soil of Europe - Its source and geochemical distribution patterns
Indium is a very rare element, which is usually not reported in geochemical data sets. It is classified as a critical metal, with important applications in the electronics industry, especially in the production of solar panels and liquid-crystal displays (LCDs).Over 4000 samples of agricultural and grazing land soil have been collected for the "Geochemical Mapping of Agricultural and Grazing Land Soil of Europe" (GEMAS) project, carried out by the EuroGeoSurveys Geochemistry Expert Group. Indium concentrations in soil have been analysed using aqua regia extraction followed by ICP-MS. Median values of In for both land use types are nearly identical, 0.0176. mg/kg for agricultural soil and 0.0177. mg/kg for grazing land soil.The spatial distribution patterns of In in European soil are mainly controlled by geology and the presence of Zn and Sn mineralisation. The preference of In to accumulate in the fine-grained fraction of soil with high clay content dominates the major anomaly patterns on the geochemical maps. In the Mediterranean region, secondary In enrichment is visible in karst areas. A notable feature of the In spatial distribution is the large difference between northern and southern Europe, with median values of 0.012 and 0.021. mg. In/kg, respectively, suggesting that, in addition to lithology, weathering and climate are important factors influencing In soil enrichment over time. \ua9 2015 Elsevier B.V
Ce, La and Y concentrations in agricultural and grazing-land soils of Europe
Ce, La and Y from agricultural (Ap) and grazing land (Gr) soils of Europe have been investigated using new
geochemical data produced by the GEMAS (Geochemical mapping of agricultural and grazing land soils) project.
Interpolated maps showing Ce, La, and Y distributions in Ap and Gr were generated using ArcView and classified with the concentration — area (CA) fractal method. The median values of the investigated elements show similar concentrations in Ap and Gr soils, while the median values obtained by XRF-total analyses are generally higher than those obtained by aqua regia extraction, ICP-MS (aqua regia). In general, high pH alkaline soils have higher REE concentrations while specific anomalies can often be correlated with known phosphate and REE mineralizations. The GEMAS and the topsoils media from the FOREGS (Forum of European Geological Surveys) Project databases are compared. FOREGS geochemical data shows larger extended anomalies, such as the European wide north–south division, which are difficult to attribute to local processes, while the GEMAS anomalies are spatially more restricted, and can be related to a number of more local factors (e.g., climate, geology, pH, clay content and presence of till)
Prediction of the concentration of chemical elements extracted by aqua regia in agricultural and grazing European soils using diffuse reflectance mid-infrared spectroscopy
The aim of this study was to develop partial least squares (PLS) models to predict the concentrations of 45 elements in soils extracted by the aqua regia (AR) method using diffuse reflectance Fourier Transform mid-infrared (MIR; 4000–500 cm1) spectroscopy. A total of 4130 soils from the GEMAS European soil
sampling program (geochemical mapping of agricultural soils and grazing land of Europe) were selected. From the full soil set, 1000 samples were randomly selected to develop PLS models. Cross-validation was used for model training and the remaining 3130 samples used for model testing. According to the ratio of
standard deviation to root mean square error (RPD) of the predictions, the elements were allocated into two main groups; Group 1 (successful calibrations, 30 elements), including those elements with RPDP1.5 (the coefficient of determination, R2, also provided): Ca (3.3, 0.91), Mg (2.5, 0.84), Al (2.4, 0.83), Fe (2.2, 0.79), Ga (2.1, 0.78), Co (2.1, 0.77), Ni (2.0, 0.77), Sc (2.1, 0.76), Ti (2.0, 0.75), Li (1.9, 0.73), Sr (1.9, 0.72), K (1.8, 0.70), Cr (1.8, 0.70), Th (1.8, 0.69), Be (1.7, 0.66), S (1.7, 0.66), B (1.6, 0.63), Rb (1.6, 0.62), V (1.6, 0.62), Y (1.6, 0.61), Zn (1.6, 0.60), Zr (1.6, 0.59), Nb (1.5, 0.58), Ce (1.5, 0.58), Cs (1.5, 0.58), Na (1.5, 0.57), In (1.5, 0.57), Bi (1.5, 0.56), Cu (1.5, 0.55), and Mn (1.5, 0.54); and Group 2 for 15 elements with RPD values lower than 1.5: As (1.4, 0.52), Ba (1.4, 0.52), La (1.4, 0.52), Tl (1.4, 0.51), P (1.4, 0.46), U (1.4, 0.45), Sb (1.3, 0.46), Mo (1.3, 0.43), Pb (1.3, 0.42), Se (1.3, 0.40), Cd (1.3, 0.40), Sn (1.3, 0.38), Hg (1.2, 0.33), Ag (1.2, 0.32) and W (1.1, 0.19). The success of the PLS models was found to be dependent on their relationships (directly or indirectly) with MIR-active soil components
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