Geochemical fingerprinting and source discrimination of agricultural soils at continental scale

2108 agricultural soil samples (Ap-horizon, 0-20cm) were collected in Europe (33 countries, area 5.6 million km2) as part of the recently completed GEMAS (GEochemical Mapping of Agricultural and grazing land Soil) soil mapping project. GEMAS soil data have been used to provide a general view of element origin and mobility with a main focus on source parent material (and source rocks) at the continental scale, either by reference to average crustal abundances or to normalized patterns of element mobility during weathering processes. The survey area covers a large territory with diverse types of soil parent materials, with distinct geological history and a wide range of climate zones, and landscapes.To normalize the chemical composition of European agricultural soil, mean values and standard deviation of the selected elements have been compared to model compositions of the upper continental crust (UCC) and mean European river suspended sediment. Some elements are enriched relative to the UCC (Al, P, Pb, Zr,) whereas others, such as Mg, Na and Sr are depleted. The concept of the UCC extended normalization pattern has been applied to selected elements. The mean values of Rb, K, Y, Ti, Al, Si, Zr, Ce and Fe are very similar to the values from the UCC model, even when standard deviations indicate slight enrichment or depletion. Zirconium has the best fit to the UCC model using both mean value and standard deviation. Lead and Cr are enriched in European soil when compared to the UCC model, but their standard deviation values span a large, particularly towards very low values, which can be interpreted as a lithological effect.GEMAS soil data have been normalized to Al and Na, taking into account the main lithologies of the UCC, in order to discriminate provenance sources. Additionally, sodium normalization highlights variations related to the soluble and insoluble behavior of some elements (e.g., K, Rb versus Ti, Al, Si, V, Y, Zr, Ba, and La, respectively), their reactivity (e.g, Fe, Mn, Zn) and association with carbonates (e.g., Ca and Sr). Maps of Europe showing the spatial distribution of normalized compositions and element ratios reveal difficulties with the use of classical element ratios because of the large lithological differences in compositions of soil parent material. The ratio maps and color composite images extracted from the GEMAS data can help to discriminate the main lithologies in Europe at the regional scale but need to be used with caution due to the complexity of superimposed processes responsible for the soil chemical composition

Arsenic in agricultural and grazing land soils of Europe

Arsenic concentrations are reported for the <2 mm fraction of ca. 2200 soil samples each from agricultural (Ap horizon, 0\u201320 cm) and grazing land (Gr, 0\u201310 cm), covering western Europe at a sample density of 1 site/2500 km2. Median As concentrations in an aqua regia extraction determined by inductively coupled plasma emission mass spectrometer (ICP-MS) were 5.7 mg/kg for the Ap samples and 5.8 mg/kg for the Gr samples. The median for the total As concentration as determined by X-ray fluorescence spectrometry (XRF) was 7 mg/kg in both soil materials. Maps of the As distribution for both land-use types (Ap and Gr) show a very similar geographical distribution. The dominant feature in both maps is the southern margin of the former glacial cover seen in the form of a sharp boundary between northern and southern European As concentrations. In fact, the median As concentration in the agricultural soils of southern Europe was found to be more than 3-fold higher than in those of northern Europe (Ap: aqua regia: 2.5 vs. 8.0 mg/kg; total: 3 vs. 10 mg/kg). Most of the As anomalies on the maps can be directly linked to geology (ore occurrences, As-rich rock types). However, some features have an anthropogenic origin. The new data define the geochemical background of As in agricultural soils at the European scale

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