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)

Geogenic and agricultural controls on the geochemical composition of European agricultural soils

Concern about the environmental impact of agriculture caused by intensification is growing as large amounts of nutrients and contaminants are introduced into the environment. The aim of this paper is to identify the geogenic and agricultural controls on the elemental composition of European, grazing an nd agricultural soils

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

The geochemistry of niobium and its distribution and relative mobility in agricultural soils of Europe

The Geochemical Mapping of Agricultural and Grazing Land Soil (GEMAS) project provides soil geochemical data for over 50 elements at a density of 1 sample per 2500 km2 across the European continent. Median baseline total concentrations of niobium (Nb) determined by X-ray fluorescence spectrometry in the <2 mm fraction of 2108 ploughed agricultural soil (0–20 cm) and 2024 grazing land (0–10 cm) samples are 13 and 12 mg/kg, respectively. These concentration levels are more than 23 times higher than the median extractable concentration of Nb obtained by aqua regia digestion. Thus >95% of Nb in soils can be considered ‘immobile’. All anomalous soil concentrations can be related to geogenic processes. Many of the elevated Nb concentrations are underlain by Hercynian granitic intrusions and alkaline volcanic rocks. High Nb levels also correspond to the occurrence of residual soils over karst areas of southeast Europe and, to some extent, loess deposits of central and Eastern Europe. Lowest Nb concentrations are found in soils developed on most recent glacial sediments of northern Europe. Comparison of the aqua regia extractable concentrations of Nb in both sample types collected within <450 m of each other show that concentrations are on average 0.12 mg/kg (15.4%) higher in grazing land soils, suggesting an influence of different land-use practises

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

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)

The use of diffuse reflectance mid-infrared spectroscopy for the prediction of the concentration of chemical elements estimated by X-ray fluorescence in agricultural and grazing European soils .

The aim of this study was to develop partial least squares (PLS) models to predict the concentrations of 45 elements in soils extracted with aqua regia (AR) using mid-infrared (MIR) 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 and MIR spectroscopy used for the development of models to predict Ag, Al, As, B, Ba, Be, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, Hg, In, K, La, Li, Mg, Mn, Mo, Na, Nb, Ni, P, Pb, Rb, S, Sb, Sc, Se, Sn, Sr, Th, Ti, Tl, U, V, W, Y, Zn and Zr concentrations extracted by AR. From the full soil set, 1000 samples were randomly selected for the development of the calibration models, with the remaining 3130 samples used for model validation. Partial least-squares calibration models were used to relate the infrared (IR) spectra and the elemental concentrations in soils. The PLS calibrations were validated using cross validation and elements classified as a function of residual predictive deviation (RPD) values and R2 of the predictions. According to the RPD and R2 values of the validations, the 45 elements were allocated into two main groups; Group 1 (successful calibrations), 30 elements including those elements with RPD and R2 values equal or higher than 1.5 and 0.55, respectively: Ca (3.3, 0.91), Mg (2.5, 0.84), Al (2.4, 0.82), Fe (2.2, 0.79), Ga (2.2, 0.79), Co (2.1, 0.77), Sc (2.1, 0.77), Ni (2.0, 0.76), Ti (2.0, 0.75), Li (1.9, 0.73), Sr (1.9, 0.73), Cr (1.8, 0.69), Th (1.8, 0.69), K (1.8, 0.68), Be (1.7, 0.66), V (1.7, 0.63), S (1.6, 0.64), B (1.6, 0.62), Y (1.6, 0.61), Zn (1.6, 0.61), Rb (1.6, 0.61), Zr (1.6, 0.59), Na (1.5, 0.57), In (1.5, 0.57), Nb (1.5, 0.57), Cs (1.5, 0.57), Ce (1.5, 0.56), Cu (1.5, 0.56), Bi (1.5, 0.55) and Mn (1.5, 0.55); and group 2 for 15 elements with RPD and R2 values lower than 1.5 and 0.55, respectively: As (1.4, 0.52), La (1.4, 0.52), Ba (1.4, 0.52), Tl (1.4, 0.51), P (1.4, 0.46), U (1.4, 0.46), 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, 0.39), Hg (1.2, 0.33), Ag (1.2, 0.32) and W (1.1, 0.19). The success of the PLS calibration models to predict AR extracted elemental concentrations in soils was found to be dependent on their relationships (directly or indirectly) with soil components that showed significant absorbances in the MIR region