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, 0–20 cm) and grazing land (Gr, 0–10 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

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: Source, distribution patterns and geochemical behaviour of Ge in agricultural and grazing land soils at European continental scale

Agricultural soil (Ap-horizon, 0–20 cm) and grazing land soil (Gr-horizon, 0–10 cm) samples were collected from a large part of Europe (33 countries, 5.6 million km2) as part of the 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 mobility 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 includes a diverse group of soil parent materials with varying geological history, a wide range of climate zones, and landscapes. The concentrations of Ge in European soil were determined by ICP-MS after an aqua extraction, and their spatial distribution patterns generated by means of a GIS software. The median values of Ge and its spatial distribution in Ap and Gr soils are almost the same (0.037 vs. 0.034 mg/kg, respectively). The majority of Ge anomalies is related to the type of soil parent material, namely lithology of the bedrock and minor influence of soil parameters such as pH, TOC and clay content. Metallogenic belts with sulphide mineralisation provide the primary source of Ge in soil in several regions in Europe, e.g. in Scandinavia, Germany, France, Spain and Balkan countries. Comparison with total Ge concentrations obtained from the Baltic Soil Survey shows that aqua regia is a very selective method with rather low-efficiency and cannot provide a complete explanation for Ge geochemical behaviour in soil. Additionally, large differences in Ge distribution are to be expected when different soil depth horizons are analysed

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

GEMAS: Spatial distribution of the pH of European agricultural and grazing land soil

During 2008 the GEochemical Mapping of Agricultural Soils (GEMAS) project collected 2108 agricultural (ploughed soil, Ap horizon, 0–20 cm) and 2023 grazing land soil samples (Gr, 0–10 cm) evenly spread over 33 European countries and covering an area of 5.6 million km2. The pH of all samples was determined by one single laboratory applying a 0.01 M CaCl2 extraction, and following a strict quality-control procedure. The resulting pH-value distributions for European Ap and Gr soil are both bimodal. Broad acidic modes, with pH between 4 and 6, and sharp alkaline modes, with pH between 7 and 8 due to the Ca2+ buffer system, are clearly separated. The European median pH is 5.8 for the GEMAS Ap soil samples and 5.5 for the GEMAS Gr soil samples. According to the pH distribution maps, Europe is separated into two main zones: northern Europe with generally lower pH values (Ap: 5.2, Gr: 4.8), dominated by acidic soils occurring in Fennoscandia, and southern Europe with higher pH values (Ap: 6.3, Gr: 5.9), dominated by carbonate rich soils. The separation line coincides with the southern border of the sediments of the last glaciation. The dominant factors controlling pH at the European scale are thus geology (crystalline bedrock) in combination with climate (temperature and precipitation). The GEMAS pH maps mainly reflect the natural site conditions on the European scale, whilst anthropogenic impact is hardly detectable. The GEMAS results provide a unique set of homogenous and spatially representative soil pH data for the continent. The data set defines a dependable continental-scale background, and offers the possibility to calibrate studies on more detailed scales

GEMAS: Cadmium distribution and its sources in agricultural and grazing land soil of Europe â\u80\u94 Original data versus clr-transformed data

Over 4000 agricultural and grazing land soil samples were collected for the â\u80\u9cGeochemical Mapping of Agricultural and Grazing Land Soil of Europeâ\u80\u9d (GEMAS) project carried out by the EuroGeoSurveys Geochemistry Expert Group. The samples were collected in 33 European countries, covering 5.6 million km2at a density of 1 sample site per 2500 km2. All samples were analysed by ICP-MS following an aqua regia extraction. The European median Cd concentration is 0.182 mg/kg in agricultural soil and 0.197 mg/kg in grazing land soil (including eastern Ukraine). The Cd map demonstrates the existence of two different geochemical background regimes in northern and southern Europe, separated by the southern limit of the Quaternary glaciation. Cadmium shows two times higher background concentrations in the older and more weathered southern European soil than in northern European soil. The spatial distribution patterns of Cd in the collected soil samples are mainly governed by geology (parent material and mineralisation), as well as weathering, soil formation and climate since the last glaciation period. Locally, in several areas, the natural anomaly pattern is overprinted by anthropogenic emissions from former mining, ore processing and related metal industries. Some Cd anomalies can be attributed to urbanisation and the use of fertilisers. A comparison of the raw data Cd concentration map with its clr-transformed counterpart and selected single element ratio maps demonstrates that substantial additional information about sources and processes governing the distribution of Cd in agricultural soil at the European scale can be obtained. Results of a PCA, carried out following the classical approach (standardised) versus a PCA based on the statistically acceptable approach, using clr-transformed data, are quite comparable

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) regression models using diffuse reflectance Fourier transform mid-infrared (MIR) spectroscopy for the prediction of the concentration of elements in soil determined by X-ray fluorescence (XRF). A total of 4130 soils from the GEMAS European soil sampling program (geochemical mapping of agricultural soils and grazing land of Europe) were used for the development of models to predict concentrations of Al, As, Ba, Ca, Ce, Co, Cr, Cs, Cu, Fe, Ga, Hf, K, La, Mg, Mn, Na, Nb, Ni, P, Pb, Rb, Sc, Si, Sr, Th, Ti, V, Y, Zn and Zr in soil using MIR spectroscopy. The results were compared with those obtained where MIR models were developed with the same soils but using the concentration of elements extracted with aqua regia (AR). The PLS models were cross-validated against the experimental log-transformed XRF values of all the elements. The calibration models were derived from a set of 1000 randomly selected calibration samples. The rest of the samples (3130) were used as an independent validation set. According to the residual predictive deviation (RPD), predictions were classified as follows: ‘‘Good quality’’, Ca (2.9), Mg (2.5), Al (2.3), Fe (2.2), Ga (2.2), Si (2.1), Na (2.0); ‘‘Indicator quality’’, V (1.9), Ni (1.9), Sc (1.9), K (1.8), Ti (1.8), Rb (1.8), Zn (1.7), Co (1.7), Zr (1.6), Cr (1.6), Sr (1.6), Y (1.6), Nb (1.6), Ba (1.5), Mn (1.5), As (1.5), Ce (1.5); ‘‘Poor quality’’, Cs (1.4), Th (1.4), P (1.4), Cu (1.4), Pb (1.3), La (1.2), Hf (1.1). Good agreement was observed between the RPD values obtained for the elements analysed in this study and those from the AR study. Despite the different elemental concentrations determined by the XRF method compared to the AR method, MIR spectroscopy was still capable of predicting elemental concentrations

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