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

GEMAS: establishing geochemical background and threshold for 53 chemical elements in European agricultural soil

The GEMAS (geochemical mapping of agricultural soil) project collected 2108 Ap horizon soil samples from regularly ploughed fields in 33 European countries, covering 5.6 million km2. The <2 mm fraction of these samples was analysed for 53 elements by ICP-MS and ICP-AES, following a HNO3/HCl/H2O (modified aqua regia) digestion. Results are used here to establish the geochemical background variation and threshold values, derived statistically from the data set, in order to identify unusually high element concentrations for these elements in the Ap samples. Potentially toxic elements (PTEs), namely Ag, B, As, Ba, Bi, Cd, Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb, Sb, Se, Sn, U, V and Zn, and emerging ‘high-tech’ critical elements (HTCEs), i.e., lanthanides (e.g., Ce, La), Be, Ga, Ge, In, Li and Tl, are of particular interest. For the latter, neither geochemical background nor threshold at the European scale has been established before. Large differences in the spatial distribution of many elements are observed between northern and southern Europe. It was thus necessary to establish three different sets of geochemical threshold values, one for the whole of Europe, a second for northern and a third for southern Europe. These values were then compared to existing soil guideline values for (eco)toxicological effects of these elements, as defined by various European authorities. The regional sample distribution with concentrations above the threshold values is studied, based on the GEMAS data set, following different methods of determination. Occasionally local contamination sources (e.g., cities, metal smelters, power plants, agriculture) can be identified. No indications could be detected at the continental scale for a significant impact of diffuse contamination on the regional distribution of element concentrations in the European agricultural soil samples. At this European scale, the variation in the natural background concentration of all investigated elements in the agricultural soil samples is much larger than any anthropogenic impact

Bioavailable 87 Sr/ 86 Sr in European soils: A baseline for provenancing studies

We present 87 Sr/ 86 Sr isotope ratios for ~1200 selected soil samples, collected by the GEMAS consortium from grazing (Gr) and agricultural (Ap) soils in Europe with the aim to better understand the strontium isotope distribution in the bioavailable fraction of the top-soil and its potential for provenancing applications. Spatial analysis shows that there is a clear distinction between coastal (&lt;100 km) and non-coastal (&gt;100 km) samples in their variance and that this variance is mirrored in the sodium concentration, suggesting an important but highly variable contribution from seaspray. We present two 87 Sr/ 86 Sr maps at 25 km × 25 km scale: one based solely on the measured data using a classical kriging approach and one based on a Random Forest model using complementary GEMAS data to predict the strontium isotope composition at the remaining 3000+ GEMAS sampling locations, including appropriate uncertainty assessment. Using a forensic Bayesian likelihood ratio approach, a tool was developed in R to create provenancing likelihood ratio maps. The maps delineate areas of high and low likelihood and allow investigators to direct their resources to areas of interest. For actual forensic case work either the measured or the modelled data can be used as reference data for the overall distribution of 87 Sr/ 86 Sr values in Europe