147 research outputs found
Graphical statistics to explore the natural and anthropogenic processes influencing the inorganic quality of drinking water, ground water and surface water
Plots of cumulative distribution functions (CDF) are a simple but powerful exploratory data analysis (EDA) tool to evaluate and compare statistical data distributions. Here, empirical CDF plots are used to compare results of four large (476 to 884 samples) national- to continental-scale inorganic water chemistry data sets: (1) European surface water, (2) European tap water, (3) European bottled waters as a proxy for groundwater and (4) Norwegian crystalline bedrock rock groundwater, all analysed at the same laboratory, albeit at different times. For many parameters (e.g., Ba, Cl-, K, SO4
2-) median values and ranges are, given the differing origins and, in some cases, treatment processes of the waters, surprisingly comparable. Unusually high concentrations of some other elements (e.g., B, Be, Br, Cs, F-, Ge, Li, Rb, Te and Zr) appear to be characteristic of deeper-seated, mature groundwaters. Other influences that can be inferred include contamination from well construction or plumbing materials (Cu, Pb, Zn – in tap waters, bottled waters and Norwegian groundwaters), water treatment (Fe, Mn – in tap- and Norwegian groundwater), bottle materials (Sb - bottled waters). The empirical CDF plots also reveal analytical issues for some elements (excessive rounding, element interferences). The best reference for natural and uncontaminated ’water’ is probably provided by the mineral water samples, representing ’deep groundwater’ at the European scale
GEMAS: colours of dry and moist agricultural soil samples of Europe
High resolution HDR colour images of all Ap samples from the GEMAS survey were acquired using a GeoTek Linescan camera. This data set will help to develop new methods for world-wide characterization and monitoring of agricultural soils which is essential for quantifying geologic and human impact on the critical zone environment
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
GEMAS: CNS concentrations and C/N ratios in European agricultural soil
A reliable overview of measured concentrations of TC, TN and TS, TOC/TN ratios, and their regional distribution patterns in agricultural soil at the continental scale and based on measured data has been missing – despite much previous work on local and the European scales. Detection and mapping of natural (ambient) background element concentrations and variability in Europe was the focus of this work. While total C and S data had been presented in the GEMAS atlas already, this work delivers more precise (lower limit of determination) and fully quantitative data, and for the first time high-quality TN data
A density-functional theory approach to the existence and stability of molybdenum and tungsten sesquioxide polymorphs
The sesquioxides of molybdenum and tungsten have been reported as thin films or on surfaces as early as 1971, but the preparation of bulk materials and their crystal structures are still unknown up to the present day. We present a systematic ab initio approach to their possible syntheses and crystal structures applying complementary methods and basis-set types. For both compounds, the corundum structure is the most stable and does not display any imaginary frequencies. Calculations targeted at a high-pressure synthesis starting from the stable oxides and metals predict a reaction pressure of 15 GPa for Mo2O3 and over 60 GPa for W2O3
GEMAS: unmixing magnetic properties of European agricultural soil
High resolution magnetic measurements provide new methods for world-wide characterization and monitoring of agricultural soil which is essential for quantifying geologic and human impact on the critical zone environment and consequences of climatic change, for planning economic and ecological land use, and for forensic applications. Hysteresis measurements of all Ap samples from the GEMAS survey yield a comprehensive overview of mineral magnetic properties in European agricultural soil on a continental scale
15 insights on the global steel transformation
15 INSIGHTS ON THE GLOBAL STEEL TRANSFORMATION
15 insights on the global steel transformation / Witecka, Wido K. (Rights reserved) ( -
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
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
Prediction of the concentration of chemical elements extracted by aqua regia in agricultural and grazing European soils using diffuse reflectance mid-infrared spectroscopy
Prediction of the concentration of chemical elements extracted by aqua regia in agricultural and grazing European soils using diffuse reflectance mid-infrared
spectroscopy / J. M. Soriano-Disla... [et al.]. - Amsterdam : Elsevier, 2013. - il., 2 figuras e 3 tabelas ; 30 cm
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 cm-1) 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 RPD ? 1.5 (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
- …