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

Author

Négrel, Philippe, Ladenberger, Anna, Reimann, Clemens, Birke, Manfred, Sadeghi, Martiya, The GEMAS Project Team: S. Albanese, M. Andersson, R. Baritz, M. J. Batista, A. Bel lan, D. Cicchella, A. Demetriades, B. De Vivo, W. De Vos, M. Duris, A. Dusza Dobek, O. A. Eggen, M. Eklund, V. Ernstsen, P. Filzmoser, D. M. A. Flight, S. Forrester, M. Fuchs, U. Fügedi, A. Gilucis, M. Gosar, V. Gregorauskiene, W. De Groot, A. Gulan, J. Halamic, E. Haslinger, P. Hayoz, R. Hoffmann, J. Hoogewerff, H. Hrvatovic, S. Husnjak, L. Janik, G. Jordan, M. Kaminari, J. Kirby, J. Kivisilla, V. Klos, F. Krone, P. Kwecko, L. Kuti, A. Lima, J. Locutura, D. P. Lucivjansky, A. Mann, D. Mackovych, M. McLaughlin, B. I. Malyuk, R. Maquil, R. G. Meuli, G. Mol, P. O'Connor, R. K. Oorts, R. T. Ottesen, A. Pasieczna, W. Petersell, S. Pfleiderer, M. Ponavic, S. Pramuka, C. Prazeres, U. Rauch, S. Radusinovic, I. Salpeteur, R. Scanlon, A. Schedl, A. J. Scheib, I. Schoeters, P. Sefcik, E. Sellersjo, F. Skopljak, I. Slaninka, A. Sorsa, R. Srvkota, T. Stafilov, T. Tarvainen, V. Trendavilov, P. Valera, V. Verougstraete, D. Vidojevic, A. Zissimos, Z. Zomeni, DINELLI, ENRICO, Negrel, P., Ladenberger, A., Reimann, C., Birke, M., Sadeghi, M., Albanese, Stefano, Andersson, M., Baritz, R., Batista, M. J., BEL LAN, A., Cicchella, D., Demetriades, A., DE VIVO, Benedetto, DE VOS, W., Dinelli, E., Duris, M., DUSZA DOBEK, A., Eggen, O. A., Eklund, M., Ernstsen, V., Filzmoser, P., Flight, D. M. A., Forrester, S., Fuchs, Fügedi, U., Gilucis, A., Gosar, M., Gregorauskiene, V., DE GROOT, W., Gulan, A., Halamic, J., Haslinger, E., Hayoz, P., Hoffmann, R., Hoogewerff, J., Hrvatovic, H., Husnjak, S., Janik, L., Jordan, G., Kaminari, M., Kirby, J., Kivisilla, J., Klos, V., Krone, F., Kwecko, P., Kuti, L., Lima, Annamaria, Locutura, J., Lucivjansky, D. P., Mann, A., Mackovych, D., Mclaughlin, M., Malyuk, B. I., Maquil, R., Meuli, R. G., Mol, G., O'Connor, P., Oorts, R. K., Ottesen, R. T., Pasieczna, A., Petersell, W., Pfleiderer, S., Ponavic, M., Pramuka, S., Prazeres, C., Rauch, U., Radusinovic, S., Salpeteur, I., Scanlon, R., Schedl, A., Scheib, A. J., Schoeters, I., Sefcik, P., Sellersjo, E., Skopljak, F., Slaninka, I., Sorsa, A., Srvkota, R., Stafilov, T., Tarvainen, T., Trendavilov, V., Valera, P., Verougstraete, V., Vidojevic, D., Zissimos, A., Zomeni, Z., Bureau de Recherches Géologiques et Minières (BRGM) (BRGM), Geological Survey of Sweden, sgu, Geological Survey of Norway (NGU), Geological Survey of Norway, Federal Institute for Geosciences and Natural Resources (BGR), Négrel, Philippe, Ladenberger, Anna, Reimann, Clemen, Birke, Manfred, Sadeghi, Martiya, The GEMAS Project Team: S. Albanese, M. Andersson, R. Baritz, M.J. Batista, A. Bel-lan, D. Cicchella, A. Demetriade, B. De Vivo, W. De Vo, Dinelli Enrico, M. Duri, A. Dusza-Dobek, O.A. Eggen, M. Eklund, V. Ernstsen, P. Filzmoser, D.M.A. Flight, S. Forrester, M. Fuch, U. Fügedi, A. Giluci, M. Gosar, V. Gregorauskiene, W. De Groot, A. Gulan, J. Halamic, E. Haslinger, P. Hayoz, R. Hoffmann, J. Hoogewerff, H. Hrvatovic, S. Husnjak, L. Janik, G. Jordan, M. Kaminari, J. Kirby, J. Kivisilla, V. Klo, F. Krone, P. Kwecko, L. Kuti, A. Lima, J. Locutura, D. P. Lucivjansky, A. Mann, D. Mackovych, M. McLaughlin, B.I. Malyuk, R. Maquil, R.G. Meuli, G. Mol, P. O'Connor, R. K. Oort, R.T. Ottesen, A. Pasieczna, W. Petersell, S. Pfleiderer, M. Ponavic, S. Pramuka, C. Prazere, U. Rauch, S. Radusinovic, I. Salpeteur, R. Scanlon, A. Schedl, A.J. Scheib, I. Schoeter, P. Sefcik, E Sellersjo, F. Skopljak, I. Slaninka, A. Sorsa, R. Srvkota, T. Stafilov, T. Tarvainen, V. Trendavilov, P. Valera, V. Verougstraete, D. Vidojevic, A. Zissimo, and Z. Zomeni

Subjects
Regosol, Soil production function, Weathering, Soil science, 010501 environmental sciences, 010502 geochemistry & geophysics, Agricultural soil, 01 natural sciences, Soil survey, Soil series, Geochemistry and Petrology, [SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry, Environmental Chemistry, 0105 earth and related environmental sciences, Soil map, Germanium, Geochemistry, Pedalfer, 15. Life on land, Pollution, Chemistry, Pedogenesis, Agriculture and Soil Science, 13. Climate action, Soil water, Earth Sciences, Geology
Abstract

International audience; 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.

Published
2016
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2. GEMAS: Prediction of solid-solution partitioning coefficients (Kd) for cationic metals in soils using mid-infrared diffuse reflectance spectroscopy

Author

Janik, Leslie J, Forrester, Sean T, Soriano Disla, José M, Kirby, Jason K, Mclaughlin, Michael J, Reimann, Clemens, The GEMAS Project Team [. . ., S. Albanese, M. Andersson, R. Baritz, M. J. Batista, A. Bel lan, M. Birke, D. Cicchella, A. Demetriades, B. De Vivo, W. De Vos, M. Ďuriš, A. Dusza Dobek, O. A. Eggen, M. Eklund, V. Ernstsen, P. Filzmoser, D. M. A. Flight, M. Fuchs, U. Fügedi, A. Gilucis, M. Gosar, V. Gregorauskiene, W. De Groot, A. Gulan, J. Halamić, E. Haslinger, P. Hayoz, R. Hoffmann, J. Hoogewerff, H. Hrvatovic, S. Husnjak, G. Jordan, M. Kaminari, V. Klos, F. Krone, P. Kwećko, L. Kuti, A. Ladenberger, A. Lima, J. Locutura, P. Lucivjansky, A. Mann, D. Mackovych, B. I. Malyuk, R. Maquil, R. G. Meuli, G. Mol, P. Négrel, P. O'Connor, K. Oorts, R. T. Ottesen, A. Pasieczna, W. Petersell, S. Pfleiderer, M. Poňavič, C. Prazeres, U. Rauch, S. Radusinović, M. Sadeghi, I. Salpeteur, R. Scanlon, A. Schedl, A. J. Scheib, I. Schoeters, E. Sellersjö, I. Slaninka, A. Šorša, R. Srvkota, T. Stafilov, T. Tarvainen, V. Trendavilov, P. Valera, V. Verougstraete, D. Vidojević, Z. Zomeni, DINELLI, ENRICO, Janik, Leslie J, Forrester, Sean T, Soriano-Disla, José M, Kirby, Jason K, Mclaughlin, Michael J, Reimann, Clemen, The GEMAS Project Team [.., S. Albanese, M. Andersson, R. Baritz, M.J. Batista, A. Bel-lan, M. Birke, D. Cicchella, A. Demetriade, B. De Vivo, W. De Vo, E. Dinelli, M. Ďuriš, A. Dusza-Dobek, O.A. Eggen, M. Eklund, V. Ernstsen, P. Filzmoser, D.M.A. Flight, M. Fuch, U. Fügedi, A. Giluci, M. Gosar, V. Gregorauskiene, W. De Groot, A. Gulan, J. Halamić, E. Haslinger, P. Hayoz, R. Hoffmann, J. Hoogewerff, H. Hrvatovic, S. Husnjak, G. Jordan, M. Kaminari, V. Klo, F. Krone, P. Kwećko, L. Kuti, A. Ladenberger, A. Lima, J. Locutura, P. Lucivjansky, A. Mann, D. Mackovych, B.I. Malyuk, R. Maquil, R.G. Meuli, G. Mol, P. Négrel, P. O'Connor, K. Oort, R.T. Ottesen, A. Pasieczna, W. Petersell, S. Pfleiderer, M. Poňavič, C. Prazere, U. Rauch, S. Radusinović, M. Sadeghi, I. Salpeteur, R. Scanlon, A. Schedl, A.J. Scheib, I. Schoeter, E Sellersjö, I. Slaninka, A. Šorša, R. Srvkota, T. Stafilov, T. Tarvainen, V. Trendavilov, P. Valera, V. Verougstraete, D. Vidojević, Z. Zomeni, and ]

Subjects
Principal Component Analysis, Cation, Spectrophotometry, Infrared, Agriculture, Hydrogen-Ion Concentration, Models, Theoretical, Partial least squares regression, Solutions, Soil, Solid-solution partitioning coefficients (K-d), Metals, Cations, Linear Models, Soil Pollutants, Least-Squares Analysis, Mid-infrared spectroscopy
Abstract

Partial least squares regression (PLSR) models, using mid-infrared (MIR) diffuse reflectance Fourier-transformed (DRIFT) spectra, were used to predict distribution coefficient (Kd) values for selected added soluble metal cations (Ag(+), Co(2+), Cu(2+), Mn(2+), Ni(2+), Pb(2+), Sn(4+), and Zn(2+)) in 4813 soils of the Geochemical Mapping of Agricultural Soils (GEMAS) program. For the development of the PLSR models, approximately 500 representative soils were selected based on the spectra, and Kd values were determined using a single-point soluble metal or radioactive isotope spike. The optimum models, using a combination of MIR-DRIFT spectra and soil pH, resulted in good predictions for log Kd+1 for Co, Mn, Ni, Pb, and Zn (R(2) ≥ 0.83) but poor predictions for Ag, Cu, and Sn (R(2) 0.50). These models were applied to the prediction of log Kd+1 values in the remaining 4313 unknown soils. The PLSR models provide a rapid and inexpensive tool to assess the mobility and potential availability of selected metallic cations in European soils. Further model development and validation will be needed to enable the prediction of log K(d+1) values in soils worldwide with different soil types and properties not covered in the existing model.

Published
2015

3. GEMAS: Prediction of solid-solution phase partitioning coefficients (Kd) for oxoanions and boric acid in soils using mid-infrared diffuse reflectance spectroscopy

Author

Janik, Leslie J, Forrester, Sean T, Soriano Disla, José M, Kirby, Jason K, Mclaughlin, Michael J, Reimann, Clemens, the GEMAS research group [. . ., S. Albanese, M. Andersson, R. Baritz, M. J. Batista, A. Bel lan, M. Birke, D. Cicchella, A. Demetriades, B. De Vivo, W. De Vos, M. _Duriš, A. Dusza Dobek, O. A. Eggen, M. Eklund, V. Ernstsen, P. Filzmoser, D. M. A. Flight, M. Fuchs, U. Fügedi, A. Gilucis, M. Gosar, V. Gregorauskiene, W. De Groot, A. Gulan, J. Halamić, E. Haslinger, P. Hayoz, R. Hoffmann, J. Hoogewerff, H. Hrvatovic, S. Husnjak, G. Jordan, M. Kaminari, V. Klos, F. Krone, P. Kwećko, L. Kuti, A. Ladenberger, A. Lima, J. Locutura, P. Lucivjansky, A. Mann, D. Mackovych, B. I. Malyuk, R. Maquil, R. G. Meuli, G. Mol, P. Négrel, P. O'Connor, K. Oorts, R. T. Ottesen, A. Pasieczna, W. Petersell, S. Pfleiderer, M. Poňnavić, C. Prazeres, U. Rauch, S. Radusinović, M. Sadeghi, I. Salpeteur, R. Scanlon, A. Schedl, A. J. Scheib, I. Schoeters, E. Sellersjö, I. Slaninka, A. Šorša, R. Srvkota, T. Stafilov, T. Tarvainen, V. Trendavilov, P. Valera, V. Verougstraete, D. Vidojević, Z. Z.o.m.e.n.i. , . . . ], DINELLI, ENRICO, Janik, Leslie J, Forrester, Sean T, Soriano-Disla, José M, Kirby, Jason K, Mclaughlin, Michael J, Reimann, Clemens and the GEMAS research group [.., S. Albanese, M. Andersson, R. Baritz, M.J. Batista, A. Bel-lan, M. Birke, D. Cicchella, A. Demetriade, B. De Vivo, W. De Vo, E. Dinelli, M. _Duriš, A. Dusza-Dobek, O.A. Eggen, M. Eklund, V. Ernstsen, P. Filzmoser, D.M.A. Flight, M. Fuch, U. Fügedi, A. Giluci, M. Gosar, V. Gregorauskiene, W. De Groot, A. Gulan, J. Halamić, E. Haslinger, P. Hayoz, R. Hoffmann, J. Hoogewerff, H. Hrvatovic, S. Husnjak, G. Jordan, M. Kaminari, V. Klo, F. Krone, P. Kwećko, L. Kuti, A. Ladenberger, A. Lima, J. Locutura, P. Lucivjansky, A. Mann, D. Mackovych, B.I. Malyuk, R. Maquil, R.G. Meuli, G. Mol, P. Négrel, P. O'Connor, K. Oort, R.T. Ottesen, A. Pasieczna, W. Petersell, S. Pfleiderer, M. Poňnavić, C. Prazere, U. Rauch, S. Radusinović, M. Sadeghi, I. Salpeteur, R. Scanlon, A. Schedl, A.J. Scheib, I. Schoeter, E. Sellersjö, I. Slaninka, A. Šorša, R. Srvkota, T. Stafilov, T. Tarvainen, V. Trendavilov, P. Valera, V. Verougstraete, D. Vidojević, Z. Zomeni., and ]

Subjects
Anions, Spectrophotometry, Infrared, Anion, Partial least squares regression, Soil, Boric Acids, Soil Pollutants, Soil Pollutant, Environmental Chemistry, Metal/metalloid, Solid-solution partitioning coefficients (Kd), Solution, Least-Squares Analysis, Mid-infrared spectroscopy, Least-Squares Analysi, Geography, Medicine (all), Agriculture, Hydrogen-Ion Concentration, Models, Theoretical, Health, Toxicology and Mutagenesi, Solutions, Europe, Calibration, Linear Models, Linear Model, Boric Acid
Abstract

The authors' aim was to develop rapid and inexpensive regression models for the prediction of partitioning coefficients (Kd), defined as the ratio of the total or surface-bound metal/metalloid concentration of the solid phase to the total concentration in the solution phase. Values of Kd were measured for boric acid (B[OH]3(0)) and selected added soluble oxoanions: molybdate (MoO4(2-)), antimonate (Sb[OH](6-)), selenate (SeO4(2-)), tellurate (TeO4(2-)) and vanadate (VO4(3-)). Models were developed using approximately 500 spectrally representative soils of the Geochemical Mapping of Agricultural Soils of Europe (GEMAS) program. These calibration soils represented the major properties of the entire 4813 soils of the GEMAS project. Multiple linear regression (MLR) from soil properties, partial least-squares regression (PLSR) using mid-infrared diffuse reflectance Fourier-transformed (DRIFT) spectra, and models using DRIFT spectra plus analytical pH values (DRIFT + pH), were compared with predicted log K(d + 1) values. Apart from selenate (R(2) = 0.43), the DRIFT + pH calibrations resulted in marginally better models to predict log K(d + 1) values (R(2) = 0.62-0.79), compared with those from PSLR-DRIFT (R(2) = 0.61-0.72) and MLR (R(2) = 0.54-0.79). The DRIFT + pH calibrations were applied to the prediction of log K(d + 1) values in the remaining 4313 soils. An example map of predicted log K(d + 1) values for added soluble MoO4(2-) in soils across Europe is presented. The DRIFT + pH PLSR models provided a rapid and inexpensive tool to assess the risk of mobility and potential availability of boric acid and selected oxoanions in European soils. For these models to be used in the prediction of log K(d + 1) values in soils globally, additional research will be needed to determine if soil variability is accounted on the calibration.

Published
2015

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