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1. GEMAS: Spatial analysis of the Ni distribution on a continental-scale using digital image processing techniques on European agricultural soil data

Author

Jordan, Gyozo, Petrik, Attila, De Vivo, Benedetto, Albanese, Stefano, Demetriades, Alecos, Sadeghi, Martiya, M. Andersson, R. Baritz, M. J. Batista, A. Bel-lan, M. Birke, D. Cicchella, W. De Vos, E. Dinelli, M. Ďuriš, 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. Halamić, E. Haslinger, P. Hayoz, R. Hoffmann, J. Hoogewerff, H. Hrvatovic, S. Husnjak, L. Janik, M. Kaminari, J. Kirby, V. Klos, F. Krone, P. Kwecko, L. Kuti, A. Ladenberger, A. Lima, J. Locutura, P. Lucivjansky, A. Mann, D. Mackovych, M. McLaughlin, B. I. Malyuk, R. Maquil, R. G. Meuli, G. Mol, P. Négrel, P. O'Connor, K. Oorts, R. T. Ottesen, A. Pasieczna, V. Petersell, S. Pfleiderer, M. Poňavič, C. Prazeres, U. Rauch, S. Radusinović, C. Reimann, I. Salpeteur, R. Scanlon, A. Schedl, A. Scheib, I. Schoeters, E. Sellersjö, I. Slaninka, J. M. Soriano-Disla, A. Šorša, R. Svrkota, T. Stafilov, T. Tarvainen, V. Trendavilov, P. Valera, V. Verougstraete, D. Vidojević and Z. Zomeni., Jordan, Gyozo, Petrik, Attila, De Vivo, Benedetto, Albanese, Stefano, Demetriades, Aleco, Sadeghi, Martiya, Andersson, M., Baritz, R., Batista, M. J., Bel-lan, A., Birke, M., Cicchella, D., De Vos, W., Dinelli, E., Ďuriš, M., Dusza-Dobek, A., Eggen, O. A., Eklund, M., Ernstsen, V., Filzmoser, P., Flight, D. M. A., Forrester, S., Fuchs, M., Fügedi, U., Gilucis, A., Gosar, M., Gregorauskiene, V., De Groot, W., Gulan, A., Halamić, J., Haslinger, E., Hayoz, P., Hoffmann, R., Hoogewerff, J., Hrvatovic, H., Husnjak, S., Janik, L., Kaminari, M., Kirby, J., Klos, V., Krone, F., Kwecko, P., Kuti, L., Ladenberger, A., Lima, A., Locutura, J., Lucivjansky, P., Mann, A., Mackovych, D., Mclaughlin, M., Malyuk, B. I., Maquil, R., Meuli, R. G., Mol, G., Négrel, P., O'Connor, P., Oorts, K., Ottesen, R. T., Pasieczna, A., Petersell, V., Pfleiderer, S., Poňavič, M., Prazeres, C., Rauch, U., Radusinović, S., Reimann, C., Salpeteur, I., Scanlon, R., Schedl, A., Scheib, A., Schoeters, I., Sellersjö, E., Slaninka, I., Soriano-Disla, J. M., Šorša, A., Svrkota, R., Stafilov, T., Tarvainen, T., Trendavilov, V., Valera, P., Verougstraete, V., D. Vidojević and Z. Zomeni., and The GEMAS Project Team: M. Andersson, R. Baritz, M.J. Batista, A. Bel-lan, M. Birke, D. Cicchella, W. De Vos, E. Dinelli, M.Ďuriš, 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. Halamić, E. Haslinger, P. Hayoz, R. Hoffmann, J.Hoogewerff, H. Hrvatovic, S. Husnjak, L. Janik, M. Kaminari, J. Kirby, V. Klos, F. Krone, P. Kwecko, L. Kuti, A. Ladenberger, A. Lima, J. Locutura, P. Lucivjansky, A. Mann, D. Mackovych, M. McLaughlin, B.I. Malyuk, R. Maquil, R.G. Meuli, G. Mol, P. Négrel, P. O'Connor, K. Oorts, R.T. Ottesen, A. Pasieczna, V. Petersell, S. Pfleiderer, M. Poňavič, C. Prazeres, U. Rauch, S. Radusinović, C. Reimann, I. Salpeteur, R. Scanlon, A. Schedl, A. Scheib, I. Schoeters, E. Sellersjö, I. Slaninka, J.M. Soriano-Disla, A. Šorša, R. Svrkota, T. Stafilov, T. Tarvainen, V.Trendavilov, P. Valera, V. Verougstraete, D. Vidojević and Z. Zomeni

Subjects
Outcrop, Lithology, Soil science, 010501 environmental sciences, 010502 geochemistry & geophysics, 01 natural sciences, Numerical differential calculation, Soil parent material, Geochemistry and Petrology, Ultramafic rock, Spatial pattern, Digital image processing, Lineament analysi, Univariate statistic, Common spatial pattern, Economic Geology, Economic geology, Scale (map), Geomorphology, Geology, Smoothing, 0105 earth and related environmental sciences
Abstract

This study demonstrates the use of digital image processing for the spatial pattern recognition and characterisation of Ni concentrations in topsoil in Europe. Moving average smoothing was applied to the TIN-interpolated grid model to suppress small irregularities. Digital image processing was applied then to the grid. Several NE-SW, E-W and NW-SE oriented features were revealed at the continental scale. The dominant NE-SW linear features follow the Variscan and Alpine orogenies. The highest variability zones are in the Alps and the Balkans where mafic and ultramafic rocks outcrop. A single major E-W oriented north-facing feature runs along the last continental glaciation zone. This zone also coincides with a series of local maxima in Ni concentration along the glaciofluvial deposits. The NW-SE elongated features are located in the Pyrenees, northern Italy, Hellas and Fennoscandia. This study demonstrates the advantages of digital image processing analysis in identifying and characterising spatial geochemical patterns unseen before on conventional colour-surface maps.

Published
2018

2. Distribution of Rb, Ga and Cs in agricultural land soils at European continental scale (GEMAS): Implications for weathering conditions and provenance

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, E. Dinelli, M. Ďuriš, 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. Halamić, 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. Kwećko, 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. Poňavič, S. Pramuka, C. Prazeres, U. Rauch, S. Radusinović, I. Salpeteur, R. Scanlon, A. Schedl, A. J. Scheib, I. Schoeters, P. Šefčik, E Sellersjö, F. Skopljak, I. Slaninka, A. Šorša, R. Srvkota, T. Stafilov, T. Tarvainen, V. Trendavilov, P. Valera, V. Verougstraete, D. Vidojević, A. Zissimos and Z. Zomeni., 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, and 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, E. Dinelli, M. Ďuriš, 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. Halamić, 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. Kwećko, 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. Poňavič, S. Pramuka, C. Prazeres, U. Rauch, S. Radusinović, I. Salpeteur, R. Scanlon, A. Schedl, A.J. Scheib, I. Schoeters, P. Šefčik, E Sellersjö, F. Skopljak, I. Slaninka, A. Šorša, R. Srvkota, T. Stafilov, T. Tarvainen, V. Trendavilov, P. Valera, V. Verougstraete, D. Vidojević, A. Zissimos and Z. Zomeni.

Subjects
Provenance, Weathering, Parent material, Fluorescence spectrometry, Geochemistry, Gallium, 010501 environmental sciences, 010502 geochemistry & geophysics, 01 natural sciences, Agricultural soil, Geochemistry and Petrology, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, 2. Zero hunger, Soil map, geography, geography.geographical_feature_category, Bedrock, Trace element, Geology, 15. Life on land, Rubidium, Caesium, [SDU]Sciences of the Universe [physics], Soil water, [SDE]Environmental Sciences
Abstract

Agricultural soil (Ap-horizon, 0–20 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. The 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 normalised 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. Total concentrations of Rb, Ga, and Cs in European soil were determined by XRF (X-ray fluorescence spectrometry). In addition, hot aqua regia available element concentrations were analysed by inductively coupled plasma-mass spectrometry ICP-MS. Their spatial distribution patterns are shown in geochemical maps. The spatial distribution of Rb, Ga and Cs in Ap soil is quite comparable for the aqua regia and XRF results. The Cs spatial pattern reflects best the large difference between trace element concentrations in northern Europe with predominantly low concentrations and southern Europe with approximately two times higher values. The maximum extent of the last glaciation is visible as a clear concentration break on the map. Lithology of the underlying bedrock is inferred as the major source of geochemical anomalies. In search for characterising the soil parent material and degree of weathering, the soil data were examined for Ga and Cs using two methods. First, the estimated degree of extractability DEi of an element in a sample was calculated by dividing aqua regia available concentrations by the total concentrations obtained by XRF analysis for Al, Na, Ca, K, Rb, Ga and Cs. The different DEi were investigated for 10 geological parent material subgroups (alkaline rocks, granite, calcareous rocks, basalt-mafic rocks, unclassified lithologies, Precambrian granitic gneiss bedrocks, loess, organic soils, schist and soil developed on coarse-grained sandy deposits). The role of clay as main carrier of Ga and Cs phases was inferred for soils developed on several types of bedrock such as granite, gneiss and alkaline rocks. Additionally, an affinity of Cs for loess and carbonate rocks has been observed.

Published
2018
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4. 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

5. 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

6. 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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