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

Partial least squares regression (PLSR) models, using mid-infrared (MIR) diffuse reflectance Fourier-transformed (DRIFT) spectra,wereusedtopredictdistributioncoefficient(Kd)valuesforselectedaddedsolublemetalcations(Agþ,Co 2þ,Cu 2þ,Mn 2þ,Ni 2þ, Pb2þ, Sn 4þ, and Zn2þ) 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 singlepointsolublemetal orradioactiveisotopespike.Theoptimummodels, usingacombinationofMIR–DRIFTspectra andsoilpH,resulted ingoodpredictionsforlogKdþ1forCo,Mn,Ni,Pb,andZn(R20.83)butpoorpredictionsforAg,Cu,andSn(R2<0.50).Thesemodels wereappliedtothepredictionoflogKdþ1valuesintheremaining4313unknownsoils.ThePLSRmodelsprovidearapidandinexpensive tool to assess the mobility and potential availability of selected metallic cations in European soils. Further model development and validationwillbeneededtoenablethepredictionoflogKdþ1valuesinsoilsworldwidewithdifferentsoiltypesandpropertiesnotcovered in the existing mode