Statistical Modeling of the Partitioning of Nonylphenol in Soil

Abstract

Partition coefficients K P of nonylphenol (NP) in soil were determined for 193 soil samples which differed widely in content of soil organic carbon (SOC), hydrogen activity, clay content, and in the content of dissolved organic carbon (DOC). By means of multiple linear regression analysis (MLR), pedotransfer functions were derived to predict partition coefficients from soil data. SOC and pH affected the sorption, though the latter was in a range significantly below the pK a of NP. Quality of soil organic matter presumably plays an important but yet not quantified role in sorption of NP. For soil samples with SOC values less than 3 g kg −1 , model prediction became uncertain with this linear approach. We suggest that using only SOC and pH data results in good prediction of NP sorption in soils with SOC higher than 3 g kg −1 . Considering the varying validity of the linear model for different ranges of the most sensitive parameter SOC, a more flexible, nonlinear approach was tested. The application of an artificial neuronal network (ANN) to predict sorption of NP in soils showed a sigmoidal relation between K P and SOC. The nonlinear ANN approach provided good results compared to the MLR approach and represents an alternative tool for prediction of NP partitioning coefficients.

Elucidating Differences in the Sorption Properties of 10 Humic and Fulvic Acids for Polar and Nonpolar Organic Chemicals

“…The few works that have investigated the variability of sorption in whole soils indicate that this variability is comparable to the variability found in isolated HAs and FAs. Krahe et al (10), for example, published experimental Ki,oc values for nonylphenol measured in 135 different soils that scattered over almost 1.5 log units. Despite this considerable variance in the sorption properties of NOM, it is still common practice in environmental fate modeling to use a single Ki,oc value for a given compound in different types of NOM.…”

Sorption of selected antiparasitics in soils and sediments

“…The linear regressions with 95% confidence bands of the used dataset fall below the individual K D values for each substance in this region of low f OC . Recommended in OECD guideline 106, the procedure of removing these soils from K OC calculations is corroborated by Krahe et al [ 72 ] who also showed that below 0.3% soil OC linear model approaches become uncertain. They argue that at low concentrations, the accuracy of OC analyses could be reduced and that other sorption surfaces could become more relevant.…”