Journalartikel
Autorenliste: Krahe, S; Düring, RA; Huisman, JA; Horn, AL; Gäth, S
Jahr der Veröffentlichung: 2006
Seiten: 221-237
Zeitschrift: Water, Air, & Soil Pollution
Bandnummer: 172
Heftnummer: 1-4
ISSN: 0049-6979
eISSN: 1573-2932
DOI Link: https://doi.org/10.1007/s11270-005-9077-7
Verlag: Springer
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.
Zitierstile
Harvard-Zitierstil: Krahe, S., Düring, R., Huisman, J., Horn, A. and Gäth, S. (2006) Statistical modeling of the partitioning of nonylphenol in soil, Water, Air, & Soil Pollution, 172(1-4), pp. 221-237. https://doi.org/10.1007/s11270-005-9077-7
APA-Zitierstil: Krahe, S., Düring, R., Huisman, J., Horn, A., & Gäth, S. (2006). Statistical modeling of the partitioning of nonylphenol in soil. Water, Air, & Soil Pollution. 172(1-4), 221-237. https://doi.org/10.1007/s11270-005-9077-7