@article{ISI:000237124700014,
  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},
  added-at = {2008-11-27T09:35:31.000+0100},
  author = {Krahe, S. and During, A. R. and Huisman, A. J. and Horn, L. A. and Gath, S.},
  biburl = {http://www.bibsonomy.org/bibtex/2e1c1474b4ad93a46c93bc28b660d9df9/soilscience},
  interhash = {e99912958296b36cb2e3f931ecd6044d},
  intrahash = {e1c1474b4ad93a46c93bc28b660d9df9},
  issn = {0049-6979},
  journal = {WATER AIR AND SOIL POLLUTION},
  keywords = {IFZ artificial_neural_networks multiple_linear_regression_analysis nonylphenol pedotransfer_function validation},
  number = {1-4},
  pages = {221-237},
  timestamp = {2008-11-27T09:35:31.000+0100},
  title = {Statistical modeling of the partitioning of nonylphenol in soil},
  volume = 172,
  year = 2006
}