Estimating octanol–air partition coefficients with octanol–water partition coefficients and Henry’s law constants

Abstract

The octanol–air partition coefficient ( K OA) is useful for predicting the partitioning behavior of organic compounds between air and environmental matrices such as soil, vegetation, and aerosol particles. At present, experimentally determined K OA values are available for only several hundred compounds. Therefore, the ability to estimate K OA is necessary for screening level evaluation of most chemicals. Although it is possible to estimate K OA from the octanol–water partition coefficient ( K OW) and Henry’s law constant (HLC), various concerns have been raised in regard to the usability of this estimation methodology. This work examines the accuracy and usability of K OW and HLC in application to a comprehensive database set of K OA values for screening level environmental assessment. Results indicate that K OW and HLC can be used to accurately predict K OA even when estimated K OW and HLC values are used. For an experimental dataset of 310 log K OA values for different compounds, the K OW–HLC method was statistically accurate as follows: correlation coefficient ( r 2): 0.972, standard deviation: 0.526, absolute mean error: 0.358 using predominantly experimental K OW and HLC values. When K OW and HLC values were estimated (using the KOWWIN and HENRYWIN programs), the statistical accuracy was: correlation coefficient ( r 2): 0.957, standard deviation: 0.668, absolute mean error: 0.479.