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

The octanol–air partition coefficient (KOA) 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 KOA values are available for only several hundred compounds. Therefore, the ability to estimate KOA is necessary for screening level evaluation of most chemicals. Although it is possible to estimate KOA from the octanol–water partition coefficient (KOW) 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 KOW and HLC in application to a comprehensive database set of KOA values for screening level environmental assessment. Results indicate that KOW and HLC can be used to accurately predict KOA even when estimated KOW and HLC values are used. For an experimental dataset of 310 log KOA values for different compounds, the KOW–HLC method was statistically accurate as follows: correlation coefficient (r2): 0.972, standard deviation: 0.526, absolute mean error: 0.358 using predominantly experimental KOW and HLC values. When KOW and HLC values were estimated (using the KOWWIN and HENRYWIN programs), the statistical accuracy was: correlation coefficient (r2): 0.957, standard deviation: 0.668, absolute mean error: 0.479.