In this paper we present a number of equilibrium partition constants for fluorotelomer alcohols and olefins among them data for air/water and octanol/air partitioning. These data are typically required for environmental fate modeling. Our data deviate substantially from those in the literature. A comprehensive check for consistency and plausibility strongly suggests that the data published here are correct. As a consequence the fluorotelomer alcohols will sorb much more to organic phases and have a smaller tendency to remain in the water phase than expected based on previous data. The presented partition data also allow us to derive descriptors for the various kinds of specific (e.g., H-bonds) and nonspecific (e.g., van der Waals) intermolecular interactions thatthe compounds can undergo. These descriptors can be used in polyparameter linear free energy relationships (pp-LFER) in orderto predict a large variety of other partition coefficients (e.g., air/solvent, solvent/ water) as well as the temperature dependence of their air/ water partitioning. The experimental and theoretical approach that we present here can serve as a general example for what needs to be done in order to ensure high quality physicochemical data for organic pollutants.
Chemicals of current environmental concern are often multifunctional and more polar and more complex than classical pollutants such as polychlorinated biphenyls (PCB) or polycyclic aromatic hydrocarbons (PAH). Traditional models for predicting the partitioning in the environment such as group contribution methods or correlations with octanol-water partitioning cannot be expected to work well for such complex chemicals. In contrast, poly parameter Linear Free Energy Relationships (pp-LFERs) have been proven to describe partitioning of polar and nonpolar chemicals in all kinds of sorbing systems. Here, a pp-LFER model for soil-water partitioning was calibrated with data for 79 polar and nonpolar compounds that cover a very wide range of the relevant intermolecular interactions. The data set used for the model calibration in this work is more diverse and covers a wider range of the chemical space than other pp-LFERs published so far. Subsequently, the experimental data for about 50 pesticides and pharmaceuticals -not involved in the model calibration- were used as independent validation of this new calibrated model. The model performs well with a standard error of 0.25 log units for fitting the calibration data and with a root-mean-square error of 0.4 log units for the pesticides and pharmaceuticals. The validation with the independent data set for pesticides and pharmaceuticals also shows that the pp-LFER model reported here performs better compared to earlier published pp-LFER models and to the traditional log Kow correlation.
Highly fluorinated organic compounds are often said to exhibit unique sorption and partition properties. Terms such as "fluorophilicity" have been used to describe these properties, and fudge factors depending on the degree of fluorination have been used in predictive partition models to make them work for fluorinated solutes. Here we demonstrate that highly fluorinated compounds differ from other molecules only in that they exhibit van der Waals interactions much smaller than those of other molecules of same size. A simple cavity model for partitioning is shown to give good results for fluorinated compounds if the nonspecific interactions are correctly parametrized.
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