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Polyparameter linear free energy relationships (pp-LFERs) can predict partition coefficients for a multitude of environmental and biological phases with high accuracy. In this work, the pp-LFER substance descriptors of 40 established and alternative flame retardants (e.g., polybrominated diphenyl ethers, hexabromocyclododecane, bromobenzenes, trialkyl phosphates) were determined experimentally. In total, 251 data for gas-chromatographic (GC) retention times and liquid/liquid partition coefficients (K) were measured and used to calibrate the pp-LFER substance descriptors. Substance descriptors were validated through a comparison between predicted and experimental log K for the systems octanol/water (K(ow)), water/air (K(wa)), organic carbon/water (K(oc)) and liposome/water (K(lipw)), revealing a high reliability of pp-LFER predictions based on our descriptors. For instance, the difference between predicted and experimental log K(ow) was <0.3 log units for 17 out of 21 compounds for which experimental values were available. Moreover, we found an indication that the H-bond acceptor value (B) depends on the solvent for some compounds. Thus, for predicting environmentally relevant partition coefficients it is important to determine B values using measurements in aqueous systems. The pp-LFER descriptors calibrated in this study can be used to predict partition coefficients for which experimental data are unavailable, and the predicted values can serve as references for further experimental measurements.

Well-calibrated polyparameter linear free energy relationships (pp-LFERs) are an accurate way to predict partition coefficients (K) for neutral organic chemicals. In this work, pp-LFER substance descriptors of 111 environmentally relevant substances, mainly pesticides, were determined experimentally using gas chromatographic (GC) retention times and liquid/liquid partition coefficients. The complete set of descriptors for 50 compounds are being reported here for the first time. Validation of the measured substance descriptors was done by comparing predicted and experimental log K for the systems octanol/water (Kow), water/air (Kwa), and organic carbon/water (Koc), all of which indicated a high reliability of pp-LFER predictions based on the determined descriptors (e.g., a root mean squared error of 0.39 for log Kow). The descriptors presented in this work in combination with existing pp-LFER system equations substantially extend (and in some cases correct) our knowledge on partition properties of these 111 chemicals. In addition, the results of this work provide insight on some general guidelines with respect to the method combination best suited for deriving descriptors for environmentally relevant compounds.

Prediction of partition coefficients is essential for screening of environmentally relevant compounds. Prediction methods using only the molecular structure as input are especially useful for this purpose. In the present study, the authors validated 3 prediction method-COSMOtherm, ABSOLV, and SPARC-which are based on more mechanistic approaches than most other quantitative structure-activity relationships. Validation was based on a consistent experimental data set of up to 270 compounds, mostly pesticides and flame retardants. The validation systems included 3 gas chromatographic (GC) columns and 4 liquid/liquid systems that represent all relevant types of intermolecular interactions. Results revealed that the overall prediction accuracy of COSMOtherm and ABSOLV is comparable, whereas SPARC performance is substantially lower than the other methods. For instance, the root mean squared error for the 4 liquid/liquid partition coefficients was 0.65 log units to 0.93 log units for COSMOtherm, 0.64 log units to 0.95 log units for ABSOLV, and 1.43 to 2.85 log units for SPARC. In addition, version and parameterization influences of COSMOtherm on the prediction accuracy were determined.

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