Henry’s Law ConstantA General-Purpose Fragment Model to Predict Log K aw from Molecular Structure

Henry’s law constant is important for assessing the environmental fate of organic compounds, including polar accumulation, indoor contamination, and the impact of airborne predominance on persistence. Moreover, it can be used in the context of alternative 3R bioassays to inform about the compound lo...

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Veröffentlicht in:Environmental science & technology 2023-01, Vol.57 (1), p.160-167
Hauptverfasser: Ebert, Ralf-Uwe, Kühne, Ralph, Schüürmann, Gerrit
Format: Artikel
Sprache:eng
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Zusammenfassung:Henry’s law constant is important for assessing the environmental fate of organic compounds, including polar accumulation, indoor contamination, and the impact of airborne predominance on persistence. Moreover, it can be used in the context of alternative 3R bioassays to inform about the compound loss through volatilization as a confounding factor. For 2636 compounds, curated experimental log K aw (air/water partition coefficient) data at 25° covering 23.6 orders of magnitude (from −18.6 to 5.0) have been collected from the literature. Subsequently, a new fragment model for predicting log K aw from molecular structures has been developed. According to the root-mean-squared error (rms) and the maximum negative and positive errors (mne and mpe), this general-purpose model outperforms COSMOtherm, EPISuite HENRYWIN, OPERA, and LSER with calculated input parameters significantly (rms 0.50 vs 0.92 vs 1.25 vs 1.28 vs 1.38, mne −2.74 vs −6.78 vs −9.11 vs −6.24 vs −6.27, mpe 2.25 vs 6.22 vs 8.27 vs 11.5 vs 7.69 log units). Initial separation into a training and prediction set (80%:20%), mutual leave-50%-out validation, and target value scrambling (temporarily wrong compound-K aw allocations) demonstrate the prediction capability, statistical robustness, and mechanistically sound basis of the fragment scheme. The new model is available to the public in fully computerized form through the ChemProp software, and can be combined with a separate existing model to extend the log K aw prediction to temperatures different from 25 °C.
ISSN:0013-936X
1520-5851
DOI:10.1021/acs.est.2c05623