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Issue 3, 2017
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Development of polyparameter linear free energy relationship models for octanol–air partition coefficients of diverse chemicals

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Abstract

The octanol–air partition coefficient (KOA) is a key parameter describing the partition behavior of organic chemicals between air and environmental organic phases. As the experimental determination of KOA is costly, time-consuming and sometimes limited by the availability of authentic chemical standards for the compounds to be determined, it becomes necessary to develop credible predictive models for KOA. In this study, a polyparameter linear free energy relationship (pp-LFER) model for predicting KOA at 298.15 K and a novel model incorporating pp-LFERs with temperature (pp-LFER-T model) were developed from 795 log KOA values for 367 chemicals at different temperatures (263.15–323.15 K), and were evaluated with the OECD guidelines on QSAR model validation and applicability domain description. Statistical results show that both models are well-fitted, robust and have good predictive capabilities. Particularly, the pp-LFER model shows a strong predictive ability for polyfluoroalkyl substances and organosilicon compounds, and the pp-LFER-T model maintains a high predictive accuracy within a wide temperature range (263.15–323.15 K).

Graphical abstract: Development of polyparameter linear free energy relationship models for octanol–air partition coefficients of diverse chemicals

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Publication details

The article was received on 21 Nov 2016, accepted on 03 Jan 2017 and first published on 11 Jan 2017


Article type: Paper
DOI: 10.1039/C6EM00626D
Citation: Environ. Sci.: Processes Impacts, 2017,19, 300-306
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    Development of polyparameter linear free energy relationship models for octanol–air partition coefficients of diverse chemicals

    X. Jin, Z. Fu, X. Li and J. Chen, Environ. Sci.: Processes Impacts, 2017, 19, 300
    DOI: 10.1039/C6EM00626D

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