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Indexed by:期刊论文

Date of Publication:2017-03-22

Journal:ENVIRONMENTAL SCIENCE-PROCESSES & IMPACTS

Included Journals:SCIE、PubMed、Scopus

Volume:19

Issue:3

Page Number:300-306

ISSN No.:2050-7887

Abstract:The octanol-air partition coefficient (K-OA) 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).