Center for Health and Environmental Risk Research, National Institute for Environmental Studies (NIES), Onogawa 16-2, 305-8506 Tsukuba, Ibaraki, Japan.
Environ Sci Technol. 2020 Dec 1;54(23):15162-15169. doi: 10.1021/acs.est.0c06506. Epub 2020 Nov 18.
Chlorinated paraffins (CPs) are highly complex mixtures of polychlorinated -alkanes with differing chain lengths and chlorination patterns. Knowledge on physicochemical properties of individual congeners is limited but needed to understand their environmental fate and potential risks. This work used a sophisticated but time-demanding quantum chemically based method COSMO-RS and a fast-running fragment contribution approach to enable prediction of partition coefficients for a large number of short-chain chlorinated paraffin (SCCP) congeners. Fragment contribution models (FCMs) were developed using molecular fragments with a length of up to C in CP molecules as explanatory variables and COSMO-RS-calculated partition coefficients as training data. The resulting FCMs could quickly provide COSMO-RS predictions for octanol-water (), air-water (), and octanol-air () partition coefficients of SCCP congeners with an accuracy of 0.1-0.3 log units root-mean-squared errors. The FCM predictions for agreed with experimental values for individual constitutional isomers within 1 log unit. The distribution of partition coefficients for each SCCP congener group was computed, which successfully reproduced experimental log ranges of industrial CP mixtures. As an application of the developed FCMs, the predicted and were plotted to evaluate the bioaccumulation potential of each SCCP congener group.
短链氯化石蜡（SCCP）是一组具有不同链长和氯化模式的高度复杂的多氯化烷烃混合物。尽管对个别同系物的物理化学性质了解有限，但为了了解其环境归宿和潜在风险，这些知识是必需的。本工作使用了一种复杂但耗时的基于量子化学的 COSMO-RS 方法和一种快速运行的片段贡献方法，从而能够预测大量短链氯化石蜡（SCCP）同系物的分配系数。使用分子片段作为解释变量，片段长度最长可达 CP 分子中的 C，将 COSMO-RS 计算的分配系数作为训练数据，开发了片段贡献模型（FCM）。由此产生的 FCM 可以快速提供 SCCP 同系物的辛醇-水（）、空气-水（）和辛醇-空气（）分配系数的 COSMO-RS 预测，其准确度为 0.1-0.3 个对数单位均方根误差。FCM 对的预测与个别构象异构体的实验值在 1 个对数单位内一致。计算了每个 SCCP 同系物组的分配系数分布，成功再现了工业 CP 混合物的实验 log 值范围。作为所开发的 FCM 的应用，预测的和被绘制出来，以评估每个 SCCP 同系物组的生物积累潜力。
