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PFAS对环境的影响:利用理论量子化学和QSPR建模填补数据空白

Michalina Mudlaff¹, Anita Sosnowska², Leonid Gorb³

¹QSAR Lab, Trzy Lipy 3, 80-172 Gdańsk, Poland.

Environment international

|March 17, 2024

概括

这项研究使用先进的模型预测了许多多化和多化基物质 (PFAS) 的生物积累潜力. 这些发现有助于理解PFAS的环境运输,并填补这些持久化学品的关键数据缺口.

科学领域:

环境化学环境化学
计算化学计算化学
毒理学毒理学毒理学

背景情况:

和多化基物质 (PFAS) 是广泛存在的,持久的环境污染物,对大约10,000种已知的化合物中的大多数有有限的实验数据.
鉴于PFAS的缓慢降解和潜在风险,评估其生物积累潜力和环境命运至关重要.

研究的目的:

为了解决PFAS生物积累潜力和物理化学性质的数据缺口.
预测影响PFAS环境传输和分散的关键参数.

主要方法:

采用了 COnductor-like Screening MOdel for Realistic Solvents (COSMO-RS) 来预测 n-octanol/水分区系数 (logK_OW) 的方法. 这是一个非常简单的方法.
开发了一种具有高精度 (R²=0.95,Q²_LOO=0.93) 的定量结构-属性关系 (QSPR) 模型,用于预测logK_OW.
利用NORMAN数据库预测4000多个PFAS的logK_OW,并计算了额外的物理化学性质 (k_H,K_AW,K_OA,K_OC).

主要成果:

该QSPR模型显示了PFAS生物积累潜力的强有力的预测性能.
含量被证实是增强PFAS生物积累的关键因素.
计算的物理化学性质与现有文献数据有很好的相关性 (R² > 0.66).

结论:

这项研究成功地填补了PFAS物理化学性质的显著数据缺口.
这项研究增强了对PFAS环境行为,运输和分散的理解.
为大量PFAS化合物提供了有价值的估计数据,有助于风险评估.

关键词:

在N-octanol/水分区系数.透和多化基物质 (PFAS) 的使用.这就是QSPR.理论化学是一种理论化学.

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