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首页> 外文期刊>Chemosphere >Measurement of octanol-air partition coefficients for liquid crystals based on gas chromatography-retention time and its implication in predicting long-range transport potential
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Measurement of octanol-air partition coefficients for liquid crystals based on gas chromatography-retention time and its implication in predicting long-range transport potential

机译：基于气相色谱 - 保留时间的液晶辛醇 - 空气分区系数的测量及其在预测远程运输潜力中的含义

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摘要

Liquid crystals (LCs) are widely used in the modern society, but their environmental fate and related human health effects remain inadequately recognized. To assist in better understanding the environmental fate of LCs, the octanol-air partition coefficients (KOA) of 21 target LCs were determined with a gas chromatographyretention time (GC-RT) approach. Four classes of traditional organic pollutants, including polycyclic aromatic hydrocarbons, organochlorides, polybrominated diphenyl ethers, and polychlorinated biphenyls were employed as reference or calibration compounds. Cluster analysis indicated that the reference and calibration compounds somewhat influenced the relative and absolute magnitudes of GC-RT results. A quantitative structure-property relationship (QSPR) model was constructed from the experimental results and outperformed a widely-used model, KOAWIN, in estimating log KOA of LCs. This model was used to predict log KOAs for 116 LCs with the same element compositions and similar structures as the target LCs. Overall persistence and long-range transport potential were predicted based on the measured and estimated log KOA values, yielding consistent results. Several LCs were shown to have comparable characteristic travel distances and transport efficiencies as the traditional organic pollutants, suggesting they are potential environmental pollutants and the QSPR model is applicable in predicting the environmental fate of LCs.
机译：液晶（LCS）广泛应用于现代社会，但它们的环境命运和相关人体健康影响仍然不充分认可。为了帮助更好地理解LCS的环境命运，用气相色谱法测定时间（GC-RT）方法测定21个靶LCS的辛醇 - 空气分区系数（KOA）。四种类别的传统有机污染物，包括多环芳烃，有机氯化物，多溴二苯醚和多氯联苯，作为参考或校准化合物。聚类分析表明参考和校准化合物有些影响GC-RT结果的相对和绝对幅度。定量结构 - 性质关系（QSPR）模型由实验结果构建，并且优于估计LCS的Log Koa的广泛使用的模型Koowin。该模型用于预测116 LCS的Log Koas，其具有与目标LCS相同的元素组成和类似的结构。基于测量和估计的日志KOA值预测总体持久性和远程传输电位，产生一致的结果。显示几种LCS具有可比性的旅行距离和传输效率作为传统的有机污染物，表明它们是潜在的环境污染物，并且QSPR模型适用于预测LCS的环境命运。

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