典型持久性有毒污染物分配系数预测方法及多介质分配规律研究

水环境中存在着众多的持久性有毒污染物（PTS），严重危及生态安全和人体健康。精确的分配系数和多介质环境模型研究对于阐明PTS的时空分布和环境分配规律具有重要价值，是PTS迫切需要研究的基础工作。本项目拟基于连续介质溶剂化模型理论和热力学关系，建立典型PTS分配系数的预测新方法。以水环境中典型PTS- - 多环芳烃、多氯联苯、多溴联苯醚和有机氯农药为目标化合物，通过实验精确测定部分目标化合物不同温度下的亨利定律常数（HLCs）、正辛醇/水分配系数（Kow）和正辛醇/空气分配系数（Koa）用于预测方法的验证。应用验证后的方法预测目标化合物不同温度下的分配系数，分析影响上述分配系数的关键因素，揭示分子结构-环境温度-分配系数之间的内在关系。在此基础上，构建大连湾和大凌河口的多介质逸度模型，研究不同季节典型PTS在水、气及各种有机相之间的迁移和分配规律，为开展其生态风险评价和污染控制提供科学支持。

There are many kinds of persistent toxic substances (PTS) in water, which seriously threaten ecological safety and human health. Precise partition coefficients and multimedia environment models are valuable for clarifying the temporal-spatial distribution and rule of partitioning in multimedia environment of PTS, which are bases urgently needed to investigate for PTS. Therefore, this project aims to develop a novel method for predicting partition coefficients of PTS between bulk phases of water, air and organic matter at different temperatures, based on the theory of continuum solvation models and thermodynamic relations. Typical PTS in water, such as polycyclic aromatic hydrocarbons, polychlorinated biphenyls, polybrominated diphenyl ethers and organochlorine pesticide, will be investigated in the present project. Henry's law constants (HLCs), octanol/water partition coefficients (Kow) and octanol/air partition coefficients (Koa) values at different temperatures of selected typical PTS will be experimentally measured, which are used to verify and revise the predictive method. Then HLCs, Kow and Koa of these pollutants at different temperatures will be predicted, key factors impacting the partition coefficients will be analyzed and the intrinsic relationships between the molecular structure, environmental temperature and the partition coefficients will be uncovered with the new method. Based on the predicted HLCs, Kow and Koa values at different temperatures, multimedia models will be developed for Dalian Bay and Daling River Estuary in order to study the rule of translation and partition of typical PTS in the real environment, which can provide scientific bases for their ecological risk assessment and pollution control.