几类典型有机污染物与有机质结合能力的定量构效关系研究

Organic matter is the important factors influencing the transport of organic pollutants in the aquatic sediments and the dissolved organic carbon-water partition coefficient (KDOC) is one of the main parameters of environmental risk assessment. Currently, the obtainment of KDOC is mainly through experimental determination, but it is bound to cost lots of manpower, material and financial resources. In consequence using existing data to predict the unknown contaminants of KDOC becomes the international development trend also hot research topic. Several kinds of typical organic pollutants will be taken as research chemicals, to investigate the KDOC values by establishing the quantitative structural-activity relationship models and experimental research. The fluorescence quenching method will be performed to evaluate the interaction of PCPPs with organic matter. The molecular fragments of organic pollutants will be split based on fragmentation scheme and analyzed the relationship between the kinds, positions and numbers of molecular fragments and coefficient (KDOC) to illustrate the promotion and inhibition effect of key chemical structures. The main molecular descriptors which can be present the physical and chemical properties of pollutants, for example Kow and EHOMO, will be screened by using quantum chemistry method, in order to establish QSAR models based on multiple classes pollutants for exploring the interaction mechanism between pollutants and organic matter. Finally through experimental verification, correction models will be calibrated. These research findings will be not only limited to the homologue also could broaden the predicted range to other classes of organic pollutants as well as provide the scientific basis for environmental risk assessment.

有机质是影响有机污染物在水体沉积物中归趋的重要因素，其吸附作用结合常数（KDOC）是环境风险评估的主要参数之一。目前KDOC的获取主要通过实验测定，这势必要耗费大量人力、物力及财力。因此利用已有数据，建立模型对污染物结合常数进行预测是国际发展趋势和热点。拟以几类典型有机污染物为研究对象，开展结合常数的定量构效关系模型（QSAR）预测与实验研究。采用荧光猝灭法测定多氯苯氧基苯酚与有机质的KDOC值；通过基团贡献法划分几类典型有机污染物的结构碎片参数，分析结构碎片及其取代位置和数量与吸附量间的相关关系，阐明关键化学结构对吸附过程的促进及抑制作用；基于量子化学方法筛选表征污染物理化性质的主要参数，如Kow，构建基于不同结构污染物的QSAR模型，探索污染物与有机质间的结合机理。最终通过实验验证，对模型进行校正。成果不仅仅局限于同系物，可拓宽到其他有机污染物的预测范围，为环境风险评估提供科学依据。

本课题选取非同系结构有机污染物为研究对象，建立了典型有机污染物理化性质参数、结构碎片与有机质结合常数KDOC之间的定量相关关系，揭示了有机污染物结构性质与有机质吸附结合作用过程的影响机理。取得的主要研究成果如下：.（1）构建了99种有机污染物的理化性质参数与KDOC之间的构效关系预测模型，拟合系数为83.3%，结果表明KDOC与摩尔体积、极化能力和碱性电离常数间呈显著性正相关，与正离子百分率、极性表面积、氢键供体个数和溶解度呈显著性负相关。建立了25种原子碎片与KDOC间的预测模型，模型拟合度可达90.0%，相关性最强的原子活性碎片为存在于芳香环结构上sp2杂化轨道上的N原子碎片，相关性最强的原子非活性碎片为存在于脂肪链结构上的sp3杂化轨道上的NH原子碎片。.（2）进一步建立了同系物分类模型，结果表明烷烃简单脂肪链化合物与有机质结合作用与辛醇水分配系数呈显著性正相关，与氢键供体个数呈显著性负相关。卤代苯与氢键受体碱度呈显著性正相关，与摩尔体积和分子质量呈显著性负相关。多环芳烃与摩尔折射率具有唯一显著性正相关。多溴联苯醚与氢键受体碱度呈唯一显著性负相关。多溴联苯醚类化合物随着溴取代基团的增多其结合吸附能力明显增加。多环芳烃类化合物的KDOC值随环数增加而显著性上升。.（3）有机质富里酸（FA）亚组分的同步荧光光谱（SFS）特征分析表明，在偏碱性pH值条件下，FA3-FA13的SFS表现出Peak A （240-280 nm），Peak B （360-380 nm）和Peak C （420-480 nm）三个主要荧光峰。研究表明，DOM的SFS荧光特征能够反映DOM中类蛋白，类富里酸和类腐殖酸组分，且类蛋白中含有类酪氨酸（200-250 nm）和类色氨酸（250-310 nm）组分。.（4）采用核磁手段详细阐明了水生植物中有机质及P的组成特征；其次，采用连续提取、固态核磁，液态核磁，碳核磁，磷核磁相结合的方法对水生植物中有机质组分及稳定性组分进行了定量化分析，并且获得了生物有效性组分及稳定组分的形态组成，为研究污染物进入水体后与有机质结合吸附作用提供技术支持。