College of Environmental Science and Engineering, China West Normal University, Nanchong, 637009, China.
School of Environment and Resource, Southwest University of Science and Technology, Mianyang, 621010, China.
Environ Pollut. 2019 Nov;254(Pt A):112959. doi: 10.1016/j.envpol.2019.112959. Epub 2019 Jul 25.
Humic acids (HAs) have been shown to dominate the photodegradation of steroid estrogens in natural waters. Nevertheless, how the photosensitizing ability of HAs relates to their structural and optical characteristics remains largely unknown. In this study, 17α-ethynylestradiol (EE2) was selected as a model compound to study to what extent easily-measurable characteristics of HAs might be used to predict their photosensitization potency. HAs were extracted from sediments of two different sources, and then subjected to structural and optical properties characterization using elemental analyzer, UV-vis spectroscopy and fluorescence spectroscopy. Photochemical experiments show that the HAs from the two sources can effectively meditate EE2 photodegradation. Although with drastically different structural and optical properties, the photosensitizing ability of these HAs towards EE2 can be well described by simple linear regressions using a spectroscopic index, the spectral slope ratio (S). This optical indicator is correlated with various physicochemical properties of HAs, including the molecular weight, lignin content, charge-transfer interaction potential, photobleaching extent and sources. No universal prediction model could be established for predicting EE2 photodegradation kinetics on the basis of S, but in specific waters S could be a powerful indictor for predicting the EE2 photodegradation sensitized by HAs.
腐殖酸（HAs）已被证明在天然水中主导着甾体雌激素的光降解。然而，HAs 的光敏能力与其结构和光学特性有何关系在很大程度上仍不清楚。在本研究中，选择 17α-乙炔基雌二醇（EE2）作为模型化合物，以研究 HAs 的哪些易于测量的特性可用于预测其光敏化能力。从两个不同来源的沉积物中提取 HAs，并使用元素分析仪、紫外可见光谱和荧光光谱对其结构和光学特性进行表征。光化学实验表明，两种来源的 HAs 都能有效地介导 EE2 的光降解。尽管结构和光学性质有很大差异，但这些 HAs 对 EE2 的光敏能力可以用一个简单的线性回归用光谱指数光谱斜率比（S）来很好地描述。该光学指标与 HAs 的各种物理化学性质相关联，包括分子量、木质素含量、电荷转移相互作用势、光漂白程度和来源。不能根据 S 建立预测 EE2 光降解动力学的通用预测模型，但在特定的水中，S 可以是预测 HAs 敏化 EE2 光降解的有力指标。
