Zuckerberg Institute for Water Research, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer 84990, Israel.
Swiss Institute for Dryland Environmental and Energy Research, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus, 84990, Israel.
Sci Total Environ. 2017 Jan 1;575:588-594. doi: 10.1016/j.scitotenv.2016.09.015. Epub 2016 Sep 9.
This study provides a tool for predicting the concentrations of the natural estrogens (NEs) estrone, 17β-estradiol and estriol in raw wastewater (WW). Data characterizing the biochemical oxygen demand (BOD), NE concentrations, and discharges of raw sewage to wastewater treatment plants (WWTPs) were collected from various publications and used in the model formulation. A strong correlation was found between the log transformed BOD and the log transformed estrone load (r=0.84, n=61), the log transformed 17β-estradiol load (r=0.89, n=52) and the log transformed estriol load (r=0.80, n=40). The models are reasonably accurate when compared to the measured concentrations and slightly better than previous modeling efforts. The relative amounts of data falling within ±50% error were 67% for estrone, 63% for 17β-estradiol, and 55% for estriol. Because the model was developed from a wide array of WWTPs from five continents, it is universal and can be used for projecting concentrations of NEs from a wide range of mixed domestic and industrial sources, but may be less precise when sources contain high levels of NEs or BOD (e.g., WW from dairy farms and food processing plants). The model is expected to improve our ability to predict the fate of NEs in WWTPs and in the receiving environment, which currently relies on estimating the concentrations of NEs in raw wastewater. Its application is especially valuable since direct measurement of NEs in raw WW is expensive and practically impossible in many developing countries due to the lack of expertise and funds.
本研究提供了一种预测原污水中天然雌激素（NEs）雌酮、17β-雌二醇和雌三醇浓度的工具。从各种出版物中收集了描述生化需氧量（BOD）、NE 浓度以及未经处理的污水排放到污水处理厂（WWTP）的数据，并用于模型制定。在对数转换的 BOD 和对数转换的雌酮负荷（r=0.84，n=61）、对数转换的 17β-雌二醇负荷（r=0.89，n=52）和对数转换的雌三醇负荷（r=0.80，n=40）之间发现了很强的相关性。与实测浓度相比，模型的准确性相当高，略优于以往的建模工作。相对误差在±50%范围内的数据量分别为雌酮的 67%、17β-雌二醇的 63%和雌三醇的 55%。由于该模型是由来自五大洲的各种 WWTP 开发的，因此它具有通用性，可以用于预测来自各种混合的家庭和工业来源的 NE 浓度，但在来源中含有高水平的 NE 或 BOD 时可能不太准确（例如，来自奶牛场和食品加工厂的 WW）。该模型有望提高我们预测 WWTP 和接收环境中 NE 命运的能力，目前这依赖于估计原污水中 NE 的浓度。由于缺乏专业知识和资金，直接测量原 WW 中的 NE 在许多发展中国家既昂贵又几乎不可能，因此该模型的应用特别有价值。
