College of Environment and Energy, South China University of Technology, Guangzhou, 510006, Guangdong, China,
Environ Sci Pollut Res Int. 2015 Jun;22(12):9554-62. doi: 10.1007/s11356-015-4369-y. Epub 2015 Mar 24.
Natural estrogens are important endocrine disrupting compounds (EDCs), which may pose adverse effects on our environment. To avoid time-consuming sample preparation and chemical analysis, estimation of their concentrations in municipal wastewater based on their human urine/feces excretion rates has been generally adopted. However, the data of excretion rates available are very limited and show significant difference among countries. In the context of increasing reporting on the concentrations of natural estrogens in municipal wastewater around the world, this study presented a simple method to estimate their human excretion rates based on the concentrations of natural estrogens in raw sewage. The estimated human excretion rates of natural estrogens among ten countries were obtained, which totally covered over 33 million population. Among these, Brazilians had the largest excretion rates with estrone (E1) and 17β-estradiol (E2) as 236.9 and 60 μg/day/P, respectively, while Iran had the lowest value of 2 μg/day/P for E1 and 0.5 μg/day/P for E2. The average estimated human excretion rates of E1, E2, and estriol (E3) are 17.3, 6.4, and 39.7 μg/day/P, respectively. When the estimated human excretion rates obtained were applied for prediction, the predicted results showed better accuracies than those based on human urinary/feces excretion rates. The method in this study is simple, cost-effective and time-saving, which may be widely applied.
天然雌激素是重要的内分泌干扰化合物（EDCs），可能对我们的环境产生不利影响。为了避免耗时的样品制备和化学分析，通常根据人类尿液/粪便排泄率来估算城市废水中的浓度。然而，现有的排泄率数据非常有限，且在国家之间存在显著差异。在世界各地越来越多报道城市废水中天然雌激素浓度的背景下，本研究提出了一种基于原污水中天然雌激素浓度来估算其人类排泄率的简单方法。获得了来自 10 个国家的天然雌激素的人类排泄率数据，这些国家的总人口超过 3300 万。其中，巴西的雌酮（E1）和 17β-雌二醇（E2）排泄率最高，分别为 236.9 和 60μg/天/人，而伊朗的 E1 和 E2 排泄率最低，分别为 2μg/天/人和 0.5μg/天/人。E1、E2 和雌三醇（E3）的平均估计人类排泄率分别为 17.3、6.4 和 39.7μg/天/人。当应用所获得的估计人类排泄率进行预测时，预测结果比基于人类尿液/粪便排泄率的预测结果更准确。本研究中的方法简单、经济高效且省时，可能会得到广泛应用。
