Heffley J D, Comber S D W, Wheeler B W, Redshaw C H
European Centre for Environment and Human Health, University of Exeter Medical School, Truro, Cornwall, UK.
Environ Sci Process Impacts. 2014 Nov;16(11):2571-9. doi: 10.1039/c4em00374h.
Newly available prescription data has been used along with census data to develop a localised method for predicting pharmaceutical concentrations in sewage influent and effluent for England, and applied to a case study: the steroid estrogens estrone, 17β-estradiol, and 17α-ethinylestradiol in a selected catchment. The prescription data allows calculation of the mass consumed of synthetic estrogens, while use of highly localised census data improves predictions of naturally excreted estrogens by accounting for regional variations in population demographics. This serves two key purposes; to increase the accuracy of predictions in general, and to call attention to the need for more accurate predictions at a localised and/or catchment level, especially in light of newly proposed regulatory measures which may in the future require removal of steroid estrogens by sewage treatment facilities. In addition, the general lack of measured sewage works data necessitated the development of a novel approach which allowed comparison of localised predictions to average national measurements of influent and effluent. Overall in the case study catchment, estrogen predictions obtained using the model described herein were within 95% confidence intervals of measured values drawn from across the UK, with large improvements to predictions of EE2 being made compared with previous predictive methods.
新获取的处方数据与人口普查数据一起被用于开发一种本地化方法，以预测英格兰污水进水和出水中的药物浓度，并应用于一个案例研究：在一个选定集水区中的甾体雌激素雌酮、17β-雌二醇和17α-乙炔雌二醇。处方数据可用于计算合成雌激素的消耗质量，而使用高度本地化的人口普查数据通过考虑人口统计学的区域差异，改进了对自然排泄雌激素的预测。这有两个关键目的；总体上提高预测的准确性，并提请注意在本地化和/或集水区层面进行更准确预测的必要性，特别是鉴于新提出的监管措施，未来可能要求污水处理设施去除甾体雌激素。此外，由于普遍缺乏实测的污水处理厂数据，有必要开发一种新方法，以便将本地化预测与全国进水和出水的平均测量值进行比较。总体而言，在案例研究集水区中，使用本文所述模型获得的雌激素预测值在从英国各地获取的测量值的95%置信区间内，与以前的预测方法相比，对乙炔雌二醇（EE2）的预测有了很大改进。
