Department of Environmental Science , Radboud University Nijmegen , 6500GL , Nijmegen , The Netherlands.
Environment Department , University of York , Heslington , York YO10 5DD , United Kingdom.
Environ Sci Technol. 2018 Nov 6;52(21):12494-12503. doi: 10.1021/acs.est.8b03862. Epub 2018 Oct 22.
Environmental risk assessment of pharmaceuticals requires the determination of their environmental exposure concentrations. Existing exposure modeling approaches are often computationally demanding, require extensive data collection and processing efforts, have a limited spatial resolution, and have undergone limited evaluation against monitoring data. Here, we present ePiE (exposure to Pharmaceuticals in the Environment), a spatially explicit model calculating concentrations of active pharmaceutical ingredients (APIs) in surface waters across Europe at ∼1 km resolution. ePiE strikes a balance between generating data on exposure at high spatial resolution while having limited computational and data requirements. Comparison of model predictions with measured concentrations of a diverse set of 35 APIs in the river Ouse (UK) and Rhine basins (North West Europe), showed around 95% were within an order of magnitude. Improved predictions were obtained for the river Ouse basin (95% within a factor of 6; 55% within a factor of 2), where reliable consumption data were available and the monitoring study design was coherent with the model outputs. Application of ePiE in a prioritisation exercise for the Ouse basin identified metformin, gabapentin, and acetaminophen as priority when based on predicted exposure concentrations. After incorporation of toxic potency, this changed to desvenlafaxine, loratadine, and hydrocodone.
环境风险评估需要确定药品的环境暴露浓度。现有的暴露建模方法通常计算要求高,需要大量的数据收集和处理工作,空间分辨率有限,并且对监测数据的评估有限。在这里,我们提出了 ePiE(环境中药物的暴露),这是一种空间显式模型,可计算欧洲各地地表水中药品活性成分(APIs)的浓度,分辨率约为 1 公里。ePiE 在以高空间分辨率生成暴露数据的同时,兼顾了计算和数据要求有限的问题。将模型预测值与在英国奥塞河(Ouse)流域和西北欧莱茵河(Rhine)流域中测量的 35 种不同 API 的浓度进行比较,结果表明约有 95%的预测值在一个数量级内。在奥塞河(Ouse)流域中,当有可靠的消费数据且监测研究设计与模型输出一致时,预测值得到了改善(95%的预测值在 6 倍以内;55%的预测值在 2 倍以内)。在对奥塞河(Ouse)流域的优先排序中应用 ePiE 时,基于预测的暴露浓度,将二甲双胍、加巴喷丁和对乙酰氨基酚确定为优先考虑的药物。在考虑了毒性效力后,这一结果变为文拉法辛、氯雷他定和氢可酮。