OBJECTIVES:Pharmaceuticals in the environment are of growing public health concern. The main objectives of this study were to develop a new emission estimation model, identify factors critical to reducing emission, and demonstrate the model's applicability for screening and priority setting. METHODS:A new emission estimation model was developed covering the life cycle pathways of pharmaceuticals from supply to discharge into surface water. The emission estimates of the model were assessed by coupling with SimpleBox to give predicted concentrations and by comparing the predicted concentrations with measured concentrations in Korean surface waters for five selected pharmaceuticals (acetaminophen, cephradine, ibuprofen, mefenamic acid, and naproxen). RESULTS:The sensitivity analysis revealed that the biodegradation rate in the sewage treatment plant and the excretion rate of pharmaceuticals were the most important factors influencing the emission rate. The uncertainty of the emission estimate was found to increase with increases in the value of the emission estimate. Once the intrinsic properties of a pharmaceutical (excretion rate, biodegradation rate, and removal rate by sludge separation) were given, the patient behavior parameters, such as participation in a Take-back program and rate of administration, were determined to have a strong influence on the emission estimate. In our study, the predicted and measured concentrations agreed with each other within one order of magnitude. Several management implications were drawn from the analysis of model outcomes. CONCLUSIONS:The model outcomes, alone or in combination with toxicity data, may potentially be used for the purposes of screening, priority setting, and the design of management programs.

译文

目的:环境中的药品日益引起人们对公共卫生的关注。这项研究的主要目的是开发一个新的排放估算模型,确定对减少排放至关重要的因素,并证明该模型在筛选和确定优先级方面的适用性。
方法:建立了一个新的排放估算模型,该模型涵盖了药品从供应到排放到地表水中的生命周期路径。通过与SimpleBox耦合以给出预测浓度,并通过将预测浓度与五种选定药物(对乙酰氨基酚,头孢拉定,布洛芬,甲芬那酸和萘普生)在韩国地表水中的测量浓度进行比较,来评估模型的排放估算值。
结果:敏感性分析表明,污水处理厂的生物降解率和药物的排泄率是影响排放率的最重要因素。发现排放估算的不确定性随着排放估算值的增加而增加。一旦给出了药物的内在特性(排泄率,生物降解率和污泥分离去除率),就可以确定患者行为参数(例如参与回收计划和给药率)具有很大的影响力在排放量估算上。在我们的研究中,预测浓度和测量浓度在一个数量级内彼此一致。通过对模型结果的分析得出了一些管理上的含义。
结论:模型结果单独或与毒性数据结合可潜在地用于筛查,确定优先重点和设计管理程序的目的。

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