Rapid Screening for Exposure to “Non-Target” Pharmaceuticals from Wastewater Effluents by Combining HRMS-Based Suspect Screening and Exposure Modeling

Active pharmaceutical ingredients (APIs) have raised considerable
concern over the past decade due to their widespread detection in
water resources and their potential to affect ecosystem health. This
triggered many attempts to prioritize the large number of known APIs
to target monitoring efforts and testing of fate and effects. However,
so far, a comprehensive approach to screen for their presence in surface
waters has been missing. Here, we explore a combination of an automated
suspect screening approach based on liquid chromatography coupled
to high-resolution mass spectrometry and a model-based prioritization
using consumption data, readily predictable fate properties and a
generic mass balance model for activated sludge treatment to comprehensively
detect APIs with relevant exposure in wastewater treatment plant effluents.
The procedure afforded the detection of 27 APIs that had not been
covered in our previous target method, which included 119 parent APIs.
The newly detected APIs included seven compounds with a high potential
for bioaccumulation and persistence, and also three compounds that
were suspected to stem from point sources rather than from consumption
as medicines. Analytical suspect screening proved to be more selective
than model-based prioritization, making it the method of choice for
focusing analytical method development or fate and effect testing
on those APIs most relevant to the aquatic environment. However, we
found that state-of-the-practice exposure modeling used to predict
potential high-exposure substances can be a useful complement to point
toward oversights and known or suspected detection gaps in the analytical
method, most of which were related to insufficient ionization.

过去十年来，药物活性成分（Active Pharmaceutical Ingredients，APIs）因在各类水资源中被广泛检出，且可能对生态系统健康造成潜在影响，引发了广泛关注。这促使诸多研究尝试对海量已知的APIs进行优先级排序，以针对性开展监测工作以及归趋与效应测试。然而迄今为止，仍缺乏一套可用于筛查地表水中APIs残留的完整分析方案。
本研究探索了一种联合分析方案：将基于液相色谱-高分辨质谱联用法的自动化可疑物筛查方法，与结合消费数据、可快速预测的归趋属性以及用于活性污泥处理工艺的通用质量平衡模型的模型驱动优先级排序方法相结合，以全面检出污水处理厂出水中具有相关暴露风险的APIs。
该方案成功检出27种未被纳入此前包含119种母体APIs的靶向分析方法的目标物。
此次新检出的APIs中，包含7种具有高生物富集性与环境持久性的化合物，以及3种被怀疑来源于污染点源而非药品消费排放的物质。
分析性可疑物筛查的选择性优于基于模型的优先级排序方法，因此该方法可作为首选方案，将分析方法开发或归趋与效应测试的重点聚焦于与水生环境关联最密切的APIs。
不过本研究发现，当前用于预测潜在高暴露物质的现行主流暴露模型，可作为有效补充，帮助识别分析方法中存在的疏漏、已知或疑似的检测盲区——此类盲区大多与质谱分析中的离子化效率不足相关。