FAME, UvA IBED: Universiteit van Amsterdam Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Science Park 904, Amsterdam 1098 XH, the Netherlands.
FAME, UvA IBED: Universiteit van Amsterdam Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Science Park 904, Amsterdam 1098 XH, the Netherlands.
Water Res. 2022 Aug 15;222:118878. doi: 10.1016/j.watres.2022.118878. Epub 2022 Jul 18.
This study aimed to provide insights into the risk posed by psychopharmaceuticals and illicit drugs in European surface waters, and to identify current knowledge gaps hampering this risk assessment. First, the availability and quality of data on the concentrations of psychopharmaceuticals and illicit drugs in surface waters (occurrence) and on the toxicity to aquatic organisms (hazard) were reviewed. If both occurrence and ecotoxicity data were available, risk quotients (risk) were calculated. Where abundant ecotoxicity data were available, a species sensitivity distribution (SSD) was constructed, from which the hazardous concentration for 5% of the species (HC) was derived, allowing to derive integrated multi-species risks. A total of 702 compounds were categorised as psychopharmaceuticals and illicit drugs based on a combination of all 502 anatomical therapeutic class (ATC) 'N' pharmaceuticals and a list of illicit drugs according to the Dutch Opium Act. Of these, 343 (49%) returned occurrence data, while only 105 (15%) returned ecotoxicity data. Moreover, many ecotoxicity tests used irrelevant endpoints for neurologically active compounds, such as mortality, which may underestimate the hazard of psychopharmaceuticals. Due to data limitations, risks could only be assessed for 87 (12%) compounds, with 23 (3.3%) compounds indicating a potential risk, and several highly prescribed drugs returned neither occurrence nor ecotoxicity data. Primary bottlenecks in risk calculation included the lack of ecotoxicity data, a lack of diversity of test species and ecotoxicological end points, and large disparities between well studied and understudied compounds for both occurrence and toxicity data. This study identified which compounds merit concern, as well as the many compounds that lack the data for any calculation of risk, driving research priorities. Despite the large knowledge gaps, we concluded that the presence of a substantial part (26%) of data-rich psychopharmaceuticals in surface waters present an ecological risk for aquatic non-target organisms.
本研究旨在深入了解欧洲地表水中国精神药物和非法药物所带来的风险，并确定当前阻碍这一风险评估的知识空白。首先，审查了地表水中国精神药物和非法药物浓度（出现）和对水生生物毒性（危害）的数据的可得性和质量。如果既有出现数据又有生态毒性数据，则计算风险比（风险）。如果有丰富的生态毒性数据，则构建物种敏感性分布（SSD），从中得出对 5%物种有危害的浓度（HC），从而得出综合多物种风险。根据所有 502 个解剖治疗类（ATC）'N'类药物和荷兰鸦片法规定的非法药物清单，将 702 种化合物归类为精神药物和非法药物。其中，343 种（49%）化合物有出现数据，而只有 105 种（15%）化合物有生态毒性数据。此外，许多生态毒性试验使用与神经活性化合物不相关的终点，如死亡率，这可能低估精神药物的危害。由于数据限制，只能评估 87 种（12%）化合物的风险，其中 23 种（3.3%）化合物表明存在潜在风险，而且几种高处方药物既没有出现数据也没有生态毒性数据。风险计算中的主要瓶颈包括缺乏生态毒性数据、测试物种和生态毒理学终点的多样性缺乏，以及在出现和毒性数据方面，研究充分和研究不足的化合物之间存在巨大差异。本研究确定了哪些化合物值得关注，以及缺乏任何风险计算数据的许多化合物，从而确定了研究重点。尽管存在巨大的知识空白，但我们的结论是，大量富含数据的精神药物的存在对水生非目标生物构成了生态风险。
