Department of Environmental and Resource Engineering (DTU Sustain), Technical University of Denmark, Bygningstorvet, Building 115, 2800 Kgs., Lyngby, Denmark.
Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf 8600, Switzerland; Institute of Civil, Environmental and Geomatic Engineering, ETH Zürich, Zurich 8093, Switzerland.
Water Res. 2022 Sep 1;223:118968. doi: 10.1016/j.watres.2022.118968. Epub 2022 Aug 9.
Urban wet-weather discharges from combined sewer overflows (CSO) and stormwater outlets (SWO) are a potential pathway for micropollutants (trace contaminants) to surface waters, posing a threat to the environment and possible water reuse applications. Despite large efforts to monitor micropollutants in the last decade, the gained information is still limited and scattered. In a metastudy we performed a data-driven analysis of measurements collected at 77 sites (683 events, 297 detected micropollutants) over the last decade to investigate which micropollutants are most relevant in terms of 1) occurrence and 2) potential risk for the aquatic environment, 3) estimate the minimum number of data to be collected in monitoring studies to reliably obtain concentration estimates, and 4) provide recommendations for future monitoring campaigns. We highlight micropollutants to be prioritized due to their high occurrence and critical concentration levels compared to environmental quality standards. These top-listed micropollutants include contaminants from all chemical classes (pesticides, heavy metals, polycyclic aromatic hydrocarbons, personal care products, pharmaceuticals, and industrial and household chemicals). Analysis of over 30,000 event mean concentrations shows a large fraction of measurements (> 50%) were below the limit of quantification, stressing the need for reliable, standard monitoring procedures. High variability was observed among events and sites, with differences between micropollutant classes. The number of events required for a reliable estimate of site mean concentrations (error bandwidth of 1 around the "true" value) depends on the individual micropollutant. The median minimum number of events is 7 for CSO (2 to 31, 80%-interquantile) and 6 for SWO (1 to 25 events, 80%-interquantile). Our analysis indicates the minimum number of sites needed to assess global pollution levels and our data collection and analysis can be used to estimate the required number of sites for an urban catchment. Our data-driven analysis demonstrates how future wet-weather monitoring programs will be more effective if the consequences of high variability inherent in urban wet-weather discharges are considered.
城市雨水排放中的合流制溢流（CSO）和雨水出口（SWO）是微污染物（痕量污染物）进入地表水的潜在途径，对环境和可能的水再利用应用构成威胁。尽管在过去十年中做出了大量努力来监测微污染物，但获得的信息仍然有限且分散。在一项荟萃研究中，我们对过去十年在 77 个地点（683 个事件，297 个检测到的微污染物）收集的测量数据进行了数据驱动分析，以调查哪些微污染物在以下方面最为重要：1）发生情况；2）对水生环境的潜在风险；3）估计在监测研究中收集数据的最小数量，以可靠地获得浓度估计值；4）为未来的监测活动提供建议。我们强调了由于其高发生率和与环境质量标准相比的临界浓度水平而应优先考虑的微污染物。这些被列为优先的微污染物包括来自所有化学类别的污染物（农药、重金属、多环芳烃、个人护理产品、药品以及工业和家庭化学品）。对超过 30,000 个事件平均浓度的分析表明，超过 50%的测量值低于定量限，这强调了需要可靠、标准的监测程序。在事件和地点之间观察到很大的变异性，并且在微污染物类别之间存在差异。对于可靠估计站点平均浓度（“真实”值周围的误差带宽为 1）所需的事件数量取决于单个微污染物。对于 CSO，可靠估计站点平均浓度所需的最小事件数中位数为 7（2 至 31，80%-四分位距），对于 SWO 为 6（1 至 25 事件，80%-四分位距）。我们的分析表明，评估全球污染水平所需的最小站点数量，并且我们的数据收集和分析可用于估计城市流域所需的站点数量。我们的数据驱动分析表明，如果考虑到城市雨水排放中固有的高度变异性的后果，未来的雨水监测计划将更加有效。
