Partners4UrbanWater, Nijmegen, the Netherlands; Department of Watermanagement, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, the Netherlands.
Partners4UrbanWater, Nijmegen, the Netherlands.
Water Res. 2023 May 15;235:119883. doi: 10.1016/j.watres.2023.119883. Epub 2023 Mar 20.
The ecological state of receiving water bodies can be significantly influenced by organic micropollutants that are emitted via stormwater runoff. Reported efforts to quantify the emission of micropollutants mainly focus on sampling at combined sewer overflows and storm sewer outfalls, which can be challenging. An alternative method, called fingerprinting, was developed and tested in this study. The fingerprinting method utilizes wastewater treatment plant (WWTP) influent samples and derives the proportion of stormwater in a sample. This is achieved by comparing the wet weather vs dry weather concentrations of substances-tracers which are present only in wastewater. It is then possible to estimate the concentration of organic micropollutants in stormwater runoff from measurements in the influent of a WWTP based on a mass balance. In this research, the fingerprinting method was applied in influent samples obtained in five WWTPs in the Netherlands. In total, 28 DWF and 22 WWF samples were used. The chosen tracers were ibuprofen, 2-hydroxyibuprofen, naproxen and diclofenac. Subsequently, the concentration in stormwater runoff of 403 organic micropollutants was estimated via the WWF samples. The substances that were present and analyzed included glyphosate and AMPA, 24 out of 254 pesticides, 6 out of 28 organochlorine pesticides, 45 out of 63 pharmaceuticals, 15 out of 15 PAHs, 2 of the 7 PCBs, and 20 of 33 other substances (e.g. bisphenol-A). A comparison with findings from other studies suggested that the fingerprinting method yields trustworthy results. It was also noted that a representative and stable dry weather flow reference concentration is a strict requirement for the successful application of the proposed method.
受纳水体的生态状况可能会受到通过雨水径流排放的有机微量污染物的显著影响。据报道,量化微量污染物排放的努力主要集中在合流污水溢流和雨水下水道出口的采样上,这可能具有挑战性。本研究开发并测试了一种替代方法,称为指纹识别法。指纹识别法利用污水处理厂(WWTP)进水样本,并根据物质示踪剂的湿季与干季浓度来推断雨水中的比例,这些示踪剂仅存在于废水中。然后,可以根据 WWTP 进水的测量值,基于质量平衡来估算雨水径流中有机微量污染物的浓度。在这项研究中,指纹识别法应用于在荷兰的五个 WWTP 获得的进水样本中。总共使用了 28 个 DWF 和 22 个 WWF 样本。所选示踪剂为布洛芬、2-羟基布洛芬、萘普生和双氯芬酸。随后,通过 WWF 样本估算了 403 种有机微量污染物在雨水径流中的浓度。存在并分析的物质包括草甘膦和 AMPA、254 种农药中的 24 种、28 种有机氯农药中的 6 种、63 种药物中的 45 种、15 种多环芳烃中的 15 种、7 种 PCB 中的 2 种和 33 种其他物质中的 20 种(例如双酚 A)。与其他研究的结果进行比较表明,指纹识别法产生了可靠的结果。还注意到,代表性且稳定的干季流量参考浓度是成功应用所提出方法的严格要求。