Department of Civil and Environmental Engineering, University of California, Davis, Davis, CA 95616, USA.
California Department of Pesticide Regulation, Sacramento, CA 95618, USA.
Environ Sci Process Impacts. 2024 Feb 21;26(2):357-367. doi: 10.1039/d3em00361b.
Treated wastewater effluent is a major contributor to concentrations of many anthropogenic chemicals in the environment. Examining patterns of these compounds measured from different catchment areas comprising the influent to a wastewater treatment plant, across many months, may reveal patterns in compound sources and seasonality helpful to management efforts. This study considers a wastewater catchment system that was sampled at six sub-catchment sites plus the treatment plant influent and effluent at seven time points spanning nine months. Wastewater samples were analyzed with LC-QTOF-MS using positive electrospray ionization and GC-QTOF-MS using negative chemical ionization and electron ionization. MS data were screened against spectral libraries to identify micropollutants. As expected, multiple classes of chemicals were represented, including pharmaceuticals, plasticizers, personal care products, and flame retardants. Patterns in the compounds seen at different sampling sites and dates reflect the varying uses and down-the-drain routes that influence micropollutant loading in sewer systems. Patterns in examined compounds revealed little spatial variation, and greater temporal variation. For example, the greatest loads of DEET were found to occur in the summer months. Additionally, groups of compounds exhibited strong correlation with each other, which could be indicative of similar down-the-drain routes (such as a group intercorrelated chemicals that are components of cleaning products) or the influence of similar physicochemical processes within the sewer system. This study contributes to the understanding of dynamics of micropollutants in sewer systems.
处理后的废水是环境中许多人为化学物质浓度的主要贡献者。检查从构成废水处理厂进水的不同集水区在多个月内测量的这些化合物的模式，可以揭示化合物来源和季节性的模式，这有助于管理工作。本研究考虑了一个废水集水系统，该系统在七个时间点在六个子集水区采样，加上处理厂进水和出水，时间跨度为九个月。使用正电喷雾电离的 LC-QTOF-MS 和使用负化学电离和电子电离的 GC-QTOF-MS 对废水样品进行了分析。MS 数据与光谱库进行了筛选，以识别微量污染物。正如预期的那样，代表了多种化学物质类别，包括药品、增塑剂、个人护理产品和阻燃剂。在不同采样点和日期看到的化合物模式反映了影响下水道系统中微量污染物负荷的不同用途和下水道排放路径。所检查化合物的模式显示出很少的空间变化，而时间变化较大。例如，发现避蚊胺的最大负荷出现在夏季。此外，一些化合物组彼此之间存在很强的相关性，这可能表明存在类似的下水道排放路径（例如，一组相互关联的化学物质是清洁产品的组成部分）或下水道系统内类似物理化学过程的影响。本研究有助于了解下水道系统中微量污染物的动态。
