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应用微生物和病原体溯源工具箱识别雨水排水管网基础设施问题:案例研究。

Application of a microbial and pathogen source tracking toolbox to identify infrastructure problems in stormwater drainage networks: a case study.

机构信息

School of Public Health, University of Alberta, Edmonton, Alberta, Canada.

Community Infrastructure, City of Airdrie, Airdrie, Alberta, Canada.

出版信息

Microbiol Spectr. 2024 Sep 3;12(9):e0033724. doi: 10.1128/spectrum.00337-24. Epub 2024 Aug 7.

Abstract

Water scarcity and increasing urbanization are forcing municipalities to consider alternative water sources, such as stormwater, to fill in water supply gaps or address hydromodification of receiving urban streams. Mounting evidence suggests that stormwater is often contaminated with human feces, even in stormwater drainage systems separate from sanitary sewers. Pinpointing sources of human contamination in drainage networks is challenging given the diverse sources of fecal pollution that can impact these systems and the non-specificity of traditional fecal indicator bacteria (FIB) for identifying these host sources. As such, we used a toolbox approach that encompassed microbial source tracking (MST), FIB monitoring, and bacterial pathogen monitoring to investigate microbial contamination of stormwater in an urban municipality. We demonstrate that human sewage frequently contaminated stormwater (in >50% of routine samples), based on the presence of the human fecal marker HF183, and often exceeded microbial water quality criteria. , a pathogen of emerging concern, was also detected in >50% of routine samples, with 75% of these pathogen-positive samples also being positive for the human fecal marker HF183, suggesting human municipal sewage as the likely source for this pathogen. MST and FIB were used to track human fecal pollution in the drainage network to the most likely point source of contamination, for which a sewage cross-connection was identified and confirmed using tracer dyes. These results point to the ubiquitous presence of human sewage in stormwater and also provide municipalities with the tools to identify sources of anthropogenic contamination in storm drainage networks.IMPORTANCEWater scarcity, increased urbanization, and population growth are driving municipalities worldwide to consider stormwater as an alternative water source in urban environments. However, many studies suggest that stormwater is relatively poor in terms of microbial water quality, is frequently contaminated with human sewage, and therefore could represent a potential health risk depending on the type of exposure (e.g., irrigation of community gardens). Traditional monitoring of water quality based on fecal bacteria does not provide any information about the sources of fecal pollution contaminating stormwater (i.e., animals/human feces). Herein, we present a case study that uses fecal bacterial monitoring, microbial source tracking, and bacterial pathogen analysis to identify a cross-connection that contributed to human fecal intrusion into an urban stormwater network. This microbial toolbox approach can be useful for municipalities in identifying infrastructure problems in stormwater drainage networks to reduce risks associated with water reuse.

摘要

水资源短缺和城市化进程的加快迫使市政当局考虑使用替代水源,例如雨水,以填补供水缺口或解决受纳城市溪流的水文变化。越来越多的证据表明,即使在与卫生下水道分开的雨水排水系统中,雨水也经常受到人类粪便的污染。由于可能影响这些系统的粪便污染来源多种多样,以及传统粪便指示细菌 (FIB) 识别这些宿主来源的特异性不强,因此,要确定排水网络中人类污染的来源具有挑战性。因此,我们使用了一个包含微生物源追踪 (MST)、FIB 监测和细菌病原体监测的工具包方法来调查城市市政雨水的微生物污染。我们的研究表明,根据人类粪便标记物 HF183 的存在,人类污水经常污染雨水(在超过 50%的常规样本中),并且经常超过微生物水质标准。也是一种新出现的关注病原体,在超过 50%的常规样本中也被检测到,其中 75%的病原体阳性样本也对人类粪便标记物 HF183 呈阳性,表明人类市政污水可能是这种病原体的来源。MST 和 FIB 用于追踪排水网络中的人类粪便污染到最有可能的污染源,对于该污染源,使用示踪染料识别并确认了污水交叉连接。这些结果表明,人类污水在雨水中普遍存在,并为市政当局提供了识别雨水排水管网中人为污染来源的工具。

重要性 水资源短缺、城市化进程加快和人口增长促使全球各国政府在城市环境中考虑将雨水作为替代水源。然而,许多研究表明,雨水在微生物水质方面相对较差,经常受到人类污水的污染,因此根据暴露类型(例如,社区花园灌溉),可能构成潜在的健康风险。基于粪便细菌的传统水质监测不能提供有关污染雨水的粪便污染来源的任何信息(即,动物/人类粪便)。在此,我们提出了一个案例研究,该研究使用粪便细菌监测、微生物源追踪和细菌病原体分析来识别导致人类粪便进入城市雨水网络的交叉连接。这种微生物工具包方法可用于市政当局识别雨水排水管网中的基础设施问题,以降低与水再利用相关的风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ee72/11371268/cbcaffacb459/spectrum.00337-24.f001.jpg

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