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Source tracking using microbial community fingerprints: Method comparison with hydrodynamic modelling

机译:使用微生物群落指纹进行源追踪:与流体动力学建模的方法比较

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摘要

Urban estuaries around the world are experiencing contamination from diffuse and point sources, which increases risks to public health. To mitigate and manage risks posed by elevated levels of contamination in urban waterways, it is critical to identify the primary water sources of contamination within catchments. Source tracking using microbial community fingerprints is one tool that can be used to identify sources. However, results derived from this approach have not yet been evaluated using independent datasets. As such, the key objectives of this investigation were: (1) to identify the major sources of water responsible for bacterial loadings within an urban estuary using microbial source tracking (MST) using microbial communities; and (2) to evaluate this method using a 3-dimensional hydrodynamic model. The Yarra River estuary, which flows through the city of Melbourne in South-East Australia was the focus of this study. We found that the water sources contributing to the bacterial community in the Yarra River estuary varied temporally depending on the estuary's hydrodynamic conditions. The water source apportionment determined using microbial community MST correlated to those determined using a 3 dimensional hydrodynamic model of the transport and mixing of a tracer in the estuary. While there were some discrepancies between the two methods, this investigation demonstrated that MST using bacterial community fingerprints can identify the primary water sources of microorganisms in an estuarine environment. As such, with further optimization and improvements, microbial community MST has the potential to become a powerful tool that could be practically applied in the mitigation of contaminated aquatic systems. (C) 2016 Elsevier Ltd. All rights reserved.
机译:世界各地的城市河口都受到来自分散点和点源的污染,这增加了公共卫生的风险。为了减轻和管理城市水道污染水平升高带来的风险,至关重要的是要确定集水区内的主要污染水源。使用微生物群落指纹进行源跟踪是一种可用于识别源的工具。但是,尚未使用独立的数据集评估从该方法得出的结果。因此,这项调查的主要目标是:(1)通过使用微生物群落的微生物来源跟踪(MST)来确定造成城市河口细菌负荷的主要水源; (2)使用3维水动力模型评估该方法。这项研究的重点是流经澳大利亚东南部墨尔本市的亚拉河河口。我们发现,对亚拉河河口细菌群落起作用的水源在时间上随河口的水动力条件而变化。使用微生物群落MST确定的水源分配与使用在河口中的示踪物的运输和混合的3维流体动力学模型确定的水源分配相关。尽管两种方法之间存在一些差异,但这项研究表明,使用细菌群落指纹的MST可以识别出河口环境中微生物的主要水源。这样,通过进一步的优化和改进,微生物群落MST有望成为一种功能强大的工具,可以切实应用于减轻污染的水生系统。 (C)2016 Elsevier Ltd.保留所有权利。

著录项

  • 来源
    《Water Research》 |2017年第1期|253-265|共13页
  • 作者单位

    Monash Univ, Dept Civil Engn, EPHM Lab, Clayton, Vic 3800, Australia;

    Monash Univ, Dept Civil Engn, EPHM Lab, Clayton, Vic 3800, Australia;

    Monash Univ, Dept Civil Engn, EPHM Lab, Clayton, Vic 3800, Australia;

    BMT WBM Pty Ltd, Water & Environm Grp, Spring Hill, Qld, Australia;

    BMT WBM Pty Ltd, Water & Environm Grp, Spring Hill, Qld, Australia;

    Monash Univ, Dept Civil Engn, EPHM Lab, Clayton, Vic 3800, Australia;

    Melbourne Water Corp, Melbourne, Vic, Australia;

    Melbourne Water Corp, Melbourne, Vic, Australia;

    Melbourne Water Corp, Melbourne, Vic, Australia;

    Monash Univ, Dept Microbiol, Micromon, Clayton, Vic 3800, Australia;

    Univ Western Australia, Sch Earth & Environm, Crawley, WA, Australia|Univ Western Australia, Oceans Inst, Crawley, WA, Australia;

    Univ Western Australia, Sch Earth & Environm, Crawley, WA, Australia|Univ Western Australia, Oceans Inst, Crawley, WA, Australia;

    Monash Univ, Dept Civil Engn, EPHM Lab, Clayton, Vic 3800, Australia;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Community profiling; Microbial source tracking (MST); Faecal source tracking; Urban stormwater; Tuflow; SourceTracker;

    机译:社区概况;微生物源跟踪(MST);粪便源跟踪;城市雨水;Tuflow;SourceTracker;

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