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COLITREND: Monitoring E. COLI dynamics at high temporal resolution in Canadian drinking water supplies using autonomous online measurement technology

COLITREND: Monitoring E. COLI dynamics at high temporal resolution in Canadian drinking water supplies using autonomous online measurement technology
COLITREND:使用自主在线测量技术以高时间分辨率监测加拿大饮用水供应中的大肠杆菌动态
批准号:
505651-2016
负责人:
Dorner, Sarah
金额:
$4.91万
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2019
资助国家:
加拿大
项目状态:
已结题
起止时间:
2019-01-01 至 2020-12-31

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中文摘要
翻译
粪便指示菌大肠杆菌的培养检测已成为饮用水水源微生物质量常规监测的基准。然而,该方法至少需要18-24小时才能提供大肠杆菌计数,这使得在微生物危害导致超过监管阈值的情况下无法采取快速和具有成本效益的决策。近年来,人们开发了新的技术来简化和加速水中大肠杆菌的检测。它们自动收集和高精度测量ß-D-glucoronidase活性,这是一种大肠杆菌特有的酶,无需培养。结果会实时传送到用户的电脑或智能手机上。在这个项目中,我们的目标是在加拿大的多个饮用水处理厂实施这项新颖的创新技术,以更好地评估它们的摄入量对粪便污染的脆弱性。设备将以精细的时间分辨率测量大肠杆菌动力学,以识别、表征和预测大肠杆菌峰值浓度,并通过基于过程的建模阐明当地水文气候学与峰值污染事件之间的关联。对于选定的地点和时期,将描述病原体的发生,以了解与测量相关的微生物风险。由于这些新技术提供的荧光单位不同于通过培养获得的经典计数,因此本项目的一个主要任务将是将信号与依赖于培养的方法产生的信号进行比较,也可以与实时PCR等不依赖于培养的方法产生的信号进行比较。更好地了解这些技术提供的信号是在早期预警系统中实施这项技术的必要先决条件,以便有效地监测水质,或作为受管制的微生物指标的改进替代品。为利用高频监测结果制定统计和建模框架将使水管理人员和管理人员能够改进监测、风险评估和决策。该项目将与来自阿尔伯塔省和魁省的工业伙伴合作,培训7名高素质人才。
英文摘要
Detection of the fecal indicator bacterium Escherichia coli by culture has been the benchmark for routine monitoring of microbiological quality in drinking water sources. However, the method requires a minimum of 18-24 hours to deliver E. coli counts, which makes it impossible to take rapid and cost-effective decisions in case of microbial hazards that lead to regulatory threshold exceedances. Recently, new technologies have been developed to streamline and accelerate E. coli detection in water. They autonomously collect and measure at high precision ß-D-glucoronidase activity, an enzyme specific to E. coli, without the need for cultivation. Results are delivered in real time to the user on its computer or smartphone. In this project, we aim at implementing the novel and innovative technology at multiple Canadian drinking water treatment plants to better assess the vulnerability of their intakes to fecal pollution. Devices will measure E. coli dynamics at fine temporal resolution to identify, characterize and predict E. coli peak concentrations and elucidate the association between local hydro-climatology and peak pollution events through process-based modelling. For selected sites and periods, the occurrence of pathogens will be described to understand the microbial risk associated with measurements. As these new technologies provide fluorescence units that are different from the classic counts obtained by culture, a major task of this project will be to compare signals to those generated by culture-dependent but also culture-independent methods such as real time PCR. A better understanding of the signals provided by these technologies is an essential pre-requisite to the implementation of this technology in early warning systems for efficient water quality monitoring or as an improved alternative to regulated microbial indicators. The development of a statistical and modelling framework for the exploitation of the high-frequency monitoring results will enable improved monitoring, risk assessment and decision-making by water managers and regulators. This project will train 7 highly qualified personnel in collaboration with industrial partners from Alberta and Québec.
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Water reuse: innovative monitoring technologies for risk reduction
  • 批准号:
    RGPIN-2019-05321
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.13万
  • 财政年份:
    2022
  • 负责人:
    Dorner, Sarah
  • 依托单位:
Water reuse: innovative monitoring technologies for risk reduction
  • 批准号:
    RGPIN-2019-05321
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.13万
  • 财政年份:
    2021
  • 负责人:
    Dorner, Sarah
  • 依托单位:
Green infrastructure for sustainable source water protection
  • 批准号:
    513260-2017
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $3.72万
  • 财政年份:
    2020
  • 负责人:
    Dorner, Sarah
  • 依托单位:
Water reuse: innovative monitoring technologies for risk reduction
  • 批准号:
    RGPIN-2019-05321
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.13万
  • 财政年份:
    2020
  • 负责人:
    Dorner, Sarah
  • 依托单位:
海外基金