Automated online monitoring of fecal pollution in water by enzymatic methods

Katalin Demeter; Jean Baptiste Burnet; Philipp Stadler; Alexander Kirschner; Matthias Zessner; Andreas H. Farnleitner

doi:10.1016/j.coesh.2020.03.002

Automated online monitoring of fecal pollution in water by enzymatic methods

Katalin Demeter
, Jean Baptiste Burnet
, Philipp Stadler
, Alexander Kirschner
, Matthias Zessner
, Andreas H. Farnleitner^*

^*Corresponding author for this work

Department of Water Quality and Health

Research output: Journal article (peer-reviewed) › Review article

13 Citations (Scopus)

Abstract

To facilitate the prompt management of public health risks from water resources, the fluorescence-based detection of the enzymatic activity of β-D-glucuronidase (GLUC) has been suggested as a rapid method to monitor fecal pollution. New technological adaptations enable now its automated, near-real-time measurement in a robust and analytically precise manner. Large data sets of high temporal or spatial resolution have been reported from a variety of freshwater resources, demonstrating the great potential of this automated method. However, the fecal indication capacity of GLUC activity and the potential link to health risk is still unclear, presenting considerable limitations. This review provides a critical evaluation of automated, online GLUC-based methods (and alternatives) and defines open questions to be solved before the method can fully support water management.

Original language	English
Pages (from-to)	82-91
Number of pages	10
Journal	Current Opinion in Environmental Science and Health
Volume	16
DOIs	https://doi.org/10.1016/j.coesh.2020.03.002
Publication status	Published - Aug 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 6 Clean Water and Sanitation

Keywords

E. coli
Fecal indicator bacteria
Fecal pollution
Rapid enzymatic methods
Water safety
β-d-Glucuronidase

ASJC Scopus subject areas

Environmental Chemistry
Public Health, Environmental and Occupational Health
Health, Toxicology and Mutagenesis

Access to Document

10.1016/j.coesh.2020.03.002

Cite this

@article{5e26ebeb95774875b1480f215644ff16,

title = "Automated online monitoring of fecal pollution in water by enzymatic methods",

abstract = "To facilitate the prompt management of public health risks from water resources, the fluorescence-based detection of the enzymatic activity of β-D-glucuronidase (GLUC) has been suggested as a rapid method to monitor fecal pollution. New technological adaptations enable now its automated, near-real-time measurement in a robust and analytically precise manner. Large data sets of high temporal or spatial resolution have been reported from a variety of freshwater resources, demonstrating the great potential of this automated method. However, the fecal indication capacity of GLUC activity and the potential link to health risk is still unclear, presenting considerable limitations. This review provides a critical evaluation of automated, online GLUC-based methods (and alternatives) and defines open questions to be solved before the method can fully support water management.",

keywords = "E. coli, Fecal indicator bacteria, Fecal pollution, Rapid enzymatic methods, Water safety, β-d-Glucuronidase",

author = "Katalin Demeter and Burnet, \{Jean Baptiste\} and Philipp Stadler and Alexander Kirschner and Matthias Zessner and Farnleitner, \{Andreas H.\}",

note = "Funding Information: This work was supported by the N{\"O} Forschungs- und Bildungsges.m.b.H., Austria ( NFB , grant number SC15-016 ), the Austrian Science Fund ( FWF , grant number W1219 ), the TU Wien, Austria (grant number GIP226TPC ), the Austrian Research Promotion Agency (FFG, grant number 841582–3735473 ), as well as the Natural Sciences and Engineering Research Council of Canada (NSERC, grant number CRDPJ-505651-16 ). Publisher Copyright: {\textcopyright} 2020 The Authors",

year = "2020",

month = aug,

doi = "10.1016/j.coesh.2020.03.002",

language = "English",

volume = "16",

pages = "82--91",

journal = "Current Opinion in Environmental Science and Health",

issn = "2468-5844",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - Automated online monitoring of fecal pollution in water by enzymatic methods

AU - Demeter, Katalin

AU - Burnet, Jean Baptiste

AU - Stadler, Philipp

AU - Kirschner, Alexander

AU - Zessner, Matthias

AU - Farnleitner, Andreas H.

N1 - Funding Information: This work was supported by the NÖ Forschungs- und Bildungsges.m.b.H., Austria ( NFB , grant number SC15-016 ), the Austrian Science Fund ( FWF , grant number W1219 ), the TU Wien, Austria (grant number GIP226TPC ), the Austrian Research Promotion Agency (FFG, grant number 841582–3735473 ), as well as the Natural Sciences and Engineering Research Council of Canada (NSERC, grant number CRDPJ-505651-16 ). Publisher Copyright: © 2020 The Authors

PY - 2020/8

Y1 - 2020/8

N2 - To facilitate the prompt management of public health risks from water resources, the fluorescence-based detection of the enzymatic activity of β-D-glucuronidase (GLUC) has been suggested as a rapid method to monitor fecal pollution. New technological adaptations enable now its automated, near-real-time measurement in a robust and analytically precise manner. Large data sets of high temporal or spatial resolution have been reported from a variety of freshwater resources, demonstrating the great potential of this automated method. However, the fecal indication capacity of GLUC activity and the potential link to health risk is still unclear, presenting considerable limitations. This review provides a critical evaluation of automated, online GLUC-based methods (and alternatives) and defines open questions to be solved before the method can fully support water management.

AB - To facilitate the prompt management of public health risks from water resources, the fluorescence-based detection of the enzymatic activity of β-D-glucuronidase (GLUC) has been suggested as a rapid method to monitor fecal pollution. New technological adaptations enable now its automated, near-real-time measurement in a robust and analytically precise manner. Large data sets of high temporal or spatial resolution have been reported from a variety of freshwater resources, demonstrating the great potential of this automated method. However, the fecal indication capacity of GLUC activity and the potential link to health risk is still unclear, presenting considerable limitations. This review provides a critical evaluation of automated, online GLUC-based methods (and alternatives) and defines open questions to be solved before the method can fully support water management.

KW - E. coli

KW - Fecal indicator bacteria

KW - Fecal pollution

KW - Rapid enzymatic methods

KW - Water safety

KW - β-d-Glucuronidase

UR - https://www.scopus.com/pages/publications/85087504941

U2 - 10.1016/j.coesh.2020.03.002

DO - 10.1016/j.coesh.2020.03.002

M3 - Review article

AN - SCOPUS:85087504941

SN - 2468-5844

VL - 16

SP - 82

EP - 91

JO - Current Opinion in Environmental Science and Health

JF - Current Opinion in Environmental Science and Health

ER -

Automated online monitoring of fecal pollution in water by enzymatic methods

Abstract

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this