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 - http://www.scopus.com/inward/record.url?scp=85087504941&partnerID=8YFLogxK
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 -