Automated Targeted Sampling of Waterborne Pathogens and Microbial Source Tracking Markers Using Near-Real Time Monitoring of Microbiological Water Quality
Jean-Baptiste Burnet,
Marc Habash,
Mounia Hachad,
Zeinab Khanafer,
Michèle Prévost,
Pierre Servais,
Emile Sylvestre,
Sarah Dorner
Affiliations
Jean-Baptiste Burnet
Canada Research Chair in Source Water Protection, Department of Civil, Geological and Mining Engineering, Polytechnique Montreal, Montreal, QC H3C 3A7, Canada
Marc Habash
School of Environmental Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada
Mounia Hachad
Canada Research Chair in Source Water Protection, Department of Civil, Geological and Mining Engineering, Polytechnique Montreal, Montreal, QC H3C 3A7, Canada
Zeinab Khanafer
Canada Research Chair in Source Water Protection, Department of Civil, Geological and Mining Engineering, Polytechnique Montreal, Montreal, QC H3C 3A7, Canada
Michèle Prévost
NSERC Industrial Chair on Drinking Water, Department of Civil, Geological and Mining Engineering, Polytechnique Montreal, Montreal, QC H3C 3A7, Canada
Pierre Servais
Écologie des Systèmes Aquatiques, Campus de la Plaine, Université Libre de Bruxelles, B-1050 Bruxelles, Belgium
Emile Sylvestre
Canada Research Chair in Source Water Protection, Department of Civil, Geological and Mining Engineering, Polytechnique Montreal, Montreal, QC H3C 3A7, Canada
Sarah Dorner
Canada Research Chair in Source Water Protection, Department of Civil, Geological and Mining Engineering, Polytechnique Montreal, Montreal, QC H3C 3A7, Canada
Waterborne pathogens are heterogeneously distributed across various spatiotemporal scales in water resources, and representative sampling is therefore crucial for accurate risk assessment. Since regulatory monitoring of microbiological water quality is usually conducted at fixed time intervals, it can miss short-term fecal contamination episodes and underestimate underlying microbial risks. In the present paper, we developed a new automated sampling methodology based on near real-time measurement of a biochemical indicator of fecal pollution. Online monitoring of β-D-glucuronidase (GLUC) activity was used to trigger an automated sampler during fecal contamination events in a drinking water supply and at an urban beach. Significant increases in protozoan parasites, microbial source tracking markers and E. coli were measured during short-term (E. coli. The proposed event sampling methodology is versatile and in addition to the two triggering modes validated here, others can be designed based on specific needs and local settings. In support to regulatory monitoring schemes, it should ultimately help gathering crucial data on waterborne pathogens more efficiently during episodic fecal pollution events.
