This study presents a multi-parameter source water risk framework for Legionella prediction in Ontario cooling tower systems, integrating three independent provincial datasets: 60 years of Ontario Provincial Water Quality Monitoring Network (PWQMN) data comprising 7,630,482 measurements across 2,128 monitoring stations; Ontario Drinking Water System Adverse Water Quality Incident (AWQI) records from 2020 to 2025 covering 18,114 documented incidents; and Public Health Ontario legionellosis surveillance data from 2019 to 2025 documenting 354 confirmed cases annually with a 76.6% hospitalization rate. Analysis reveals that the Grand River watershed scores 14 of 15 on a composite Legionella risk index derived from peer-reviewed physicochemical risk parameters. Simultaneous seasonal elevation of hardness (mean 278 mg/L), temperature (Q3 mean 20.8°C, within the amoeba growth window), turbidity (mean 42.7 NTU), total phosphorus (above Ontario eutrophication threshold), and iron (311 µg/L) creates a predictable multi-parameter convergence every summer that current Water Management Plans do not address. Five years of AWQI records reveal that low chlorine residual incidents — a documented consequence of elevated hardness and pH reducing disinfection efficacy — increased from 142 in 2021-22 to 192 in 2024-25, following a parallel trajectory to Legionella case counts. The 2024-25 fiscal year recorded a 10-fold increase in documented exceedances coinciding with the largest Legionella outbreak in Middlesex-London Health Unit history. The Presignal Multi-Parameter Legionella Risk Framework is proposed for integration with ASHRAE Standard 188-2021 Water Management Plans. Ontario currently has no provincial cooling tower registry and no mandatory predictive monitoring standard. This paper provides the scientific basis for both. Related work: Grand River Source Water Paper — DOI: 10.5281/zenodo.19653415. Legionella Seasonal Correlation Paper — DOI: 10.5281/zenodo.19695022.
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John Carter
Associated Press
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John Carter (Fri,) studied this question.
www.synapsesocial.com/papers/69f6e6478071d4f1bdfc6ea6 — DOI: https://doi.org/10.5281/zenodo.19935260