Integrating meteorological data into linear mixed models for sunlight inactivation of indicator organisms in natural...

Sunlight plays a crucial role in inactivating pathogens and is a key determinant of environmental persistence. However, meteorological conditions can have a varied and challenging role in the prediction of inactivation rates. This study examines the persistence of viruses and bacteria in a natural lake environment under variable weather, particularly cloud cover. A contaminant event was simulated by diluting wastewater with lake water, or spiking in MS2 and phi6 bacteriophages, enclosing the mixture in dialysis bags suspended with the lake and exposing them to natural sunlight for three to four days. All microorganisms achieved 4-log inactivation within three days, with viruses being three times more sensitive to sunlight than bacteria. Notably, bacterial inactivation rate constants increased over the experimental timeframe, while viral rate constants remained relatively constant. Repair mechanisms were observed in bacteria (-0.016 ± 0.0029 h^-1) but not in viruses. Based on detailed weather station data, the impact of diverse meteorological conditions was examined using linear mixed models (LMMs) for both viruses and bacteria, enabling prediction of inactivation rates throughout the summer months. These models quantified the influence of various factors, including temperature, cloud cover percentage, cloud height, water depth, solar irradiance, and zenith angle. The results highlight significant differences between laboratory and natural environmental conditions, particularly the impact of fluctuating meteorological factors on pathogen inactivation rates.