Meteorological and Air Quality Effects on Bioaerosol Detection Using WIBS-NEO and IBAC-2 in Dublin City

This study evaluates the performance of two real-time fluorescence-based bioaerosol sensors, the WIBS-NEO and IBAC-2, operating in urban Dublin, Ireland, and assesses the influence of different meteorological and pollution parameters on their outputs. This was done by comparing particle sensor data to meteorological variables and air quality metrics. Over the 41-day campaign, Urticaceae pollen and Cladosporium spores were the dominant bioaerosols recorded, comprising 78% and 66% of total pollen and fungal spore concentrations, respectively. Correlation analyses revealed several significant variables: fluorescent BC-type particles (>8 μm) detected by WIBS-NEO strongly correlated with pollen concentrations (r = 0.84 after excluding high-wind days). For fungal spores, PM₁₀ and grass minimum temperature were the most significant parameters related to variability. Anthropogenic pollutants, particularly NO_X and combustion-related aerosols, were found to correlate with fluorescence signals, especially for smaller particles (<2 μm), underscoring urban detection challenges. Wind trajectory analysis identified the likely source of Urticaceae pollen as northerly green spaces (e.g., Phoenix Park), while Cladosporium spores showed multidirectional transport. Multiple linear regression (MLR) analysis achieved strong correlation ((Formula presented.) = 0.82 for pollen, 0.78 for fungal spores), highlighting the value of incorporating multiple environmental variables to investigate the complex relationships between urban environmental conditions and bioaerosol sensor outputs. Both instruments exhibited operational limitations under the study conditions. The WIBS-NEO outperformed the IBAC-2 in biological discrimination due to its multi-channel single particle fluorescence capabilities. However, operational limitations emerged during higher wind speeds, comparable to moderate breezes (>16.6 km/h), which affected sampling comparability when compared with traditional methods. This study investigates how meteorological conditions and air quality influence bioaerosol detection in an urban environment. The use of MLR techniques to examine the complex relationships between environmental variables and fluorescent sensor outputs may help inform future bioaerosol modelling efforts.