Hot and dry conditions elevate grass pollen and sub-pollen particle concentrations in Melbourne, Australia
Abstract
A Wideband Integrated Bioaerosol Sensor (WIBS) was used in conjunction with chemical tracer analysis for the first time during the 2022–2023 grass pollen season in Melbourne, Australia. WIBS detected continuous levels of bioaerosol throughout the campaign. From 18th November to 7th December 2022, fluorescent particles accounted for an average of 10% of total particles in number, corresponding to an estimated 0.18 μg m−3 PM2.5 (14%) and 0.49 μg m−3 PM10 (25%). Using mannitol as a chemical tracer, fungal spores were estimated to contribute to an average of 2% of PM2.5 and 9% of PM10 mass. Analysis of fructose in PM2.5 as a marker for sub-pollen particles (SPPs) showed elevated concentrations during periods of hot and dry weather. There was negligible fructose observed with rain, suggesting that SPP production is not limited to water absorption processes or high relative humidity in Melbourne. Estimates of SPP mass via fructose corresponded to the equivalent of 1.1 m−3 intact pollen grains on average, 2% of the total pollen concentration, 7% of PM2.5 fluorescent particle mass, and 1% of PM2.5 mass. New hourly measured grass pollen data confirmed the timing and magnitude of grass pollen emissions in the Victorian Grass Pollen Emission Model (VGPEM) and captured the strong diurnal variation. Five grass pollen rupturing mechanisms using different meteorological drivers were tested against the WIBS and fructose measurements. Whilst the WIBS and model were not well correlated, likely due to the complex mixture of bioaerosols and low relative abundance of SPPs, the mechanical wind speed rupturing mechanism represented the fructose time series well. Conceptually, this suggests that mechanical rupturing describes SPP formation during hot and dry conditions in Melbourne. Long-term measurements in Melbourne will improve SPP formation process forecasting.
- This article is part of the themed collection: Bioaerosols: detection, transport and risk assessment