Lessons from automatic airborne pollen monitoring by holography at three Australian sites - Andelija Milic; Beth Addison-Smith; Izhar Ullah; James K. Douch; Benedict J. Keaney; Paul J. Beggs; Simon G. Haberle; Janet M. Davies (Aerobiologia, 2026)
Automatic airborne pollen monitoring offers potential to enable real-time, sustainable environmental health information to assist with management of allergic respiratory disease. Automatic systems, however, have not been widely deployed in the Southern Hemisphere, where there is considerable biodiversity. An automatic holography-based device combined with a classification algorithm was trialled in Australia for 15 months over the main pollen seasons in subtropical Brisbane, and temperate Canberra and Sydney. Common airborne pollen taxa were monitored in parallel using Hirst-type volumetric traps, with manual observations serving as a reference. In Brisbane, the monitoring campaign coincided with the most extreme grass (Poaceae) pollen season ever observed. The automatic system assigned daily Poaceae pollen concentrations with high accuracy (ρ = 0.84, p p = 0.14). In Canberra, Poaceae and Betula were detected with a moderate to high correlation to manual observations (ρ = 0.67, p p Betula and Cupressaceae were, however, mistakenly assigned to Poaceae, and Betula was also misclassified as other Betulaceae taxa: Corylus and Carpinus . Pinaceae pollen was well recognized by the automatic system at this site (ρ = 0.59, p p = 0.35). The automatic system performed poorly in Sydney, where daily pollen concentrations were low, with high misassignment. While automatic pollen monitoring reduced the need for site visits and expedited daily forecasts, inconsistencies in classification and concentration levels between methods highlight the need to calibrate automatic systems to previously trained and locally relevant, regularly monitored pollen and their levels.

The ability of automated fluorometry and holography to discern airborne grass pollen beyond family level - Izhar Ullah; Andelija Milic; Beth Addison-Smith; Saeideh Hajighasemi; Darren Wraith; Janet M. Davies (Aerobiologia, 2026)
Grass pollen is the major outdoor allergen source, inducing allergic rhinitis in susceptible people. In Australia, the considerable prevalence of allergic rhinitis (23.8%) and asthma (11%) is creating a major health and economic burden. Subtropical grass species exhibit distinct ecological and phylogenetic differences compared with temperate grasses, including variations in pollen allergen composition and immune response. Traditional light microscopy, however, cannot differentiate between airborne grass pollen of various subfamilies. This study hypothesizes that automated holography and fluorometry sensing can discern grass pollen beyond family level (Poaceae). This project applied automatic sensing to five aerosolized dried grass pollen samples from Panicoideae; Paspalum notatum (Bahia grass) and Sorghum halepense (Johnson grass), Chloridoideae; Cynodon dactylon (Bermuda grass), and Pooideae; Lolium perenne (Ryegrass) and Phleum pratense (Timothy grass). Datasets were examined for differences in distributions of holography-derived particle features and emitted fluorescence spectra. In three repeated measurement campaigns of the same dry L. perenne pollen sample, distributions of particle features, and relative fluorescence intensity values suggested that reliability and reproducibility of automatic sensors remain a challenge. Data from five grass pollen types, even within the same subfamily, showed distinct morphological and fluorescence profiles, particularly at excitation 280 nm with 357 nm emission. The automated monitoring was also capable of distinguishing dried and freshly collected local P. notatum pollen. To translate these new insights for improved respiratory disease management, further research with broader data collection and validation with key locally relevant pollen taxa will be required for more precise real-time monitoring of grass pollen exposure.

Analysis of quality control outcomes of grass pollen identification and enumeration: experience matters - Andelija Milic; Beth Addison-Smith; Shanice Van Haeften; Janet M. Davies (Aerobiologia, 2021)

Standardising pollen monitoring: quantifying confidence intervals for measurements of airborne pollen concentration - Beth Addison-Smith; Darren Wraith; Janet M. Davies (Aerobiologia, 2020)

Quality control of pollen identification and quantification exercise for the AusPollen Aerobiology Collaboration Network: a pilot study - Andelija Milic; Beth Addison-Smith; Penelope J. Jones; Paul J. Beggs; Bircan Erbas; Janet M. Davies (Aerobiologia, 2020)