A Comparison of the Poleno Jupiter Automated Pollen Monitor with the Traditional Hirst Method

Asthma and seasonal allergic rhinitis are common conditions affecting health, wellbeing, and work place productivity. Current pollen monitoring requires experienced technicians and has a lag of at least 24 h, which limits usefulness for patient management. We evaluated agreement of daily pollen concentrations from an automated real-time sampler, the Swisens Poleno Jupiter, with a traditional Hirst-type trap using technician counting over a single monitoring season in England. We used regression models to assess the impact of weather covariates on differences. Total pollen showed a strong correlation (r = 0.74) but moderate Intraclass Correlation (ICC = 0.52) between devices, due to concentrations (total and taxa level) being higher for the manual than the automated sampler. For individual pollen taxa, strong correlation and good agreement was observed for Pinus, Alnus and Fraxinus throughout the monitoring period. Strong correlation but low/moderate agreement was observed for Poaceae (grass), Betula, Quercus and Taxus/Cupressus. No correlation or agreement was observed for Corylus and Platanus. Temperature explained most of the variability between samplers. We conclude that daily total pollen can be tracked using an automated Poleno, as can grass within its flowering season, but Poleno recognition algorithms developed for mainland Europe need further refinements for UK species. Improving agreement in quantification is of particular importance given that current allergenic thresholds are based on manual readings.

Authors

Institutions

Publication Details

Journal
Atmosphere
Published
2026-07-22
DOI
https://doi.org/10.3390/atmos17070705
Primary Topic
Allergic Rhinitis and Sensitization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Comparison of the Poleno Jupiter Automated Pollen Monitor with the Traditional Hirst Method

Leah Cuthbertson, Anna Hansell, Fiona A. Symon, Katie Eminson et al.
Atmosphere
Allergic Rhinitis and Sensitization
article

A Comparison of the Poleno Jupiter Automated Pollen Monitor with the Traditional Hirst Method

Leah Cuthbertson, Anna Hansell, Fiona A. Symon, Katie Eminson, Jack Satchwell
article en

Abstract

Asthma and seasonal allergic rhinitis are common conditions affecting health, wellbeing, and work place productivity. Current pollen monitoring requires experienced technicians and has a lag of at least 24 h, which limits usefulness for patient management. We evaluated agreement of daily pollen concentrations from an automated real-time sampler, the Swisens Poleno Jupiter, with a traditional Hirst-type trap using technician counting over a single monitoring season in England. We used regression models to assess the impact of weather covariates on differences. Total pollen showed a strong correlation (r = 0.74) but moderate Intraclass Correlation (ICC = 0.52) between devices, due to concentrations (total and taxa level) being higher for the manual than the automated sampler. For individual pollen taxa, strong correlation and good agreement was observed for Pinus, Alnus and Fraxinus throughout the monitoring period. Strong correlation but low/moderate agreement was observed for Poaceae (grass), Betula, Quercus and Taxus/Cupressus. No correlation or agreement was observed for Corylus and Platanus. Temperature explained most of the variability between samplers. We conclude that daily total pollen can be tracked using an automated Poleno, as can grass within its flowering season, but Poleno recognition algorithms developed for mainland Europe need further refinements for UK species. Improving agreement in quantification is of particular importance given that current allergenic thresholds are based on manual readings.

AtmosphereVol. 17(7)
University of Leicester (GB), Leicester General Hospital (GB), NIHR Leicester Cardiovascular Biomedical Research Unit (GB), NIHR Leicester Biomedical Research Centre (GB)
Openalex Percentile: Top 10%
Allergic Rhinitis and Sensitization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.