ArticleInternational journal of environmental research and public health2022
Detecting Airborne Pollen Using an Automatic, Real-Time Monitoring System: Evidence from Two Sites.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Can a single pollen measurement site provide exposure information for health research across an entire state? Results from a study of allergic-type asthma associated with thunderstorms (2007-2018).Journal of exposure science & environmental epidemiology · 2026Pooled it
- From field to sky: measurement and modeling of transgenic switchgrass pollen dispersal in the atmosphere.Environmental monitoring and assessment · 2026Article
- Toward Accurate Real-Time Bioaerosol Monitoring in the Particle Size Range 1 μm-70 μm.ACS ES&T air · 2025Article
- Automating airborne pollen classification: Identifying and interpreting hard samples for classifiers.Heliyon · 2025Article
- Article
- Climate change, airborne allergens, and three translational mitigation approaches.EBioMedicine · 2023Review
- Field Evaluation of an Automated Pollen Sensor.International journal of environmental research and public health · 2022Article
- Detection and Recognition of Pollen Grains in Multilabel Microscopic Images.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Airborne pollen monitoring has been an arduous task, making ecological applications and allergy management virtually disconnected from everyday practice. Over the last decade, intensive research has been conducted worldwide to automate this task and to obtain real-time measurements. The aim of this study was to evaluate such an automated biomonitoring system vs. the conventional 'gold-standard' Hirst-type technique, attempting to assess which may more accurately provide the genuine exposure to airborne pollen. Airborne pollen was monitored in Augsburg since 2015 with two different methods, a novel automatic Bio-Aerosol Analyser, and with the conventional 7-day recording Hirst-type volumetric trap, in two different sites. The reliability, performance, accuracy, and comparability of the BAA500 Pollen Monitor (PoMo) vs. the conventional device were investigated, by use of approximately 2.5 million particles sampled during the study period. The observations made by the automated PoMo showed an average accuracy of approximately 85%. However, it also exhibited reliability problems, with information gaps within the main pollen season of between 17 to 19 days. The PoMo automated algorithm had identification issues, mainly confusing the taxa of
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.