Articles | Volume 14, issue 12
https://doi.org/10.5194/amt-14-7693-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-7693-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Dec 2021
Research article |
| 08 Dec 2021
| 08 Dec 2021
Assessment of real-time bioaerosol particle counters using reference chamber experiments
Gian Lieberherr
CORRESPONDING AUTHOR
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
Kevin Auderset
Federal Institute of Metrology (METAS), Bern-Wabern, Switzerland
Bertrand Calpini
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
Bernard Clot
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
Benoît Crouzy
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
Martin Gysel-Beer
Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen, Switzerland
Thomas Konzelmann
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
José Manzano
Technological University of Dublin, Dublin, Ireland
now at: Technical University of Munich, Munich, Germany
Andrea Mihajlovic
BioSense Institute – Research Institute for Information Technologies in Biosystems, University of Novi Sad, Novi Sad, Serbia
Alireza Moallemi
Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen, Switzerland
David O'Connor
Technological University of Dublin, Dublin, Ireland
Dublin City University, Dublin, Ireland
Branko Sikoparija
BioSense Institute – Research Institute for Information Technologies in Biosystems, University of Novi Sad, Novi Sad, Serbia
Eric Sauvageat
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
now at: Institute of Applied Physics and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Fiona Tummon
Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
Konstantina Vasilatou
CORRESPONDING AUTHOR
Federal Institute of Metrology (METAS), Bern-Wabern, Switzerland
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Cited
22 citations as recorded by crossref.
- Comparison of computer vision models in application to pollen classification using light scattering G. Daunys et al. 10.1007/s10453-022-09769-0
- Airborne bacteria viability and air quality: a protocol to quantitatively investigate the possible correlation by an atmospheric simulation chamber V. Vernocchi et al. 10.5194/amt-16-5479-2023
- Is the oxidative potential of components of fine particulate matter surface-mediated? K. Baumann et al. 10.1007/s11356-022-24897-3
- Recent progress in online detection methods of bioaerosols T. An et al. 10.1016/j.fmre.2023.05.012
- Extending traceability in airborne particle size distribution measurements beyond 10 µm: Counting efficiency and unit-to-unit variability of four aerodynamic particle size spectrometers K. Vasilatou et al. 10.1080/02786826.2022.2139659
- Explainable AI for unveiling deep learning pollen classification model based on fusion of scattered light patterns and fluorescence spectroscopy S. Brdar et al. 10.1038/s41598-023-30064-6
- Pollen classification using a single particle fluorescence spectroscopy technique B. Swanson et al. 10.1080/02786826.2022.2142510
- Traceable methods for calibrating condensation particle counters at concentrations down to 1 cm−3 H. Sakurai et al. 10.1088/1681-7575/acf5f1
- Towards standardisation of automatic pollen and fungal spore monitoring: best practises and guidelines F. Tummon et al. 10.1007/s10453-022-09755-6
- Manual and automatic quantification of airborne fungal spores during wheat harvest period I. Simović et al. 10.1007/s10453-023-09788-5
- Comparative Analysis of Traditional and Advanced Clustering Techniques in Bioaerosol Data: Evaluating the Efficacy of K-Means, HCA, and GenieClust with and without Autoencoder Integration M. Moss et al. 10.3390/atmos14091416
- Towards European automatic bioaerosol monitoring: Comparison of 9 automatic pollen observational instruments with classic Hirst-type traps J. Maya-Manzano et al. 10.1016/j.scitotenv.2022.161220
- Verifying the viable particle counts of biofluorescent particle counters by using inkjet aerosol generators K. Iida et al. 10.1080/02786826.2024.2316836
- A portable flow tube homogenizer for aerosol mixing in the sub-micrometre and lower micrometre particle size range S. Horender et al. 10.1088/1361-6501/ac81a1
- False positives: handling them operationally for automatic pollen monitoring B. Crouzy et al. 10.1007/s10453-022-09757-4
- Measurement report: Atmospheric fluorescent bioaerosol concentrations measured during 18 months in a coniferous forest in the south of Sweden M. Petersson Sjögren et al. 10.5194/acp-23-4977-2023
- Bioaerosol Sensor for In Situ Measurement: Real-Time Measurement of Bioaerosol Particles in a Real Environment and Demonstration of the Effectiveness of Air Purifiers to Reduce Bioaerosol Particle Concentrations at Hot Spots U. Yanagi et al. 10.3390/atmos14111656
- Climate change, airborne allergens, and three translational mitigation approaches P. Beggs et al. 10.1016/j.ebiom.2023.104478
- A Modified Spectroscopic Approach for the Real-Time Detection of Pollen and Fungal Spores at a Semi-Urban Site Using the WIBS-4+, Part I E. Markey et al. 10.3390/s22228747
- Real-time pollen identification using holographic imaging and fluorescence measurements S. Erb et al. 10.5194/amt-17-441-2024
- The role of automatic pollen and fungal spore monitoring across major end-user domains F. Tummon et al. 10.1007/s10453-024-09820-2
- Automatic detection of airborne pollen: an overview J. Buters et al. 10.1007/s10453-022-09750-x
20 citations as recorded by crossref.
- Comparison of computer vision models in application to pollen classification using light scattering G. Daunys et al. 10.1007/s10453-022-09769-0
- Airborne bacteria viability and air quality: a protocol to quantitatively investigate the possible correlation by an atmospheric simulation chamber V. Vernocchi et al. 10.5194/amt-16-5479-2023
- Is the oxidative potential of components of fine particulate matter surface-mediated? K. Baumann et al. 10.1007/s11356-022-24897-3
- Recent progress in online detection methods of bioaerosols T. An et al. 10.1016/j.fmre.2023.05.012
- Extending traceability in airborne particle size distribution measurements beyond 10 µm: Counting efficiency and unit-to-unit variability of four aerodynamic particle size spectrometers K. Vasilatou et al. 10.1080/02786826.2022.2139659
- Explainable AI for unveiling deep learning pollen classification model based on fusion of scattered light patterns and fluorescence spectroscopy S. Brdar et al. 10.1038/s41598-023-30064-6
- Pollen classification using a single particle fluorescence spectroscopy technique B. Swanson et al. 10.1080/02786826.2022.2142510
- Traceable methods for calibrating condensation particle counters at concentrations down to 1 cm−3 H. Sakurai et al. 10.1088/1681-7575/acf5f1
- Towards standardisation of automatic pollen and fungal spore monitoring: best practises and guidelines F. Tummon et al. 10.1007/s10453-022-09755-6
- Manual and automatic quantification of airborne fungal spores during wheat harvest period I. Simović et al. 10.1007/s10453-023-09788-5
- Comparative Analysis of Traditional and Advanced Clustering Techniques in Bioaerosol Data: Evaluating the Efficacy of K-Means, HCA, and GenieClust with and without Autoencoder Integration M. Moss et al. 10.3390/atmos14091416
- Towards European automatic bioaerosol monitoring: Comparison of 9 automatic pollen observational instruments with classic Hirst-type traps J. Maya-Manzano et al. 10.1016/j.scitotenv.2022.161220
- Verifying the viable particle counts of biofluorescent particle counters by using inkjet aerosol generators K. Iida et al. 10.1080/02786826.2024.2316836
- A portable flow tube homogenizer for aerosol mixing in the sub-micrometre and lower micrometre particle size range S. Horender et al. 10.1088/1361-6501/ac81a1
- False positives: handling them operationally for automatic pollen monitoring B. Crouzy et al. 10.1007/s10453-022-09757-4
- Measurement report: Atmospheric fluorescent bioaerosol concentrations measured during 18 months in a coniferous forest in the south of Sweden M. Petersson Sjögren et al. 10.5194/acp-23-4977-2023
- Bioaerosol Sensor for In Situ Measurement: Real-Time Measurement of Bioaerosol Particles in a Real Environment and Demonstration of the Effectiveness of Air Purifiers to Reduce Bioaerosol Particle Concentrations at Hot Spots U. Yanagi et al. 10.3390/atmos14111656
- Climate change, airborne allergens, and three translational mitigation approaches P. Beggs et al. 10.1016/j.ebiom.2023.104478
- A Modified Spectroscopic Approach for the Real-Time Detection of Pollen and Fungal Spores at a Semi-Urban Site Using the WIBS-4+, Part I E. Markey et al. 10.3390/s22228747
- Real-time pollen identification using holographic imaging and fluorescence measurements S. Erb et al. 10.5194/amt-17-441-2024
Latest update: 26 Apr 2024
Short summary
Today there is no standard procedure to validate bioaerosol and pollen monitors. Three instruments were tested, focusing on detecting particles of different sizes. Only one instrument was able to detect the smallest particles (0.5 µm Ø), whereas the others performed best at the largest tested particles (10 µm Ø). These results are the first step towards a standardised validation procedure. The need for a reference counting method for larger particles (pollen grains: 10–200 µm Ø) was emphasised.
Today there is no standard procedure to validate bioaerosol and pollen monitors. Three...
