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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2018-432
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2018-432
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 21 Jan 2019

Research article | 21 Jan 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Automatic pollen recognition with the Rapid-E particle counter: the first-level procedure, experience and next steps

Ingrida Šaulienė1, Laura Šukienė1, Gintautas Daunys1, Gediminas Valiulis1, Lukas Vaitkevičius1, Predrag Matavulj2, Sanja Brdar2, Marko Panic2, Branko Sikoparija2, Bernard Clot3, Benoît Crouzy3, and Mikhail Sofiev1,4 Ingrida Šaulienė et al.
  • 1Siauliai University, Šiauliai, 76352 Lithuania
  • 2BioSensе Institute - Research Institute for Information Technologies in Biosystems, University of Novi Sad, Novi Sad, 21000, Serbia
  • 3Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, 1530, Switzerland
  • 4Finnish Meteorological Institute, Helsinki, 00560, Finland

Abstract. Pollen-induced allergy is among the most-prevalent non-contagious diseases, with about a quarter of European population sensitive to various atmospheric bioaerosols. In most European countries, pollen information is based on a weekly-cycle Hirst-type pollen trap method. This method is labour-intensive, requires narrow specialization abilities and substantial time, so that the pollen data are always delayed, subject to sampling- and counting-related uncertainties. Emerging new approaches to automatic pollen monitoring can, in principle, allow for real-time availability of the data with no human involvement.

The goal of the current paper is to evaluate the capabilities of the new Plair Rapid-E pollen monitor and to construct the first-level pollen recognition algorithm. The evaluation was performed for three devices located in Lithuania, Serbia and Switzerland, with independent calibration data and classification algorithms. The Rapid-E output data include multi-angle scattering images and the fluorescence spectra recorded at several times for each particle reaching the device. Both modalities of the Rapid-E output were treated with artificial neural networks (ANN) and the results were combined to obtain the pollen type. For the first classification experiment, the monitor was challenged with a large variety of pollen types and the quality of many-to-many classification was evaluated. It was shown that in this case, both scattering- and fluorescence- based recognition algorithms fall short of acceptable quality. The combinations of these algorithms performed better exceeding 80 % accuracy for 5 out of 11 species. Fluorescence spectra showed similarities among different species ending up with three well-resolved groups: (Alnus, Corylus, Betula and Quercus), (Salix and Populus), and (Festuca, Artemisia, Juniperus). Within these groups, pollen is practically non-distinguishable for the first-level recognition procedure. Construction of multi-steps algorithms with sequential discrimination of pollen inside each group seems to be one of possible ways forwards. In order to connect the classification experiment to existing technology, a short comparison with the Hirst measurements is presented and an issue of the false-positive pollen detections by Rapid-E is discussed.

Ingrida Šaulienė et al.
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Ingrida Šaulienė et al.
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Short summary
The goal is to evaluate the capabilities of the new Rapid-E monitor and to construct the first-level pollen recognition algorithm. The output data were treated with ANN aiming at classification of the injected pollen. Algorithms based on scattering and fluorescence data alone fall short of acceptable quality. The combinations of these exceeded 80 % accuracy for 5 out of 11 pollen species. Constructing multi-steps algorithms with sequential discrimination of pollen can be a possible way forwards.
The goal is to evaluate the capabilities of the new Rapid-E monitor and to construct the...
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