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Towards an Automatic Pollen Detection System in Ambient Air Using Scattering Functions in the Visible Domain

Pollen grains strongly affect human health by inducing allergies. Although the monitoring of airborne pollens particles is of major importance, the current measurement methods are manually conducted and are expensive, limiting the number of monitoring stations. Thus, there is a need for relatively l...

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Autores principales: Renard, Jean-Baptiste, El Azari, Houssam, Richard, Jérôme, Lauthier, Johann, Surcin, Jérémy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269840/
https://www.ncbi.nlm.nih.gov/pubmed/35808483
http://dx.doi.org/10.3390/s22134984
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author Renard, Jean-Baptiste
El Azari, Houssam
Richard, Jérôme
Lauthier, Johann
Surcin, Jérémy
author_facet Renard, Jean-Baptiste
El Azari, Houssam
Richard, Jérôme
Lauthier, Johann
Surcin, Jérémy
author_sort Renard, Jean-Baptiste
collection PubMed
description Pollen grains strongly affect human health by inducing allergies. Although the monitoring of airborne pollens particles is of major importance, the current measurement methods are manually conducted and are expensive, limiting the number of monitoring stations. Thus, there is a need for relatively low-cost instruments that can work automatically. The possible detection of pollen in urban ambient air (Paris, France) has been reported using the LOAC optical aerosol counter. These measurements indicate that the pollen grains and their nature could be determined using their scattering properties. For this purpose, the scattering functions (intensity and linear polarization) of 21 different airborne pollens were established in the laboratory using a PROGRA2 instrument. The linear polarization curves were close together, with a maximum polarization lower than 10% in the red domain and 5% in the green domain. The variability from one sample to another was partly due to the different sizes of the grains. An instrument with an absolute accuracy of about ±1% for polarization measurements should then be needed, coupled with a counting instrument to take into account the effects of size. On the other hand, the scattering curves for intensity presented with different shapes and strong differences up to a factor of 20 at some scattering angles, due to the size, shape, surface texture, and composition of the grains. Thus, we propose a proof of concept for new automated sensors that can be used in dense networks to count and identify pollen grains by analyzing the light they scatter at some specific angles.
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spelling pubmed-92698402022-07-09 Towards an Automatic Pollen Detection System in Ambient Air Using Scattering Functions in the Visible Domain Renard, Jean-Baptiste El Azari, Houssam Richard, Jérôme Lauthier, Johann Surcin, Jérémy Sensors (Basel) Article Pollen grains strongly affect human health by inducing allergies. Although the monitoring of airborne pollens particles is of major importance, the current measurement methods are manually conducted and are expensive, limiting the number of monitoring stations. Thus, there is a need for relatively low-cost instruments that can work automatically. The possible detection of pollen in urban ambient air (Paris, France) has been reported using the LOAC optical aerosol counter. These measurements indicate that the pollen grains and their nature could be determined using their scattering properties. For this purpose, the scattering functions (intensity and linear polarization) of 21 different airborne pollens were established in the laboratory using a PROGRA2 instrument. The linear polarization curves were close together, with a maximum polarization lower than 10% in the red domain and 5% in the green domain. The variability from one sample to another was partly due to the different sizes of the grains. An instrument with an absolute accuracy of about ±1% for polarization measurements should then be needed, coupled with a counting instrument to take into account the effects of size. On the other hand, the scattering curves for intensity presented with different shapes and strong differences up to a factor of 20 at some scattering angles, due to the size, shape, surface texture, and composition of the grains. Thus, we propose a proof of concept for new automated sensors that can be used in dense networks to count and identify pollen grains by analyzing the light they scatter at some specific angles. MDPI 2022-07-01 /pmc/articles/PMC9269840/ /pubmed/35808483 http://dx.doi.org/10.3390/s22134984 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Renard, Jean-Baptiste
El Azari, Houssam
Richard, Jérôme
Lauthier, Johann
Surcin, Jérémy
Towards an Automatic Pollen Detection System in Ambient Air Using Scattering Functions in the Visible Domain
title Towards an Automatic Pollen Detection System in Ambient Air Using Scattering Functions in the Visible Domain
title_full Towards an Automatic Pollen Detection System in Ambient Air Using Scattering Functions in the Visible Domain
title_fullStr Towards an Automatic Pollen Detection System in Ambient Air Using Scattering Functions in the Visible Domain
title_full_unstemmed Towards an Automatic Pollen Detection System in Ambient Air Using Scattering Functions in the Visible Domain
title_short Towards an Automatic Pollen Detection System in Ambient Air Using Scattering Functions in the Visible Domain
title_sort towards an automatic pollen detection system in ambient air using scattering functions in the visible domain
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269840/
https://www.ncbi.nlm.nih.gov/pubmed/35808483
http://dx.doi.org/10.3390/s22134984
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