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Spatial Variation of Airborne Pollen Concentrations Locally around Brussels City, Belgium, during a Field Campaign in 2022–2023, Using the Automatic Sensor Beenose.
- Source :
-
Sensors (14248220) . Jun2024, Vol. 24 Issue 12, p3731. 13p. - Publication Year :
- 2024
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Abstract
- As a growing part of the world population is suffering from pollen-induced allergies, increasing the number of pollen monitoring stations and developing new dedicated measurement networks has become a necessity. To this purpose, Beenose, a new automatic and relatively low-cost sensor, was developed to characterize and quantify the pollinic content of the air using multiangle light scattering. A field campaign was conducted at four locations around Brussels, Belgium, during summer 2022 and winter–spring 2023. First, the consistency was assessed between the automatic sensor and a collocated reference Hirst-type trap deployed at Ixelles, south-east of Brussels. Daily average total pollen concentrations provided by the two instruments showed a mean error of about 15%. Daily average pollen concentrations were also checked for a selection of pollen species and revealed Pearson and Spearman correlation coefficients ranging from 0.71 to 0.93. Subsequently, a study on the spatial variability of the pollen content around Brussels was conducted with Beenose sensors. The temporal evolution of daily average total pollen concentrations recorded at four sites were compared and showed strong variations from one location to another, up to a factor 10 over no more than a few kilometers apart. This variation is a consequence of multiple factors such as the local vegetation, the wind directions, the altitude of the measurement station, and the topology of the city. It is therefore highly necessary to multiply the number of measurement stations per city for a better evaluation of human exposure to pollen allergens and for more enhanced pollen allergy management. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14248220
- Volume :
- 24
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Sensors (14248220)
- Publication Type :
- Academic Journal
- Accession number :
- 178190407
- Full Text :
- https://doi.org/10.3390/s24123731