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

Sensors (Basel). 2022 Jul 1;22(13):4984. doi: 10.3390/s22134984.

Abstract

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.

Keywords: instrument; polarization; pollens; scattering.

MeSH terms

  • Aerosols
  • Air
  • Air Pollutants* / analysis
  • Environmental Monitoring* / methods
  • Humans
  • Pollen / chemistry

Substances

  • Aerosols
  • Air Pollutants

Grants and funding

This research received no external funding.