Detection and identification of shape, size, and concentration of particulate matter in ambient air using bright field microscopy-based system

Abstract

Currently, air pollution monitoring for supplemental information is performed using optical sensors based on light scattering by particulate matter. These devices provide results in the form of particle counts and the concentration of particulate matter is calculated and demonstrated in real-time. We have developed a bright field (BF) microscopy-based system for air quality monitoring (AQM) in real-time, named SENSurAIR, which provides not only just counts but shape, size as well as concentration. The system comprises a mini vacuum pump, cyclone separator, LED light source (λ = 480 nm), and bright field microscopic unit. The pump drives the ambient air toward the sampling media so that PM2.5 is impacted and deposited. The light rays from the source are incident on the sampling media, and microscopic unit records images of particulate matter. The custom-developed algorithm then processes the recorded images to identify the shape, size distribution, and concentration of PM2.5. The size and shape of PM2.5 are the principal factors that help identify the sources contributing to PM2.5 in ambient air. The developed device is evaluated by collocating with the reference grade Beta Attenuation Monitoring (BAM) system. The system is fully automatic, compact, low-cost, and can be integrated with a wireless network for data communication. The simultaneous monitoring of shape, size, and concentration using the developed device is unique and which will be highly useful to alarm the health hazards due to the existing pollution.