Application of low-cost air quality monitoring sensor to assess the exposure of ambient air pollution due to pm2.5 and PM10

Abstract

Recent high ambient concentration of particulate matter (PM), such as air pollutants, has its multimodal effects on the environment and human health especially for the least developing countries because of the high cost associated with monitoring it. The aim of this study is to introduce a low-cost air quality monitoring (AQM) sensor to assess human exposure to support the health impact assessment and environmental policy formulation. A low-cost AQM sensor using light scattering technology, AirVisual (AV) pro was used in four sites in Dhaka city of Bangladesh in a period of five and a half months spreading from Feb 2019 to Aug 2019. Validation of the equipment was done comparing it with two equivalent equipment-HIM-6000 portable air quality monitor and BAM-1020 continuous particulate monitor. The correlations between the AV pro and BAM-1020 were found fairly strong (R2 = 0.77) at the US Embassy in Dhaka. The correlations between the AV pro and HIM-6000 were found also very strong (R2 = 0.91) at Mirpur Cantonment. This study defines the four heterogeneous environments in Mirpur–12, Mirpur Cantonment, Baridhara, and Darus Salam to conduct extensive statistical analysis of spatial, seasonal, diurnal, and temporal variations of air pollution. The results showed that Mirpur–12 to be the most polluted zone (mean PM2.5 = 122.62 µg/m3, mean PM10 = 186.84 µg/m3) after application of low-cost AQM sensor. It also revealed changes in PM concentrations in terms of time, meteorological condition, and place. Maximum PM concentration occurs when the traffic volume is high in the morning and evening and reduces from pre-monsoon to monsoon. This paper also highlights the utility and vulnerability of a low-cost monitoring sensor like AV pro to measure the PM concentration. With the above analysis, further studies are needed to prove the relationship between health impact assessment and human exposure to PM2.5 and PM10 concentration via low-cost sensors.