Air mapping during COVID-19 and association between air pollutants and physiochemical parameters of the plants using structural equal modeling: a case study.

Abstract

In urban areas around the world, air pollution introduced by vehicular movement is a key concern. However, restricting vehicular traffic during the COVID-19 shutdown improved air quality to some extent. This study was conducted out in the smart city of Bhubaneswar, which is also the state capital of Odisha, India. The study has tried to map Bhubaneswar by collecting the air quality data before, during, and after the COVID lockdown of six air quality monitoring stations present in Bhubaneswar established under "National Ambient Air Monitoring Program" (NAMP). Furthermore, plants, which are the most vulnerable to air pollution, can show a variety of visible changes depending on their level of sensitivity. Moreover, leaves of Mangifera indica, Monoon longifolium, Azadirachta indica, Millettia pinnata, Aegle marmelos were collected from nearby of six air monitoring stations to assess the "Air Pollution Tolerance Index." M. indica was found to be intermediately tolerant, and all of the other species were found to be sensitive. The structural equation modeling results also revealed a significant relationship between total chlorophyll content, relative water content, ascorbic acid content, leaf extract pH, APTI with species, air quality index, and PM10.