Time Series Analysis of Air Quality of an Industrial District of India Using Remote Sensing and GIS: Impact of Covid-19 Lockdown

Abstract In the wake of Covid-19, most countries in the world had lockdowns, shutting down most of the human activities, leading to a never before seen condition of minimum anthropogenic intervention. This caused a unique situation where the earth healed, so as the air quality. This study provides a comparative time series analysis of the ground level and the remotely sensed technique of air quality measurement, showing the results in the best available resolution to date and also the daily variation of the pollutants and air quality index (AQI) in various plots. The plan of the study also included the derivation of particle matter 2.5 (PM2.5) from aerosol optical depth (AOD) to get the remote sensing-based PM 2.5 variation for the study area Howrah using a Geographically Weighted Regression (GWR) model to get an adequate spatiotemporal variation of the pollutant. The study shows an overall improvement of the air quality for the lockdown periods, but again an increase in pollutants level as the restrictions were eased down again. The maximum level of AQI decreased by 53.264% for the year 2020 and 5.183% for the year 2021 as compared to the not-lockdown period in 2019. The overall comparison between the graphs of AQI, SO2, NO2, PM10, and PM2.5 suggests better quality of air in the year 2020 as compared to 2019 and 2021, the latter being better than the middle one. The O3 showed an increasing trend for the year 2020 when there was a noticeable decrease in all other criteria pollutant levels.