Data Science Approach of COVID-19’s Lockdown Impact on Pollution in India

Abstract

In December 2019, a newly identified novel corona virus similar to the SARS-CoV-2 A pneumonia pandemic broke out in Wuhan, Hubei Province, and quickly spread throughout the country., which in turn spread faster to all corners of the world making it a pandemic trouble. India recorded its first COVID-19 positive case in Kerala on January 30, 2020., as a sequence of that the nation declared a nation-wide lockdown prolonged from the 25th of March to the 31st of May, 2020, with a subsequent unlock period to diminish the spread of COVID-19 syndrome. Due to the imposed limits, pollution levels in cities around the country significantly decreased in just a few days, raising arguments about lockdown as an effective alternative tool for mitigating air pollution. The current study used data from the air quality index (AQI) recorded during this tough phase to examine the effects of the shutdown on the air quality of India. This project compared data on air quality for the ideal phase determining the variations in pollutant concentrations during the lockdown, analyzing daily Air Quality Index data for eight major pollutant parameters (PM10, PM2.5, CO, NO2, O3, BTX, NH3 and SO2). A meta-analysis of continuous data  was performed to decide the mean and standard deviation of each lockdown phase, and their differences computed in percentage in comparison to the last five years [2015-2020]. With access to a large amount of granular data relating to the concentration of major air pollutants in India, this work analyses and summarizes the background, key points, and core measures in the country and provinces, and it will be interesting to see if the claim of reduced air pollution is actually backed by data.