Multivariate and spatial analysis of reduced urban air pollution during COVID-19 pandemic in Delhi

Abstract

Towards the end of 2019, a novel contagious virus (COVID-19) came out of Wuhan, China and turned into a disastrous pandemic. Many countries were completely or partially locked down. The ongoing pandemic has greatly affected our society and economy but, on the other side, it had effects upon the natural environment, as it rejuvenated itself. The present study repots the air quality and spatial distribution of air quality parameters (PM10, PM2.5, NO2, SO2, O3 and CO) in Delhi, taking into account data from 36 monitoring stations, for the months of January - April 2019 and 2020, respectively before and during the COVID-19 pandemic. The statistical tools like box plot, Pearson's correlation, and PCA were used to interpret air pollution data before and during the lockdown period. The results revealed the characteristics of pollutants with respect to location, relationship between pollutants, and monitoring their level in compliance with the limits set by the legislation. The results of multivariate analysis were further spatially analyzed by mapping the distribution of pollutants by using the Inverse Distance Weighted interpolation. The result revealed the gradual reduction in the pollutant concentrations (PM10, PM2.5, CO, SO2) and an increment in ozone concentration was observed, which was due to a drastic reduction in NO2, especially during March and April 2020, immediately after the declared lockdown in the region. The overall study indicated that the interventions for urban air pollution mitigation are crucial in the regeneration of nature.