ABSTRACT
Delhi was one of India's COVID-19 hotspots, with significant death rates during the year 2021. This study looked at the link between COVID-19 cases in Delhi, and key meteorological variables. The study found that COVID-19 cases during the second wave (P2-March- May 2021) were much higher than during the first wave (P1-Jan-Feb 2021) in Delhi. During P1 (Jan-Feb 2021) the mean PM2.5, PM10, NO2 and CO concentrations were greater than that of P2 (March-May 2021) while the reverse happened for SO2 and O3. Spearman correlation test indicated that COVID-19 cases maintained a significant positive correlation with the high temperature of P2 (March-May 2021) and high humidity of P1 (Jan-Feb 2021) in line with the accepted notion that COVID-19 transmitted favourably in hot and humid climates. The Multilayer perceptron (MLP) model indicated that COVID-19 spread was supported by air pollutants and climate variables like PM2.5, NO2, RH, and WS in P1(Jan-Feb 2021) and PM2.5 and O3 in P2 (March-May 2021). Owing to chemical coupling, across all six monitoring stations, O3 maintained an inverse relationship with NO2 throughout the COVID-19 phases in Delhi. The city dwellers had health risks also due to PM pollution at varying degrees, indicated by high hazard quotients (HQs), requiring lowering of air pollution concentrations on an urgent basis. [ FROM AUTHOR] Copyright of Journal of Applied & Natural Science is the property of Applied & Natural Science Foundation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)