Abstract
COVID-19 infection affects respiratory system; thus, air pollution and
meteorological factors also contribute majorly to its transmission. This
study is aiming to estimate and comprehend the linkages between
contribution of PM 2.5 concentrations and meteorological parameters to
spreading coronavirus infection in Gurugram, a badly affected city of
India due to COVID-19 pandemic. We employed some statistical analysis on
daily average data of PM 2.5 concentrations and meteorological
constraints with daily COVID-19 cases during March 2020-February 2022.
Time series analysis was conducted to optimize PM 2.5 concentrations
associated with COVID-19 cases. The Pearson correlation test was applied
to investigate the correlations between PM 2.5 concentrations,
meteorological parameters, and COVID-19 cases. The PCA was applied to
reveal the most significant factor attributable to affect the rate of
COVID-19 transmission in Gurugram. The highest cases of COVID-19
(25,7375) were observed in the month of February when PM 2.5
concentration was 286.6µg/m 3, 12.64˚C temperature, 73.81% RH and
68.265 km/h wind speed; while minimum cases (3125) were found in the
month of March with the 18.18µg/m3 PM 2.5 concentration, 10.62˚C
temperature, 50.05% RH, and 83.295km/h wind speed. The principal
component analysis revealed that the daily COVID-19 cases were
significantly positively correlated with PM 2.5 concentrations, RH, and
temperature. However, daily COVID-19 cases were negatively or poorly
correlated with wind speed. COVID-19 pandemic is prominently affected by
PM 2.5 while RH and temperature were found as important meteorological
factors significantly affect its human-to-human transmission. This study
may provide the useful indications to regulatory bodies to modify the
environmental health policies.