  One of the main contributors to air pollution is particulate matter (PMxy),
which causes several COVID-19 related diseases such as respiratory problems and
cardiovascular disorders. Therefore, the spatial and temporal trend analysis of
particulate matter and the mass concentration of all aerosol particles less
than 2.5 m in diameter (PM2.5) has become critical to control the risk factors
of co-morbidity of a patient. Lockdown plays a significant role in maintaining
COVID-19 cases as well as air pollution, including particulate matter. This
study aims to analyse the effect of the lockdown on controlling air pollution
in metropolitan cities in India through various statistical modelling
approaches. Most research articles in the literature assume a linear
relationship between responses and covariates and take independent and
identically distributed error terms in the model, which may not be appropriate
for analysing such air pollution data. In this study, we performed a pattern
analysis of daily PM2.5 emissions in various major activity zones during 2019
and 2020. By measuring the lockdown effect, we also considered seasonal
influence.
