LAUSR

Background and Objective: There have been significant effects of the current coronavirus-19 (COVID-19) infection outbreak on many facets of everyday life, particularly the environment. Despite the fact that a number of studies have already been published on the topic, an analysis of those studies’ findings on COVID-19’s effects on environmental pollution is still lacking. The goal of the research is to look into greenhouse gas emissions and air pollution in Bangladesh when COVID-19 is under rigorous lockdown. The specific drivers of the asymmetric relationship between air pollution and COVID-19 are being investigated. Methods: The nonlinear relationship between carbon dioxide ( CO2 ) emissions, fine particulate matter (PM2.5), and COVID-19, as well as its precise components, are also being investigated. To examine the asymmetric link between COVID-19 factors on CO2 emissions and PM2.5, we employed the nonlinear autoregressive distributed lag (NARDL) model. Daily positive cases and daily confirmed death by COVID-19 are considered the factors of COVID-19, with lockdown as a dummy variable. Results: The bound test confirmed the existence of long-run and short-run relationships between variables. Bangladesh’s strict lockdown, enforced in reaction to a surge of COVID-19 cases, reduced air pollution and dangerous gas emissions, mainly CO2, according to the dynamic multipliers graph.