Dynamics of Air Quality: Exploring Short and Long-Term Effects via ARDL Modeling

The connection among air pollution and respirational disorders has been the subject of extensive environmental science research. The primary contributors to air effluence are nitrogen dioxide (NO
2
), sulfur dioxide (PM10), and particulate matter (PM10). The goal of this research study is to determine the correlation among various air quality variables. This investigation helps to regulate how the changes in air quality index variables (PM2.5, SO
2
, and NO
2
) affect the PM10 level. $\mathrm{SO}_{2}, \mathrm{NO}_{2}$, and PM10 are the three primary factors utilized to determine the PM10 concentration in the air. Here, the ARDL time series method is used to study the association between different variables. The research findings reveal that NO
2
and PM2.5 have a transient influence on the absorption of PM10 in the atmosphere, whereas NO
2
has no lasting effect. While short-term insignificance of variable SO
2
is evident, its long-term efficacy in determining PM10 levels is noteworthy.