Modeling the effects of air pollution and meteorological variables on mortality from respiratory diseases: insights from the ARDL

This research investigates the correlation between exposure to air pollutants, meteorological variables, and respiratory-related mortality in Mashhad, Iran. To analyze both short- and long-run relationships, cointegration tests and the Autoregressive Distributed Lag (ARDL) model were employed. The study considered key air pollutants, namely SO₂, PM2.5, O₃, NO₂, and CO, alongside meteorological variables such as wind speed, temperature, rainfall, pressure, and relative humidity. The results indicated strong associations between air pollution, weather conditions, and respiratory mortality. According to the results of the ARDL long-run model, wind speed and atmospheric pressure were significantly correlated with mortality due to respiratory diseases. Furthermore, findings from the short-run ARDL model revealed that a 1% increase in temperature, PM_2.5, and NO₂ led to increases in respiratory mortality by 0.24%, 0.99%, and 1.78%, respectively. Notably, a 1% increase in atmospheric pressure was associated with a substantial 135.2% rise in respiratory-related deaths. Conversely, higher concentrations of O₃ and SO₂ were linked to reductions in mortality by 1.68% and 2.45%, respectively. Overall, both short- and long-run findings highlight atmospheric pressure and wind speed as the most influential meteorological factors, while PM_2.5, O₃, and NO₂ emerge as the most impactful air pollutants. These findings suggest that targeted environmental and public health policies are essential to mitigate respiratory health risks.