Meteorology Driven Ozone Variability

Meteorology plays a significant role in influencing ground-level ozone (O₃) concentrations that can adversely affect public health through exposure to elevated O₃ levels. Currently, regulatory compliance measurements rely on large, expensive instruments that provide O₃ averaged data over extended periods. In recent years, continuous air quality monitoring stations have gained popularity for real-time O₃ monitoring in outdoor environments (mostly in metropolitan cities). However, there is a lack of comprehensive studies evaluating the impact of local meteorological conditions on O₃ levels in both road and rural settings. This study aims to assess the interaction between major meteorological variables and O₃ concentrations at a high-traffic road site and no-traffic rural site. A comparative analysis was conducted using high-precision reference instruments in uncontrolled outdoor environments. Single-factor GAM (generalized additive model) demonstrated strong performance (R² = 0.95–0.96) and deviance explained (95–96%). When paired variables were incorporated, the multi-factor GAM further improved performance and explained 97–99% of the variability in O₃ concentrations. The multi-factor GAM outperformed the GLM (generalized linear model) (R² = 0.88–0.89) and achieved superior results (R² = 0.979–0.987; deviance explained = 98.2–98.8%) in accurately predicting O₃ levels and can be applied in various occupational environments like personal exposure monitoring among industry workers.