Ozone is a significant atmospheric pollutant with notable hazards to human health, and its formation mechanism is complex, but current research on ozone formation mechanisms often neglects the exploration of causal relationships. This study develops the CausalMedZone (Causality and Mediation pathway analysis for ozone) model, a causal inference-based framework designed to investigate ozone formation mechanisms. This model aims to identify key explanatory variables in the ozone formation process by explicitly modeling causal relationships among pollutants, thereby uncovering the true drivers of ozone pollution. Additionally, CausalMedZone integrates mediation and moderation effects to construct ozone formation pathways, providing a comprehensive understanding of how key pollutants and meteorological conditions interact to influence ozone formation. CausalMedZone effectively elucidates the causes of ozone pollution in Shijiazhuang, reveals a dual pathway where PM2.5 directly promotes ozone formation and indirectly inhibits it through NO2, with CO and relative humidity significantly moderating the PM2.5 NO2 and NO2 O3 pathways, respectively (R2 = 0.70). Furthermore, the model demonstrates broad applicability in heterogeneity analysis across the Beijing-Tianjin-Hebei region, revealing significant differences in ozone formation mechanisms among cities: Beijing exhibits a NO2-dominated ozone suppression pathway (R2 = 0.70), while Shijiazhuang and Tianjin show a PM2.5 NO2 coupling pathway (R2 = 0.80 & 0.75). These findings provide a scientific foundation for developing region-specific and precise ozone pollution control strategies.
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