Scenario-dependent O3 driver identification and formation responses to VOCs/NOx emission reduction pathways from integrated and sectoral sources in the Beijing-Tianjin-Hebei region, China

Persistent surface ozone (O₃) in China's Beijing-Tianjin-Hebei region, driven by complex meteorology-precursor interactions, has become a critical air quality crisis. A longstanding challenge in O₃ pollution mitigation is identifying drivers of O₃ formation and its response to precursor emissions. Using explainable ensemble machine learning, scenario-based modeling and empirical kinetic modeling approach, we quantified O₃ formation drivers and evaluated scenario-dependent responses to integrated/sectoral precursor emission reductions across multiple dynamic scenarios. We demonstrate that temperature, solar radiation, and nitrogen dioxide dominate O₃ formation across pollution levels. Meteorological conditions for O₃ dispersion varied significantly between 2013–2023, with 2021/2023 representing the most favorable/unfavorable years, highlighting strong interannual variability. Spatiotemporal O₃-precursor sensitivity exhibited volatile organic compound (VOC)-limited dominance, modulated by dynamic meteorology and pollution levels. While Only-VOCs reductions significantly decreased O₃, they have inevitable limitations. VOCs/nitrogen oxides (NO_x) = 3:1 pathways enhanced O₃ mitigation in Beijing and Shijiazhuang but remained suboptimally efficient. Notably, deepening NO_x reductions promoted a shift toward NO_x-limited regimes, further improving the efficiency of O₃ decrease. Extreme meteorology and heavy pollution increased O₃ reduction potential compared to baseline scenarios, with industrial VOCs control proving most effective for sectoral interventions. These findings inform scenario-specific precursor emission policies to address severe O₃ pollution.