Accelerating Regime Restructuring of Ozone Sensitivity From VOC‐Limited to Transitional With Heatwave Intensification

Abstract In eastern China, heatwaves increasingly co‐occur with extreme ozone pollution, posing substantial public health risks. However, the spatiotemporal heterogeneity of heatwave levels and their nonlinear modulation of photochemical mechanisms remain insufficiently resolved. Integrating explainable machine learning with WRF–CAMx simulations, this study quantifies key drivers of ozone variability, characterizes nationwide heatwave evolution, and evaluates how heatwave levels affect surface ozone formation and precursor control efficiency in the Yangtze River Delta (YRD). Machine learning results show that meteorological factors explain over 70% of daytime ozone variability, with temperature, solar radiation, and relative humidity exerting dominant influences. A threshold‐like temperature–ozone response is identified in the YRD, with ozone growth weakening above approximately 38°C. A decadal analysis (2014–2023) shows heterogeneous heatwave patterns across China. Driven by background warming, mild heatwaves prevail in coastal regions, whereas stronger events are concentrated in inland basins and northwestern China. Further analysis shows that the heatwave level critically reshapes atmospheric chemical sensitivity. Extreme heat accelerates radical cycling and NO x oxidation, weakens NO titration, and shifts ozone formation from VOC‐limited conditions during non‐heatwaves to transitional regimes during heatwaves, reducing the rebound associated with only‐NO x reductions. Results indicate that NO x ‐oriented strategies become markedly more effective under severe heatwaves than under climatological mean conditions. Overall, the results indicate that air quality management should shift from static, climatology‐based mitigation frameworks to dynamic, climate‐adaptive strategies that adjust precursor reduction ratios according to heatwave level, achieving synergistic air quality and climate benefits.