Abstract China’s Spring Festival, with consistent ∼30% NOx (NO + NO2) reductions annually, provides a natural experiment to investigate oxidant response to emission reductions. Unlike isolated events such as the COVID‐19 lockdown, the Spring Festivals offer a more robust decade‐long (2015–2024) data set. Analysis of these observations reveals a striking shift in oxidant (Ox = O3 + NO2) response from negative to positive values over time despite similar emission reduction patterns each year. Chemical transport modeling indicates that meteorological factors are the primary drivers of these variations. Machine learning analysis further identifies cloud cover and radiation changes as controlling factors, with strong correlations between ΔOx and meteorological parameters (R = 0.85–0.94) across all regions. These findings challenge conventional assumptions about emission control effectiveness, showing that meteorological variability overrides expected chemical responses. Our results indicate that emission reduction policies must adaptively account for meteorological conditions to effectively mitigate ozone pollution in a changing climate.