Assessment of Diverse Control Measure Effectiveness During Successive PM_2.5 Pollution Episodes in Central China: Implications for Regional Heavy Pollution Mitigation Strategies

Abstract. Henan Province in Central China frequently experiences heavy winter PM_2.5 pollution. Previous studies have revealed the important roles of meteorology and anthropogenic emissions in regional haze. However, how short-term changes in the intensity of control measures translate into changes in source emissions and PM_2.5 chemical composition remains insufficiently understood. This study selected two successive province-wide PM_2.5 heavy pollution episodes, one occurring from December 22, 2023, to January 3, 2024 (E1) and another one during January 8–14, 2024 (E2). We integrate air-quality and chemical-composition observations with continuous emission monitoring and satellite data to reconstruct daily source-resolved emissions, and further apply partial-correlation analysis and WRF-CAMx simulations to evaluate the relationships between emission changes and atmospheric responses. During E1, coordinated controls targeted industrial and mobile sources, together with enhanced warnings in high-emission northwestern cities. During E2, the measures attenuated, leading to a 13 % increase in NO_x and primary PM emissions compared to E1. Correspondingly, concentrations of PM_2.5, and its major components nitrate (NO₃^-) and organic matter (OM) increased by 42 %, 44 %, and 25 %, respectively. Partial correlation analysis and WRF-CAMx simulation mutually verify that such incremental emissions were the key driver of rapid NO₃^– and OM accumulation, forming a closed-loop in diagnosing the fundamental driver of heavy PM_2.5 pollution episodes in Central China. Therefore, in order to eliminate PM_2.5 heavy pollution in the future, on top of necessary regulation for the industry sector, more efforts should be devoted to reducing emissions from diesel vehicles and residential combustion.