Although national emission control policies have contributed to long-term reductions in PM2.5 levels, responses across neighboring cities remain heterogeneous, complicating the evaluation of policy effectiveness. This study diagnoses the spatial structure and examines temporal evolution of intercity-scale (tens of kilometers) and neighborhood-scale (a few kilometers) PM2.5 components, separated from background variation including long-range transport, by applying a recently proposed spatial decomposition framework based on spatial coherence to long-term air quality monitoring network data in South Korea (2016–2023). Within this framework, a hierarchical averaging scheme uses coherence-based neighboring stations to define the intercity-scale variability of background-removed PM2.5 concentrations. Focusing on the cold season (DJFM), spatial diagnosis reveals dominant intercity-scale contributions in the Seoul Metropolitan Area (SMA) and neighboring industrialized areas, highlighting the effectiveness of air control zone-based policies. In contrast, neighborhood-scale contributions predominate in high-PM2.5 stations, particularly in the Southeastern Area (SEA), indicating the need for localized interventions. Temporal analysis reveals a structural transition beginning in 2019/20 DJFM, characterized by simultaneous trend reversals: intercity-scale components shifted from increasing to decreasing in the SMA, an area with intensive urban and industrial emissions, while the opposite occurred in the SEA, a coastal city cluster. This transition coincided with the implementation of the Seasonal PM Management policy and the COVID-19 lockdown. The variations in the intercity-scale component broadly align with residual emission intensities of PM2.5 and NOx, defined as deviations from national emission trends based on the Clean Air Policy Support System emission inventory. These results reveal a structural shift in intercity-scale PM2.5 variability and its linkage to emissions, offering a scalable diagnostic tool for evaluating policy effectiveness and underscoring the need for scale-specific air quality management strategies.

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