An evaluation approach to PM_2.5 policy effectiveness over South Korea based on a newly proposed scalable spatial decomposition method

Abstract Air quality management policies often exhibit spatial inconsistencies in effectiveness due to the diverse spatial scales of air pollution variability, which result from source characteristics as well as geographical and meteorological factors. To address this, the present study proposes a scalable spatial decomposition method to separate spatiotemporal air pollution data into background (nationwide), intercity-scale (tens of kilometers), and neighborhood-scale (several kilometers) components. This decomposition was achieved by introducing spatially varying effective ranges for intercity-scale variability at each station, based on the correlation coefficient distance of the background-removed component. Applying this approach to hourly fine particulate matter (PM 2.5 ) concentrations from 535 monitoring stations across South Korea for 2021–2022, we evaluated the effectiveness of PM 2.5 management policies. During the polluted cold season (December to March), the intercity-scale component contributed an average of approximately 18% of the total PM 2.5 concentration in the Seoul Metropolitan Area (SMA) and Central Area (CA), which are densely populated and industrialized regions. In contrast, this component helped reduce PM 2.5 levels in southeastern coastal areas, where high winds facilitate dispersion. The neighborhood-scale component contributed positively to PM 2.5 levels near industrial complexes and ports but negatively in residential and commercial areas. The results demonstrate the effectiveness of central government-led intercity-scale regulations on total emissions allowances in the SMA and CA and highlight the need for additional local management targeting individual point sources near industrial complexes and ports. This study provides intuitive spatial decomposition tools for understanding PM 2.5 pollution across spatial scales and offers policymakers a foundation for developing multi-scale mitigation strategies.