Urban air pollution, particularly particulate matter (PM), poses significant health risks in metropolitan areas like Seoul. Understanding heavy metal distribution across different particle sizes is crucial for source identification and pollution control strategies. This study investigated heavy metal concentrations in PM10 and PM2.5 . Samples were collected 4-5 times monthly from January 2024 to April 2025 at an air monitoring station in Guui-dong, Gwangjin-gu, Seoul. Mass concentrations were determined using gravimetric methods, and 11 heavy metals (Pb, Cd, Cr, Cu, Mn, Fe, Ni, As, Al, Ca, Mg) were analyzed using ICP-MS and ICP-OES. Data were classified into normal days, yellow dust, and PM2.5 advisory periods.
Results revealed distinct patterns under different atmospheric conditions compared to normal days. Yellow dust events showed strong PM10-PM2.5 correlations for soil-derived elements but weak PM10-PM2.5 correlations for anthropogenic metals, while PM2.5 advisories exhibited the opposite pattern with enhanced PM10-PM2.5 correlations for anthropogenic metals but reduced PM10-PM2.5 correlations for soil-derived elements. The study demonstrates that meteorological conditions significantly influence particle size-specific heavy metal distribution patterns. Comprehensive analysis of both PM10 and PM2.5 is essential for effective air quality management and suggests that both particle sizes should be considered when applying machine learning techniques. This research provides foundational data for future policy development in urban environments.
