ABSTRACT
South Korea and China have implemented increasingly stringent mitigation measures to reduce the health risks from PM2.5 exposure, jointly conducting a ground-based air quality observation study in Northeast Asia. Dispersion normalized positive matrix factorization (DN-PMF) was used to identify PM2.5 sources in Seoul and Beijing and assess the effectiveness of the seasonal management programs (SMPs) through a comparative study. Samples were collected during three periods: January-December 2019, September 2020-May 2021, and July 2021-March 2022. In Seoul, ten sources were resolved (Secondary nitrate: 8.67 µg/m3, 34 %, Secondary sulfate: 5.67 µg/m3, 22 %, Motor vehicle: 1.83 µg/m3, 7.2 %, Biomass burning: 2.30 µg/m3, 9.1 %, Residual oil combustion: 1.66 µg/m3, 6.5 %, Industry: 2.15 µg/m3, 8.5 %, Incinerator: 1.39 µg/m3, 5.5 %, Coal combustion: 0.363 µg/m3, 1.4 %, Road dust/soil: 0.941 µg/m3, 3.7 %, Aged sea salt: 0.356 µg/m3, 1.4 %). The SMP significantly decreased PM2.5 mass concentrations and source contributions of motor vehicle, residual oil combustion, industry, coal combustion, and biomass burning sources (p-value < 0.05). For Seoul, the reduction effects of the SMPs were evident even considering the influence of the natural meteorological variations and the responses to COVID-19. In Beijing, nine sources were resolved (Secondary nitrate: 12.6 µg/m3, 28 %, Sulfate: 8.27 µg/m3, 18 %, Motor vehicle: 3.77 µg/m3, 8.4 %, Biomass burning: 2.70 µg/m3, 6.0 %, Incinerator: 4.50 µg/m3, 10 %, Coal combustion: 3.52 µg/m3, 7.8 %, Industry: 5.01 µg/m3, 11 %, Road dust/soil: 2.92 µg/m3, 6.5 %, Aged sea salt: 1.63 µg/m3, 3.6 %). Significant reductions in PM2.5 mass concentrations and source contributions of industry, coal combustion, and incinerator (p-value < 0.05) were observed, attributed to the SMP and additional measures enforced before the 2022 Beijing Winter Olympics. Unlike comparing PM2.5 mass concentration variations using conventional methods, investigation of the source contribution variations of PM2.5 by using DN-PMF can provide a deeper understanding of the effectiveness of the air quality management policies.