Characteristics and Source Identification for PM2.5 Using PMF Model: Comparison of Seoul Metropolitan Area with Baengnyeong Island

To establish and implement effective policies for controlling fine particle matters (PM2.5), which is associated with high-risk diseases, continuous research on identifying PM2.5 sources was conducted. This study utilized the positive matrix factorization (PMF) receptor model to estimate the sources and characteristics of PM2.5 between Baengnyeong Island (BNI) and the Seoul Metropolitan Area (SMA). We conducted PMF modeling and backward trajectory analysis using the data on PM2.5 and its components collected from 2020 to 2021 at the Air quality Research Centers (ARC). The PMF modeling identified nine pollution sources in both BNI and the SMA, including secondary sulfate, secondary nitrate, vehicles, biomass burning, dust, industry, sea salt particles, coal combustion, and oil combustion. Secondary particulate matter, vehicles, and biomass burning were found to be major contributors to PM2.5 concentrations in both regions. A backward trajectory analysis indicated that air masses, passing through BNI to the SMA, showed higher concentrations and contributions of ammonium nitrate, vehicles, and biomass burning in the SMA site compared to BNI site. These findings suggest that controlling nitrogen oxides (NOx) and ammonia emissions in the SMA, as well as monitoring the intermediate products that form aerosols, such as HNO3, are needed.