Source apportionment of PM2.5 at the coastal area in Korea Original Research Article

In this study, we analyzed the chemical composition of fine particulate matter 2.5 μm or less (PM2.5) collected at Incheon, the coastal area in Seoul, Korea every third day from June 2009 to May 2010. Based on the analyzed chemical species in the PM2.5 samples, the sources of PM2.5 were identified using a positive matrix factorization (PMF). Nine sources of PM2.5 were determined from PMF analysis. The major sources of PM2.5 were secondary nitrate (25.4%), secondary sulfate (19.0%), motor vehicle 1 (14.8%) with a lesser contribution from industry (8.5%), motor vehicle 2 (8.2%), biomass burning (6.1%), soil (6.1%), combustion and copper production emissions (6.1%), and sea salt (5.9%). From a paired t-test, it was found that yellow sand samples were characterized as having higher contribution from soil sources (p < 0.05). Furthermore, the likely source areas of PM2.5 emissions were determined using the conditional probability function (CPF) and the potential source contribution function (PSCF). CPF analysis identified the likely local sources of PM2.5 as motor vehicles and sea salt. PSCF analysis indicated that the likely source areas for secondary particles (sulfate and nitrate) were the major industrial areas in China. Finally, using the source contribution of PM2.5 and associated organic composition data, principal component analysis (PCA) was conducted to evaluate the accuracy of the PM2.5 source apportionments by PMF. The PCA analysis confirmed eight of the nine PM2.5 sources. Our result implies that the chemical composition analysis of PM2.5 data and various modeling techniques can effectively identify the potential contributing sources.