Identification of source areas of polycyclic aromatic hydrocarbons in Ulsan, South Korea, using hybrid receptor models and the conditional bivariate probability function

Abstract

This study identifies the emission source areas for the atmospheric polycyclic aromatic hydrocarbons (PAHs) detected in Ulsan, South Korea.

Abstract

This study identifies the emission source areas for the atmospheric polycyclic aromatic hydrocarbons (PAHs) detected in Ulsan, South Korea. To achieve this, in addition to a conditional bivariate probability function (CBPF), two hybrid receptor models – the three-dimensional potential source contribution function (3D-PSCF) model and the 3D concentration weighted function (3D-CWT) model – were used, both of which adopt trajectory segments within the mixing layer. Notably, the fraction-weighted trajectory (FWT), a combination of PAH gas/particle partitioning with a hybrid receptor model, was introduced for the first time in this study to support the identification of emission source areas using other approaches ( i.e., 3D-PSCF, 3D-CWT, and CBPF). Consequently, it was found that gaseous PAHs in Ulsan mostly originated from local emission sources ( i.e., transportation and industrial emissions) throughout the year, whereas particulate PAHs were likely to originate from emission sources in China ( e.g., Shandong, Hebei, and Liaoning) during spring and winter via long-range transport. However, in summer and fall, the influence of local emissions on particulate PAHs appeared to be stronger. The FWT was able to distinguish between local and distant sources more effectively, especially in summer and fall, i.e., the periods when local sources increased their contribution. This study thus increases the understanding of the long-range transport of PAHs in Northeast Asia, and the novel FWT approach exhibits the potential to be employed in the source area identification of various semi-volatile organic chemicals.