Hybrid receptor models overestimate the contribution of background areas (no specific emission sources), like the Yellow Sea in Korea. This study aimed to improve model performances using Advanced Concentration Emission and Retention Time Weighted Trajectory (ACERWT). ACERWT was combined with a positive matrix factorization (PMF), back trajectory, and Regional Emission Inventory in Asia (REAS). The PMF receptor model used one year of data from Korea’s Central Air Environment Research Center. In the PMF receptor model, eight sources (dust/soil, secondary nitrate, biomass burning, vehicles, secondary sulfate, industry, coal combustion and sea salt) influenced PM_2.5 pollution at the receptor site (Daejeon, Korea). Secondary sulfate was the most dominant source, followed by secondary nitrate and vehicle sources. ACERWT results showed high contributions from China, Japan, and Korean regions, while the contribution from the Yellow Sea was significantly lower. Several regions, such as the eastern and south-eastern areas of China, the southern area of Taiwan, the western area of Tokyo, and the central area of Korea, showed high contributions due to large-scale emission facilities and industrial complexes. In this study, the ACERWT model significantly improved its performance regarding regional contributions to PM_2.5 pollution at the receptor site.

Aims: This study aimed to study the long-range transport of anthropogenic carbonaceous aerosol at Gosan, Korea Study Design: Chemical composition of fine particles (aerodynamic diameter < 2.5㎛) and PAHs of TSP measured at Gosan during six intensive measurement periods covering four seasons. And the chemical characteristics of particulate matter were classified and compared each other according to the major source areas identified by using backward trajectory analysis in order to study the impact of distant source regions on the carbonaceous aerosol at Gosan, Korea. Place and Duration of Study: Sample: Gosan, Jeju Island in Republic of Korea, from 13 to 25 Nov. 2001, from 29 Mar. to 11 Apr. 2002, from 27 Aug. to 11 Sep. 2002, from 14 to 26 Feb 2003, from 6 to 22 Jun. 2003, and from 18 Aug. to 1 Sep. 2003. Methodology: In order to investigate the chemical composition of fine particles, 7 major ion components, 21 trace elements, organic and elemental carbon of PM_2.5 were measured. In addition, particulate hazardous pollutants including 17 polycyclic aromatic hydrocarbons (PAHs) were analyzed. The measured data were classified according to the dominant source area identified with the three-day backward trajectory analysis. Then several ratios of species combining EC, OC, SO₄^2-, K⁺ and PAH compounds were used to identify potential sources of carbonaceous materials. Results: Quite different characteristic in the chemical composition of fine particles was observed by regional groups of backward trajectories. Concentrations of ion components including secondary aerosol such as SO₄^2- and NH₄⁺ were relatively high when air masses were originated from north China. Concentrations of OC and gaseous PAHs were higher when they transported from Japan than from other source regions. High concentrations of secondary aerosols as well as particulate PAHs were observed in the air mass from north China with a higher correlation between them. Elemental carbon had a better correlation in this case not only with secondary aerosols, but also with OC and CO, implying that carbonaceous materials were originated from long-distance combustion sources. Especially positive correlation with benzo(ghi)perylene suggested that they also had a vehicular origin. Conclusion: The results showed that biomass burning and vehicular emissions mainly influenced ambient fine particles when they derived from north China and the Korea peninsula while fossil fuel combustion chiefly affected them when they originated in south China during six intensive measurement periods.

As urban areas increasingly support carbon neutrality goals, understanding localized greenhouse gas (GHG) emissions is critical. This study investigates GHG concentrations and their emission sources in Seoul using high-resolution monitoring data of CO₂ and CH₄ , along with co-emitted air pollutants including CO, NO₂, and PM_2.5 . The concentrations of CO₂ and CH₄ exhibited notable spatial and temporal variability and were strongly correlated with CO and NO₂, suggesting the predominance of combustion-related sources in the region. Positive matrix factorization (PMF) was applied to time-resolved air quality data collected at the Seoul supersite, identifying 11 distinct emission sources contributing to GHG levels. Among these, gasoline and diesel vehicles were the dominant contributors to both GHG and PM_2.5 concentrations. This result highlights the significant impact of traffic-related emissions in densely populated urban areas and is consistent with existing GHG emission inventories for Seoul, reinforcing the utility of monitoring-based source apportionment. The statistical analysis of integrated GHG and air pollutant data demonstrates the effectiveness of data-driven approaches in identifying key emission sources. These findings provide a scientific basis for prioritizing emission reduction efforts and support the formulation of comprehensive mitigation strategies. Ultimately, the results contribute to the development of science-based, region-specific carbon neutrality policies that address both air pollution and climate change in major metropolitan regions such as Seoul.