Source apportionment of greenhouse gases and PM2.5 in Seoul using positive matrix factorization

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.