2025/05/05 by Evangelia Siouti, Ksakousti Skyllakou, David Patoulias +4 · 1 voice
Earth and Planetary Sciences · Environmental Science · #Air Quality Monitoring and Forecasting #Air Quality and Health Impacts #Atmospheric chemistry and aerosols
paper · doi:10.1016/j.atmosenv.2025.121277
openalex publication_date 2025/05/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23
Chemical transport models often use moderate spatial resolution to simulate atmospheric pollution, thereby limiting the model's ability to represent variations in urban areas. Additionally, the contributions of individual sources of pollution transported to the urban areas of interest from elsewhere are rarely quantified. In this study, we developed an approach to simulate air quality, focusing on PM 2.5 (particulate matter with a diameter lower than 2.5 μm), and its local and regional sources at high spatial resolution of 1x1 km 2 . The approach is applied in the largest city of Greece, Athens. The PMCAMx chemical transport model is employed in combination with the source apportionment algorithm, PSAT (Particle Source Apportionment Technology), to quantify the concentrations and sources of PM 2.5 , organic aerosol (OA) and elemental carbon (EC) for a typical summer and winter month. A novel approach is developed, allowing the quantification of the contributions of sources not only inside the simulated urban area but also of the regional sources located outside. Model predictions were combined with population distribution data to provide estimations for human exposure not only to total PM 2.5 concentrations but also to specific sources within the city. Residential biomass burning and transportation were found to be the dominant local sources of PM 2.5 exposure. The higher resolution (1x1 km 2 ) offered a more detailed representation of PM 2.5 spatial variability than a coarser one (36x36 km 2 ). This underscores the importance of capturing local sources in specific areas of the domain. The proposed approach can be used to provide estimates of human exposure to specific local and regional sources of primary and secondary PM 2.5 in an urban area.