Assessing the added value of high-resolution PM2.5 mapping for population exposure estimates in Seoul, South Korea

Accurate representation of fine particulate matter (PM_2.5) at urban scales remains a major challenge in air pollution modelling, as conventional chemical transport models (CTMs) are typically operated at kilometer-scale resolution, which may smooth out strong local concentration gradients. Such limitations can influence not only the interpretation of model results but also the application of model-derived concentration fields to exposure-related analyses.

In this study, we assess the added value of high-resolution PM_2.5 concentration fields for urban-scale air pollution modelling applications by comparing population-weighted exposure (PWE) estimates derived from multiple PM₂.₅ datasets. Daily PM_2.5 fields from CMAQ simulations at 9 km resolution, observation-based gridded PM_2.5, and a deep-learning-based super-resolution PM_2.5 product at 100 m resolution were harmonized on a common analysis grid over the Seoul metropolitan area. These concentration fields were combined with 100 m gridded population data to calculate district-level PWEs for 25 administrative districts.

The results show that CMAQ reproduces the broad spatial patterns of PM_2.5 across Seoul, while the high-resolution PM_2.5 product reveals localized variability that is not captured at coarser resolution, particularly in densely populated districts. Comparison with observation-based PWEs indicates that exposure estimates derived from the high-resolution PM_2.5 fields are often closer to observations than those based on the original CMAQ outputs, although the magnitude of improvement varies by district. Population distribution maps further highlight that spatial heterogeneity in population density plays a key role in shaping district-level exposure patterns.

Overall, this study demonstrates that enhancing the spatial representation of PM_2.5 concentration fields can provide additional insight when air pollution model outputs are applied to population exposure assessment in urban environments. The proposed framework illustrates a practical approach for evaluating the application-level benefits of high-resolution air quality products within air pollution modelling studies.

 

Acknowledgement

This research was supported by the Korea National Institute of Health (KNIH) research project(Project No. 2024-ER0606-01) and the Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry & Technology Institute (KEITI), funded by the Ministry of Environment (MOE).