100-Meter High-Resolution Modeling and Validation of PM and NO2 Concentrations in Urban Areas of South Korea

  Fine particulate matter (PM) and nitrogen dioxide (NO₂) are major air pollutants that significantly contribute to health risks, including cardiovascular and respiratory diseases. This study develops and validates 100-meter resolution air pollution data for South Korean cities, focusing on PM and NO₂ concentrations. A hybrid modeling approach combining the Chemical Transport Model (CMAQ) and the Dispersion Model (CALPUFF) was employed to estimate the spatiotemporal distribution of these pollutants in major metropolitan areas, including Seoul, Busan, and Incheon.

  The CMAQ model generated baseline data at typical resolutions of 9 km and 1 km grids, which were further refined using the CALPUFF model to produce high-resolution 100 m datasets. The hybrid modeling approach integrated primary pollutant concentrations from CMAQ with CALPUFF's precise dispersion modeling to accurately reflect localized pollutant variations critical for urban health assessments. The resulting 100 m resolution data were validated by comparing them with roadside air quality monitoring measurements, demonstrating high correlation and ensuring temporal and spatial reliability.

  This study overcomes the limitations of traditional 1 km and 9 km resolution datasets and presents a novel approach for analyzing fine-scale pollutant distributions in urban environments. The methodology is applicable to other regions globally, particularly those facing severe air pollution challenges, and serves as a foundational tool for urban air quality improvement efforts. The generated data will facilitate research on the relationship between air pollution exposure and health outcomes and support the development of targeted air quality management policies. Future work will focus on integrating real-time air quality monitoring data to improve model accuracy and support the implementation of evidence-based air quality management policies.

 

Acknowledgement

  This research was supported by the Korea National Institute of Health (KNIH) research project (Project No. 2024-ER0606-00) and the Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry & Technology Institute (KEITI), funded by the Ministry of Environment (MOE).