A Study on the seasonal correlation between O3 and PM2.5 in Seoul

Tropospheric ozone (O₃) and fine particulate matter (PM_2.5) are key air pollutants that significantly impact air quality, human health, and the environment. O₃, a secondary pollutant, is primarily formed through photochemical reactions involving nitrogen oxides (NOx) and volatile organic compounds (VOCs) under sunlight, with its levels peaking in summer. In contrast, PM_2.5 comprises both primary emissions and secondary aerosols, often showing higher concentrations in winter due to heating-related emissions and reduced atmospheric dispersion. In Korea, PM_2.5 monitoring officially began in 2015, enabling more detailed analyses of its seasonal trends and correlations with other pollutants.

This study analyzed the seasonal correlation between O₃ and PM_2.5 using data from 25 air quality monitoring stations in Seoul from 2015 to 2024. Seasonal correlations were evaluated using Pearson correlation coefficients, and the relative contributions of NOx and PM_2.5 to O₃ levels were quantified through multiple linear regression models. A strong positive correlation was observed during summer (June, July, and August), attributed to the simultaneous formation of these pollutants driven by enhanced atmospheric oxidation capacity under strong sunlight and high temperatures. In contrast, winter (January, February, and December) exhibited a weak negative correlation, influenced by aerosol-radiation interactions and the O₃ titration effect, where O₃ is depleted through reactions with NOx.

Unlike previous studies that primarily focused on either O₃ or PM_2.5 trends independently, this study integrates seasonal correlation analyses with a quantitative assessment of the interplay between NOx and PM_2.5 in O₃ suppression. The findings indicate that NOx plays a more dominant role than PM_2.5 in reducing O₃ levels, especially under low O₃ conditions. Seoul, as a megacity with complex emission sources and distinct seasonal dynamics, provides valuable insights that can inform air quality management strategies in other urban areas worldwide.

These findings provide a foundation for optimizing seasonal air quality management policies, particularly in regions with similar emission patterns and meteorological conditions. Future studies could extend this analysis by incorporating real-time meteorological data or applying chemical transport models to better capture the mechanisms driving seasonal variations in O₃ and PM_2.5.

 

Acknowledgments:

This research was supported by Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry & Technology Institute (KEITI) funded by the Ministry of Environment (MOE)