Spatiotemporal variability patterns of PM2.5 in severe pollution events based on a large dataset from air quality monitoring stations over South Korea

East Asia has suffered from severe air pollution, particularly concerning particulate matter less than 2.5 µm in diameter (PM_2.5). Although air quality in Korea has been gradually improved with respect to annual mean PM_2.5 and PM₁₀ concentrations, high PM pollution events have been worse in their peak concentrations and durations.

In this study, we attempted to find statistically how the characteristics of PM_2.5 pollution over Korea have changed with a focus on temporal and spatial variations. Hourly PM_2.5 concentration data were obtained from 374 air quality monitoring stations (AQMS) throughout the country from January 2015 to June 2019. With obtained air quality data, we selected high PM pollution periods based on the national air pollution standard, and examined how the magnitudes and durations of high PM pollution events, as well as the background concentrations, have changed since 2015 over Korea. Additionally, we applied the time-lag correlation method to see how the onsets of PM_2.5 pollution events differ in space and how high PM_2.5 spread out in time. We also applied the coefficient of divergence (COD) to countrywide datasets of PM_2.5 as a measure of spatial heterogeneity of PM_2.5 distributions.

Although annual mean concentrations of PM_2.5 tend to decline from 2015 to 2018, the peak concentrations and durations for severe PM_2.5 pollution events tend to increase in most regions of Korea for the periods of January to April. We also categorized the characteristic distribution patterns in severe PM events combining the time-lag correlation and COD results. In most pollution events, the time-lag distributions showed clear delay patterns of pollution events from the reference area (Seoul). Additionally, COD results showed a clear heterogeneity of PM_2.5 distributions as the distance from the reference area increases along the time-lag. Although spatial correlations and COD results of PM_2.5 concentrations between the reference area and other regions indicated heterogeneous distributions, time-lag corrected COD values imply that PM_2.5 over much wider regions of Korea are homogeneously distributed in both magnitudes and temporal variations. The R² values were significantly improved after time-lag correction. These results imply that high PM_2.5 events are significantly affected by synoptic weather conditions over most regions of Korea; thus, potential modification of synoptic weather patterns in East Asia caused by climate change can be an important factor for variations in high PM_2.5 pollution events.

Keywords: coefficient of divergence (COD), PM_2.5 pollution events, spatial heterogeneity of PM distributions, pattern analysis.