Hwa-Woon Lee

This study examined the impact of foreign SO₂ emission changes on the aerosol direct radiative effects (ADRE) in South Korea. Simulations that applied basic emissions (BASE) and simulations that applied reduced SO₂ emissions from foreign sources (R_FSO2) were performed, respectively, using the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) two-way coupled model. In addition, the difference between the two experimental results was calculated (i.e., R_FSO2 minus BASE) to quantitatively identify the impact of foreign SO₂ emission reduction. The reduction in foreign SO₂ emissions caused a decrease in the concentration of SO₂ flowing in from overseas to South Korea. As a result, a clear decrease in SO₄²⁻ concentration was shown mainly in the southwest coast of South Korea. The difference in PM_2.5 concentration in South Korea according to the foreign SO₂ emission reduction did not correspond to the difference in SO₄²⁻ concentration; it was determined in a complex way by the changes in SO₄²⁻ concentration caused by SO₂ concentration changes, and the subsequent series of changes in NO₃⁻ and NH₄⁺ concentrations. The differences in SO₄²⁻ and PM_2.5 concentrations caused by the foreign SO₂ reduction also affected the ADRE changes in South Korea. The distribution of ADRE difference between the two experiments was not consistent with the distribution of PM_2.5 concentration difference, but it was very similar to the distribution of SO₄²⁻ concentration difference. These results imply that the ADRE of South Korea is not simply proportional to PM_2.5 concentration and may be determined by concentration changes of SO₄²⁻.

Surface ozone (O₃) is a harmful pollutant and effective strategies must be developed for its reduction. In this study, the impact of meteorological factors on the annual O₃ variability for South Korea were analyzed. In addition, the regional differences of meteorological factors in six air quality regions in South Korea (Seoul Metropolitan Area, SMA; Central region, CN; Honam, HN; Yeongnam, YN; Gangwon, GW; Jeju, JJ) were compared. The analysis of ground observation data from 2001 to 2017 revealed that the long-term variability of O₃ concentration in South Korea continuously increased since 2001, and the upward trend in 2010 to 2017 (Period 2, PRD2) was 29.8% higher than that in 2001 to 2009 (Period 1, PRD1). This was because the meteorological conditions during PRD2 became relatively favorable for high O₃ concentrations compared to conditions during PRD1. In particular, the increase in the solar radiation (SR) and maximum temperature (TMAX) and the decrease in the precipitation (PRCP) and wind speed (WS) of South Korea in PRD2 were identified as the main causes for the rise in O₃ concentrations. When meteorological factors and O₃ variability were compared among the six air quality regions in South Korea during PRD1 and PRD2, significant differences were observed. This indicated that different meteorological changes occurred in South Korea after 2010 due to the different topographical characteristics of each region; thus, O₃ variability also changed differently in each region. Interestingly, for the regions with almost similar meteorological changes after 2010, the O₃ concentration changed differently depending on the difference in the distribution of emissions. These results indicate that the O₃–meteorology relationship shows spatiotemporal differences depending on the topographical and emission distribution characteristics of each area and implies that it is necessary to fully consider such differences for efficient O₃ reduction.

In this study, we apply the four-dimensional variational (4D-Var) data assimilation to optimize initial ozone state and to improve the predictability of air quality. The numerical modeling systems used for simulations of atmospheric condition and chemical formation are the Weather Research and Forecasting (WRF) model and the Community Multiscale Air Quality (CMAQ) model. The study area covers the capital region of South Korea, where the surface measurement sites are relatively evenly distributed. The 4D-Var code previously developed for the CMAQ model is modified to consider background error in matrix form, and various numerical tests are conducted. The results are evaluated with an idealized covariance function for the appropriateness of the modified codes. The background error is then constructed using the NMC method with long-term modeling results, and the characteristics of the spatial correlation scale related to local circulation are analyzed. The background error is applied in the 4D-Var research, and a surface observational assimilation is conducted to optimize the initial concentration of ozone. The statistical results for the 12 h assimilation periods and the 120 observatory sites show a 49.4 % decrease in the root mean squared error (RMSE), and a 59.9 % increase in the index of agreement (IOA). The temporal variation of spatial distribution of the analysis increments indicates that the optimized initial state of ozone concentration is transported to inland areas by the clockwise-rotating local circulation during the assimilation windows. To investigate the predictability of ozone concentration after the assimilation window, a short-time forecasting is carried out. The ratios of the RMSE (root mean squared error) with assimilation versus that without assimilation are 8 and 13 % for the +24 and +12 h, respectively. Such a significant improvement in the forecast accuracy is obtained solely by using the optimized initial state. The potential improvement in ozone prediction for both the daytime and nighttime with application of data assimilation is also presented.