Assessment of air quality measures in Northeast Asia using atmospheric chemical transport model

Abstract

Air pollution in Northeast Asia is caused by a complex interaction between local sources, natural sources, and long-range transport. The severe air pollution has caused environmental, social, and political problems, adversely affecting human health due to exposure to high concentrations of air pollutants. Accordingly, measures to control emissions and improve air quality have been implemented in South Korea and China. It is crucial to quantitatively evaluate the actual effectiveness of these policies, separate from other factors that can affect air quality. Therefore, the topic of dissertation is “Assessment of air quality measures in Northeast Asia using atmospheric chemical transport model”. It is mainly divided into four chapters. The research background and objectives were described in the first chapter. In the second chapter, the impact of meteorology, emission reduction, and the COVID19 pandemic on PM2.5 concentrations in South Korea and China was quantified in 2020. Since 2016, meteorological conditions have impacted PM2.5 concentrations, leading to an increase. However, as a result of air quality management policies, PM2.5 concentrations decreased in 2020. Additionally, the impact of COVID19 in China was found to be significant enough to be comparable to the annual effects caused by air quality management policies. During this period, the seasonal management system was implemented in South Korea for the first time, which led to limitations in quantifying its effects. To address these limitations, domestic and transboundary contributions were separated, and the impact of the first seasonal management policy in South Korea accounted for approximately 57% of the long- term policy (compared to 2016). In the third chapter, the changes in regional contribution to PM2.5 concentrations in South Korea in accordance with air quality measures were analyzed. By comparing the results of the Brute Force Method (BFM) and CMAQ-ISAM, the pros and cons of each methodology were identified, and a Hybrid Method that could compensate for the shortcomings was presented. The Hybrid Method was used for NO3 -. It was able to address the issue of calculating the contribution to - only from NH4 + (BFM) and the issue where the boundary condition represents 90% of NO3 (CMAQ-ISAM). To compare the study periods of 2016 and 2022, three types of emission data (KORUSv5, SIJAQv2, ASIA-AQv3) were utilized. The comparison revealed that, despite using the latest data, the emission amounts were not necessarily smaller. However, NOX and SO2, which mainly decreased due to emission reduction measures, were also reflected in the emission data. Primary PM (POC, EC) reflected the impact of the emission data, and in the case of secondary PM, SO4 2-, NH4 tended to decrease and NO3 - increased due to the oxidant-limiting effect. In addition, the model confirmed the tendency for O3 concentration to increase due to a decrease in NO2 concentration. Upon analysis of high concentration cases, these changes became more evident, indicating the necessity for the implementation of air quality management measures for each substance. Through this study, factors that affect air quality and regional contributions can be identified, which can provide a scientific foundation for future plans.