Analysis of a Severe PM2.5 Episode in the Seoul Metropolitan Area in South Korea from 27 February to 7 March 2019: Focused on Estimation of Domestic and Foreign Contribution

Abstract

In this study, domestic and foreign contributions to a severe PM2.5 episode in South Korea, in which “emergency reduction measures against particulate matter” were issued, were analyzed. During the period between 27 February and 7 March in 2019 when high PM2.5 concentrations occurred, the PM2.5 concentration in the Seoul metropolitan area (SMA) in South Korea was approximately 87.3 μg/m3 on average, and a severe PM2.5 concentration level of approximately 113.4 μg/m3 was observed between 3 March and 5 March. The results of the analysis conducted using the HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model and meteorological observation data showed that northwesterly wind or westerly winds were formed during the P1 and P3 periods when the PM2.5 concentration markedly increased. When the PM2.5 concentrations in East Asia were simulated using the Community Multiscale Air Quality (CMAQ), it was found that the high PM2.5 concentrations that occurred in the SMA of South Korea were mostly affected by PM2.5 transported over long distances and following atmospheric stagnation. When the domestic and foreign contributions were evaluated using the brute-force method (BFM), the foreign and domestic contribution concentrations were found to be 62.8 and 16.8 μg/m3, respectively, during the target period of this study. It was also found that the foreign contribution was 78.8%, while the domestic contribution was 21.2%.

The implication of the air quality pattern in South Korea after the COVID-19 outbreak

“…The improvement of the aerosol pollution without a significant NO 2 change reveals the strong contribution of external factors to the domestic aerosol pollution in South Korea. A study for February and March 2019 indicated the dominant contribution of transboundary transport to the haze in the Korean peninsula 33 . This feature is simply confirmed with the general pattern of back-trajectories obtained from the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model 34 calculation (Fig.…”

Five Year Trends of Particulate Matter Concentrations in Korean Regions (2015–2019): When to Ventilate?

“…Despite the efforts of the Korean government to improve air quality during the past decades based on several laws and regulations such as the Clean Air Conservation Act of 1991 and the Special Act on the Improvement of Air Quality in Seoul Metropolitan Area of 2003, the problem of air pollution is far from being solved in South Korea. The public’s concerns about the health risks associated with particulate matter exposure have substantially increased recently in South Korea, particularly after experiencing the record levels of outdoor PM 2.5 concentrations in many parts of the country in February and March 2019 [ 30 ]. Soon after these events, the national assembly of South Korea passed a series of bills which declared PM air pollution as a “social disaster” and provided emergency measures to tackle the problem, such as mandatory installation of air purifiers in classrooms, distribution of masks to vulnerable groups, and the promotion of low-emission vehicles [ 31 ].…”

Forecasting the Concentration of Particulate Matter in the Seoul Metropolitan Area Using a Gaussian Process Model

“…Reggente et al [19] proposed a GPR model to predict ultrafine particle (UFP) concentrations, also called PM0.1 concentrations. The proposed GPR model utilized the air quality data (CO, NO 2 , NO, O 3 ) from three monitoring sites in an urban area, approximately a small-scaled city with size 3.93 km 2 . This study empirically demonstrated that GPR outperforms Bayesian linear models.…”

“…Recently, the population of Seoul was affected by fine dust or particulate matter (PM) in the atmosphere [1]. Although some conjectured that the PM originated from outside metropolitan area [2][3][4], others also emphasized on sources such as traffic, the human activity, and the chemical reactions in the atmosphere in the area [5,6]. In addition to the problem of the sources, the dynamics of PM needs to be modeled to aid the prediction of the concentration of PM to address the exposure to the population.…”