Assessment of long-range transboundary aerosols in Seoul, South Korea from Geostationary Ocean Color Imager (GOCI) and ground-based observations

Back-trajectory analyses for evaluating the transboundary transport effect to the aerosol pollution in South Korea

This study performed a back-trajectory analysis to determine the influence of transboundary transport on the extent of aerosol pollution in South Korea, based on 5-year PM2.5 measurements (2015-2019) in five cities covering South Korea. A transboundary transport case was selected if a back trajectory passed over a dedicated region (BOX 1 and BOX 2) in the Yellow Sea. First, we found that the frequency of transboundary transport largely increases in the high pollution case, and this pattern is almost consistent for all months and all five cities, indicating the importance of investigating the horizontal direction of air mass movement associated with PM2.5, which has been discussed extensively in previous studies. In this study, we also examined the altitude change and straight moving distance (defined as travel distance) of back trajectories regarding the extent of local PM2.5. Consequently, we found that back trajectories in high aerosol pollution showed much lower altitudes and shorter travel differences, implying a significant contribution of surface emissions and stagnant air conditions to severe aerosol pollution. As a result, the local PM2.5 level was not significantly enhanced when the air mass passed over the Yellow Sea if transboundary transport occurred at high altitudes with rapid movement (i.e., high altitude and long travel distance back-trajectory). Based on these results, we suggest utilizing the combined information of the horizontal direction, altitude variation, and length of back trajectories to better evaluate transboundary transport.

Retrieval of aerosol optical properties from GOCI-II observations: Continuation of long-term geostationary aerosol monitoring over East Asia

Since the Geostationary Ocean Color Imager (GOCI) was successfully launched in 2010, the GOCI Yonsei aerosol retrieval (YAER) algorithm has been continuously updated to retrieve hourly aerosol optical properties. GOCI-II has 4 more channels including UV, finer spatial resolution (250 m), and daily full disk coverage as compared to GOCI, and was launched in February 2020, onboard the GEO-KOMPSAT-2B (GK-2B) satellite. In this study, we extended the YAER algorithm to GOCI-II data based on its improved performance in many aspects and present the first results of aerosol optical properties retrieved from GOCI-II data. Utilizing the overlapping period between the GOCI-II and GOCI in geostationary Earth orbit, we present GOCI-II aerosol retrievals for high aerosol-loading cases over East Asia and show that these have a consistent spatial distribution with those from GOCI. Furthermore, GOCI-II provides AOD at an even higher spatial resolution, revealing finer changes in aerosol concentrations. Validation results for one year data show that the GOCI-II AOD has a correlation coefficient of 0.83 and a ratio within the expected error (EE) of 59.4 % when compared with the aerosol robotic network (AERONET) data. We compared statistical metrics for the GOCI and GOCI-II AODs to assess the consistency between the two datasets. In addition, it was found that there is a strong correlation between the two datasets from the comparison of gridded GOCI and GOCI-II AOD products. It is expected that data from GOCI-II will continue long-term aerosol records with high accuracy that can be used to address air-quality issues over East Asia.

Regional classification of high PM10 concentrations in the Seoul metropolitan and Chungcheongnam-do areas, Republic of Korea

Since the Seoul metropolitan area is a highly developed megacity, many people are often exposed to high concentrations of particulate matter (PM), with mean aerodynamic diameters equal to or less than 10 μm (PM10), in cold seasons. PM10 concentrations can be influenced by a combination of various factors, including meteorological conditions, anthropogenic emissions, atmospheric chemical reactions, transboundary transport, and geographic characteristics. However, the establishment of an efficient air quality management plan remains challenging due to the limited understanding of the regional PM concentration characteristics. Here, the Seoul metropolitan (Seoul, Gyeonggi-do, and Incheon) and Chungcheongnam-do (Chungcheongnam-do, Daejeon, and Sejong) areas were regionally classified to identify the spatiotemporal air quality in areas where megacities and emission sources are mixed. The four representative regions were determined using the K-means clustering method based on the temporal variations in the observed PM10 concentrations. The first cluster consisted of small cities in the southern and eastern parts of Gyeonggi-do and Chungcheongnam-do, respectively, while the second cluster consisted of Incheon, West Gyeonggi-do, and Seoul. In addition, the third and fourth clusters included West Chungcheongnam-do and East Gyeonggi-do, which are adjacent to the Yellow Sea and downstream area of the westerly wind, respectively. The characteristics of each cluster during the high PM10 concentration events are explainable by wind patterns and the local air pollutant emissions, including nitrogen oxides and sulfur oxides. The obtained regional classification was different from the provincial-level administrative division of South Korea. Therefore, the present study is expected to be a scientific basis for overcoming the limitations of air quality management in administrative districts.

Do heat waves worsen air quality? A 21-year observational study in Seoul, South Korea

Heat waves are generally known to deteriorate air quality. However, the impacts of heat waves on air quality can substantially vary depending on characteristics of heat waves. In this study, we examine air quality changes in Seoul during heat waves and their associations with large-scale atmospheric patterns. For this, air quality data from 25 stations and meteorological data from 23 weather stations and reanalysis datasets during July and August of 2001-2021 are used. Under heat waves, the mean daily PM₁₀, NO₂, and CO concentrations decrease by 7.9 %, 6.1 %, and 4.6 %, respectively, whereas the mean daily PM_2.5, O₃, and SO₂ concentrations increase by 4.1 %, 17.2 %, and 2.9 %, respectively. The atmospheric circulation under heat waves is less favorable for long-range transport of air pollutants to Seoul. The PM_2.5/PM₁₀ ratio increases under heat waves, indicating that the secondary formation of aerosols becomes more important under heat waves. 37 % of the heat wave days are accompanied by severe O₃ pollution exceeding the O₃ concentration standard in South Korea. There is a significant variability of air quality in Seoul within heat waves. The heat wave days with higher concentrations of PM_2.5, PM₁₀, O₃, NO₂, and CO than their non-heat wave means exhibit a prominent difference in large-scale atmospheric pattern from the heat wave days with lower concentrations. This difference is characterized by a zonal wave-like pattern of geopotential height, which is similar to the circumglobal teleconnection pattern known as one of the major patterns for heat waves in South Korea. This zonal wave-like pattern produces more stagnant conditions over Seoul.

Assessment of air quality in North Korea from satellite observations

North Korea's air quality is poorly understood due to a lack of reliable data. Here, we analyzed urban- to national-scale air quality changes in North Korea using multi-year satellite observations. Pyongyang, Nampo, Pukchang, and Munchon were identified as pollution hotspots. On a national scale, we found that North Korea experienced 6.7, 17.8, and 20.6 times greater amounts of nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and carbon monoxide (CO) per unit primary energy supply (PES) than South Korea from 2005 to 2018. Besides, North Korea had a 24.3 times larger aerosol optical depth (AOD) per PES than South Korea from 2011 to 2018. Severe CO and aerosol pollution is aligned with extensive biofuel combustion. High SO₂ pollution corresponds with the strong coal dependence of the industry. The change rates of the national average columns for NO₂, SO₂, and CO were + 3.6, -4.4, and -0.4 % yr^-1, respectively. The AOD change rate was -4.8 % yr^-1. Overall decreasing trends, except for NO₂, are likely due to a decline in coal-fired PES. Positive NO₂ trends are consistent with increasing industrial activities. Each pollutant showed consistent patterns of linear trends, even after correcting the influence of transboundary pollution. Flue gas control and biofuel consumption reduction seem necessary to improve North Korea's air quality.