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The Center for Air Quality &Control at the Seoul Research Institute of Public Health and the Environment (SIHE) has monitored changes in the concentration of fine dust in Seoul over the past 10 years and investigated meteorological factors as well as fine particulate matter (PM2.5), sulfur dioxide (SO2), and nitrogen dioxide (NO2) concentrations in northeastern China and its contribution to the PM2.5 concentration in Seoul. The concentration of fine dust in Seoul in 2020 was 21 µg/m3, which is down 16% from 2019 and the lowest since 2010. In 2020, China’s emissions of pollutants such as NO2 have decreased significantly due to regional blockades, social distancing, and factory shutdowns caused by COVID-19. As a results, the concentration of precursors such as SO2 and NO2, and PM2.5 in northeastern China are also decreased, which contributed to the reduction in PM2.5 concentration in Seoul caused by westerly winds blowing. In addition, the ratio of east and south winds that usually contain low concentrations of pollutants was more than 30% of the total air currents into Seoul, which is the highest in the last three years. Moreover, the mean wind velocity and the amount of precipitation were also the highest recorded values of 2.4 m/s and 1651.0 mm, respectively. Calculations using Comprehensive Air quality Model with eXtensions (CAMx)-Particulate Source Apportionment Technology (PSAT) show that the contribution of external inflows to the PM2.5 concentration in Seoul was 65%. We believe that the reasons for the low PM2.5 concentration in 2020 are due to meteorological factors and a decrease in air pollution in northeastern China. Meanwhile, the major contribution of emissions in Seoul (resuspended road dust and non-exhaust dust) was high. When the concentration of PM2.5 was high, the contribution of resuspended road dust was reduced due to an increase of secondary generating materials. Currently, data on emission reduction due to the COVID-19 cannot be assessed, which we believe will enable more accurate contribution calculations in the future. © 2021

High concentrations of PM2.5 have become a serious environmental issue in South Korea, which ranked 1st or 2nd among OECD countries in terms of population exposure to PM2.5. Quantitative understanding of PM2.5 source attribution is thus crucial for developing efficient air quality mitigation strategies. Here we use a suite of extensive observations of PM2.5 and its precursors concentrations during the international KORea-US cooperative Air Quality field study in Korea (KORUS-AQ) in May–June 2016 to investigate source contributions to PM2.5 in South Korea under various meteorological conditions. For the quantitative analysis, we updated a 3-D chemical transport model, GEOS-Chem, and its adjoint with the latest regional emission inventory and other recent findings. The updated model is evaluated by comparing against observed daily PM2.5 and its component concentrations from six ground sites (Bangnyung, Bulkwang, Olympic park, Gwangju, Ulsan, and Jeju). Overall, simulated concentrations of daily PM2.5 and its components are in a good agreement with observations over the peninsula. We conduct an adjoint sensitivity analysis for simulated surface level PM2.5 concentrations at five ground sites (except for Bangnyung because of its small population) under four different meteorological conditions: dynamic weather, stagnant, extreme pollution, and blocking periods. Source contributions by regions vary greatly depending on synoptic meteorological conditions. Chinese contribution accounts for almost 68% of PM2.5 in surface air in South Korea during the extreme pollution period of the campaign, whereas an enhanced contribution from domestic sources (57%) occurs for the blocking period. Results from our sensitivity analysis suggest that the reduction of domestic anthropogenic NH3 emissions could be most effective in reducing population exposure to PM2.5 in South Korea (effectiveness = 14%) followed by anthropogenic SO2 emissions from Shandong region (effectiveness = 11%), domestic anthropogenic NOx emissions (effectiveness = 10%), anthropogenic NH3 emissions from Shandong region (effectiveness = 8%), anthropogenic NOx emissions from Shandong region (effectiveness = 7%), domestic anthropogenic OC emissions (effectiveness = 7%), and domestic anthropogenic BC emissions (effectiveness = 5%).

To understand the characteristics of air quality in the Seoul Metropolitan Area, intensive measurements were conducted under the Korea-United States Air Quality (KORUS-AQ) campaign. Trace gases such as O3, NOx, NOy, SO2, CO, and volatile organic compounds (VOCs), photochemical byproducts such as H2O2 and HCHO, aerosol species, and meteorological variables including planetary boundary layer height were simultaneously measured at Olympic Park in Seoul. During the measurement period, high O3 episodes that exceeded the 90 ppbv hourly maximum occurred on 14 days under four distinct synoptic meteorological conditions. Furthermore, local circulation such as land–sea breeze and diurnal evolution of the boundary layer were crucial in determining the concentrations of precursor gases, including NOx and VOC as well as O3. During such episodes, the nighttime NOx and VOC and daytime UV levels were higher compared to non-episode days. The overall precursor levels and photochemical activity were represented fairly well by variations in the HCHO, which peaked in the morning during the high O3 episodes. This study revealed that toluene was the most abundant VOC in Seoul, and its concentration increased greatly with NOx due to the large local influence under stagnant conditions. When O3 was highly elevated concurrently with PM2.5 under dominant westerlies, NOx and VOCs were relatively lower and CO was noticeably higher than in other episodes. Additionally, the O3 production efficiency was the highest due to a low NOx with the highest NOz/NOy ratio among the four episodes. When westerlies were dominant in transport-south episode, the nighttime concentration of O3 remained as high as 40~50 ppbv due to the minimum level of NOx titration. Overall, the Seoul Metropolitan Area is at NOx-saturated and VOC-limited conditions, which was diagnosed by indicator species and VOC/NOx ratios.

The Korea – United States Air Quality Study (May – June 2016) deployed instrumented aircraft and ground-based measurements to elucidate causes of poor air quality related to high ozone and aerosol concentrations in South Korea. This work synthesizes data pertaining to aerosols (specifically, particulate matter with aerodynamic diameters

Photolysis of nitrous acid (HONO) is recognized as an early-morning source of OH radicals in the urban air. During the Korea-US air quality (KORUS-AQ) campaign, HONO was measured using quantum cascade - tunable infrared laser differential absorption spectrometer (QC-TILDAS) at Olympic Park in Seoul from 17 May, 2016 to 14 June, 2016. The HONO concentration was in the range of 0.07-3.46 ppbv, with an average of 0.93 ppbv. Moreover, it remained high from 00:00-05:00 LST. During this time, the mean concentration was higher during the high-O3 episodes (1.82 ppbv) than the non-episodes (1.20 ppbv). In the morning, the OH radicals that were produced from HONO photolysis were 50% higher (0.95 pptv) during the high-O3 episodes than the non-episodes. Diurnal variations in HOx and O3 concentrations were simulated by the F0AM model, which revealed a difference of ~20 ppbv in the daily maximum O3 concentrations between the high-O3 episodes and non-episodes. Furthermore, the HONO concentration increased with an increase in relative humidity (RH) up to 80%; the highest HONO was associated with the top 10% NO2 in each RH group, confirming that NO2 is one of the main precursors of HONO. At night, the conversion ratio of NO2 to HONO was estimated to be 0.88×10-2 h-1; this ratio was found to increase with an increase in RH. The Aitken mode particles (30-120 nm), which act as catalyst surfaces, exhibited a similar tendency with a conversion ratio that increased along with RH, indicating the coupling of surfaces with HONO conversion. Using an artificial neural network (ANN) model, HONO concentrations were successfully simulated with measured variables (r2 = 0.66 as an average of five models). Among these variables, NOx, aerosol surface area, and RH were found to be the main factors affecting the ambient HONO concentrations. The results reveal that RH facilitates the conversion of NO2 to HONO by constraining the availability of aerosol surfaces. This study demonstrates the coupling of HONO with the HOx-O3 cycle in the Seoul Metropolitan Area (SMA) and provides practical evidence of the heterogeneous formation of HONO by employing the ANN model.

In this study, we simultaneously measured the PM10 and PM2.5 mass concentrations and their heavy metal content for three days at a subway station in Seoul to investigate the airborne PM flows. The average concentrations were 59 µg m–3, 37 µg m–3, 111 µg m–3, and 369 µg m–3 for the PM10 and 43 µg m–3, 28 µg m–3, 58 µg m–3, and 132 µg m–3 for the PM2.5 at the outdoor air inlet, in the concourse, on the platform, and in the tunnel, respectively. We also found strong correlations between the temporal variations at adjacent sampling locations for both fractions, although they were higher for the PM2.5. Additionally, of the airborne trace metals detected at the sampling locations inside the station (the concourse, platform, and tunnel), iron (Fe) displayed the highest concentration and was thus selected as a tracer of PM. Applying a simple mass balance model to the Fe concentrations and ventilation rates revealed that 78% of the PM10 and 62% of the PM2.5 on the platform emanated from the tunnel, whereas 84% of the PM10 and 87% of the PM2.5 in the concourse originated outdoors (and arrived in the filtered air). These results further confirm that reducing PM emission from the tunnel is the most effective strategy for improving air quality on the platform and achieving compliance with the national guideline.