Understanding the global distribution of atmospheric black carbon (BC) is essential for unveiling its climatic effect. However, there are still large uncertainties regarding the simulation of BC transport due to inadequate information about the removal process. We accessed the wet removal rate of BC in East Asia based on long-term measurements over the 2010–2016 period at three representative background sites (Baengnyeong and Gosan in South Korea and Noto in Japan). The average wet removal rate, represented by transport efficiency (TE), i.e., the fraction of undeposited BC particles during transport, was estimated to be 0.73 in East Asia from 2010 to 2016. According to the relationship between accumulated precipitation along trajectory and TE, the wet removal efficiency was lower in East and North China but higher in South Korea and Japan, implying the importance of the aging process and frequency of exposure to below- and in-cloud scavenging conditions during air mass transport. Moreover, the wet scavenging in winter and summer showed the highest and lowest efficiency, respectively, although the lowest removal efficiency in summer was primarily associated with a reduced BC aging process because the in-cloud scavenging condition was dominant. The average half-life and e-folding lifetime of BC were 2.8 and 7.1 d, respectively, which is similar to previous studies, but those values differed according to the geographical location and meteorological conditions of each site. Next, by comparing TE from the FLEXible PARTicle (FLEXPART) Lagrangian transport model (version 10.4), we diagnosed the scavenging coefficients (s⁻¹) of the below- and in-cloud scavenging scheme implemented in FLEXPART. The overall median TE from FLEXPART (0.91) was overestimated compared to the measured value, implying the underestimation of wet scavenging coefficients in the model simulation. The median of the measured below-cloud scavenging coefficient showed a lower value than that calculated according to FLEXPART scheme by a factor of 1.7. On the other hand, the overall median of the calculated in-cloud scavenging coefficients from the FLEXPART scheme was highly underestimated by 1 order of magnitude, compared to the measured value. From an analysis of artificial neural networks, the convective available potential energy, which is well known as an indicator of vertical instability, should be considered in the in-cloud scavenging process to improve the representative regional difference in BC wet scavenging over East Asia. For the first time, this study suggests an effective and straightforward evaluation method for wet scavenging schemes (both below and in cloud), by introducing TE along with excluding effects from the inaccurate emission inventories.

Weekly rain samples were collected in coastal areas of the Shihwa Basin (Korea) from June 2000 to November 2007. The study region includes industrial, rural, and agricultural areas. Wet precipitation was analyzed for conductivity, pH, Cl⁻, NO₃⁻, SO₄²⁻, Na⁺, K⁺, Mg²⁺, NH₄⁺, and Ca²⁺. The major components of precipitation in the Shihwa Basin were NH₄⁺, volume-weighted mean (VWM) of 44.6 µeq∙L⁻¹, representing 43% of all cations, and SO₄²⁻, with the highest concentration among the anions (55%) at all stations. The pH ranged from 3.4 to 7.7 with a VMM of 4.84. H⁺ was weakly but positively correlated with SO₄²⁻ (r = 0.39, p < 0.001) and NO₃⁻ (r = 0.38, p < 0.001). About 66% of the acidity was neutralized by NH₄⁺ and Ca²⁺. The Cl⁻/Na⁺ ratio of the precipitation was 37% higher than seawater Cl⁻/Na⁺. The high SO₄²⁻/NO₃⁻ ratio of 2.3 is attributed to the influence of the surrounding industrial sources. Results from positive matrix factorization showed that the precipitation chemistry in Shihwa Basin was influenced by secondary nitrate and sulfate (41% ± 1.1%), followed by sea salt and Asian dust, contributing 23% ± 3.9% and 17% ± 0.2%, respectively. In this study, the annual trends of SO₄²⁻ and NO₃⁻ (p < 0.05) increased, different from the trends in some locations, due to the influence of the expanding power generating facilities located in the upwind area. The increasing trends of SO₄²⁻ and NO₃⁻ in the study region have important implications for reducing air pollution in accordance with national energy policy.

The black carbon (BC) and carbon monoxide (CO) emission ratios were estimated and compiled from long-term, harmonized observations of the ΔBC∕ΔCO ratios under conditions unaffected by wet deposition at four sites in East Asia, including two sites in South Korea (Baengnyeong and Gosan) and two sites in Japan (Noto and Fukuoka). Extended spatio-temporal coverage enabled estimation of the full seasonality and elucidation of the emission ratio in North Korea for the first time. The estimated ratios were used to validate the Regional Emission inventory in ASia (REAS) version 2.1 based on six study domains (“East China”, “North China”, “Northeast China”, South Korea, North Korea, and Japan). We found that the ΔBC∕ΔCO ratios from four sites converged into a narrow range (6.2–7.9 ng m⁻³ ppb⁻¹), suggesting consistency in the results from independent observations and similarity in source profiles over the regions. The BC∕CO ratios from the REAS emission inventory (7.7 ng m⁻³ ppb⁻¹ for East China – 23.2 ng m⁻³ ppb⁻¹ for South Korea) were overestimated by factors of 1.1 for East China to 3.0 for South Korea, whereas the ratio for North Korea (3.7 ng m⁻³ ppb⁻¹ from REAS) was underestimated by a factor of 2.0, most likely due to inaccurate emissions from the road transportation sector. Seasonal variation in the BC∕CO ratio from REAS was found to be the highest in winter (China and North Korea) or summer (South Korea and Japan), whereas the measured ΔBC∕ΔCO ratio was the highest in spring in all source regions, indicating the need for further characterization of the seasonality when creating a bottom-up emission inventory. At levels of administrative districts, overestimation in Seoul, the southwestern regions of South Korea, and Northeast China was noticeable, and underestimation was mainly observed in the western regions in North Korea, including Pyongyang. These diagnoses are useful for identifying regions where revisions in the inventory are necessary, providing guidance for the refinement of BC and CO emission rate estimates over East Asia.

Variations in concentrations of PM_2.5, particulate matters of diameters below 2.5 μm, vary following both meteorological conditions and emissions controls. Meteorological conditions particularly affect short‐term high PM_2.5 episodes through accumulations, transports, and secondary formations. This study quantifies the meteorological impacts on high PM_2.5 episodes in the Seoul Metropolitan Area (SMA), Korea, for the period 2016–2018 using empirical and statistical methods. Synoptic weather maps of 77 high PM_2.5 episodes in 2016 are grouped into two synoptic types: onshore winds associated with migratory pressure systems over the SMA and offshore winds from continental high pressure extending toward the SMA. We applied principal component analysis and regression to extract the dominant synoptic types controlling PM_2.5 variability. It identifies two major principal components (PCs) from 12 surface and upper‐air meteorological variables for 2017–2018. Weather patterns in 49 examples of the high‐positive PCs show that the two PCs are capable of reproducing the synoptic weather patterns relevant for high PM_2.5 episodes. To quantify the relationship between the synoptic weather patterns and PM_2.5 levels, the two PCs are further classified into four groups according to their signs. Positive‐ and negative‐PC groups are associated with about 82% and 73% of high‐ and low‐PM_2.5 episodes, respectively, suggesting that most of the high/low PM_2.5 episodes in the SMA can occur under the two PCs‐dominant weather conditions. The results can be utilized as a reference for daily predictions of high PM_2.5 episodes, as well as for quantitative analysis of the climatic influence on the long‐term PM_2.5 variability.

We estimated fine-mode black carbon (BC) concentrations at the surface using AERONET data from five AERONET sites in Korea, representing urban, rural, and background. We first obtained the columnar BC concentrations by separating the refractive index (RI) for fine-mode aerosols from AERONET data and minimizing the difference between separated RIs and calculated RIs using a mixing rule that can represent a real aerosol mixture (Maxwell Garnett for water-insoluble components and volume average for water-soluble components). Next, we acquired the surface BC concentrations by establishing a multiple linear regression (MLR) between in-situ BC concentrations from co-located or adjacent measurement sites, and columnar BC concentrations, by linearly adding meteorological parameters, month, and land-use type as the independent variables. The columnar BC concentrations estimated from AERONET data using a mixing rule well reproduced site-specific monthly variations of the in-situ measurement data, such as increases due to heating and/or biomass burning and long-range transport associated with prevailing westerlies in the spring and winter, and decreases due to wet scavenging in the summer. The MLR model exhibited a better correlation between measured and predicted BC concentrations than those based on columnar concentrations only, with a correlation coefficient of 0.64. The performance of our MLR model for BC was comparable to that reported in previous studies on the relationship between aerosol optical depth and particulate matter concentration in Korea. This study suggests that the MLR model with properly selected parameters is useful for estimating the surface BC concentration from AERONET data during the daytime, at sites where BC monitoring is not available.

Ambient PM_2.5, well-known for its adverse impacts on human health, is a very heterogeneous pollutant. Its chemical composition and attributable sources vary by region, influenced by meteorological and geographical conditions as well as emission sources. However, administrative policies are currently focused on mass concentrations. However, not all PM_2.5 sources provide equally toxic particles. Thus, those sources that should be the focus of controls has not been the priority. In the present study, we conducted source apportionment utilizing positive matrix factorization (PMF) and investigated the association of PM_2.5 source contributions with emergency department visits (EDVs) in major megacities in South Korea. Overall, an interquartile range (IQR) increment in source contribution increased the number of emergency room visits. Industry and coal combustion sources, marked by heavy metals, were principally associated with the adverse health impacts. However, the sources showing significant associations with EDVs differed across the study area. In addition, we found that region-specific relationships between PM_2.5 sources and morbidity were plausible, considering the existence of relevant sources such as industrial complexes and coal-fired power plants. The analysis of source contributions according to wind conditions also supported the source-morbidity relationships. These findings suggest that administrative policies for PM_2.5 control should be established and implemented considering region-specific characteristics of the links between PM_2.5 sources and health impacts to maximize the control's public health effects. Furthermore, the results of the present study indicate that PMF was an effective method for linking acute exposure to PM_2.5 source types with health outcomes to prioritize its sources.