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Abstract Seosan is a concentrated industrial complex in the midwestern region of Korea. A study was conducted from December 2020 to January 2021, measuring PM2.5 and chemical components in Seosan using online instruments every hour. The concentration of PM2.5 during the winter season was 31.4±17.8 μg/m3, exceeding the national ambient air quality standard of Korea. The mass fraction of organic matter, elemental carbon, three major ions, five minor ions, crustal elements, and trace elements in PM2.5 accounted for 24.5%, 4.36%, 32.0%, 2.82%, 4.11%, and 5.17% of the total PM2.5 mass concentration, respectively. Source identification was conducted using positive matrix factorization modeling, revealing eight sources of PM2.5: Secondary inorganic aerosol (SIA), vehicle exhaust, industry, coal combustion, biomass burning/incinerator, oil combustion, soil, and aged sea salt. Source contributions varied during high pollution episodes (HPE), with SIA dominating in HPE1 and soil and aged sea salt in HPE2. The potential source contribution function and conditional probability function were utilized to estimate the potential local and regional emission areas for the identified sources. In Seosan, vehicle exhaust and biomass burning/incinerator were primarily influenced by local sources. SIA, industry, and oil combustion sources were significantly affected by short-range transport from eastern China. Soil and aged sea salt, which exhibited high contributions during HPE2, were associated with long-range transport from Inner Mongolia. Coal combustion was attributed to both local sources, particularly large industrial complexes near Seosan, and long-range transport from Northeast China and Inner Mongolia. Graphical Abstract

In this study, 34 volatile organic compounds (VOCs) were analyzed using an online VOCs instrument at 30-min intervals from November 16 to November 23, 2023, in Ulaanbaatar (UB), the capital of Mongolia for the first time. The average concentration of the 34 VOCs was 13.0 ± 11.1 ppb, with the top 10 compounds, such as benzene, toluene, ethylbenzene, and xylenes (BTEX), constituting 80 % of the total. The concentrations of n-hexane, n-heptane, and undecane tended to increase significantly during high-concentration episode period (HEP). Compared to other studies, BTEX concentration levels in UB were higher than those in Seoul and Beijing, but lower than in Southeast Asian cities. Positive matrix factorization (PMF) identified four VOCs sources: vehicle exhaust (33.8 %), industrial/coal combustion (25.3 %), secondary formation precursors (21.3 %), and solvent usage (19.6 %). Vehicle exhaust and industrial/coal combustion sources increased during rush hours and were strongly correlated with nitrogen oxides. During HEP, stagnant air mass led to increased contributions from vehicle exhaust and industrial/coal combustion sources, indicating a significant local impact. Solvent usage appeared to be influenced by building materials and exterior painting which increased with high relative humidity. Secondary formation precursors increased in concentration during daytime and were highly correlated with ozone. Among the measured compounds, benzene was assessed for lifetime health risk, showing that adults with the prolonged exposure exhibited higher risk than infants and children. However, during HEP, children were also at increased risk, despite their shorter exposure duration. Based on the concentration levels of VOCs and the associated health risks, the results highlight that the need for a policy on ambient VOCs management in UB, with a particular focus on local source management.

Underground shopping malls (USMs) are often open or semi-open environments with interconnected passageways, resulting in the sharing of indoor air. However, indoor air quality (IAQ) within these spaces can vary due to many diverse emission sources. We investigated the relationships between IAQ and geographical areas, as well as IAQ and store types, within USMs, in Korea.In 2020, we studied 10 different USMs, with a total of 128 outlets. We conducted comprehensive IAQ assessments (including measurements of fine particles (PM2.5), aldehydes, and volatile organic compounds (VOCs)) in stores, passages, and outdoor areas. The stores were categorized into three types: clothing, fashion accessories, and food services. Additionally, we measured environmental factors such as CO2 levels and presence of storefront walls.PM2.5 levels were higher outdoors, whereas aldehyde and VOC levels exhibited elevations within passages and the interior of stores than in the outdoor environment. The store-to-passage ratios for PM2.5, individual aldehydes, and VOC concentrations ranged from 1.06 to 4.93. Formaldehyde and total VOC (TVOC) concentrations were found to be elevated in clothing and fashion accessory stores, whereas PM2.5 concentrations were more prominent in food service establishments. Specific individual compounds, including propionaldehyde, hexaldehyde, benzene, n-heptane, toluene, n-octane, xylene, d-limonene, n-undecane, n-dodecane, and ethylbenzene concentrations exhibited associations with store types. Multivariate regression models demonstrated positive associations between most aldehydes and VOCs with CO2 concentrations and presence of storefront walls.This study underscored variations within USMs based on area and store type. Aldehyde and VOC concentrations were notably higher in clothing and fashion accessory stores than in food service outlets; these elevations were closely linked to CO2 levels and presence of storefront walls. These findings suggest that monitoring CO2 levels within USM stores, optimizing air-conditioning systems, and designing future stores without storefront walls can collectively contribute to an overall improvement of IAQ within USMs.

Abstract Background Although many indoor public places have implemented smoke-free regulations, private homes have remained sources of tobacco smoke pollutants. This study examined differences in urinary cotinine concentrations in the Korean non-smoking adult population between living in smoking and smoke-free homes, and the relationship of urinary cotinine concentrations with socio-demographic factors in smoke-free homes. Methods Samples from 2575 non-smoking adults (≥19 years old) in the Korean National Environmental Health Survey cycle 3 (2015–2017), a representative Korean study, were used. Smoking and smoke-free homes were defined based on whether there were smokers at homes. Weighted linear regression models were used to determine urinary cotinine concentrations and identify factors associated with urinary cotinine. Results The geometric mean of urinary cotinine concentrations for non-smoking adults living in smoking homes was 2.1 μg/L (95% confidence interval [CI] = 1.8–2.4), which was significantly higher than the mean of 1.3 μg/L (95% CI = 1.2–1.4) for those living in smoke-free homes. Urinary cotinine concentrations were different significantly by home smoking status in most socio-demographic subgroups. Data from smoke-free home showed urinary cotinine concentration in adults was significantly higher in those who lived in homes with ventilation duration

Particle-phase concentrations were measured at 10, 80, and 200 m from the roadside of a national highway near Seoul in January and May 2008. The highway has two lanes each way, with an average hourly traffic volume of 1,070 vehicles. In January 2008, PM10 concentrations decreased from 10 to 80 m but increased at 200 m. Black carbon (BC) decreased only slightly with distance due to the influence of biomass burning and open burning from the surrounding areas. In May 2008, the effect of secondary formation on both PM10 and PM2.5 was significant due to high temperatures compared with January. Because on-road emissions had little effect on secondary formation for a short time, variations in PM10 concentrations became smaller, and PM2.5 concentrations increased with distance. The effects of fugitive dust on PM concentrations were greater in May than in January when the mean temperature was below freezing. In the composition variations, the amounts of primary ions, organic carbon (OC), and BC were larger in January, while those of secondary ions and others were larger in PM10, as well as PM2.5 in May.