Characteristics of volatile organic compounds in the metropolitan city of Seoul, South Korea: Diurnal variation, source identification, secondary formation of organic aerosol, and health risk

Geographic information system-based determination of priority monitoring areas for hazardous air pollutants in an industrial city

Industrial cities are hotspots for many hazardous air pollutants (HAPs), which are detrimental to human health. We devised an identification method to determine priority HAP monitoring areas using a comprehensive approach involving monitoring, modeling, and demographics. The methodology to identify the priority HAP monitoring area consists of two parts: (1) mapping the spatial distribution of selected categories relevant to the target pollutant and (2) integrating the distribution maps of various categories and subsequent scoring. The identification method was applied in Ulsan, the largest industrial city in South Korea, to identify priority HAP monitoring areas. Four categories related to HAPs were used in the method: (1) concentrations of HAPs, (2) amount of HAP emissions, (3) the contribution of industrial activities, and (4) population density in the city. This method can be used to select priority HAP monitoring areas for intensive monitoring campaigns, cohort studies, and epidemiological studies.

Mapping the spatial distribution of primary and secondary PM2.5 in a multi-industrial city by combining monitoring and modeling results

Industrial cities are strongly influenced by primary emissions of PM2.5 from local industries. In addition, gaseous precursors, such as sulfur oxides (SOX), nitrogen oxides (NOX), and volatile organic compounds (VOCs), emitted from industrial sources, undergo conversion into secondary inorganic and organic aerosols (SIAs and SOAs). In this study, the spatial distributions of primary and secondary PM2.5 in Ulsan, the largest industrial city in South Korea, were visualized. PM2.5 components (ions, carbons, and metals) and PM2.5 precursors (SO2, NO2, NH3, and VOCs) were measured to estimate the concentrations of secondary inorganic ions (SO42-, NO3-, and NH4+) and secondary organic aerosol formation potential (SOAFP). The spatial distributions of SIAs and SOAs were then plotted by combining atmospheric dispersion modeling, receptor modeling, and monitoring data. Spatial distribution maps of primary and secondary PM2.5 provide fundamental insights for formulating management policies in different districts of Ulsan. For instance, among the five districts in Ulsan, Nam-gu exhibited the highest levels of primary PM2.5 and secondary nitrate. Consequently, controlling both PM2.5 and NO2 emissions becomes essential in this district. The methodology developed in this study successfully identified areas with dominant contributions from both primary emissions and secondary formation. This approach can be further applied to prioritize control measures during periods of elevated PM levels in other industrial cities.

Distribution and ecological risk assessment of priority water pollutants in surface river sediments with emphasis on industrially affected areas

Priority water pollutants comprising six plasticizers, 18 volatile organic compounds (VOCs), total petroleum hydrocarbon (TPH), 1,4-dioxane, epichlorohydrin, formaldehyde, acrylamide, and cyanides were determined in surface river sediments to assess their distribution patterns and ecological risks. Among these, di (2-ethylhexyl) phthalate (DEHP), toluene, TPH, and acrylamide were frequently found in sediments. The industrial sites had higher concentrations of ∑plasticizers (median 628 ng/g dry weight (dw)), ∑VOCs (median 3.35 ng/g dw), acrylamide (median 0.966 ng/g dw), and TPH (median 152 μg/g dw) in sediments than the mixed and non-industrial areas. The other pollutants did not show the significant differences in levels according to site types because of their relatively low detection frequencies. Volatile and soluble substances as well as hydrophobic pollutants were predominantly detected in surface sediments from industrial areas. Sediment contamination patterns were affected by the size and composition of the industrial zones around the sampling sites. The ecological risks determined using the sediment quality guidelines (DEHP, VOCs, and TPH) and the mean probable effect level quotients (DEHP) were mostly acceptable. However, the two most representative industrial regions (the largest industrial area and the first industrial city) showed risks of concern for DEHP and TPH.

Passive air sampling of VOCs, O3, NO2, and SO2 in the large industrial city of Ulsan, South Korea: spatial-temporal variations, source identification, and ozone formation potential

Concerns about volatile organic compounds (VOCs) have increased due to their toxicity and secondary reaction with nitrogen oxides (NOX) to form ozone (O3). In this study, passive air sampling of VOCs, O3, NO2, and SO2 was conducted in summer, fall, winter, and spring from 2019 to 2020 at six industrial and ten urban sites in Ulsan, the largest industrial city in South Korea. Over the entire sampling period, the concentration of toluene (mean: 8.75 μg/m3) was the highest of the 50 target VOCs, followed by m,p-xylenes (4.52 μg/m3), ethylbenzene (4.48 μg/m3), 3-methylpentane (4.40 μg/m3), and n-octane (4.26 μg/m3). Total (Σ50) VOC levels did not statistically differ between seasons, indicating that large amounts of VOCs are emitted into the atmosphere throughout the year. On the other hand, O3, NO2, and SO2 exhibited strong seasonal variation depending on the meteorological conditions and emission sources. The spatial distribution of Σ50 VOCs, NO2, and SO2 indicated that industrial complexes were major sources in Ulsan, while O3 had the opposite spatial distribution. Using a positive matrix factorization model, five major sources were identified, with industrial effects dominant. Aromatic compounds, such as m,p,o-xylenes, toluene, and 1,2,4-trimethylbenzene, significantly contributed to O3 formation. The VOC/NO2 ratio and O3 concentrations suggested that reducing VOC emissions is more effective than reducing NO2 emissions in terms of preventing the secondary formation of O3. The findings of this study allow for a better understanding of the relationship between VOCs, O3, NO2, and SO2 in industrial cities.