• Journal of Korean Society for Atmospheric Environment
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• v.33 no.6
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• pp.593-604
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• 2017

The suspended particulate matter(PM) was measured in subway tunnel of Seoul Line 1 to 9 in order to evaluate the pollution degree and characteristics of the PM in the subway tunnel. Also, to analyze the effect of outdoor aerosol concentration on the PM concentration of subway tunnels, the ambient PM concentration around the subway station was extracted by spatial analysis using $PM_{10}$ data of Seoul air pollution monitoring network. Finally, in order to understand pollution pattern in the Seoul subway tunnels, cluster analysis was performed based on input data set such as PM levels in tunnel, tunnel depth, length, curvature radius, outdoor ambient air pollution levels and so on. The average concentration of $PM_{10}$, $PM_{2.5}$, and $PM_1$ on subway tunnels were $98.0{\pm}37.4$, $78.4{\pm}28.7$, and $56.9{\pm}19.2{\mu}g/m^3$, respectively. As a result of the cluster analysis, tunnels from Seoul subway Line-1 to Line-9 were classified into five classes, and the concentrations and physical properties of the tunnels were compared. This study can provide a method to reduce PM concentration in tunnel for each pollution pattern and provide basic information about air quality control in Seoul subway tunnel.

• Particle and aerosol research
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• v.10 no.1
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• pp.1-8
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• 2014

In this study, we have developed a real-time monitoring device for measuring $PM_{10/2.5/1}$ of ambient aerosol particles. The real-time PM (Particulate Matter) monitor was based on the light scattering method and had 16 channels in particle size. The laboratory and field tests were carried out to evaluate the performance of the PM monitor developed. Arizona Road Dust particles ranging from diameter of 0.1 to $20{\mu}m$ were generated as test particles in the laboratory test. The field test was carried out at the Seoul Meteorological Observatory. We can obtain the particle size and number concentration (particle size distribution) only from the real-time PM monitor developed. Therefore, the average density of aerosol particles was used to obtain the PM data from the particle size distribution. The $PM_{10/2.5/1}$ results of the PM monitor were compared with the data of the Grimm Dust Monitor (Model 1.108) and a beta ray gauge (Thermo Fisher Scientific). As a result, it was shown that the $PM_{10/2.5/1}$ results obtained by the real-time PM monitor agreed well with the data of the reference devices, and overall, the real-time PM monitor could be used as a PM monitoring device for real-time monitoring of the ambient particles.

• Journal of Environmental Health Sciences
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• v.31 no.4 s.85
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• pp.301-308
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• 2005

The purpose of this study was to characterize mass concentration of $PM_{10}\;to,\;PM_{2.5}$ and metallic composition using Minivol Portable Sampler from May 2003 to May 2004 in metropolitan city, Seoul. Annual average concentration of $PM_{10}$ were $57.67({\pm}28.20)\;{\mu}g/m^3\;and\;PM_{2.5},\;were\;42.06({\pm}20.23)\;{\mu}g/m^3$. The concentration was the highest in winter because persistent thermal inversion and in spring, particulate matter concentration was high because of yellow-sand events. The average $PM_{2.5}/PM_{10}$ ratio was 0.73. This indicated $PM_{2.5}$ fraction played a significant role in air pollution. The atmospheric metallic elements in the $PM_{10},PM_{2.5}$ came different emission sources such as soil, traffic, industry and resuspended particles. The results showed that average $PM_{10}$ composition order as Fe>Zn>Pb>Cu>Mn. The metallic elements Zn and Fe were the largest composition in the $PM_{2.5}$

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.66-74
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• 2004

DPF technology has been considered as one of the most effective methods for reducing diesel particulate emission. PSA Peugeot Citroen introduced the DPF equipped diesel passenger car, Peugeot 607 HDI Sedan, in 2000 for the first time in the world, in which SiC filter, an oxidation catalyst, cerium based fuel born catalyst and post-injection technology were used for PM regeneration. In the present study, the characteristics of the Peugeot 607 DPF system were studied on chassis dynamometer and real road driving conditions. The change of emissions and fuel economy during 80,000km operation were also tested. Additionally, ash contents accumulated in the DPF filter was analyzed and particle size distributions was investigated after running of 80,000km.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.18 no.4
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• pp.262-270
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• 2008

This study was conducted to measure concentrations of particulate matter ($PM_{10}$, $PM_{2.5}$) and endotoxin in thirty public facilities (7 elderly-care facilities, 4 hypermarkets, 4 university hospitals, 7 child-care facilities, 4 subway stations and 4 bus terminals) from September 2004 to February 2007 in Seoul and Gyeonggi-do province. $PM_{10}$ or $PM_{2.5}$ was measured with glass fiber filter and mini volume air sampler for 6 to 8 hours in indoor and outdoor of the facilities and expressed as ${\mu}g/m^3$. After weighing the filter, endotoxin was analyzed by Limulus Ameobocyte Lysate method ($EU/m^3$). $PM_{10}$ in indoor air was higher (GM and GSD was 78.00 and $1.92\;{\mu}g/m^3$, respectively) than the outdoor air (GM and GSD was 60.70 and $2.23\;{\mu}g/m^3$, respectively, I/O=1.28). All measurements was not exceeded the national maintenance standard. Elderly-care and child-care facilities showed relatively higher concentrations ($83.27\;{\mu}g/m^3$ and $81.75\;{\mu}g/m^3$; I/O=2.01 and 1.19, respectively) than hypermarkets or university hospitals. The highest PM2.5 was seen in child-care facilities ($62.15\;{\mu}g/m^3$, I/O=2.42). The I/O of the endotoxin in the PM10 and the $PM_{2.5}$ was exceeded 1.0 (1.37 and 1.57, respectively). Indoor $PM_{10}$ was affected by user/day and humidity, and endotoxin in the PM10 was affected by temperature. In conclusion, elderly- and child-care facilities are high priority facilities to be improved indoor air quality.

• Nutrition Research and Practice
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• v.15 no.6
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• pp.686-702
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• 2021

BACKGROUND/OBJECTIVES: Schisandrae Fructus, the fruit of Schisandra chinensis Baill., has traditionally been used as a medicinal herb for the treatment of various diseases, and has proven its various pharmacological effects, including anti-inflammatory and antioxidant activities. In this study, we investigated the inhibitory effect of Schisandrae Fructus ethanol extract (SF) on inflammatory and oxidative stress in particulate matter 2.5 (PM2.5)-treated RAW 264.7 macrophages. MATERIALS/METHODS: To investigate the anti-inflammatory and antioxidant effects of SF in PM2.5-stimulated RAW 264.7 cells, the levels of pro-inflammatory mediator such as nitric oxide (NO) and prostaglandin E₂ (PGE₂), cytokines including interleukin (IL)-6 and IL-1β, and reactive oxygen species (ROS) were measured. To elucidate the mechanism underlying the effect of SF, the expression of genes involved in the generation of inflammatory factors was also investigated. We further evaluated the anti-inflammatory and antioxidant efficacy of SF against PM2.5 in the zebrafish model. RESULTS: The results indicated that SF treatment significantly inhibited the PM2.5-induced release of NO and PGE₂, which was associated with decreased inducible NO synthase and cyclooxygenase-2 expression. SF also attenuated the PM2.5-induced expression of IL-6 and IL-1β, reducing their extracellular secretion. Moreover, SF suppressed the PM2.5-mediated translocation of nuclear factor-kappa B (NF-κB) from the cytosol into nuclei and the degradation of inhibitor IκB-α, indicating that SF exhibited anti-inflammatory effects by inhibiting the NF-κB signaling pathway. In addition, SF abolished PM2.5-induced generation of ROS, similar to the pretreatment of a ROS scavenger, but not by an inhibitor of NF-κB activity. Furthermore, SF showed strong protective effects against NO and ROS production in PM2.5-treated zebrafish larvae. CONCLUSIONS: Our findings suggest that SF exerts anti-inflammatory and antioxidant effects against PM2.5 through ROS-dependent down-regulating the NF-κB signaling pathway, and that SF can be a potential functional substance to prevent PM2.5-mediated inflammatory and oxidative damage.

• Journal of Life Science
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• v.32 no.8
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• pp.647-658
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• 2022

Particulate matter (PM) is known to be involved in the onset and progression of various diseases by promoting oxidative and inflammatory reactions as air pollutants containing various small particles that are harmful. In this study, the protective efficacy of herbal medicines was evaluated in human corneal epithelial cells (hCECs) to select natural products that can protect the eye, the primary organ directly exposed to external pollutants from PM. As a result, five candid ate herbal medicines [Cheonmundong, Asparagus Rhizome; Seokchangpo, Aciru Gramineri Rhizoma; Hwangryeon, Coptidis Rhizoma; Gamgug, Chrysanthemi Indici Flos; and Geumjanhwa (Marigold flower petals)] which showed inhibitory efficacy on PM_2.5-induced cytotoxicity, were selected from among 12 candidate herbal medicines. To evaluate the antioxidant activity of these candidate substances, the reactive oxygen species (ROS) scavenging ability was investigated, and it was found that the extracts of Seokchangpo, Cheonmundong and Hwangryeon showed a significant inhibitory effect on PM_2.5-induced ROS production, which was correlated with the preservation of mitochondrial activity. In addition, it was confirmed that they could block DNA damage caused by PM_2.5 through analysis of 8-hydroxy-2'-deoxyguanosine generation and phosphorylated-H2A histone family member X (γ- H2AX) expression. Furthermore, the increase in inflammasome activity and inflammatory response in PM_2.5-treated hCECs was also canceled in the presence of these extracts. Although additional studies are needed, the results of this study will be used as primary data to find novel natural compounds that protect hCECs from PM.

• Journal of Environmental Health Sciences
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• v.42 no.5
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• pp.324-332
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• 2016

Objectives: The annual average of PM10 in Seoul was $45{\mu}/m^3$, which surpasses the WHO annual guidelines ($20{\mu}/m^3$). Most previous analyses of the effects of PM exposure have been retrospective studies using single hospital data, and fewer studies have attempted to address the relationship of PM10 and hospital costs. This study was conducted to investigate the effects of the concentration of PM10 on hospital visits, admissions and hospital costs in patients with respiratory and cardiovascular diseases. Methods: Medical data from the National Health Insurance Service and the monthly average of PM10 from National Institute of Environmental Research were used to identify the effects of PM10 on hospital visits, admissions and hospital costs. We applied Poisson regression and linear regression to perform the analysis. Results: The relative risks for admissions per $10{\mu}/m^3$ increase in PM10 were 23.11%, 10.2% and 6.9% increases for acute bronchiolitis, asthma and bronchitis, respectively. The relative risk for hospital visits per $10{\mu}/m^3$ increase in PM10 were 10.4%, 6.7% and 5.9% for chronic obstructive pulmonary disease, asthma and chronic sinusitis, respectively. For cardiovascular disease, the relative risk for admissions per $10{\mu}/m^3$ increase in PM10 were 2.2% and 2.1% increases in angina and acute myocardial infarction, respectively. A $10{\mu}/m^3$ increase in the monthly average of PM10 corresponded to 170,723,000 won (95% CI: 125,587,000-215,860,000 won), 123,636,000 won (95% CI: 47,784,000-199,487,000 won) and 78,571,000 won (95% CI: 29,062,000-128,081,000 won) increases in hospital costs for asthma, acute tonsillitis and chronic sinusitis, respectively. Conclusion: Hospital admissions for respiratory and cardiovascular disease were associated with PM10 levels. PM10 exposure is also associated with increased costs for respiratory diseases.

• Environmental Analysis Health and Toxicology
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• v.29
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• pp.5.1-5.7
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• 2014

Objectives Numerous studies have revealed the adverse health effects of acute and chronic exposure to particulate matter less than $10{\mu}m$ in aerodynamic diameter ($PM_{10}$). The aim of the present study was to examine the spatial distribution of $PM_{10}$ concentrations and cardiovascular mortality and to investigate the spatial correlation between $PM_{10}$ and cardiovascular mortality using spatial scan statistic (SaTScan) and a regression model. Methods From 2008 to 2010, the spatial distribution of $PM_{10}$ in the Seoul metropolitan area was examined via kriging. In addition, a group of cardiovascular mortality cases was analyzed using SaTScan-based cluster exploration. Geographically weighted regression (GWR) was applied to investigate the correlation between $PM_{10}$ concentrations and cardiovascular mortality. Results An examination of the regional distribution of the cardiovascular mortality was higher in provincial districts (gu) belonging to Incheon and the northern part of Gyeonggi-do than in other regions. In a comparison of $PM_{10}$ concentrations and mortality cluster (MC) regions, all those belonging to MC 1 and MC 2 were found to belong to particulate matter (PM) 1 and PM 2 with high concentrations of air pollutants. In addition, the GWR showed that $PM_{10}$ has a statistically significant relation to cardiovascular mortality. Conclusions To investigate the relation between air pollution and health impact, spatial analyses can be utilized based on kriging, cluster exploration, and GWR for a more systematic and quantitative analysis. It has been proven that cardiovascular mortality is spatially related to the concentration of $PM_{10}$.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.251-259
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• 2024

Fine particulate matter, especially PM2.5 with a diameter of less than 2.5 micrometers, poses significant health and economic risks. This study focuses on the Seoul region of South Korea, aiming to analyze PM2.5 data and trends from 2017 to 2022 and develop a mid-term prediction model for PM2.5 concentrations. Utilizing collected and produced air quality and weather data, reanalysis data, and numerical model prediction data, this research proposes an ensemble evaluation method capable of adapting to trend changes. The ensemble method proposed in this study demonstrated superior performance in predicting PM2.5 concentrations, outperforming existing models by an average F1 Score of approximately 42.16% in 2019, 58.92% in 2021, and 34.79% in 2022 for future 3 to 6-day predictions. The model maintains performance under changing environmental conditions, offering stable predictions and presenting a mid-term prediction model that extends beyond the capabilities of existing deep learning-based short-term PM2.5 forecasts.