• 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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.6
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• pp.706-714
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• 2020

Currently, 90 % of the world's population breathes air with a fine dust content exceeding the World Health Organization's annual average exposure limit (10 ㎍/㎥). Global efforts have been devoted toward reducing secondary pollutants and ultra-fine dust through regulations on nitrogen oxides released over land and sea. Domestic efforts have also aimed at creating clean marine environments by reducing sulfur emissions, which are the primary cause of dust accumulation in ships, through developing and distributing environment-friendly ships. Among the technologies for reducing harmful emissions from diesel engines, electrostatic precipitator offer several advantages such as a low pressure loss, high dust collection efficiency, and NOx removal and maintenance. This study aims to increase the durability of a ship by improving equipment quality through failure mode effects analysis for the preventive maintenance of an electrostatic precipitator that was developed for reducing fine dust particles emitted from the 2,427 kW marine diesel engines in ships with a gross tonnage of 999 tons. With regard to risk priority, failure mode 241 (poor dust capture efficiency) was the highest, with an RPN of 180. It was necessary to determine the high-risk failure mode in the collecting electrode and manage it intensively. This was caused by clearance defects, owing to vibrations and consequent pin loosening. Given that pin loosening is mainly caused by vibrations generated in the hull or equipment, it is necessary to manage the position of pin loosening.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.175-184
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• 2017

Recently, PM10 is becoming a main issue in Korea because it causes a variety of diseases, such as respiratory and ophthalmologic diseases. This research studied to spatial information application cases for evaluating the feasibility of the location for PM10 observation stations utilizing Geogrphic Information System(GIS) spatial analysis. The spatial Information application cases for optimal location assessment were investigated to properly manage PM10 observation stations which are closely related with public spatial data and health care. There are 31 PM10 observation stations in Seoul city and the observed PM10 data at these stations were utilized to understand the overall assessment of PM10 stations to properly manage using interpolation methods. The estimated PM10 using Inverse Distance Weighted(IDW) and Kriging techniques and the map of PM10 concentrations of monitoring stations in Seoul city were compared with public spatial data such as precipitation, floating population, elementary school location. On the basis of yearly, seasonal and daily PM10 concentrations were used to evaluate the feasibility analysis and the location of current PM10 monitoring stations. The estimated PM10 concentrations were compared with floating population and calculated 2015 PM10 distribution data using zonal statistical methods. The national spatial data could be used to analyze the PM10 pollution distribution and additional determination of PM10 monitoring sites. It is further suggested that the spatial evaluation of national spatial data can be used to determine new location of PM10 monitoring stations.

• Journal of Plant Biotechnology
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• v.49 no.2
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• pp.145-149
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• 2022

Airborne fine dust (FD) particles smaller than 10 ㎛ in diameter (PM10) are one of the major causes of air pollution in East Asia, including Korea, and have become a major contributor to respiratory and skin problems. FD inordinately promotes the production of reactive oxygen species and inflammatory response in macrophages, leading to cell damage and death. Rosa rugosa, a deciduous shrub of the Rosa genus, has been used in traditional East Asian herbal medicine to treat various illnesses. The present study investigated the anti-inflammatory effects of R. rugosa organ extracts on PM10-stimulated RAW264.7 macrophages. Compared to non-treated RAW264.7 cells, treatment with 100 ㎍.ml^-1 PM10 resulted in increased nitric oxide (NO) production, similar to lipopolysaccharide treatment. Additionally, 100 ㎍/ml stem extract reduced NO production by more than 45% compared to mock treatment. Furthermore, PM10-induced expression of interleukin (IL)-1β, IL-6, inducible NO synthase, and cyclooxygenase-2 was significantly reduced by stem extract treatment, indicating that the anti-inflammatory effect of the stem extract is mediated by the inhibition of pro-inflammatory mediators in PM10-stimulated RAW 264.7 cells. These results indicate that the R. rugosa stem could be considered a natural remedy with a protective effect against inflammatory responses induced by harmful airborne dust.

• Journal of the Korean earth science society
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• v.34 no.3
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• pp.249-256
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• 2013

For the purpose of recording polarization of the earth's atmosphere, the entire sky was photographed using the all-sky camera when the Sun was just above the horizon. The ratio and width of polarization were defined using the photograph, and a method to measure them was developed. Time-series photography of the polarization ratio and its width enabled us to qualitatively analyze the polarization phenomena which changes depending on the weather conditions. Findings indicated that polarization was co-related with air pollutants in a meaningful way. The polarization phenomena of the Earth's atmosphere are influenced by air pollutants. The more air pollutants exist in the air, the lower polarization ratio and the bigger polarization width it has. It is suggested that air pollutants disperses more photons, which makes it possible to observe the polarization phenomena in the vast area of the sky.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.118-129
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• 2016

Many epidemiological studies, relying on administrative air pollution monitoring data, have reported the association between particulate matter ($PM_{10}$) air pollution and human health. These monitoring data were collected at a limited number of fixed sites, whereas government-generated health data are aggregated at the area level. To link these two data types for assessing health effects, it is necessary to estimate area-level concentrations of $PM_{10}$. In this study, we estimated district (Gu)-level $PM_{10}$ concentrations using a previously developed pointwise exposure prediction model for $PM_{10}$ and three types of point locations in Seoul, Korea. These points included 16,230 centroids of the largest census output residential areas, 422 community service centers, and 610 centroids on the 1km grid. After creating three types of points, we predicted $PM_{10}$ annual average concentrations at all locations and calculated Gu averages of predicted $PM_{10}$ concentrations as representative Gu-estimates. Then, we compared estimates to each other and to measurements. Prediction-based Gu-level estimates showed higher correlations with measurement-based estimates as prediction locations became more population representative ($R^2=0.06-0.59$). Among the three estimates, grid-based estimates gave lowest correlations compared to the other two(0.35-0.47). This study provides an approach for estimating area-level air pollution concentrations and assesses air pollution health effects using national-scale administrative health data.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.3
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• pp.168-176
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• 2012

A total of 48 dust samples were collected from large shopping mall parking lots in Daegu metropolitan city in March 2011. Samples were sieved through a 100 ${\mu}m$ mesh and the concentration of 14 elements have been determined using by ICP after acid extraction. Results showed that Ca, Fe, K, Mg, Mn, Na and V were affected by natural sources while Cd, Cr, Cu, Ni, Pb and Zn were affected by anthropogenic sources. The measured values were remarkably higher in components from natural sources than in components from anthropogenic sources. Anthropogenic trace element concentrations of ground roof dust were higher than those of ground and underground indoor dust. A large percentage of trace elements came from natural sources rather than anthropogenic sources. The percentage composition of chemicals of ground roof dust were higher than those of ground and underground indoor dust. This study showed that investigated parking lots were rarely contaminated with hazardous heavy metals. The heavy metal pollution of ground roof were higher than those of ground and underground indoors. The correlation analysis among trace elements suggest that components in ground roof were more highly correlated than those in ground and underground indoor. Also anthropogenic trace element levels were well correlated with parking lot age and parking density.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.919-932
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• 2019

Fine particulate matter (PM2.5) is not only affected by anthropogenic emissions, but also intensifies, migrates, decreases by hydrometeorological factors. Therefore, it is essential to understand relationships between the hydrometeorological factors and PM2.5 concentration. In Korea, PM2.5 concentration is measured at the ground observatories and estimated data are given to locations where observatories are not present. In this way, the data is not suitable to represent an area, hence it is impossible to know accurate concentration at such locations. In addition, it is hard to trace migration, intensification, reduction of PM2.5. In this study, we analyzed the relationships between hydrometeorological factors, acquired from Global Land Data Assimilation System (GLDAS), and PM2.5 by means of Bayesian Model Averaging (BMA). By BMA, we also selected factors that have meaningful relationship with the variation of PM2.5 concentration. 4 PM2.5 concentration models for different seasons were developed using those selected factors, with Aerosol Optical Depth (AOD) from MODerate resolution Imaging Spectroradiometer (MODIS). Finally, we mapped the result of the model, to show spatial distribution of PM2.5. The model correlated well with the observed PM2.5 concentration (R ~0.7; IOA ~0.78; RMSE ~7.66 ㎍/㎥). When the models were compared with the observed PM2.5 concentrations at different locations, the correlation coefficients differed (R: 0.32-0.82), although there were similarities in data distribution. The developed concentration map using the models showed its capability in representing temporal, spatial variation of PM2.5 concentration. The result of this study is expected to be able to facilitate researches that aim to analyze sources and movements of PM2.5, if the study area is extended to East Asia.

• Particle and aerosol research
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• v.7 no.2
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• pp.49-57
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• 2011

High concentration of PM10 was reported on late July, 2005 in Seoul along with high particulate ion concentrations in PM2.5. To identify the reason for the severe air pollution episode, time series analysis of the PM10 concentration in the monitoring sites over Korea, wind sector analysis, trend analysis of the ion concentrations, and air mass trajectory analysis were carried out. It was found that the episode could be classified into two separate periods; first one between July 22 and 27 and second one between July 28 and 31. During the first period, the PM10 concentrations at Seoul were in good correlation with the PM10 concentration three hours before at Chuncheon. Trajectory analysis showed that air mass moved from north and turned to west at Kangwon province to Seoul. The concentrations of PM10 mass and ionic species were lower than the second period. During the second period, air mass moved from northern China to Seoul directly and the PM10 concentrations all over the mid-Korean peninsula showed the same trend. These observations suggest that the air pollution during the second period was affected by direct transport of air pollutants from northern China. Thus, the air quality at Seoul during both periods were influenced by long-range transport from outside rather than by local sources, but with different transport patterns.

• Journal of Environmental Impact Assessment
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• v.28 no.2
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• pp.101-112
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• 2019

Over the last few years, air pollution ($PM_{10}$, $PM_{2.5}$) in the Seoul metropolitan area (SMA) has emerged as one of the most concerned and threatening environmental issues among the residents. It brings about various harmful effects on human health, as well as ecosystem and industrial activities. Governments and individuals pay various costs to mitigate the level of air pollutants. This study aims to empirically find the willingness to pays (WTP) among the parents from different socio-cultural groups - international and domestic groups to mitigate air pollution ($PM_{10}$, $PM_{2.5}$) in their residential area. Contingent Valuation Methods (CVM) is used with employing single-bounded dichotomous choice technique to elicit the respondent's WTP. Using tobit (censored regression) and probit models, the monthly mean WTP of the pooled sample for green electricity which contributes to improve air quality in the region was estimated as 3,993 KRW (3.58 USD). However, the mean WTP between the international group and domestic group through a sub-sample analysis shows broad distinction as 3,325KRW (2.98 USD) and 4,449 KRW (3.98 USD) respectively. This is because that socio-cultural characteristics of each group such as socio-economic status, personal experience, trust in institutions and worldview are differently associated with the WTP. Based on the results, the society needs to raise awareness of lay people to find a strong linkage between the current PM issue and green electricity. Also, it needs to improve trust in the government's pollution abatement policy to mobilize more assertive participation of the people from different socio-cultural background.