• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1733-1741
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• 2020

This study analyzed the effect of meteorological factors on the concentration of PM10 (particulate matter 10) in the atmosphere and the variation of rainwater quality using multivariate statistical analysis. The concentration of PM10 in the atmosphere was continuously measured during eleven precipitation events with a custom-built PM sensor node. A total of 183 rainwater samples were analyzed for pH, EC (electrical conductivity), and water-soluble cations (Na+, Mg2+, K+, Ca2+, NH4+) and anions (Cl-, NO3-, SO42-). The data has been analyzed using two multivariate statistical techniques (principal component analysis, PCA, and Pearson correlation analysis) to identify relationships among PM10 concentrations in the atmosphere, meteorological factors, and rainwater quality factors. When the rainfall intensity was relatively strong (> 5 mm/h, rainfall type 1), the PM10 concentration in the atmosphere showed a negative correlation (r = -0.55, p < 0.05) with cumulative rainfall. The PM10 concentration increased the concentration of water-soluble ions (r = 0.25) and EC (r = 0.4), and decreased the pH (r = -0.7) of rainwater samples. However, for rainfall type 2 (< 5 mm/h), there was no negative correlation between the PM10 concentration in the atmosphere and cumulative rainfall and no statistically significant correlation between the PM10 concentration in the atmosphere and rainwater quality.

• Asian Journal of Atmospheric Environment
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• v.10 no.4
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• pp.217-225
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• 2016

The purpose of the study was to initially investigate the concentration patterns of $PM_1$, $PM_{2.5}$ and $PM_{10}$ in the Seoul subway lines, and then to figure out the PM behaviors of internal and external sources inside subway tunnels. The PMs were monitored by a light scattering real-time monitor during winter (Jan. 8-26 in 2015) and summer (July 2-Aug. 7 in 2015) in tunnel air, in passenger cabin air, and in the ambient air. The daily average $PM_{10}$, $PM_{2.5}$, and $PM_1$ concentrations on these object lines were $101.3{\pm}38.4$, $81.5{\pm}30.2$, and $59.7{\pm}19.9{\mu}g/m^3$, respectively. On an average, the PM concentration was about 1.2 times higher in winter than in summer and about 1.5 times higher in underground tunnel sections than in ground sections. In this study, we also calculated extensively the average PM mass ratios for $PM_{2.5}/PM_{10}$, $PM_1/PM_{10}$, and $PM_1/PM_{2.5}$; for example, the range of $PM_{2.5}/PM_{10}$ ratio in tunnel air was 0.82-0.86 in underground tunnel air, while that was 0.48-0.68 in outdoor ground air. The ratio was much higher in tunnel air than in outdoor air and was always higher in summer than in winter in case of outdoor air. It seemed from the results that the in/out air quality as well as a proper amount of subway ventilation must be significant influence factors in terms of fine PM management and control for the tunnel air quality improvement.

• 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 $PM_{2.5}$

• Ecology and Resilient Infrastructure
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• v.9 no.1
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• pp.36-58
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• 2022

In this study, the weather conditions corresponding to the increase in the environmental concentration of fine dust (PM₁₀) and ultrafine dust (PM_2.5) from 2001 to 2019 in Jeju and Seogwipo cities were analyzed. The increase in the levels of PM₁₀ and PM_2.5 was observed in the order: spring > winter > autumn > summer. In both cities, PM₁₀ and PM_2.5 levels increased more frequently during the day in spring and summer and at night in autumn and winter, with PM_2.5 showing a greater increase in concentration than PM₁₀. The air temperature and wind speed corresponding with increased levels of PM₁₀ were higher than their respective seasonal averages in spring and winter, but lower in summer and autumn. Relative humidity was lower than the seasonal average during all seasons. The air temperature variation corresponding with increased levels of PM_2.5 showed the same seasonal trend as that observed for PM₁₀. The relative humidity was higher than the respective seasonal averages in spring and summer, and lower in winter. The wind speed was lower than the seasonal average in both the cities. When the PM₁₀ and PM_2.5 levels increased, the wind direction was from the north and the west during the day and varied according to the season at night. The rate of the increase in the PM₁₀ concentration was the highest in both cities at the wind speed of 1.6 - 3.4 ms^-1 during the day and night except during night in the summer. The highest concentration of PM_2.5 was observed with the wind speed range of 1.6 - 3.4 ms^-1 in Jeju, and 0.3 - 1.6 ms^-1 in Seogwipo. The results of this study applied to urban and landscape planning will aid in the formulation of strategies to reduce the adverse effects of fine particular matter.

• Journal of Environmental Health Sciences
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• v.31 no.1
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• pp.39-46
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• 2005

This study was performed to investigate the concentration of $PM_{10}$ and $PM_{2.5}$ in inside train and platform of subway 1, 2, 4 and 5 in Seoul, KOREA. $PM_{10}$, $PM_{2.5}$, temperature, humidity and carbon dioxide were monitored using Portable Aerosol Spectrometer at afternoon (between 13:00 and 16:00). The concentrations of $PM_{10}$ and $PM_{2.5}$ in inside train were monitored to be higher than those measured in platform. In addition, $PM_{10}$ concentration in both platform and inside train were found to be greatly higher than range of from 35 ${\mu}g/m^3$ to 81${\mu}g/m^3$ in ambient air reported by Ministry of Environment. This study found that there were many inside train in subway 1, 2, 4 line where exceeded 150 ${\mu}g/m^3$ of Korean PM10 standard. The average percentage that exceeded PM10 standard was 83.3% in line 1, 37.9% in line 2 and 63.1% in line 4, respectively. In particular, most of inside train in subway line 1 were over PM10 limit. PM2.5 concentration ranged from 77.7 ${\mu}g/m^3$ to 158.2 ${\mu}g/m^3$, which were found to be greatly higher than ambient air PM2.5 standard promulgated by United States Environmental Protection Agency (US-EPA) (24 hours arithmatic mean : 65 ${\mu}g/m^3$, year average : 15 ${\mu}g/m^3$). The percentage of $PM_{2.5}$ in $PM_{10}$ was 86.2% in platform, 81.7% in inside train, 80.2% in underground and 90.2% in ground. These results indicated that fine particles ($PM_{2.5}$) accounted for most of $PM_{10}$.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.123-138
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• 2018

To sustainably monitor air pollution in Seoul, the number of Air Pollution Monitoring Station has been gradually increased by Korea's Ministry of Environment. Although particulate matters(PM), one of the pollutants measured at the stations, have an significant influence on human body, the concentration of PM in Korea came in second among 35 OECD member countries. In this study, using the data of PM concentration from the stations, distribution maps of PM10 and PM2.5 concentrations over Seoul were generated, and spatial factors potentially related to PM distribution were investigated. Based on a circumscribed hexagon about a circle in radius of 500 meters created as a basic unit, Seoul was sectionalized and PM concentration map was generated using the interpolation technique of 'inverse distance weighting'. The distributions of PM concentrations were investigated with commuting time by administrative district and the outcome was related with land-use type and volume of traffic. Results from this analysis indicated distribution pattern of PM10 concentration was different from that of PM2.5 by administrative district and time. The distribution of PM concentration was strongly related to not only the size of business and trafficked areas among the land-use type, but also the existence of urban green. Further analysis of the relationship between the PM concentration and detailed land-use and urban green maps can be helpful to identify spatial factors which have an impact on the PM concentration on the regional scale.

• Journal of Environmental Health Sciences
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• v.34 no.2
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• pp.137-147
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• 2008

This study evaluated the effects of the human activity and outdoor air on concentrations of size-selective particulate matters (PM) by conducting a realtime measurement in classrooms and on roofs at 4 elementary schools, 3 middle schools and 3 high schools in Incheon City. PM concentrations featured repetitive pattern of increasing during break time (including lunch hours) and cleaning time while decreasing during class hours. This trend was more prominent with inhalable PM and PM10 than fine PMs (PM2.5, PM1.0). The indoor/outdoor (I/O) ratio of inhalable PM and PM10 exceeded 1 while that of fine PMs was close to or below 1. The PM2.5 (out)/PM10 (out) ratio stood at 0.59 (${\pm}0.16$) and the PM2.5 (in)/PM10 (in) ratio was 0.29 (${\pm}0.09$), suggesting that occupant activity had a greater effect upon coarse particles (PM10-PM2.5) than upon fine particles (PM2.5, PM1.0). The correlations between the indoor and the outdoor PM concentrations showed a stronger positive correlation for fine particles than that of coarse particles. The linear regression analysis of PM concentrations indoor and outdoor indicated a higher determinant coefficient ($r^2>0.9$), and consistency for fine particles than in case of coarse particles. In conclusion, the results of this study suggest that the indoor coarse particle concentration is more attributed to occupant activity and the indoor fine particle concentration is more influenced by outdoor air pollution.

• Journal of Environmental Health Sciences
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• v.31 no.5 s.86
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• pp.379-386
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• 2005

[ $PM_{10},\;PM_{2.5},\;CO_2\;and\;CO$ ] in driver cabins of subway line from 5 to 8 were monitored from 07:00 through 21:00 (or 19:30 or 20:00) on May. Driver cabin of subway line 7 showed the highest $PM_{10},\;PM_{2.5},\;CO_2\;and\;CO$ concentrations. General Linear Model indicated that subway line, subway location (ground and underground track) and running time (morning and afternoon) significantly influenced the concentrations of $PM_{10},\;PM_{2.5},\;CO_2\;and\;CO$ (p=0.000). Daily profile of $PM_{10},\;PM_{2.5},\;CO_2\;and\;CO$, expressed as an 30 minutes average, showed similar variation pattern over day period. These concentrations showed the highest concentrations between 07:00 and 09:00 of rush hour, slightly dropped and again rose slightly after 18:00. In correlation analysis, significant relations among $PM_{10},\;PM_{2.5},\;CO_2\;and\;CO$ were detected (p<0.01). In particular, correlation coefficient between $PM_{10}\;and\;PM_{2.5}$ was highly significant (r=0.884). Regression analysis also concluded that $PM_{10}$ concentration significantly explained 71.4% of variation of $PM_{2.5}$ concentration (p=0.000, $R^2=0.714$). Correlations by CO with $PM_{10}\;and\;PM_{2.5}$ were 0.451 and 0.520, which were higher than those by $CO_2$. Further study is needed to examine the sources of $PM_{2.5}$ and CO in subway and to compare pollutants concentration among subway lines.

• Journal of Environmental Health Sciences
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• v.20 no.4
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• pp.80-89
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• 1994

It was reported that BCF's (Bioconcentration Factor) on Carbaryl and BPMC in concentration of 1, 2, 5 and 10 ppm, previously. Carassius auratus(goldfish) was chosen as test organism. Carbamates in fish and in test water were extracted with n-hexane and acetonitrile. GC-ECD was used to detecting and quantitating of Carbamates. Also, partition coefficients were determined with Stir flask method. To evaluate environmental toxicological profiles of tested compounds, experimental concentration were 0.05, 0.1 and 0.5 ppm in contrast to previous report. It was considered that higher BCFs of BPMC due to its higher partition coefficient compared to Carbaryl. The obtained results were as follows: 1. It was possible to determine short term BCF of Carbaryl and BPMC through relatively simple procedure in environmental concentrations. 2. BCF$_3$ of Carbaryl in concentration of 0.05, 0.1 and 0.5 ppm were 4.666 $\pm$ 0.002, 3.622 $\pm$ 0.004, 1.200 $\pm$ 0.002 and BCF$_5$ were 3.897 $\pm$ 0.005, 4.219 $\pm$ 0.017 and 1.186 $\pm$ 0.054, respectively. In the case of BPMC in same condition, BCF$_3$ were 4.077 $\pm$ 0.014, 4.900 $\pm$ 0.005, 4.750 $\pm$ 0.009 and BCF$_5$ were 3.465 $\pm$ 0.010, 4.612 $\pm$ 0.011 and 4.075 $\pm$ 0.012, respectively. 3. Carbaryl concentration in fish extract was increased as increasing test concentration, but BCF were decreased as prolonging test period, especially dropped at 0.5 ppm. 4. In the case of BPMC, BCF were decreased as increasing test concentration, but the concentration in fish extract of 3-day test group was slightly higher than that of 5-day test group. 5. Higher BPMC concentration in fish extract was due to its higher partition coefficient to compared with Carbaryl. 6. Determined logP of Carbaryl and BPMC were 2.200 and 3.180. But the calculated BCF using suggested equation was so different that predict BCF. It is suggested that BCF's of Carbamates have to be determined by experiment.

• Journal of Nutrition and Health
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• v.28 no.9
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• pp.855-861
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• 1995

The longitudinal change of vitamin A concentration and secretion in transitional milk of 32 Korean lactating wormen and vitamin A intake of infants were studied 7, 10 and 15 days postpartum. Retinol concentration of the milk averaged 93.6$\pm$47.1, 80.1$\pm$41.6 and 66.7$\pm$33.5$\mu\textrm{g}$/100ml at 7, 10 and 15 days postpartum respectively and showed decreasing trend in total mothers. $\beta$-carotene concentration showed similar decreasing trend averaged 13.4$\pm$10.6, 8.2$\pm$4.6 and 5.3$\pm$3.4$\mu\textrm{g}$/100ml respectively. Vitamin A concentration decreased with the respective amount of 94.9$\pm$47.1, 80.5$\pm$41.5 and 67.3$\pm$33.0 R.E../100ml during the lactation. The average vitamin A secretion in the milk of all mothers appeared 410.0 R.E/day. Vitamin A secretion of multiparae (450.1 R.E./100ml) appeared not significantly higher than those of primiparae(370.0 R.E./100ml). The average vitamin A intake of infants in the milk averaged 333.7 R.E./day and was 95.3% of RDA for infants. Vitamin A intake per body weight of infants in the milk averaged 110.6, 91.9 and 79.2 R.E./kg/day respectively.