• Journal of Environmental Science International
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• v.24 no.11
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• pp.1525-1540
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• 2015

In order to clarify the contribution rate of PM concentration due to regional emission distribution, Brute force analysis were carried out using numerical estimated PM data from WRF-CMAQ. The emission from Kyeongki region including Seoul metropolitan is the largest contribution of PM concentration than that from other regions except for emission of trans-country and source itself. Contribution rate of self emission is also the largest at Kyeongki region and its rate reach on over 95 %. And the rate at Gangwon region also higher than any region due to synoptic wind pattern. Due to synoptic wind direction at high PM episode, pollutants at downwind area along from west to east and from north to south tends to mix intensively and its composition is also complicated. Although the uncertainty of initial concentration of PM, the contribution of regional PM concentration tend to depend on the meteorological condition including intensity of synoptic and mesoscale wind and PM emission pattern over upwind region.

• Journal of Environmental Health Sciences
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• v.30 no.3
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• pp.221-229
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• 2004

We estimated decreasing rate of indoor air pollutants which are PM10 and $NO_2$ by the air cleaner in indoor environment. This study respectively examined concentration of PM10 and $NO_2$ two times in 34 sites located in Seoul and Kyung-gi Do from April to September in 2003. Sectional period was respectively divided for operating the air cleaner and non-operating the air cleaner. Moreover, questionnaire was executed to grasp physical characteristic of objective building and residential characteristic of residents by using method of self-entry. There was a trend that concentration of PM10 and $NO_2$ separated number of residents during operating period respectively decreased among indoor air. According to the existence of smoker in indoor, both concentration of PM10 and $NO_2$ during operating period decreased in each case, and according to existence of pets, both cases decreased concentration of pollutants by operating the air cleaner. We used Monte-Calro simulation to remove uncertainty and identify efficiency of eliminated pollutants such as PM10 and $NO_2$ by the air cleaner. Average efficiency of removal for PM10 and $NO_2$ were 61.84${\pm}$23.04% and 48.67${\pm}$18.03% respectively.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.11
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• pp.1111-1115
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• 2008

The characterization of PM$_{2.5}$ and PM$_{10}$ concentration is considered by analysis of ionic and heavy metal component to measured suspended particle at atmosphere in Hoseo university of Asan area. The variation of concentration is studied at the periods of asian dust occured. In asian dust, the PM$_{2.5}$ ratio is decreased from 79.7% to 40.1%, whereas the size-classified mean concentration of suspended particle is increased largely. It is found that the PM$_{2.5}$ ratio is decreased relatively because the coarse particle is increased largely according to the analysis of the mass concentration to divide the fine and coarse particle on 2.1 $\mu$m basis. It is observed that the Ca$^{2+}$ion is about 40 magnifications and Na$^+$, SO$_4{^{2-}}$ ion is increased in sequence in coarse particle, whereas the variation of ionic concentration is slightly increased in the fine particle. Furthermore, Mn, Fe, Zn, and Al are increased in sequence as the result of heavy metal component analysis, and Al is shown the most increased as mass concentration.

• 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 $PM_{2.5}$

• Journal of Environmental Science International
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• v.14 no.5
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• pp.463-471
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• 2005

This study is designed to investigate the characteristics of $PM_{10}$ concentration and the chemical composition of heavy metallic components in the $PM_{10}$ sampled in western Busan from March to May, 2003. $PM_{10}$measurement was done during springtime of 2003, totaling 29 days: 9 days in March, 10 days in April and 10 days in May. With a sampling time of 24 hours, it started 9:00 AM on that day and ended 9:00 AM the next day. The mean contribution ratio of soil during springtime was $10.3\%$. Al had a significant correlation with Ca, Fe, Mg and Si and little correlation with Na, Ni and Zn.

• Journal of Environmental Science International
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• v.31 no.12
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• pp.999-1012
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• 2022

To investigate the reason for the spatial difference in PM_2.5 (Particulate Matter, < 2.5 ㎛) concentration despite a similar synoptic pattern, a synoptic analysis was performed. The data used for this study were the daily average PM_2.5 concentration and meteorological data observed from 2016 to 2020 in Busan and Seoul metropolitan areas. Synoptic pressure patterns associated with high PM_2.5 concentration episodes (greater than 35 ㎍/m³) were analyzed using K-means cluster analysis, based on the 900 hPa geopotential height of NCEP (National Centers for Environmental Prediction) FNL (Final analysis) data. The analysis identified three sub-groups related to high concentrations occurring only in Busan and Seoul metropolitan areas. Although the synoptic patterns of high PM_2.5 concentration episodes that occur independently in Busan and Seoul metropolitan areas were similar, there was a difference in the intensity of pressure gradient and its direction, which tends to be an important factor determining the movement time of pollutants. The spatial difference in PM_2.5 concentration in the Korean Peninsula is due to the difference and direction of the atmospheric pressure gradient that develops from southwest to northeast direction.

• Journal of Environmental Science International
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• v.31 no.12
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• pp.1069-1078
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• 2022

This study investigated the weather conditions, fine particle concentration, and ion components in PM_2.5 when two cold fronts passed through Busan in succession on February 1 and 2, 2021. A analysis of the surface weather chart, AWS, and backward trajectory revealed that the first cold front passed through the Busan at 0900 LST on February 1, 2021, with the second cold front arriving at 0100 LST on February 2, 2021. According to the PM₁₀ concentration of the KMA, the timing of the cold front passage had a close relationship with the occurrence of the highest concentration of fine particles. The transport time of the cold front from Baengnyeongdo to Mt. Gudeok was approximately 11 hours . The PM₁₀ and PM_2.5 concentrations in Busan started to increase after the first cold front had passed, and the maximum concentration occurred two hours after the second cold front passed. The SO₄^2-, NO₃^-, and NH₄⁺ concentration in PM_2.5 started to increase from 1100 to 1200 LST on February 1, after the first cold front passed, and peaked at 0100 LST to 0300 LST on February 2. However, the highest Ca²⁺ concentration was recorded 2-3 hours after the second cold front had passed.

• Journal of odor and indoor environment
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• v.16 no.3
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• pp.277-286
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• 2017

The objectives of this study were to investigate the effects of $PM_{10}$ and $O_3$ concentration on the symptoms of allergic diseases. The questionnaire was used to determine whether or not symptoms of allergic diseases were present from September to October 2012. The air pollution concentration data used was the corresponding point CEM (continuous emission monitoring) data. The average concentration of $PM_{10}$ was $56.09{\mu}g/m^3$ in the control area, and the concentration in the exposed area was $40.44{\mu}g/m^3$. In the two areas, concentration of $O_3$ was 28.73 ppb and 28.74 ppb, respectively. The total average concentrations of $PM_{10}$ and $O_3$ were $45.66{\mu}g/m^3$ and 28.73 ppb in the Gwangyang area. The rate of asthma diagnosis was higher in the control area (9.6%) than in the exposed area (4.1%), but the rate of allergy eye disease was higher in the exposed area (23.9%) than in the control area (16.5%). There was a significant difference in the symptoms of some allergic diseases when the relative concentration of $PM_{10}$ and $O_3$ were high and low.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.1
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• pp.89-96
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• 2020

Adverse impact of Particulate Matters(PM10, PM2.5; PMs) significantly affects daily lives. Major countermeasures for reducing concentration of PMs were focused on emission source without considering spatial difference of PMs concentration. Thus, this study analyzed spatial·temporal distribution of PMs with observation data as well as potential contributing factors on PMs concentration. The annual average concentration of PMs have been decreased while the particulate matter warnings and alerts were significantly increased in 2018. The average concentration of PMs in spring and winter was higher than the other seasons. Also, the spatial distribution of PMs were also showed seasonality while concentration of PMs were higher in Seoul-metropolitan areas in all seasons. Climate variables, emission source, spatial structure and potential PM sinks were selected major factors which could affects on ambient concentrations of PMs. This paper suggest that countermeasures for mitigating PM concentration should consider characteristics of area. Climatic variables(temperature, pressure, wind speed etc.) affects concentrations of PMs. The effects of spatial structure of cities(terrain, ventilation corridor) and biological sinks(green infrastructure, urban forests) on concentration of PMs should be analyzed in further studies. Also, seasonality of PMs concentration should be considered for establishing effective countermeasures to reduce ambient PMs concentration.

• Journal of Environmental Science International
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• v.23 no.3
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• pp.447-457
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• 2014

The number concentrations, the mass concentrations and the elemental concentrations of $PM_{10}$ have measured at Gosan site in Jeju, Korea, from March 2010 to December 2010. And the correlation and the factor analysis for the number, the mass and the elemental concentrations of $PM_{10}$ are performed to identify their relationships and sources. The average $PM_{10}$ number concentration is observed $246\;particles/cm^3$($35.7{\sim}1,017\;particles/cm^3$) and the average $PM_{10}$ mass concentration is shown $50.1{\mu}g/m^3$($16.7{\sim}441.4{\mu}g/m^3$) during this experimental period. The number concentrations are significantly decreased with increasing particle size, hence the concentrations for the smaller particles less than $2.5{\mu}m$($PM_{2.5}$) are contributed 99.6% to the total $PM_{10}$ number concentrations. The highest concentration of the 20 elements in $PM_{10}$ determined in this study is shown by S with a mean value of $1,497ng/m^3$ and the lowest concentration of them is found by Cd with a mean value of $0.57ng/m^3$. The elements in $PM_{10}$ are evidently classified into two group based on their concentrations: In group 1, including S>Na>Al>Fe>Ca>Mg>K, the elemental mean concentrations are higher than several hundred $ng/m^3$, on the other hand, the concentrations are lower than several ten $ng/m^3$ in group 2, including Zn>Mn>Ni>Ti>Cr>Co>Cu>Mo>Sr>Ba>V>Cd. The size-separated number concentrations are shown positively correlated with the mass concentrations in overall size ranges, although their correlation coefficients, which are monotonously increased or decreased with size range, are not high. The concentrations of the elements in group 1 are shown highly correlated with the mass concentrations, but the concentrations in group 2 are shown hardly correlated with the mass concentrations. The elements originated from natural sources have been predominantly related to the mass concentrations while the elements from anthropogenic sources have mainly affected on the number concentrations of $PM_{10}$.