• Journal of Korean Society for Atmospheric Environment
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• v.28 no.3
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• pp.348-356
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• 2012

It is very important to investigate air pollutants and emissions emitted from open burning in order to control nonpoint sources effectively. In this study, we utilized incineration simulator proposed by U.S. EPA and investigated concentrations of TSP, PM10, PM2.5 from woods and household wastes burning to calculate emission factors and build emission inventories. The results of experiment with 15 kg of woods and 3 kg of household wastes using the incineration simulator were as follows: in case of woods burning, TSP concentration was $66.4mg/m^3$, PM10 concentration was $28.4mg/m^3$, PM2.5 concentration was $17.9mg/m^3$, respectively; in case of household wastes burning, TSP concentration was $118.4mg/m^3$, PM10 concentration was $66.8mg/m^3$, PM2.5 concentration was $55.2mg/m^3$, respectively. Concentrations from household burning, as stated above, were higher than those from woods burning. Emission factors (EFs) for woods and household wastes burning were calculated as 2.45 and 6.75 g/kg for TSP, 0.86 and 5.45 g/kg for PM10, 0.78 and 4.81 g/kg for PM2.5, respectively. EFs of TSP, PM10, PM2.5 calculated from household wastes burning were higher than those of woods burning. When we added PM emissions from woods burning and household wastes burning to Korean National Emission Inventory named as Clean Air Policy Support System (CAPSS), CAPSS annual emissions of TSP, PM10, PM2.5 were increased by 0.08~0.26% (An increase rate for TSP, PM10, PM2.5 were 0.08~0.10%, 0.16~0.20% and 0.18~0.26%, respectively). Note that we assumed that the 1% of household wastes is emitted by open burning.

• Journal of Environmental Health Sciences
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• v.34 no.4
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• pp.300-310
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• 2008

In order to further determine the mass concentration and ion composition of size-segregated particulate matter (PM) during the non-Asian dust storm of spring, $PM_{2.5}$ (fine particle), $PM_{10-2.5}$ (coarse particle), and $PM_{over-10}$ (PM with an aerodynamic diameter larger than $10{\mu}m$) were collected using a MCI (multi-nozzle cascade impactor) sampler of a three-stage filter pack in the spring season of 2007 in the Iksan area. During the sampling period from 5 April to 21 April, a total of 34 samples for size-segregated PM were collected, and then measured for PM mass concentrations by gravimetric measurements and for water-soluble inorganic ion species by using ion chromatography. Average mass concentrations of $PM_{2.5}$, $PM_{10-2.5}$, $PM_{over-10}$ were $35.4{\pm}11.5{\mu}g/m^3$, $13.3{\pm}5.5{\mu}g/m^3$ and $9.5{\pm}4.7{\mu}g/m^3$, respectively. On average, $PM_{2.5}$ accounted for 74% of $PM_{10}$. Compared with the literature from other areas in Korea, the measured concentration of $PM_{2.5}$ were relatively high. Water-soluble inorganic ion fractions in $PM_{2.5}$, $PM_{10-2.5}$, and $PM_{over-10}$ were found to be 47.8%, 28.5%, and 14.7%, respectively. Among the water-soluble inorganic ion species, $SO_4^{2-}$, $NO_3^-$ and $NH_4^+$ were the main components in $PM_{2.5}$, while $NO_3^-$ dominantly existed in both $PM_{10-2.5}$ and $PM_{over-10}$. Non-seasalt $SO_4^{2-}$ (nss-$SO_4^{2-}$ and $NO_3^-$ were found to mainly exist as the neutralized chemical components of $(NH_4)_2SO_4$ and $NH_4NO_3$ in fine particles.

• Journal of Environmental Health Sciences
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• v.46 no.3
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• pp.276-284
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• 2020

Objectives: This study was conducted to identify the effects of PM₁₀ and PM_2.5 on hospital visits in the Incheon area over the period of 2016-2018. Methods: We applied correlation analysis and Poisson regression to perform the analysis using cardiovascular disease and respiratory disease data from the National Health Insurance Service and the daily average PM₁₀ and PM_2.5 from the Korea Environment Corporation adjusting for time lag. Results: When the daily average PM₁₀ concentration increased by 10 ㎍/㎥, the number of cardiovascular disease patients were 1.002 times higher (95% CI [Confidence Interval]; 1.000-1004) in Ganghwa County. As the daily average PM_2.5 concentration increased by 10 ㎍/㎥, the number of cardiovascular disease patients were 1.012 times higher (95% CI; 1.008-1.016) in Ganghwa County. As the daily average PM₁₀ concentration increased by 10 ㎍/㎥, the respiratory disease patients were 1.003 times (95% CI; 1.002-1.004) higher in Gyeyang and Michuhol Counties. As the PM_2.5 concentration increased by 10 ㎍/㎥, the respiratory disease patients were 1.003 times higher (95% CI; 1.002-1.005) in Bupyeong County. Conclusions: In some parts of the Incheon area there was a correlation between the number of patients with respiratory and cardiovascular conditions and the concentration of PM₁₀ and PM_2.5.

• Journal of Environmental Health Sciences
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• v.34 no.1
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• pp.34-41
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• 2008

The objective of this study is to provide the research data on the actual concentrations of $PM_{10},\;PM_{2.5},\;PM_1\;and\;CO_2$ in Seoul subway carriages. Mean concentrations of $PM_{10},\;PM_{2.5}\;and\;PM_1,\;and\;CO_2$ in subway carriages were investigated at levels of $215.1{\pm}101.4{\mu}g/m^3,\;86.9{\pm}38.6{\mu}g/m^3,\;27.0{\pm}11.4{\mu}g/m^3,\;and\;1,588{\pm}714ppm$, respectively. The mean concentrations in subway carriages were higher when the train ran on an underground track rather than on an above ground track. The measured concentration of particulate matter varied with the time of day and was highest in the morning, followed by noon and evening while the $CO_2$ concentration was highest in the morning, followed by evening and noon. In relation to correlation among the pollutants: the correlation between $PM_{10}\;and\;PM_{2.5}$ was 0.92, and that between $PM_{2.5}\;and\;PM_1$ was 0.94. The inclusion rate of $PM_{2.5}\;to\;PM_{10}$ was $41{\pm}7%$ and that of $PM_1\;to\;PM_{2.5}\;was\;32{\pm}4%$. In addition, the $CO_2$ concentration had a positive relation with the number of people in a carriage, whereas the concentration of $PM_{10}$ had negative correlation to the number of people. In relation to these two pollutants we calculated using a regression equation (34.06+0.04$CO_2$(ppm)-0.09 PM10$({\mu}g/m^3)$($R^2$=0.30, p<0.01, n=707), that a maximum number of 61 persons would ensure that each pollutant is maintained below the criteria level, applicable to subway stations.

• 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 Impact Assessment
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• v.16 no.5
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• pp.327-340
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• 2007

The $PM_{10}$ and $PM_{2.5}$ aerosols were collected at Busan from March to May, 2005, and the concentrations of some metallic elements were analysed to study their characteristics. The mean concentration of $PM_{10}$ was $66.5{\pm}23.0{\mu}g/m^3$ with a range of 22.2 to $118.1{\mu}g/m^3$. The mean concentration of $PM_{2.5}$ was $46.1{\pm}17.2{\mu}g/m^3$ with a range of 9.7 to $83.3{\mu}g/m^3$. The ratio of $PM_{2.5}/PM_{10}$ was 0.69 at Busan. The distribution of metallic elements for $PM_{10}$ and $PM_{2.5}$ were Cd${\ldots}$ ${\ldots}$ $PM_{10}$ were $94.9{\mu}g/m^3$ and $63.7{\mu}g/m^3$, respectively. And The mean mass concentrations of Asian dust and non Asian dust in $PM_{2.5}$ were $56.9{\mu}g/m^3$ and $45.1{\mu}g/m^3$, respectively. The mean values of crustal enrichment factors for five elements (Cd, Cu, Pb, V and Zn) were all higher than 10, possibly suggesting the influence of anthropogenic sources. The soil contribution ratios for $PM_{10}$ and $PM_{2.5}$ were 20.5% and 19.4, respectively.

• Journal of Environmental Science International
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• v.30 no.6
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• pp.465-474
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• 2021

This research investigated the characteristics of fine particle concentration and ionic elements of PM_2.5 during sea breeze occurrences during summertime in Busan. The PM₁₀ and PM_2.5 concentrations of summertime sea breeze occurrence days in Busan were 46.5 ㎍/m³ and 34.9 ㎍/m³, respectively. The PM₁₀ and PM_2.5 concentrations of summertime non-sea breeze occurrence days in Busan were 25.3 ㎍/m³ and 14.3 ㎍/m³, respectively. The PM_2.5/PM₁₀ ratios of sea breeze occurrence days and non-sea breeze occurrence days were 0.74 and 0.55, respectively. The SO₄^2-, NH₄⁺, and NO₃^- concentrations in PM_2.5 of sea breeze occurrence days were 9.20 ㎍/m³, 4.26 ㎍/m³, and 3.18 ㎍/m³ respectively. The sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR) of sea breeze occurrence days were 0.33 and 0.05, respectively. These results indicated that understanding the fine particle concentration and ionic elements of PM_2.5 during sea breeze summertime conditions can provide insights useful for establishing a control strategy of urban air quality.

• Asian Journal of Atmospheric Environment
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• v.9 no.4
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• pp.280-287
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• 2015

The high time-resolution monitoring data are essential to estimate rapid changes in chemical compositions, concentrations, formation mechanisms, and likely sources of atmospheric particulate matter (PM). In this study, $PM_{2.5}$ sulfate, $PM_{2.5}$, $PM_{10}$, and the number concentration of size-resolved PMs were monitored in Fukuoka, Japan by good time-resolved methods during the springtime. The highest monthly average $PM_{2.5}$ sulfate was found in May ($8.85{\mu}g\;m^{-3}$), followed by April ($8.36{\mu}g\;m^{-3}$), March ($8.13{\mu}g\;m^{-3}$), and June ($7.22{\mu}g\;m^{-3}$). The cases exceed the Japanese central government's safety standard for $PM_{2.5}$ ($35{\mu}g\;m^{-3}$) reached 10.11% during four months campaign. The fraction of $PM_{2.5}$ sulfate to $PM_{2.5}$ varied from 12.05% to 68.11% with average value of 35.49% throughout the entire period of monitoring. This high proportion of sulfate in $PM_{2.5}$ is an obvious characteristic of the ambient $PM_{2.5}$ in Fukuoka during the springtime. However, the average fraction of $PM_{2.5}$ sulfate to $PM_{2.5}$ in three rain events occurred during our intensive campaign fell right down to 15.53%. Unusually high $PM_{2.5}$ sulfate (> $30{\mu}g\;m^{-3}$) marked on three days were probably affected by the air parcels coming from the Chinese continent, the natural sulfur in the remote marine atmosphere, and a large number of ships sailing on the nearby sea. The theoretical number concentration of $(NH_4)_2SO_4$ in $PM_{0.5-0.3}$ was originally calculated and then compared to $PM_{2.5}$ sulfate. A close resemblance between the diurnal variations of the theoretically calculated number concentration of $(NH_4)_2SO_4$ in $PM_{0.5-0.3}$ and $PM_{2.5}$ sulfate concentration indicates that the secondary formed $(NH_4)_2SO_4$ was the primary form of sulfate in $PM_{2.5}$ during our monitoring period.

• Particle and aerosol research
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• v.19 no.4
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• pp.111-128
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• 2023

Chungcheongnam-do has various emission sources, including large-scale facilities such as power plants, steel and petrochemical industry complexes, which can lead to the severe PM pollution. Here, we measured concentrations of PM₁₀, PM_2.5, and its metallic elements at a suburban site in Taean, Chungcheongnam-do from September 2017 to June 2022. During the measurement period, the average concentrations of PM₁₀ and PM_2.5 were 58.6 ㎍/m³ (9.6~379.0 ㎍/m³) and 35.0 ㎍/m³ (6.1~132.2 ㎍/m³), respectively. The concentration of PM₁₀ and PM_2.5 showed typical seasonal variation, with higher concentration in winter and lower concentration in summer. When high concentrations of PM_2.5 occurred, particulary in winter, the fraction of Zn and Pb components considerably increased, indicating a significant contribution of Zn and Pb to high-PM_2.5 concentration. In addition, Zn and Pb exhibited the highest correlation coefficient among all other metallic elements of PM_2.5. A backward trajectory cluster analysis and CPF model were performed to examine the origin of PM_2.5. The high concentration of PM_2.5 was primarily influenced by emissions from industrial complexes located in the northeast and northwest areas.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.635-646
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• 2018

This study sought to identify the characteristics of seasonal concentration differences of particulate matter influenced by land cover types associated with particulate matter emission and reductions, namely forest and urbanized regions. PM10 and PM2.5 was measured with quantitative concentration in 2016 on 23 urban air monitoring stations in Seoul, classified the stations into 3 groups based on the ratio of urbanized and forest land covers within a range of 3km around station, and analysed the differences in particulate matter concentration by season. The center values for the urbanized and forest land covers by group were 53.4% and 34.6% in Group A, 61.8% and 16.5% in Group B, and 76.3% and 6.7% in Group C. The group-specific concentration of PM10 and PM2.5 by season indicated that the concentration of Group A, with high ratio of forests, was the lowest in all seasons, and the concentration of Group C, with high ratio of urbanized regions, had the highest concentration from spring to autumn. These inter-group differences were statistically significant. The concentration of Group C was lower than Group B in the winter; however, the differences between Groups B to C in the winter were not statistically significant. Group A concentration compared to the high-concentration groups by season was lower by 8.5%, 11.2%, 8.0%, 6.8% for PM10 in the order of spring, summer, autumn and winter, and 3.5%, 10.0%, 4.1% and 3.3% for PM2.5. The inter-group concentration differences for both PM10 and PM2.5 were the highest in the summer and grew smaller in the winter, this was thought to be because the forests' ability to reduce particulate matter emissions was the most pronounced during the summer and the least pronounced during the winter. The influence of urbanized areas on particulate matter concentration was lower compared to the influence of forests. This study provided evidence that the particulate matter concentration was lower for regions with higher ratios of forests, and subsequent studies are required to identify the role of green space to manage particulate matter concentration in cities.