• 한국대기환경학회지
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• 제25권1호
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• pp.75-89
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• 2009

The purpose of this study was to identify $PM_{2.5}$ sources and to estimate their contributions to the border of Yongin-Suwon area, based on the analysis of the $PM_{2.5}$ mass concentration and the associated inorganic elements, ions and carbon components. The contribution of $PM_{2.5}$ sources were estimated by using a positive matrix factorization (PMF) model to identify air emission sources. For this study, $PM_{2.5}$ samples were collected from May, 2007 to April, 2008. The inorganic elements were analyzed by an ICP-AES. The ionic components in $PM_{2.5}$ were analyzed by an Ie. The carbon components were also analyzed by DRI/OGC analyzer. After performing PMF modeling, a total of 12 sources were identified and their contributions were quantitatively estimated. The contributions from each emission source were as follows: 11.3% from oil combustion source, 3.4% from bus/highway source, 5.8% from diesel vehicle source, 4.7% from gasoline vehicle source, 8.8% from biomass burning source, 15.1 % from secondary sulfate, 5.2% from secondary nitrate source, 13.4% from industrial related source, 4.1% from Cl-rich source, 19.6% from soil related source, 1.0% from aged sea salt, and 7.4% from coal combustion source, respectively. This study provides basic information on the major sources affecting air quality, and then it will help to effectively control $PM_{2.5}$ in this study area.

• 한국대기환경학회지
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• 제19권6호
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• pp.701-717
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• 2003

The objective of this study was to extensively estimate the air quality trends of the study area by surveying con-centration trends in months or seasons, after analyzing the mass concentration of PM-10 samples and the inorganic lements, ion, and total carbon in PM-10. Also, the study introduced to apply the PMF (Positive Matrix Factoriza-tion) model that is useful when absence of the source profile. Thus the model was thought to be suitable in Korea that often has few information about pollution sources. After obtaining results from the PMF modeling, the existing sources at the study area were qualitatively identified The PM-10 particles collected on quartz fiber filters by a PM-10 high-vol air sampler for 3 years (Mar. 1999∼Dec.2001) in Kyung Hee University. The 25 chemical species (Al, Mn, Ti, V, Cr, Fe, Ni, Cu, Zn, As, Se, Cd, Ba, Ce, Pb, Si, N $a^{#}$, N $H_4$$^{+}$, $K^{+}$, $Mg^{2+}$, $Ca^{2+}$, C $l^{[-10]}$ , N $O_3$$^{[-10]}$ , S $O_4$$^{2-}$, TC) were analyzed by ICP-AES, IC, and EA after executing proper pre - treatments of each sample filter. The PMF model was intensively applied to estimate the quantitative contribution of air pollution sources based on the chemical information (128 samples and 25 chemical species). Through a case study of the PMF modeling for the PM-10 aerosols. the total of 11 factors were determined. The multiple linear regression analysis between the observed PM-10 mass concentration and the estimated G matrix had been performed following the FPEAK test. Finally the regression analysis provided source profiles (scaled F matrix). So, 11 sources were qualitatively identified, such as secondary aerosol related source, soil related source, waste incineration source, field burning source, fossil fuel combustion source, industry related source, motor vehicle source, oil/coal combustion source, non-ferrous metal source, and aged sea- salt source, respectively.ively.y.

• 한국대기환경학회지
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• 제25권4호
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• pp.275-288
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• 2009

The Korean government strengthened the environmental polices to manage and enhance Metropolitan Area air quality, and also has enforced "Special Act on Seoul Metropolitan Air Quality Improvement (SASMAQI)" issued in Dec. 2004. Recently government expanded the Seoul Metropolitan Air Quality Management District (SMAQMD) to the outskirts satellite cities of Seoul area through the "Revised Law Draft of SASMAQI". The SMAQMD has been alloted the allowable emission loads to the local governments on the basis of the carrying $PM_{10}$ capacity. However, in order to establish the effective air quality control strategy for $PM_{10}$, it is necessary to understand the corresponding sources which have a potential to directly impact ambient $PM_{10}$ concentration. To deal with the situations, many receptor methodologies have been developed to identify the origins of pollutants and to determine the contributions of sources of interests. The objective of this study was to extensively identify $PM_{10}$ sources and to estimate their contributions at the metropolitan area. $PM_{10}$ samples were simultaneously collected at the 3 semi-industrialized local cities in the Seoul metropolitan area such as Hwasung-si, Paju-si, and Icheon-si sites from April 15 to May 31, 2007. The samples collected on the teflon membrane filter by one $PM_{10}$ cyclone sampler were analyzed for trace metals and soluble ions and samples on the quartz fiber filter by another sampler were analyzed for OC and EC. Source apportionment study was then performed by using a positive matrix factorization (PMF) receptor model. A total of 6 sources were identified and their contributions were estimated in each monitoring site. Contribution results on Hwasung, Paju, and Icheon sites were as follows: 33%, 27%, and 27% from soil source, 26%, 26%, and 21% from secondary aerosol source, 11%, 11%, and 12% from biomass burning, 12%, 6%, and 5% from sea salt, 7%, 15%, and 19% from industrial related source, and finally 11%, 15%, and 16% from mobile and oil complex source, respectively. This study provides information on the major sources affecting air quality in the receptor sites and thus it will help to manage the ambient air quality in the metropolitan area by establishing reasonable control strategies, especially for the anthropogenic emission sources.

• 한국대기환경학회지
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• 제33권4호
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• pp.319-325
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• 2017

In this study, the new particulate matter emissions considering condensable PM (CPM) of stationary pollutant sources were calculated to modify the CAPSS emissions based on only filterable PMs in Seoul and Incheon. When the new calculated emissions were compared to the existing filterable PM based emissions of local governments, different contribution patterns of emission sources were found. For example, the proportion of mobile sources was high when the filterable PM was considered; however, the contribution of non-industrial sources was dominant in Seoul when the emissions of CPM were considered. Also, the proportion of energy industrial combustion and manufacturing combustion sources was significant in Incheon when CPM emissions considered. Therefore, it seems to be much desirable to consider CPM emissions for determining adequate locations of collective energy facilities and manufacturing combustion facilities in the future. In addition, CPM should be considered to solve the dust problem nationwide. The emission analysis, diagnosis, prediction and countermeasures using CPM emissions should be appropriately performed.

• 한국대기환경학회지
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• 제19권6호
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• pp.719-731
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• 2003

In order to maintain and manage ambient air quality, it is necessary to identify sources and to apportion its sources for ambient particulate matters. The receptor methods were one of the statistical methods to achieve reasonable air pollution strategies. Also, receptor methods, a field of chemometrics, is based on manifold applied statistics and is a statistical methodology that analyzes the physicochemical properties of gaseous and particulate pollutant on various atmospheric receptors, identifies the sources of air pollutants, and quantifies the apportionment of the sources to the receptors. The objective of this study was 1) after obtaining results from the PMF modeling, the existing sources of air at the study area were qualitatively identified and the contributions of each source were quantitatively estimated as well. 2) finally efficient air pollution management and control strategies of each source were suggested. The PMF model was intensively applied to estimate the quantitative contribution of air pollution sources based on the chemical information (128 samples and 25 chemical species). Through a case study of the PMF modeling for the PM-10 aerosols, the total of 11 factors were determined. The multiple linear regression analysis between the observed PM-10 mass concentration and the estimated G matrix had been performed following the FPEAK test. Finally the regression analysis provided quantitative source contributions (scaled G matrix) and source profiles (scaled F matrix). The results of the PMF modeling showed that the sources were apportioned by secondary aerosol related source 28.8 ％, soil related source 16.8％, waste incineration source 11.5%, field burning source 11.0%, fossil fuel combustion source 10%, industry related source 8.3％, motor vehicle source 7.9%, oil/coal combustion source 4.4％, non-ferrous metal source 0.3％. and aged sea- salt source 0.2％, respectively.

• 한국환경과학회지
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• 제17권4호
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• pp.359-364
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• 2008

PM10 samples were collected from July 2007 to Oct. 2007 at Gwaebopdong(inland area) and Dongsamdong(coastal area), in Busan. This paper investigates the contribution of emission sources to PM10 mass in Busan. Source apportionment results derived from the chemical mass balance(CMB) method. A source profiles applied in this study is organized to minimize the collinearity among sources type via statistical method. Source profiles applied in this study utilized a measured value of fine particle directly sampled from metropolitan area such as Seoul and Incheon, After a CMB modeling, sulfate and nitrate related sources among those contributing to PM10 in Busan showed high contribution by 36.53% in Gwaebopdong and 42.02% in Dongsamdong.

• 한국가금학회:학술대회논문집
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• 한국가금학회 1999년도 제16차 정기총회및학술발표회
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• pp.11-33
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• 1999

This study was conducted to determine the embryonic stages for the isolation of the highest number of PGCs and to improve PGCs enrichment method. The primordial germ cells(PGCs) from different sources of chick embryos were isolated. The embryonic stage having the highest number of PGCs from each sources was selected ; 1-day-old embryos for germinal crescent (stage 6-8), 2.5-day-old embryos for blood (stage 17-18) and 5.5-day-old embryos for gonad (stage 27-28). The number of PGCs from one embryonic germinal crescent, blood and gonad was about 87$\pm$1.8, 103$\pm$4.0, and 932$\pm$10.9, respectively. The viability of PGCs after Ficoll from each sources was similar, showing approximately 70%. the PGCs enrichment method was improved using Ficoll density gradient centrifugation. After this step the purity of PGCs from germinal crescent, blood, and gonad was 45$\pm$9.10%, 85$\pm$1.18%, and 86$\pm$0.19%, respectively. Also, PGCs were picked up by mouth pipette to improve the purity. This improved method for the separation of PGCs from different sources will serve as a useful too to preserve the foundation stocks of poultry and to produce germline chimeras.

• 한국환경과학회지
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• 제27권4호
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• pp.241-250
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• 2018

The objective of this study was to estimate air quality trends in the study area by surveying monthly and seasonal concentration trends. To do this, the mass concentration of $PM_{10}$ samples and the metals, ions, and total carbon in the $PM_{10}$ were analyzed. The mean concentration of $PM_{10}$ was $33.9{\mu}g/m^3$. The composition of $PM_{10}$ was 39.2% ionic species, 5.1% metallic species, and 26.6% carbonic species (EC and OC). Ionic species, especially sulfate, ammonium, and nitrate, were the most abundant in the $PM_{10}$ and had a high correlation coefficient with $PM_{10}$. Seasonal variation of $PM_{10}$ showed a similar pattern to those of ionic and metallic species. with high concentration during the winter and spring seasons. $PM_{10}$ showed high correlation with the ionic species $NO_3{^-}$ and $NH_4{^+}$. In addition, $NH_4{^+}$ was highly correlated with $SO{_4}^{2-}$ and $NO_3{^-}$. We obtained four factors through factor analysis and determined the pollution sources using the United States Environmental Protection Agency(U.S. EPA) pollution profile. The first factor accounted for 51.1% of $PM_{10}$ from complex sources, that is, soil, motor vehicles, and secondary particles: the second factor indicated marine sources; the third factor, industry-related sources; and the last factor, heating-related sources. However, the pollution profile used in this study may be somewhat different from the actual situation in Korea because it was from US EPA. Therefore, to more accurately estimate the pollutants present, it is necessary to create a pollution profile for Korea.

• 한국환경과학회지
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• 제24권6호
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• pp.793-806
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• 2015

The purpose of this study is to find out the air flow patterns affecting the PM10 concentration in Busan and the potential sources within each trajectory pattern. The synoptic air flow trajectories are classified into four clusters by HYSPLIT model and the potential sources of PM10 are estimated by PSCF model for each cluster from 2008 to 2012. The potential source locations of PM10 are compared with the distribution of PM10 anthropogenic emissions in east Asia developed in 2006 for the NASA INTEX-B mission. The annual mean concentrations of PM10 in Busan decreased from $51ug/m^3$ in 2008 to $43ug/m^3$ in 2012. The monthly mean concentrations of PM10 were high during a spring season, March to May and low during a summer season, August and September. The cluster2 composed of the air trajectories from the eastern China to Busan through the west sea showed the highest frequency, 44 %. The cluster1 composed of the air trajectories from the inner Mongolia region to Busan through the northeast area of China showed the second high frequency, 26 %. The cluster3 and 4 were composed of the trajectories originated in the southeast sea and the east sea of Busan respectively and showed low frequencies. The concentrations of in each cluster were $47ug/m^3$ in cluster1, $56ug/m^3$ in cluster2, $42ug/m^3$ in cluster3 and $37ug/m^3$ in cluster4. From these results, it was proved that the cluster1 and 2 composed of the trajectories originated in the east and northeast area of China were the causes of high PM10 concentrations in Busan. The results of PSCF and CWT model showed that the potential sources of the high PM10 concentrations were the areas of the around Mongolia and the eastern China having high emissions of PM10 from Beijing, Hebei to Shanghai through Shandong, Jiangsu.

• Environmental Engineering Research
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• 제19권4호
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• pp.331-338
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• 2014

Descriptive statistics methods were used to study the spatiotemporal variations and sources of ambient particulate matter ($PM_{10}$) in Luzhou, China. The analyzed datasets were collected from four national air quality monitoring stations: Jiushi (S1), Xiaoshi (S2), Zhongshan (S3), Lantian (S4) over the period of 2003-2012. This city was subjected serious $PM_{10}$ pollution, and the long-term annual average $PM_{10}$ concentrations varied from 76 to $136{\mu}g/m^3$. The maximum concentration was more than 3-fold of the annual average ($40{\mu}g/m^3$) issued by EPA-China for the ambient air quality. General temporal pattern was characterized by high concentrations in winter and low concentrations in summer, and general spatial gradient was in the reduction order of S2 > S4 > S3 > S1, which were both due to different particulate contributors and special meteorological conditions. The source apportionment indicated that vehicular emissions, road dusts, coal burning and chemical dusts were the major contributors of the identified $PM_{10}$ pollution, and the vehicular emissions and the road wear re-suspended particles dominated the heavy $PM_{10}$ pollution in recent years. Two other potential sources, agricultural and celebration activities could decrease the air quality in a short term. Finally, some corresponding suggestions and measures were provided to improve the air quality.