• Journal of Korean Society for Atmospheric Environment
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• v.21 no.3
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• pp.329-341
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• 2005

The purpose of this study is to study the $PM_{2.5}$ source characteristics affecting the Seoul area using a chemical mass balance (CMB) receptor model. This study was also to evaluate the $PM_{2.5}$ source profiles, which were directly measured and developed. Asian Dust Storm usually occurred in the spring, and very high $PM_{2.5}$ concentrations were observed in the fall among the sampling periods. So the ambient data collected in the spring and fall were evaluated. The CMB model results as well as the $PM_{2.5}$ source profiles were validated using the diagnostic categories, such as: source contribution estimate, t-statistic, R-square, Chi-square, and percent of total mass explained. In the spring months, the magnitude of $PM_{2.5}$ mass contributors was in the following order: Chinese aerosol $(31.7\%)>$ secondary aerosols ($22.3\%$: ammonium sulfate $13.4\%$ and ammonium nitrate $8.9\%)>$ vehicles ($16.1\%$: gasoline vehicle $1.4\%$ and diesel vehicles $14.7\%)>$biomass burning $(15.5\%)>$ geological material $(10.5\%)$. In the fall months, the general trend of the $PM_{2.5}$ mass contributors was the following: biomass burning $(31.1\%)>$ vehicles ($26.9\%$: gasoline vehicle $5.1\%$ and diesel vehicles $21.8\%)>$ secondary aerosols ($23.0\%$: ammonium sulfate $9.1\%$ and ammonium nitrate $13.9\%)>$ Chinese aerosol $(10.7\%)$. The results show that the $PM_{2.5}$ mass in the Seoul area was mainly affected by the Chinese area.

• Particle and aerosol research
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• v.10 no.1
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• pp.9-17
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• 2014

Several studies have been carried out on the source contribution of the particulate Polycyclic Aromatic Hydrocarbons (PAHs) over Seoul by using the Chemical Mass Balance Model (CMB)(Lee and Kim, 2007; Kim et al., 2013). To confirm the validity of the modeling results, the modified model employing a photochemical loss rate along with varying residence times and the standard model that considers no loss were compared. It was found that by considering the photochemical loss rate, a better performance was obtained as compared to those obtained from the standard model in the CMB calculation. The modified model estimated higher contributions from coke oven, transportation, and biomass burning by 4 to 8%. However, the order of the relative importance of major sources was not changed, coke oven followed by transportation and biomass burning. Thus, it was concluded that the standard CMB model results are reliable for identifying the relative importance of major sources.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.5
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• pp.437-448
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• 2015

The purpose of this study is to present the source contribution of the fine particles ($PM_{2.5}$) in Chungju area using the CMB (chemical mass balance) method throughout the four seasons in Korea. The Chungju's annual average level of $PM_{2.5}$ was $48.2{\mu}g/m^3$, which exceeded two times higher than standard air quality. Among these particles, the soluble ionic compounds represent 54.2% of fine particle mass. Additionally, the OC concentration in Chungju stayed similar to other domestic cities, while the EC concentration decreased significantly compared to other domestic/international cities. The concentration of sulfur represented the highest composition (8%) among the fine particle compounds. According to the CMB results, the general trend of the $PM_{2.5}$ mass contributors was the following: secondary aerosols (50.5%: ammonium sulfate 26.5% and ammonium nitrate 24.0%) > gasoline vehicle (18.3%) > biomass burning (11.0%) > industrial boiler (6.0%) > diesel vehicles (4.4%). The contribution of the secondary aerosols was the main cause than others. This impact is assumed to be emitted from air pollutants of urban cities or neighbor countries such as China.

• Particle and aerosol research
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• v.12 no.2
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• pp.27-36
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• 2016

The PMF result was compared with the result from the Chemical Mass Balance (CMB) modelling (Lee and Kim, 2007) to estimate major source of PAHs observed at Seoul from August 2002 to December 2003. Five major sources were estimated from PMF and CMB modellings respectively. Among them three major sources (coal combustion for residential, coke oven and biomass burning) were identified at both models.

• Journal of Environmental Science International
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• v.12 no.2
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• pp.217-225
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• 2003

Samples of size-fractionated PM10 (airborne particulate matter with aerodynamic diameter less than $10\mu\textrm{m}$) were collected at an urban site in Jeju city from May to September 2002. The mass concentration and chemical composition of the samples were measured. The data sets were then applied to the CMB receptor model to estimate the source contribution of PM10 in Jeju area. The average PM10 mass concentration was 28.80$\mu\textrm{g}/m^3$ ($24.6~33.49\mu\textrm{g}/m^3$), and the FP (fine particle with aerodynamic diameter less than $2.l\mu\textrm{m}$ fraction in PM10 was approximately 8% higher than the CP (coarse particle with aerodynamic diameter greater than $2.l\mu\textrm{m}$ and less than $10\mu\textrm{m}$ fraction in PM10. The CP composition was obviously different from the FP composition, that is, the most abundant water soluble species was nitrate ion in the FP, but sulfate ion in the CP. Also sulfur was the most dominant element in the FP, however, sodium was that in the CP. From CMB receptor model results, it was found that road dust was the largest contributor to the CP mass concentration (45% of the CP) and ammonium nitrate, domestic boiler, and marine aerosol were major sources to the CP mass. However, the secondary aerosol was the most significant contributor to the FP mass concentration (45% of the FP). In this study, it was suggested that the contributions of soil dust and gasoline vehicle became very low due to collinearity with road dust and diesel vehicle, respectively.

• Journal of Korean Society for Atmospheric Environment
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• v.17 no.2
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• pp.119-131
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• 2001

A total of 328 ambient PM-10 samples was collected by a PM-10 high volume air sampler during the periods of February 1997 to February 1999 from Kyung Hee University at Suwon Campus. The samples were analyzed for their bulk chemical compositions(Cu, Fe, Pb, Zn, Al, $Na^{+}$, $NH_{4}^{+}$, $K^{+}$, $Ca^{2+]$, $Mg^{2+}$, $Cl^{-}$, $NO_{3}^{-}$, and $SO_{4}^{2-}$ by both an atomic absorption spectrophotometer and an ion chromatograph. The purpose of this study was t develop a receptor methodology for quantitative assessment of PM-10 sources. The data obtained from this study were ex-tensively examined using the target transformation factor analysis(TTFA) and the chemical mass balance (CMB). When TTFA was initially applied seasonal basis. five sources(such as automobile-related, sulfate-related, incine-ration, soil and combustion-related) were identified both during winter and fall. Since the total number and the type of sources were resolved by TTFA for the four seasons, CMB was employed to cross-check the results of TTEA. The total of six source categories identified by TTEA was intensively investigated on the basis of source profiles acquired from various source libraries established both in Korea and abroad. The results of this study showed the applicability of two popular receptor models as a new methdology for quantitative assessment PM-10 sources in Korea. Seasonally segmented data sets with the combined application of TTFA and CMB yielded a physically reasonable source apportionment result and provided a mean to increase the number of potential sources. Furthermore, this study suggested the possibility of the CMB application to ambi-ent data from Korea after identifying potential sources through traditional factor analysis.

• Journal of Environmental Impact Assessment
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• v.14 no.4
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• pp.227-235
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• 2005

Source contribution for VOCs collected in Seoul metropolitan area was conducted using PAMs (Photochemical assessment monitoring system) data and CMB(Chemical Mass Balance) model8.0, in order to estimate spatial and temporal variations of VOCs source contribution in that area, and also to compare with corresponding emission inventory. VOCs data used in model calculation were collected at 6 different sites of PAMs(Seokmori, Guwoldong, Simgokdong, Bulgwangdong, Jeongdong and Yangpyeong) and 22 out of 56 VOCs species were analyzed from June 2002 to march 2003 and used for CMB model estimation. The result showed that vehicle exhaust, coating and energy combustion were important sources of VOCs in Seoul metropolitan area, averaging 32.6%, 25.5% and 25.1%, respectively. In this study as well as other references, it was revealed that vehicle exhaust is the main contributor of urban area VOCs, but there is remarkable contrast between emission inventory and model estimation. Vehicle exhaust portion is seriously underestimated while coating is usually overestimated in emission estimates, compared to CMB results. Therefore, it is considered to assert and confirm the uncertainty of emission estimates and clarify the distinction between two other source apportionment methods.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.E1
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• pp.32-43
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• 2008

Source samples were collected to construct source profiles for 9 different source types, including soil, road dust, gasoline/diesel-powered vehicles, a municipal incinerator, industrial sources, agricultural/biomass burning, marine aerosol, and a coal-fired power plant. Seasonal profiles for 'Chinese aerosol', aerosols derived from the urban area of China, were reconstructed from seasonal $PM_{2.5}$ compositions reported in Beijing, China. Ambient $PM_{2.5}$ at a receptor site was also measured during each of the four seasons, from April 2001 to February 2002, in Seoul. The Chemical Mass Balance receptor model was applied to quantify source contributions during the study period using the estimated source profiles. Consequently, motor vehicle exhaust (33.0%), in particular 23.9% for diesel-powered vehicles, was the largest contributor affecting the $PM_{2.5}$ levels in Seoul, followed by agricultural/biomass burning (21.5%) and 'Chinese aerosol' (13.1%), indicating contributions from long-range transport. The largest contributors by season were: for spring, 'Chinese aerosol' (31.7%); for summer, motor vehicle exhaust (66.9%); and for fall and winter, agricultural/biomass burning (31.1% and 40.1%, respectively). These results show different seasonal patterns and sources affecting the $PM_{2.5}$ level in Seoul, than those previously reported for other cities in the world.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.216-225
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• 2003

Fine particles with aerodynamic diameter less than 2.5 ${\mu}m$ (PM2.5) were collected from three sites in Beijing during April, August, and November 2000 and January 2001. After chemical components in samples are analyzed, a chemical mass balance (CMB) receptor model using PARs as tracers is applied to quantify the source contributions to PM2.5 in Beijing. The results show that the major sources are coal combustion, fugitive dust, vehicle exhaust, secondary sulfate and nitrate, and organic matter while biomass burning and construction dust contribute only a small fraction. In addition, source inventory in Beijing is used to determine the primary source contributions. The two methods result in comparable results. Source apportionment at three sampling sites presents similar contributions to PM2.5 although the sites are far away from each other. However, distinct seasonal pattern is presented for the source contributions from coal combustion, fugitive dust, biomass burning, secondary sulfate and nitrate.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.3
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• pp.302-313
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• 2008

The purposes of this study are to investigate the concentration levels of fine particles, so called PM$_{2.5}$, to identify the affecting sources, and to estimate quantitatively the source contributions of PM$_{2.5}$. Ambient air sampling was seasonally carried out at two sites in Pohang(a residential and an industrial area) during the period of March to December 2003. PM$_{2.5}$ samples were collected by high volume air samplers with a PM$_{10}$ Inlet and an impactor for particle size segregation, and then determined by gravimetric method. The chemical species associated with PM$_{2.5}$ were analyzed by inductively coupled plasma spectrophotometery(ICP) and ion chromatography(IC). The results showed that the most significant season for PM$_{2.5}$ mass concentrations appeared to be spring, followed by winter, fall, and summer. The annual mean concentrations of PM$_{2.5}$ were 36.6 $\mu$g/m$^3$ in the industrial and 30.6 $\mu$g/m$^3$ in the residential area, respectively. The major components associated with PM$_{2.5}$ were the secondary aerosols such as nitrates and sulfates, which were respectively 4.2 and 8.6 $\mu$g/m$^3$ in the industrial area and 3.7 and 6.9 $\mu$g/m$^3$ in the residential area. The concentrations of chemical component in relation to natural emission sources such as Al, Ca, Mg, K were generally higher at both sampling sites than other sources. However, the concentrations of Fe, Mn, Cr in the industrial area were higher than those in the residential area. Based on the principal component analysis and stepwise multiple linear regression analysis for both areas, it was found that soil/road dust and secondary aerosols are the most significant factors affecting the variations of PM$_{2.5}$ in the ambient air of Pohang. The source apportionments of PM$_{2.5}$ were conducted by chemical mass balance(CMB) modeling. The contributions of PM$_{2.5}$ emission sources were estimated using the CMB8.0 receptor model, resulting that soil/road dust was the major contributor to PM$_{2.5}$, followed by secondary aerosols, vehicle emissions, marine aerosols, metallurgy industry. Finally, the application and its limitations of chemical mass balance modeling for PM$_{2.5}$ was discussed.