• Proceedings of the Korea Air Pollution Research Association Conference
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• 2006.10a
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• pp.213-214
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• 2006

• Environmental Engineering Research
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• v.25 no.2
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• pp.147-162
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• 2020

The main objective of this study is to estimate the levels of pollution to which the community is presently exposed and to model the regimes of local air quality. Diurnal, daily, and monthly variations of NO, NO₂, SO₂, and O₃ were thoroughly investigated in three areas; namely, residential, industrial, and terminal in Ras Al-Khafji. There is obvious diurnal variation in the concentration of these pollutants that clearly follows the diurnal variation of atmospheric temperature and main anthropogenic and industrial activities. Correlation analysis showed that meteorological conditions play a vital role in shaping the pattern and transportation of air pollutants and photochemical processes affecting O₃ formation and destruction. Bivariate polar plots, an effective graphical tool that utilizes air pollutant concentrations' dependence on wind speed and wind direction, were used to identify prevailing emission sources. Non-buoyant ground-level sources like domestic heating and street transport emissions, various industrial stacks, and airport-related activities were considered dominant emission sources in observatory sites. This study offers valuable and detailed information on the status of air quality, which has considerable, quantifiable, and important public health benefits.

• Journal of Korean Society for Atmospheric Environment
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• v.25 no.2
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• pp.154-166
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• 2009

In this study, 1-hour integrated $PM_{2.5}$ mass and chemical composition concentrations were monitored at the St. Louis-Midwest Supersite in Illinois. Time-resolved samples were collected one week in each of June 2001 (22 June to 28 June), November 2001 (7 November to 13 November), and March 2002 (19 March to 25 March). A total of 427 samples were collected by CAMM (continuous ambient mass monitor) and 15 compounds were analyzed by AAS, PILS (particle-into-liquid sampler), and TOT (thermal optical transmittance) method. PMF was applied to identify the sources and apportion the $PM_{2.5}$ mass to each source for highly time resolved data. In addition, the nonparametric regression (NPR) was applied to identify the predominant directions of local sources relative to wind direction. Also, this study performed compare the NPR analysis and location of actual local point sources at the St. Louis area. The PMF modeling identified nine sources and the average mass was apportioned to gasoline vehicle, road dust, zinc smelter, copper production, secondary sulfate, diesel emission, secondary nitrate, iron+steel, and lead smelter, respectively. These results suggested that this study results will be help for $PM_{2.5}$ source apportionment studies at similar metropolitan area, establish $PM_{2.5}$ standard, and establish effective emissions reduction strategies in Korea.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.2
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• pp.105-117
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• 2015

Sources related to road dust is one of the biggest sources, which is responsible for a large portion of emission. In particular, PM2.5 is a potential cause for respiratory diseases, thus it should be managed and a mitigation plan using results of statistical apportionment modeling such as chemical mass balance needs to be established. Recently, identifying sources of PM2.5 and analyzing the contribution of the road dust through a contribution assessment is required. Therefore, this study provides the chemical source profiles of PM2.5 using IC, GC/MS, OCEC, and XRF for both paved sidewalk and paved roadway collected at seven different sampling sites. As a result, for paved sidewalk, $NH{_4}^+$ (70%), $NO{_3}^-$ (12%), $PO{_4}^-$ (9%), and $SO{_4}^{2-}$ (9%) have been analyzed in PM2.5 mass. Major molecular marker such as Si has been indicated as $12.0{\pm}3.4%$ and $13.6{\pm}6.9%$ for paved sidewalk and roadway, respectively. PAHs such as Fluoranthene, Pyrene, Chrysene, and 1,3,5-Triphenylbenzene are suggested as molecular markers for road dust.

• 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.8 no.4
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• pp.229-239
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• 1992

A receptor model application was performed by using a chemical mass balance (CMB) model to identify and apportion the specific source of airborne organic pollutants, particularly polynuclear aromatic hydrocarbons (PAHs). Source profiles of PAHs produced from the combustion of fossil fuels for CMB modeling were prepared by measuring them in emission gases. The emission sources which were examineed for the development of PAH source profiles are a coal-fired furnace using Yontan, a bunker-C iol heating boiler, and gasoline-and diesel engine automobiles. The ambient concentrations of PAHs were determined at four sites in Daejon city in 1991 with a seasonal variation. Wintertime air samples contained more extractable organic matter than summertime samples. The results of CMB modeling were various depending on the sampling sites and seasons, but the emission from bunker-C oil heating boliers was the predominant factor to affect local air quality throughout the year.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.6
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• pp.508-519
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• 2015

The objective of this study was to quantitatively estimate $PM_{2.5}$ source contribution in Gyeongsan. Ambient $PM_{2.5}$ samples have been collected on zefluor, quartz and nylasorb filter by $PM_{2.5}$ samplers of cyclone method from September 2010 to December 2012. Collected samples were analyzed for determining 17 inorganic elements, 8 ions, and 8 carbon components after pretreatment. Based on these chemical information, the PMF model was applied to estimate the quantitative contribution of air pollution sources. The results of the PMF modeling showed that the sources were apportioned by biomass burning source (15.5%), secondary sulfate source (16.0%), industry source (10.4%), soil source (7.0%), gasoline source (9.1%), incinerator source (10.4%), diesel emission source (11.0%), and secondary nitrate source (20.6%), respectively. To analyze local source impacts from various wind directions, the CPF analysis were performed using source contribution results with the wind direction values measured at the site.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.6
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• pp.711-722
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• 2011

This study is aimed to estimate the $PM_{2.5}$ source apportionment at Seoul intensive monitoring site located in Seoul metropolitan area. Time-resolved chemical compositions of $PM_{2.5}$ are measured in real time using ambient ion monitor, semi-continuous carbon monitor, and on-line XRF at Seoul intensive monitoring site in 2010. The mass concentration of $PM_{2.5}$ was simultaneously monitored with eight ionic species (${SO_4}^{2-}$, $NO_3{^-}$, $Cl^-$, $NH_4{^+}$, $Na^+$, $K^+$, $Mg^{2+}$, $Ca^{2+}$), two carbonaceous species (OC and EC), and fourteen elements (Si, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Zn, As, Se, Pb) in 1-hr interval. The data sets were then analyzed using EPA PMF version 3 to identify sources and contributions to $PM_{2.5}$ mass. EPA PMF modeling identified eight PM2.5 sources, including soil dust, secondary sulfate, secondary nitrate, motor vehicle, coal combustion, oil combustion, biomass burning, and municipal incineration. This study found that the average $PM_{2.5}$ mass was apportioned to anthropogenic sources such as motor vehicle, fuel combustion, and biomass burning (61%) and secondary aerosols, including sulfate and nitrate (38%).

• Journal of the Korean GEO-environmental Society
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• v.20 no.1
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• pp.5-11
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• 2019

The main objective of this study was to analyse polycyclic aromatic hydrocarbons in surface sediments obtained from near Nakdong estuary, and to estimate ecological risks of PAHs using PAHs concentrations. The main constituents of sediments were $SiO_2$, $Al_2O_3$, CaO, $Fe_2O_3$, and ignition loss of sediments ranged from 2.97% and 8.39%. Total concentrations of PAHs ranged from $128.4ng\;g^{-1}$ and $507.4ng\;g^{-1}$, and the major PAHs were 2 ring and 4 ring aromatic hydrocarbons. Each concentrations of PAHs are all below effect range low, which indicated that each PAHs in 8 studying sites show low ecological risk. From M-ERM-Q analyses, M-ERM-Q values of 8 studying sites are below 0.1 indicating low ecological risk. From source apportionment analyses, PAHs come from grass, wood, charcoal combustion for N-1 and N-7, petroleum combustion for N-5 and N-6, petroleum pollution for N-2, N-3, N-4, N-8.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2006.04a
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• pp.174-176
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• 2006