• Asian Journal of Atmospheric Environment
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• v.8 no.3
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• pp.126-139
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• 2014

In order to estimate the influence of sources on $PM_{2.5}$ in the industrial area of Japan, we carried out a source analysis using chemical component data of $PM_{2.5}$. $PM_{2.5}$ samples were collected intermittently at an industrial area in Japan from July 2010 to November 2012. Water soluble ions ($Cl^-$, $NO_3{^-}$, $SO{_4}^{2-}$, $Na^+$,$NH_4{^+}$, $K^+$, $Mg^{2+}$, $Ca^{2+}$), elements (Al, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Cd, Sb, Pb), and carbonaceous species (OC, EC) of the $PM_{2.5}$ (a total of 198 samples) were analyzed. Positive Matrix Factorization (PMF) model was applied to the data of those chemical components to identify the source of $PM_{2.5}$. At this observation site, nine factors were extracted. The major contributors of $PM_{2.5}$ were secondary sulfate 1, in which loading factors of $SO{_4}^{2-}$ and $NH_4{^+}$ were large (percentage source contribution: 20.9%), traffic, in which loading factors of OC (organic carbon) and EC (elemental carbon) were large (20.8%), secondary sulfate 2, in which loading factors of K and $SO{_4}^{2-}$ were large (8.0%), steel mills (7.8%), secondary chloride and nitrate (7.0%), soil (5.0%), heavy oil combustion (3.8%), sea salt (3.8%), and coal combustion (2.3%). The conditional probability function (CPF) and the potential source contribution function (PSCF) were carried out to examine the influence of a regional source and a broad-based source, respectively. CPF results supported local source influences such as steel mills, sea salt, traffic, coal combustion, and heavy oil combustion. PSCF results suggested that ships in the East China Sea, an industrial area of the east coastal region of China, and an active volcano in the Kyushu region of Japan were potential regional sources of secondary sulfate 1. Secondary sulfate 2 was affected by the burning of biomass fields and by coal combustion in Chinese urban areas such as Beijing, Hebei, and western Inner Mongolia. Source characterization using continuous data from one site showed a potential source representing fossil fuel combustion is affected both by regional and broad-based sources.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.4
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• pp.439-454
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• 2008

The purpose of this study was to extensively identify $PM_{10}$ sources and to estimate their contributions to the study area, based on the analysis of the $PM_{10}$ mass concentration and the associated inorganic elements, ions, and total carbon. The contribution of $PM_{10}$ sources was estimated by applying a receptor method because identifying air emission sources were effective way to control the ambient air quality. $PM_{10}$ particles were collected from May to November 2007 in the Yongin-Suwon bordering area. $PM_{10}$ samples were collected on quartz filters by a $PM_{10}$ high-volume air sampler. The inorganic elements (Al, Mn, V, Cr, Fe, Ni, Cu, Zn, Cd, Pb, Si, Ba, Ti and Ag) were analyzed by an ICP-AES after proper pre-treatments of each sample. The ionic components of these $PM_{10}$ samples ($Cl^_$, $NO_3^-$, $SO_4^{2-}$, $Na^+$, $NH_4^+$, $K^+$, $Ca^{2+}$, and $Mg^{2+}$) were analyzed by an IC. The carbon components (OC1, OC2, OC3, OC4, OP, EC1, EC2 and EC3) were also analyzed by DRI/OGC analyzer. Source apportionment of $PM_{10}$ was performed using a positive matrix factorization (PMF) model. After performing PMF modeling, a total of 8 sources were identified and their contribution were estimated. Contributions from each emission source were as follows: 13.8% from oil combustion and industrial related source, 25.4% from soil source, 22.1% from secondary sulfate, 12.3% from secondary nitrate, 17.7% from auto emission including diesel (12.1%) and gasoline (5.6%), 3.1% from waste incineration and 5.6% from Na-rich source. This study provides information on the major sources affecting air quality in the receptor site, and therefore it will help us maintain and manage the ambient air quality in the Yongin-Suwon bordering area by establishing reliable control strategies for the related sources.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.3
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• pp.223-238
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• 2015

The $PM_{2.1}$ was collected by LVCI (low volume cascade impactor) during Group-A Period (September 1990 to December 2012) and the $PM_{2.5}$ was collected by HVAS (high volume air sampler) during Group-B Period (September 2009 to April 2012) at Kyung Hee University, Global Campus located on the boarder of Yongin and Suwon. The 8 water-soluble ions ($Na^+$, $NH_4{^+}$, $K^+$, $Mg^{2+}$, $Ca^{2+}$, $Cl^-$, $ NO_3{^-}$, and $SO_4{^{2-}}$) were analyzed by IC, and the 14 inorganic elements (Al, Mn, Si, Fe, Cu, Pb, Cr, Ni, V, Cd, Ba, Zn, Ti, Ag) were analyzed by XRF and ICP-AES after performing proper pre-treatments of each sample filter. The average total mass fractions of $SO_4{^{2-}}$, $NO_3{^-}$, and $NH_4{^+}$+ to $PM_{2.5}$ samples during Group-B Period were 0.39 in normal days, 0.44 in haze days, and 0.27 in Asian dust days, respectively; however, the average total mass fractions of Al, Fe, and Si to $PM_{2.5}$ mass were 0.043 in normal days, 0.021 in haze days, and 0.036 in Asian dust days, respectively. Especially the concentration of Pb was significantly decreased during Group-B Period rather than during Group-A Period, while Cr and Ni was increased during Group-B Period. In this study, we intensively compared the annual and seasonal patterns of major chemical species among normal days, haze days, and Asian dust days. Further we developed mass fraction profiles by collecting episode cases of haze days and Asian dust days, which were consisting of 22 chemical species. Those profiles are considered to be useful when applying various receptor models and establishing air quality management plans near future.

• Journal of Environmental Science International
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• v.18 no.6
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• pp.645-654
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• 2009

Lab-scale Electrodialysis(ED) system with different membranes combined with before or after pyroma process were carried out to remove nitrate from two pickling acid wastewater containing high concentrations of $NO_3\;^-$(${\approx}$150,000 mg/L) and F($({\approx}$ 160,000 mg/L) and some heavy metals(Fe, Ti, and Cr). The ED system before Pyroma process(Sample A) was not successful in $NO_3\;^-$ removal due to cation membrane fouling by the heavy metals, whereas, in the ED system after Pyroma process(Sample B), about 98% of nitrate was removed because of relatively low $NO_3\;^-$ concentration (about 30,000 mg/L) and no heavy metals. Mono-selective membranes(CIMS/ACS) in ED system have no selectivity for nitrate compared to divalent-selective membranes(CMX/AMX). The operation time for nitrate removal time decreased with increasing the applied voltage from 10V to 15V with no difference in the nitrate removal rate between both voltages. Nitrate adsorption of a strong-base anion exchange resin of $Cl\;^-$ type was also conducted. The Freundlich model($R^2$ > 0.996) was fitted better than Langmuir mode($R^2$ > 0.984) to the adsorption data. The maximum adsorption capacity ($Q^0$) was 492 mg/g for Sample A and 111 mg/g for Sample B due to the difference in initial nitrate concentrations between the two wastewater samples. In the regeneration of ion exchange resins, the nitrate removal rate in the pickling acid wastewater decreased as the adsorption step was repeated because certain amount of adsorbed $NO_3\;^-$ remained in the resins in spite of several desorption steps for regeneration. In conclusion, the optimum system configuration to treat pickling acid wastewater from stainless-steel industry is the multi-processes of the Pyroma-Electrodialysis-Ion exchange.

• Journal of Environmental Science International
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• v.26 no.11
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• pp.1297-1306
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• 2017

This study identified physical characteristics and aerosol particle sources of $PM_{10}$ and $PM_{2.5}$ in the industrial complex of Busan Metropolitan City, Korea. Samples of $PM_{10}$, $PM_{2.5}$ and also soil, were collected in several areas during the year of 2012 to investigate elemental composition. A URG cyclone sampler was used for collection. The samples were collected according to each experimental condition, and the analysis method of SEM-EDX was used to determine the concentration of each metallic element. The comparative analysis indicated that their mass concentration ranged from 1% to 3%. The elements in the industrial region that were above 10% were Si, Al, Fe, and Ca. Those below 5% were Na, Mg, and S. The remaining elements (1% of total mass) consisted of elements such as Ni, Co, Br and Pb. Finally, a statistical tool was applied to the elemental results to identify each source for the industrial region. From a principal components analysis (SPSS, Ver 20.0) performed to analyze the possible sources of $PM_{10}$ in the industrial region, five main factors were determined. Factor 1 (Si, Al), which accounted for 15.8% of the total variance, was mostly affected by soil and dust from manufacturing facilities nearby, Factors 2 (Cu, Ni), 3 (Zn, Pb), and 4 (Mn, Fe), which also accounted for some of variance, were mainly related to iron, non-ferrous metals, and other industrial manufacturing sources. Also, five factors determined to access possible sources of $PM_{2.5}$, Factor 1 (Na, S), accounted for 13.5% of the total variance and was affected by sea-salt particles and fuel incineration sources, and Factors 2 (Ti, Mn), 3 (Pb, Cl), 4 (K, Al) also explained significant proportions of the variance. Theses factors mean that the $PM_{2.5}$ emission sources may be considered as sources of incineration, and metals, and non-ferrous manufacturing industries.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.1
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• pp.74-85
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• 2013

Since the underground transportation system is a closed environment, indoor air quality problems may seriously affect many passengers' health. The purpose of this study was to understand $PM_{10}$ characteristics in the underground air environment and further to quantitatively estimate $PM_{10}$ source contributions in a Seoul Metropolitan subway station. The $PM_{10}$ was intensively collected on various filters with $PM_{10}$ aerosol samplers to obtain sufficient samples for its chemical analysis. Sampling was carried out in the M station on the Line-4 from April 21 to 28, July 13 to 21, and October 11 to 19 in the year of 2010 and January 11 to 17 in the year of 2011. The aerosol filter samples were then analyzed for metals, water soluble ions, and carbon components. The 29 chemical species (OC1, OC2, OC3, OC4, CC, PC, EC, Ag, Al, Ba, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Si, Ti, V, Zn, $Cl^-$, $NO_3{^-}$, $SO_4{^{2-}}$, $Na^+$, $NH_4{^+}$, $K^+$, $Mg^{2+}$, $Ca^{2+}$) were analyzed by using ICP-AES, IC, and TOR after proper pretreatments of each sample filter. Based on the chemical information, positive matrix factorization (PMF) model was applied to identify the $PM_{10}$ sources and then six sources such as biomass burning, outdoor, vehicle, soil and road dust, secondary aerosol, ferrous, and brakewear related source were classified. The contributions rate of their sources in tunnel are 4.0%, 5.8%, 1.6%, 17.9%, 13.8% and 56.9% in order.

• 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%).

• Bulletin of the Korean Chemical Society
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• v.33 no.11
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• pp.3651-3656
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• 2012

The size-segregated atmospheric aerosols have been collected at 1100 m site of Mt. Halla in Jeju, a background area in Korea, using 8-stage cascade impact air sampler during Asian dust and non-Asian dust storm periods. Their ionic and elemental species were analyzed, in order to examine the pollution characteristics and composition change between Asian dust and non-Asian dust periods. The major ionic species such as nss-$SO_4{^{2-}}$, $NH_4{^+}$, and $K^+$ were predominantly distributed in the fine particles (below $2.1{\mu}m$ diameter), and besides the $NO_3{^-}$ was distributed more in coarse particle fraction than fine particle. On the other hand, the typical soil and marine species i.e., nss-$Ca^{2+}$, $Na^+$, $Cl^-$, and $Mg^{2+}$, were mostly existed in the coarse particles (over $2.1{\mu}m$ diameter). As well in the elemental analysis of aerosols, the major soil-originated Al, Fe, Ca, and others showed prominently high concentrations in the coarse particle fraction, whereas the anthropogenic S and Pb were relatively high in the fine particle fraction. From the comparison of aerosol compositions between Asian dust and non-Asian dust periods, the concentrations of the soil-originated species such as nss-$Ca^{2+}$, Al, Ca, Fe, Ti, Mn, Ba, Sr have increased as 2.7-4.2 times during the Asian dust periods. Meanwhile the concentrations of nss-$SO_4{^{2-}}$ and $NO_3{^-}$ have increased as 1.4 and 2.0 times, and on the contrary $NH_4{^+}$ concentrations have a little bit decreased during the Asian dust periods. Especially the concentrations of both soil-originated ionic and elemental species increased noticeably in the coarse particle mode during the dust storm periods.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.5
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• pp.590-603
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• 2006

Size-and time-resolved aerosol samples were collected using an eight-stage Davis rotating unit for monitoring (DRUM) sampler from 23 March to 29 April 2001 at Gosan, Jeju Island, Korea, which is one of the super sites of Asia-Pacific Regional Aerosol Characterization Experiment(ACE-Asia). These samples were analyzed using synchrotron X-ray fluorescence for 3-hr average concentrations of 19 elements including Al, Si, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Se, Br, Rb, and Pb. The size-resolved data sets were then analyzed using the positive matrix factorization(PMF) technique to identify possible sources and estimate their contributions to particulate matter mass. PMF analysis uses the uncertainty of the measured data to provide an optimal weighting. Twelve sources were resolved in eight size ranges($0.09{\sim}12{\mu}m$) and included continental soil, local soil, sea salt, biomass/biofuel burning, coal combustion, oil combustion, municipal incineration, nonferrous metal source, ferrous metal source, gasoline vehicle, diesel vehicle, and volcanic emission. The PMF result of size-resolved source contributions showed that natural sources represented by local soil, sea salt, continental soil, and volcanic emission contributed about 79% to the predicted primary particulate matter(PM) mass in the coarse size range ($1.15{\sim}12{\mu}m$) while anthropogenic sources such as coal combustion and biomass/biofuel burning contributed about 58% in the fine size range($0.56{\sim}2.5{\mu}m$). The diesel vehicle source contributed mostly in ultra-fine size range($0.09{\sim}0.56{\mu}m$) and was responsible for about 56% of the primary PM mass.

• Korean Journal of Crystallography
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• v.8 no.1
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• pp.6-14
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• 1997

The crystal structures of $Sr_{31}K_{30}-X\;(Sr_{31}K_{30}Si_{100}A1_{92}O_{384};\;a=25.169(5) {\AA}$) and $Sr_{8.5}Tl_{75}-X (Sr_{8.5}Tl_{75}Si_{100}A1_{92}O_{384};\;a=25.041(5) {\AA}$) have been determined by single-crystal X-ray diffraction techniques in the cubic space group $\=F{d3}\;at\;21(1)^{\circ}C$. Each crystal was prepared by ion exchange in a flowing stream of aqueous $Sr(ClO_4)_2\;and\;(K\;or\;T1)NO_3$ whose mole ratio was 1 : 5 for five days. Vacuum dehydration was done at $360^{\circ}C$ for 2d. Their structures were refined to the final error indices $R_1=0.072\;and\;R_w=0.057$ with 293 reflections, and $R_1= 0.058\;and\;R_w=0.044$ with 351 reflections, for which $I>2{\sigma}(I)$, respectively. In dehydrated $Sr_{31}K_{30}-X,\;all\;Sr^{2+}$ ions and $K^+$ ions are located at five different crystallographic sites. Six-teen $Sr^{2+}$ ions per unit cell are at the centers of the double six-rings (site I), filling that position. The remaining 15 $Sr^{2+}$ ions and 17 $K^+$ ions fill site II in the supercage. These $Sr^{2+}$ and $K^+$ ions are recessed ca $0.45{\AA}\;and\;1.06{\AA}$ into the supercage, respectively, from the plane of three oxygens to which each is bound. ($Sr-O=2.45(1){\AA}\;and\;K-O=2.64(1){\AA}$) Eight $K^+$ ons occupy site III'($K-O=3.09(7){\AA}\;and\;3.11(10){\AA}$) and the remaining five $K^+$ ions occupy another site III'($K-O=2.88(7){\AA}\;and\;2.76(7){\AA}$). In $Sr_{8.5}Tl_{75}-X,\;Sr^{2+}\;and\;Tl^+$ ions also occupy five different crystallographic sites. About 8.5 $Sr^{2+}$ ions are at site I. Fifteen $Tl^+$ ions are at site I' in the sodalite cavities on threefold axes opposite double six-rings: each is $1.68{\AA}$ from the plane of its three oxygens ($T1-O=2.70(2){\AA}$). Together these fill the double six-rings. Another 32 $Tl^+$ ions fill site II opposite single six-rings in the supercage, each being $1.48{\AA}$ from the plane of three oxygens ($T1-O=2.70(1){\AA}$). About 18 $Tl^+$ ions occupy site III in the supercage ($T1-O=2.86(2){\AA}$), and the remaining 10 are found at site III' in the supercage ($T1-O=2.96(4){\AA}$).