• Economic and Environmental Geology
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• v.39 no.6 s.181
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• pp.675-687
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• 2006

The purpose of this study is to determine the geochemical characteristics of the stream sediments in the Cheongpung area. So that we can understand the natural background and predict the prospects of geochemical disaster, if any. We collected the stream sediments samples by wet sieving along the primary channels and slow dried the collected samples in the laboratory and ground them to pass a 200 mesh using an alumina mortar and pestle for chemical analysis. Miner-alogical characteristics, major, trace and rare earth elements were determined by XRD, XRF, ICP-AES and NAA analysis methods. For geochemical characteristics on the geological group of stream sediments, the studied area was grouped into granitic gneiss area, metatectic gneiss area, Dado tuff area, Yuchi conglomerate area, and Neungju flow area in the Cheongpung area. Contents of major elements for the stream sediments in the Cheongpung area were $SiO_2\;47.31{\sim}72.81\;wt.%,\;A1_2O_3 \;11.26{\sim}21.88\;wt.%,\;Fe_2O_3\;2.83{\sim}8.39\;wt.%,\;CaO\;0.34{\sim}7.54\;wt.%,\;MgO\; 0.55{\sim}3.59\;wt.%,\;K_2O\;1.71{\sim}4.31\;wt.%,\;Na_2O\;0.56{\sim}2.28\;wt.%,\;TiO_2\;0.46{\sim}1.24\;wt.%,\;MnO\;0.04{\sim}0.27\;wt.%,\;P_2O_5\;0.02{\sim}0.45\;wt.%$. The con-tents of trace and rare earth elements for the stream sediments were $Ba\;700ppm{\sim}8990ppm,\;Be\;1.0{\sim}3.50ppm,\;Cu\;6.20{\sim}60ppm,\;Nb\;12{\sim}28ppm,\;Ni\;4.4{\sim}61ppm,\;Pb\;13{\sim}34ppm,\;Sr\;65{\sim}787ppm,\;V\;4{\sim}98ppm,\;Zr\;32{\sim}164ppm,\;Li\;21{\sim}827ppm,\;Co\;3.68{\sim}65ppm,\;Cr\;16.7{\sim}409ppm,\;Cs\;2.72{\sim}37.1ppm,\;Hf\;4.99{\sim}49.2ppm,\;Rb\;71.9{\sim}649ppm,\;Sb\;0.16{\sim}5.03ppm,\;Sc\;4.97{\sim}52ppm,\;Zn\;26.3{\sim}375ppm,\;Ce\;60.6{\sim}373ppm,\;Eu\;0.82{\sim}6ppm,\;Yb\;0.71{\sim}10ppm$.

• 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.

• 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 Environmental Science International
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• v.23 no.3
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• pp.447-457
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• 2014

The number concentrations, the mass concentrations and the elemental concentrations of $PM_{10}$ have measured at Gosan site in Jeju, Korea, from March 2010 to December 2010. And the correlation and the factor analysis for the number, the mass and the elemental concentrations of $PM_{10}$ are performed to identify their relationships and sources. The average $PM_{10}$ number concentration is observed $246\;particles/cm^3$($35.7{\sim}1,017\;particles/cm^3$) and the average $PM_{10}$ mass concentration is shown $50.1{\mu}g/m^3$($16.7{\sim}441.4{\mu}g/m^3$) during this experimental period. The number concentrations are significantly decreased with increasing particle size, hence the concentrations for the smaller particles less than $2.5{\mu}m$($PM_{2.5}$) are contributed 99.6% to the total $PM_{10}$ number concentrations. The highest concentration of the 20 elements in $PM_{10}$ determined in this study is shown by S with a mean value of $1,497ng/m^3$ and the lowest concentration of them is found by Cd with a mean value of $0.57ng/m^3$. The elements in $PM_{10}$ are evidently classified into two group based on their concentrations: In group 1, including S>Na>Al>Fe>Ca>Mg>K, the elemental mean concentrations are higher than several hundred $ng/m^3$, on the other hand, the concentrations are lower than several ten $ng/m^3$ in group 2, including Zn>Mn>Ni>Ti>Cr>Co>Cu>Mo>Sr>Ba>V>Cd. The size-separated number concentrations are shown positively correlated with the mass concentrations in overall size ranges, although their correlation coefficients, which are monotonously increased or decreased with size range, are not high. The concentrations of the elements in group 1 are shown highly correlated with the mass concentrations, but the concentrations in group 2 are shown hardly correlated with the mass concentrations. The elements originated from natural sources have been predominantly related to the mass concentrations while the elements from anthropogenic sources have mainly affected on the number concentrations of $PM_{10}$.

• Food Science and Preservation
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• v.12 no.6
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• pp.656-661
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• 2005

To develop food additives from pyroligneous liquor, we first examined the physicochemical characteristics of volatile substances. The pH, gravity, acidity, solution tar, and scorched remains in the pyroligneous liquor were 2.50, 1.020, $0.8\%$ $2.31\%$ and $0.008\%$ respectively. The main compounds of pyroligneous liquor were 2,6-dimethoxyphenol (syringol), 2-hydroxy-2-cyclopenten-l-one, 1,2-benzenediol (catechol), phenol, 2 (5H)-furanone, 2-methoxyphenol (guaiacol), 5-hydroxymethyl-2 furancarboxaldehyde were found in organic phase, whereas catechol, 1,4 : 3,6-dianhydro-${\alpha}d$-glucopyranose, cyclopropyl carbinol, 5-hydroxymethyl-2 furancarboxaldehyde in aqueous phase.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.5
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• pp.543-553
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• 2010

Almost five million citizens a day are using subways as a means of traffic communication in the Seoul metropolitan. As the subway system is typically a closed environment, indoor air pollution problems frequently occurs and passengers complain of mal-health impact. Especially $PM_{10}$ is well known as one of the major pollutants in subway indoor environments. The purpose of this study was to compare the indoor air quality in terms of $PM_{10}$ and to quantitatively compare its source contributions in a Seoul subway platform before and after installing platform screen doors (PSD). $PM_{10}$ samples were collected on the J station platform of Subway Line 7 in Seoul metropolitan area from Jun. 12, 2008 to Jan. 12, 2009. The samples collected on membrane filters using $PM_{10}$ mini-volume portable samplers were then analyzed for trace metals and soluble ions. A total of 18 chemical species (Ba, Mn, Cr, Cd, Si, Fe, Ni, Al, Cu, Pb, Ti, $Na^+$, $NH_4^+$, $K^+$, $Mg^{2+}$, $Ca^{2+}$, $Cl^-$, and ${SO_4}^{2-}$) were analyzed by using an ICP-AES and an IC after performing proper pre-treatments of each sample filter. Based on the chemical information, positive matrix factorization (PMF) model was applied to identify the source of particulate matters. $PM_{10}$ for the station was characterized by three sources such as ferrous related source, soil and road dust related source, and fine secondary aerosol source. After installing PSD, the average $PM_{10}$ concentration was decreased by 20.5% during the study periods. Especially the contribution of the ferrous related source emitted during train service in a tunnel route was decreased from 59.1% to 43.8% since both platform and tunnel areas were completely blocked by screen doors. However, the contribution of the fine secondary aerosol source emitted from various outside combustion activities was increased from 14.8% to 29.9% presumably due to ill-managed ventilation system and confined platform space.

• 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.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 Environmental Science International
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• v.25 no.11
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• pp.1541-1554
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• 2016

To understand the characteristics of vanadium leaching from soils formed by the weathering of basalts, paleo soil at Gosan, Jeju Island, Korea, and several present-day soils from neighboring areas were collected. Leaching experiments were carried out by two approaches: 1) batch experiments under various geochemical conditions (redox potential (Eh) and pH) and 2) continuous leaching experiments under conditions similar to those of natural environments. From the batch experiments, leached vanadium concentrations were highest under alkaline (NaOH) conditions, with a maximum value of $2,870{\mu}g/L$, and were meaningful (maximum value, $114{\mu}g/L$) under oxidizing ($H_2O_2$) conditions, whereas concentrations under other conditions (acidic-HCl, $neutral-NaHCO_3$, and $reducing-Na_2S_2O_3$) were negligible. This indicated that the geochemical conditions, in which soil-water reactions occurred to form groundwater with high vanadium concentrations, were under alkaline-oxidizing conditions. From the continuous leaching experiments, the pH and leached vanadium concentrations of the solution were in the ranges of 5.45~5.58 and $6{\sim}9{\mu}g/L$, respectively, under $CO_2$ supersaturation conditions for the first 15 days, whereas values under $O_2$ aeration conditions after the next 15 days increased to 8.48~8.62 and $9.7{\sim}12.2{\mu}g/L$, respectively. Vanadium concentrations from the latter continuous leaching experiments were similar to the average concentration of groundwater in Jeju Island ($11.2{\mu}g/L$). Furthermore leached vanadium concentrations in continuous leaching experiments were highly correlated with pH and Al, Cr, Fe, Mn and Zn concentrations. The results of this study showed that 1) alkaline-oxidizing conditions of water-rock (soil) interactions were essential to form vanadium-rich groundwater and 2) volcanic soils can be a potential source of vanadium in Jeju Island groundwater.

• Ocean and Polar Research
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• v.24 no.2
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• pp.123-134
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• 2002

Seasonal variations of settling particles and metal fluxes were monitored at a nearshore site of Marian Cove, King Geroge Island, Antarctica from 28th February 1998 to 22nd January 2000. Near-bottom sediment traps were deployed at 30m water depth of the cove, and sampling bottles were recovered every month by SCUBA divers. Total particulate flux and metal concentrations were determined from the samples. Total particulate flux showed a distinct seasonality, high in austral summer and low in austral winter: the highest flux $(21.97g\;m^{-2}d^{-1})$ was found in February of 1999, and the lowest $(2.47g\;m^{-2}d^{-1})$ in September of 1998, when sea surface was frozen completely. Lithogenic particle flux accounted for 90% of the total flux, and showed a significantly negative correlation with the thickness of snow accumulation around the study site. It was suggested that the most of the lithogenic particles trapped in the bottles was transported by melt water stream from the surrounding land. Fluxes of Al, Fe, Ti, Mn, Zn, Cii, Co, Ni, Cr, Cd, and Pb showed similar seasonal variations with the total flux, and their averaged fluxes were 34000, 9000,960, 180, 13.8, 17.6, 3.0,2.1, 5.4, 0.02, and $1.5nmol\;m^{-2}d^{-1}$ respectively. Among the metals, Cu and Cd showed the most noticeable seasonal patterns. The Cd flux correlated positively with the fluxes of biogenic components while the Cu flux correlated with both the lithogenic and biogenic particle fluxes. The Cu flux peak in the late summer is likely related to a substantial amount of inflow of ice melt water laden with Cu-enriched lithogenic particles. On the other hands, the Cd flux peak in the early spring may be associated with the unusually early occurred phytoplankton bloom.