• Economic and Environmental Geology
• /
• v.39 no.6 s.181
• /
• pp.675-687
• /
• 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 $Ba\;700ppm{\sim}8990ppm,\;Be\;1.0{\sim}3.50ppm,\;Cu\;6.20{\sim}60ppm,\;Nb\;12{\sim}28ppm,\;Ni\;4.4{\sim}61ppm,\;Pb\;13{\sim}34ppm,\;Sr\;65{\sim}787ppm,\;V\;4{\sim}98ppm,\;Zr\;32{\sim}164ppm,\;Li\;21{\sim}827ppm,\;Co\;3.68{\sim}65ppm,\;Cr\;16.7{\sim}409ppm,\;Cs\;2.72{\sim}37.1ppm,\;Hf\;4.99{\sim}49.2ppm,\;Rb\;71.9{\sim}649ppm,\;Sb\;0.16{\sim}5.03ppm,\;Sc\;4.97{\sim}52ppm,\;Zn\;26.3{\sim}375ppm,\;Ce\;60.6{\sim}373ppm,\;Eu\;0.82{\sim}6ppm,\;Yb\;0.71{\sim}10ppm$.

• Economic and Environmental Geology
• /
• v.38 no.4 s.173
• /
• pp.481-492
• /
• 2005

The purpose of this study is to determine geochemical characteristics for stream sediments in the Gwangju area. We collect the stream sediments samples by wet sieving along the primary channels and dry these samples slowly in the laboratory and grind to under 200mesh using an alumina mortar fur chemical analysis. Major elements, trace and rare earth elements are determined by XRF, ICP-AES and NAA analysis methods. For geochemical characteristics on geological groups of stream sediments, we separate geologic groups which are derived from Precambrian granite gneiss area, Jurassic granite area and Cretaceous Hwasun andesite area. Contents range of major elements for stream sediments in the Gwangju area are $SiO_2\;51.89\~70.63\;wt.\%,\;Al_2O-3\;12.91\~21.95\;wt.\%,\;Fe_2O_3\;3.22\~9.89\;wt.\%,\;K_2O\;1.85\~4.49\;wt.\%,\;MgO\;0.68\~2.90\;wt.\%,\;Na_2O\;0.48\~2.34\;wt.\%,\;CaO\;0.42\~6.72\;wt.\%,\;TiO_2\;0.53\~l.32\;wt.\%,\;P_2O_5\;0.06\~0.51\;wt.\%\;and\;MnO\;0.05\~0.69\;wt.\%.$ According to the AMF diagram for stream sediments and rocks, the stream sediments are plotted on boundary of tholeiitic series and calk alkaline series, which shows that contents of $Fe_2O_3$ are higher in stream sediments than rocks. According to variation diagram of $SiO_2$ versus $(K_2O+Na_2O),$ stream sediments are plotted on subalkaline series. Contents range of trace and rare earth elements for stream sediments in the Gwangiu area are Ba$590\~2170$ppm, Be1\~2.4$ppm, Cu$13\~79$ppm, Nb$20\~34$ppm, Ni$10\~50$ppm, Pb$17\~30$ppm, Sr$70\~1025$ ppm, V$42\~135$ppm, Zr$45\~171$ppm, Li$19\~77$ppm, Co$4.3\~19.3$ppm, Cr$28\~131$ppm, Cs$3.1\~17.6$ppm, Hf$5\~27.6$ppm, Rb$388\~202$ppm, Sb$0.2\~l.2$ ppm, Sc$6.4\~17$ppm, Zn$47\~389$ppm, Pa$8.8\~68.8$ppm, Ce$62\~272$ppm, Eu$1\~2.7$ppm and Yb$0.9\~6$ppm.

• Conservation Science in Museum
• /
• v.30
• /
• pp.71-88
• /
• 2023

This paper examined the visible characteristics and chemical composition of glass beads from the Joseon Dynasty as well as the associations thereof. It also explored the characteristics and uses of glass beads by region. This study covered a total of 1,819 pieces excavated from 25 locations in the Gyeonggi, Chungcheong, and Gyeongsang regions, of which 537 pieces were analyzed for their chemical composition. Glass beads of the Joseon Dynasty take a variety of shapes such as a Round, Coil, Floral, Segmented, Flat, Oval, and Calabash. Colors vary from shades of brown (brown, lemon yellow) and shades of blue (Bluish-Green, greenish-Blue, Purple-Blue) to shades of white (colorless, white) and shades of green (Green, Greenish-Blue, Greenish-Brown). Brown accounts for the largest percentage, followed by Bluish-Green, greenish-Blue. It was identified that Drawing technique was the most common glass bead production technique of the Joseon Dynasty. Potassium oxide (K₂O) was the most common flux agent for glass beads, while the potash glass and mixed alkali glass groups account for the largest quantity. The choice of stabilizers depended on the type of flux agents used, but the most common were calcium oxide (CaO) and aluminum oxide (Al₂O₃). The potash glass and potash lead glass groups are high in CaO and low in Al₂O₃, the mixed alkali glass group is high in CaO, and the lead glass group is low in CaO. In terms of the association between color and shape, most of the beads with shade of brown and blue have round shapes of brown and blue have spherical shapes, while the coil shape is prominent in blue beads. A high percentage of green and colorless beads also take the shape of a coil, while white beads in general have a floral shape. In terms of the association between shape and chemical composition, round, floral and segmented shapes account for a high percentage of the potash glass group, while coil and flat shapes are common in the mixed alkali glass group. This paper also analyzed the colorants for each color based on the association between color and chemical composition. Iron (Fe) was used as the colorant for brown and white, and titanium (Ti) and iron were used for light yellow. Purple-Blue was produced by by cobalt (Co), and greenish-Blue, Bluish-Green, green, Greenish-Blue were produced by iron and copper (Cu). Colorless beads had a generally low colorant content.

• Economic and Environmental Geology
• /
• v.42 no.3
• /
• pp.177-193
• /
• 2009

The Samgwang deposit consists of eight massive mesothermal quartz veins that filled NE and NW-striking fractures along fault zones in Precambrian granitic gneiss of the Gyeonggi massif. The mineralogy and paragenesis of the veins allow two separate discrete mineralization episodes(stage I=quartz and calcite stage, stage II-calcite stage) to be recognized, temporally separated by a major faulting event. The ore minerals are contained within quartz and calcite associated with fracturing and healing of veins that occurred during both mineralization episodes. The hydrothermal alteration of stage I is sericitization, chloritization, carbonitization, pyritization, silicification and argillization. Sericitic zone occurs near and at quartz vein and include mainly sericite, quartz, and minor illite, carbonates and chlorite. Chloritic zone occurs far from quartz vein and is composed of mainly chlorite, quartz and minor sericite, carbonates and epidote. Fe/(Fe+Mg) ratios of sericite and chlorite range 0.45 to 0.50(0.48$\pm$0.02) and 0.74 to 0.81(0.77$\pm$0.03), and belong to muscovite-petzite series and brunsvigite, respectiveIy. Calculated $Al_{IV}$-FE/(FE+Mg) diagrams of sericite and chlorite suggest that this can be a reliable indicator of alteration temperature in Au-Ag deposits. Calculated activities of chlorite end member are $a3(Fe_5Al_2Si_3O_{10}(OH)_6$=0.0275${\sim}$0.0413, $a2(Mg_5Al_2Si_3O_{10}(OH)_6$=1.18E-10${\sim}$7.79E-7, $a1(Mg_6Si_4O_{10}(OH)_6$=4.92E-10${\sim}$9.29E-7. It suggest that chlorite from the Samgwang deposit is iron-rich chlorite formed due to decreasing temperature from high temperature(T>450$^{\circ}C$). Calculated ${\alpha}Na^+$, ${\alpha}K^+$, ${\alpha}Ca^{2+}$, ${\alpha}Mg^{2+}$ and pH values during wallrock alteration are 0.0476($400^{\circ}C$), 0.0863($350^{\circ}C$), 0.0154($400^{\circ}C$), 0.0231($350^{\circ}C$), 2.42E-11($400^{\circ}C$), 7.07E-10($350^{\circ}C$), 1.59E-12($400^{\circ}C$), 1.77E-11($350^{\circ}C$), 5.4${\sim}$6.4($400^{\circ}C$), 5.3${\sim}$5.7($350^{\circ}C$)respectively. Gain elements(enrichment elements) during wallrock alteration are $TiO_2$, $Fe_2O_3(T)$,CaO, MnO, MgO, As, Ag, Cu, Zn, Ni, Co, W, V, Br, Cs, Rb, Sc, Bi, Nb, Sb, Se, Sn and Lu. Elements(Ag, As, Zn, Sc, Sb, Rb, S, $CO_2$) represents a potential tools for exploration in mesothermal and epithermal gold-silver deposits.

• Asian Journal of Atmospheric Environment
• /
• v.8 no.3
• /
• pp.126-139
• /
• 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
• /
• v.31 no.3
• /
• pp.223-238
• /
• 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 Korean Society of Occupational and Environmental Hygiene
• /
• v.24 no.4
• /
• pp.547-555
• /
• 2014

Objective: This study was conducted to investigate the association between subjective distress symptoms and argon welding among workers in Gyeongnam Province shipyard. Method: 31 argon and 29 non-argon welding workers were selected as study subjects in order to measure concentrations of personal dust, welding fumes and other hazardous materials such as ZnO, Pb, Cr, FeO, MnO, Cu, Ni, $TiO_2$, MgO, NO, $NO_2$, $O_3$, $O_2$, $CO_2$, CO and Ar. An interviewer-administered questionnaire survey was also performed on the same subjects. The items queried were as follows: age, height, weight, working duration, welding time, welding rod amounts used, drinking, smoking, and rate of subjective distress symptoms including headache and other symptoms such as fever, vomiting and nausea, metal fume fever, dizziness, tingling sensations, difficulty in breathing, memory loss, sleep disorders, emotional disturbance, hearing loss, hand tremors, visual impairment, neural abnormality, allergic reaction, runny nose and stuffiness, rhinitis, and suffocation. Statistical analysis was performed using SPSS software, version 18. Data are expressed as the mean ${\pm}SD$. An ${\chi}^2$-test and a normality test using a Shapiro wilk test were performed for the above variables. Logistic regression analysis was also conducted to identify the factors that affect the total score for subjective distress symptoms. Result: An association was shown between welding type (argon or non-argon welding) and the total score for subjective distress symptoms. Among the rate of complaining of subjective distress symptoms, vomiting and nausea, difficulty breathing, and allergic reactions were all significantly higher in the argon welding group. Only the concentration of dust and welding fumes was shown to be distributed normally after natural log transformation. According to logistic regression analysis, the correlations of working duration and welding type (argon or non-argon) between the total score of subjective distress symptoms were found to be statistically significant (p=0.041, p=0.049, respectively). Conclusion: Our results suggest that argon welding could cause subjective distress symptoms in shipyard workers.

• Journal of Environmental Science International
• /
• v.23 no.3
• /
• pp.447-457
• /
• 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 $PM_{10}$.

• Journal of Korean Society for Atmospheric Environment
• /
• v.28 no.5
• /
• pp.538-555
• /
• 2012

The purpose of this study was to understand $PM_{2.5}$ chemical characteristics on the Suwon/Yongin area and further to quantitatively estimate $PM_{2.5}$ source contributions. The $PM_{2.5}$ sampling was carried out by a high-volume air sampler at the Kyung Hee University-Global Campus from November, 2010 to October, 2011. The 40 chemical species were then analyzed by using ICP-AES(Ag, Ba, Cr, Cu, Fe, Mn, Ni, Pb, Si, Ti, V and Zn), IC ($Na^+$, $K^+$, $NH_4{^+}$, $Mg^{2+}$, $Ca^{2+}$, $NO_3{^-}$, ${SO_4}^{2-}$ and $Cl^-$), DRI/OGC (OC1, OC2, OC3, OC4, OP, EC1, EC2 and EC3) and GC-FID (acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benzo[a]anthracene, benzo[b]fluoranthene, benzo[a] pyrene, indeno[1,2,3-cd] pyrene, benzo[g,h,i]perylene and dibenzo[a,h,]anthracene). When applying PMF model after performing proper data treatment, a total of 10 sources was identified and their contributions were quantitatively estimated. The average contribution to $PM_{2.5}$ emitted from each source was determined as follows; 26.3% from secondary aerosol source, 15.5% from soil and road dust emission, 15.3% from vehicle emission, 15.3% from illegal biomass burning, 12.2% from incineration, 7.2% from oil combustion source, 4.9% from industrial related source, and finally 3.2% from coal combustion source. In this study we used the ratios of PAHs concentration as markers to double check whether the sources were reasonably classified or not. Finally we provided basic information on the major $PM_{2.5}$ sources in order to improve the air quality in the study area.

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