• Economic and Environmental Geology
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• v.44 no.5
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• pp.413-431
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• 2011

An Epithemal Au-Ag mineralized zone is developed in the Moisan area of Hwangsan-myeon, Haenam-gun, Jeol-lanam-do, Korea, which is located in the southwestern part of the Ogcheon metamorphic zone. It is hosted in the Hwangsan volcaniclastics of the Haenam Formation of the Late Cretaceous Yucheon Group. This research investigated the characteristics of bedding arrangement, fold, fault, fracture system, quartz vein and the time-relationship of the fracture system to understand the geological structure related to the formation of the mineralized zone. On the basis of this result, the tectonic environment at the time of the mineralization was considered. Beds mainly trend east-northeast and gently dip into north-northwest or south-southeast. Their poles have been rearranged by subhorizontal-upright open fold of (east)-northeast trend as well as dip-slip fault. Fracture system was formed through at least 6~7 different deformation events. D1 event; formation phase of the main fracture set of EW (D1-1) and NS (D1-2) trends with a good extensity, D2 event; that of the extension fracture of NW trend, and conjugate shear fracturing of the EW (dextral) and NS (sinistral) trends, D3 event; that of the extension fracture of NE trend, and conjugate shear refracturing of the EW (sinistral) and NS (dextral) trends, D4 event; that of the extension fracture of NS trend showing a poor extensity, D5 event; that of the extension fracture of NW trend, and conjugate shear refracturing of the EW (dextral) and NS (sinistral) trends, D6 event; that of the extension fracture of EW trend showing a poor extensity. Frequency distribution of fracture sets of each deformation event is D1-1 (19.73 %)> D1-2 (16.44 %)> D3=D5 (14.79 %)> D2 (13.70 %)> D4 (12.33 %)> D6 (8.22 %) in descending order. The average number of fracture sets within 1 meter at each deformation event is D6 (5.00)> D5 = D4 (4.67)> D2 (4.60)> D3 (4.13)> D1-1 (3.33)> D1-2 (2.83) in descending order. The average density of all fractures shows 4.20 fractures/1 m, that is, the average spacing of all fractures is more than 23.8 cm. The frequency distribution of quartz veins at each orientation is as follows: EW (52 %)> NW (28 %)> NS (12 %)> NE (8 %) trends in descending order. The average density of all quartz veins shows 4.14 veins/1 m, that is, the average spacing of all quartz veins is more than 24.2 cm. Microstructural data on the quartz veins indicate that the epithermal Au-Ag mineralization (ca. 77.9~73.1 Ma) in the Moisan area seems to occur mainly along the existing D1 fracture sets of EW and NS trends with a good extensity not under tectonic stress but non-deformational environment directly after epithermal rupture fracturing. The D1 fracturing is considered to occur under the unstable tectonic environment which alternates compression and tension of NS trend due to the oblique northward subduction of the Izanagi plate resulting in the igneous activity and deformation of the Yucheon Group and the Bulguksa igneous rocks during Late Cretaceous time.

• Economic and Environmental Geology
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• v.22 no.1
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• pp.35-63
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• 1989

Geochemical characteristics of the Guryongsan (Ogcheon) uraniferous black slate show that this is an analogue to the conventional Chattanooga and Alum shales in occurrences. Whereas, its highest enrichment ratio in metals including uranium, among others, is explained by the cyclic sedimentation of the black muds and quartz-rich silts, and the uniform depositional condition with some what higher pH condition compared to the conditions of the known occurrences. The cyclic sedimentation, caused by the periodic open and close of the silled basin, has brought about the flush-out) of the uranium depleted water and the recharge with the new metal-rich sea water, which consequently contributed to the high concentration of metals in mud. The metal-rich marine black muds, which mostly occur in the early to middle Palaeozoic times, is attributed by the geologic conditions which related to the atmospheric oxygen contents, and these are scarcely met in the late Precambrian and/or with the onset of Palaeozoic era in the geologic evolution of the earth.

• Economic and Environmental Geology
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• v.38 no.6 s.175
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• pp.663-673
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• 2005

This study investigates the relationship between the geochemical maps and the gold-silver deposit locations. Geochemical maps of 21 elements, which are published by KIGAM, locations of gold-silver deposits, and 1:1,000,000 scale geological map of Korea are utilized far this investigation. Pixel size of the basic geochemical maps is 250m and these data are resampled in 1km spacing for the statistical analyses. Relationship between the mine location and the geochemical data are investigated using bayesian statistics and decision tree algorithms. For the bayesian statistics, each geochemical maps are reclassified by percentile divisions which divides the data by 5, 25, 50, 75, 95, and $100\%$ data groups. Number of mine locations in these divisions are counted and the probabilities are calculated. Posterior probabilities of each pixel are calculated using the probability of 21 geochemical maps and the geological map. A prediction map of the mining locations is made by plotting the posterior probability. The input parameters for the decision tree construction are 21 geochemical elements and lithology, and the output parameters are 5 types of mines (Ag/Au, Cu, Fe, Pb/Zn, W) and absence of the mine. The locations for the absence of the mine are selected by resampling the overall area by 1 km spacing and eliminating my resampled points, which is in 750m distance from mine locations. A prediction map of each mine area is produced by applying the decision tree to every pixels. The prediction by Bayesian method is slightly better than the decision tree. However both prediction maps show reasonable match with the input mine locations. We interpret that such match indicate the rules produced by both methods are reasonable and therefore the geochemical data has strong relations with the mine locations. This implies that the geochemical rules could be used as background values oi mine locations, therefore could be used for evaluation of mine contamination. Bayesian statistics indicated that the probability of Au/Ag deposit increases as CaO, Cu, MgO, MnO, Pb and Li increases, and Zr decreases.

• Economic and Environmental Geology
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• v.19 no.2
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• pp.109-122
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• 1986

Mn-Pb-Zn-Ag deposits of the Janggun mine are hosted in the Cambro-Ordovician Janggun limestone mostly along the contacts of the Jurassic Chunyang granite. The deposits are represented by several ore pipes and steeply dipping lenticular bodies consisting of lower Pb-Zn-Ag sulfide ores and upper manganese carbonate and oxide ores. The former consists mainly of arsenic, antimony, silver, manganese, and tin-bearing sulfides, whereas the latter are characterized by hypogene rhodochrosite, and superficial manganese oxides including todorokite, nsutite, pyrolusite, cryptomelane, birnesite and janggunite. Origin of the upper manganese ore deposits has been a controversial subject among geologists for this mine: hydrothermal metasomatic vs. syngenetic sedimentary origin. Syngenetic advocators have proposed a new sedimentary rock, rhodochrostone, which is composed mainly of rhodochrosite in mineralogy. In the present study, carbon, oxygen and sulfur isotopic compositions were analayzed obtaining results as follows: Rhodochrosite minerals, (Mn, Ca, Mg, Fe) $CO_3$, from hydrothermal veins, massive sulfide ores and replacement ores in dolomitic limestone range in isotopic value from -4.2 to -6.3‰ in ${\delta}^{13}C$(PDB) and +7.6 to +12.9‰ in ${\delta}^{18}O$(SMOW) with a mean value of -5.3‰ in ${\delta}^{13}C$ and +10.7‰ in ${\delta}^{18}O$. The rhodochrosite bearing limestone and dolomitic limestone show average isotopic values of -1.5‰ in ${\delta}^{13}C$ and +17.5‰ in ${\delta}^{18}O$, which differ from those of the rhodochrosite mentioned above. This implies that the carbon and oxygen in ore fluids and host limestone were not derived from an identical source. ${\delta}^{34}S$ values of sulfide minerals exhibit a narrow range, +2.0 to +5.0‰ and isotopic temperature appeared to be about $288{\sim}343^{\circ}C$. Calculated initial isotopic values of rhodochrosite minerals, ${\delta}^{18}O_{H_2O}=+6.6$ to +10.6‰ and ${\delta}^{13}C_{CO_2}=-4.0$ to -5.1 ‰, strongly suggest that carbonate waters should be deep seated in origin. Isotopic data of manganese oxide ores derived from hypogene rhodochrosites suggest that the oxygen of the limestone host rock rather than those of meteoric waters contribute to form manganese oxide ores above the water table.

• Korean Journal of Food Science and Technology
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• v.7 no.4
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• pp.229-237
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• 1975

An attempt was made to utilize the enzyme produced by Asp. oryzae as meat tenderizer. The production, purification, and various properties of proteinase produced by Asp. oryzae were investigated. Results obtained are as follow; 1. A strain which had the highest proteolytic activity was selected among 9 Aspergillus species. 2. Culture medium consisted of wheat bran 10g, 2% glucose, 0.03% urea and 0.1% $MgSO_4$ (pH 6.5). Mold was incubated at $30^{\circ}C$ for 3 days. 3. Enzyme extract from culture medium were fractionated with ammonium sulfate and purified by Sephadex G-75 column chromatography. 4. When pH of reaction mixture was controlled, maximal activity of proteinase by Asp. oryzae was obtained at pH 3, pH 6.6, $8.4{\sim}8.5$ and pH 10.0 to 10.5. Those results were interpreted to show that enzyme consists of acid proteinase, neutral proteinase and alkaline proteinase. Enzyme was stable at pH 6 to 10. 5. Opt. temperature for proteinase activity was $50^{\circ}C$, but enzyme was stable up to $40^{\circ}C$. 6. The proteinase was inhibited by $Ag^+$. It was also inhibited by EDTA. 7. When myofibrillar proteins were treated by proteinase from Asp. oryzae, ATPase activities of myofibrillar proteins changed remarkably. Accordingly, it was concluded that proteinase produced by Asp. oryzae were able to be used as meat tenderizer.

• 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 Korean Society for Atmospheric Environment
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• v.28 no.5
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• pp.538-555
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• 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.

• Atmosphere
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• v.29 no.4
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• pp.481-499
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• 2019

National Institute of Meteorological Sciences has conducted a total 54 cloud seeding experiments with a silver iodide and calcium chloride using aircrafts from 2008 to 2018. The goal of the experiments is to improve the techniques of precipitation enhancement in Korea. The cloud seeding experiments using the silver iodide and calcium chloride were 36 and 18 times, respectively. During the cloud seeding experiments of the silver iodide and calcium chloride, the average values of total cloud amount for two kinds of seeding materials were 9.6 for and 8.1, respectively. The cloud type with the highest occurrence was Nimbostratus (Ns)-Stratus (St) (58%) in the silver iodide cloud seeding experiment. It was Altostratus (As)-Stratocumulus (Sc) (44%) in the calcium chloride cloud seeding experiment. Compared to probability of obtaining cloud seeding effect of the experiments using a leased aircraft, the probability using an atmospheric research aircraft increased from 43% to 63% in the silver iodide cloud seeding experiment and from 29% to 75% in the calcium chloride cloud seeding experiment. However, the increasing tendency was only shown during the one year experiment (2018). To get the meaningful statistical tendency of the cloud seeding effects, it is needed to implement many experiments in several years. Further we have to more clearly understand the characteristics of clouds developing in Korea and implement the cloud seeding experiments under a variety of weather conditions in order to develop the optimized precipitation enhancement technology in Korea.

• 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.