• Resources Recycling
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• v.9 no.4
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• pp.16-27
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• 2000

In order to produce raw material powder of advanced magnetic material by spray roasting process, newly modified spray roasting system was developed in this work. In this spray roasting system, raw material solution was effectively atomized and sprayed into the reaction furnace. Also, uniform temperature distribution inside reaction furnace made thermal decomposition process fully completed, and produced powder was effectively collected in cyclone and bag filter. This system equipped with apparatus which can purify hazard produced gas. In this study complex acid solution was prepared by dissolution of mill scale and ferro-Mn into the acid solution, and the pH of this complex acid solution was controlled about to 4. It was conformed that mill scale and ferro-Mn containing a lot of impurities such as $SiO_2$, P and Al could be used as raw material by reducing the impurities content of complex acid solution below 20 ppm. Complex oxide powder of Fe-Mn system was produced by spraying purified complex acid solution into the spray roaster through nozzle, and the variations of produced powder characters were studied by changing he reaction conditions such as reaction temperature, the injection velocity of solution and air, nozzle tip size and concentration of solution. The morphology of produced powder had spherical shape under the most experimental conditions, and concentration of solution. The morphology of produced powder has spherical shape under the most experimental conditions, and the composition and the particle size distribution were almost uniform, which tells the excellence of this spray roasting system. The grain size of most produced powder was below 100 nm. From the above results, it will be possible to produce ultra fine oxide powder from the chloride of Fe, Mn, Ni, Cu and rare earth by using this spray roasting system, and also to produce ultra fine pure metal powder by changing reaction atmosphere.

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

• Journal of agriculture & life science
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• v.46 no.4
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• pp.141-153
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• 2012

Samples collected from six tomato farms(A, B, C : soil culture, D, E, F : Nutriculture) located in Gyeongsangnam-do were tested for the analyses of biological(sanitary indications, major foodborne pathogens, fungi), chemical(heavy metals, pesticides) and physical hazards. The highest levels of total bacteria(7.5 log CFU/g) and coliforms(5.0 log CFU/g) in soil culture farms were higher than those of nutriculture farms(total bacteria: 2.5 log CFU/mL, coliforms: 0.6 log CFU/mL). In crops and personal hygiene soil culture farms showed a slightly higher contamination levels. From all farms, the levels of fungi in soil farms were higher than those of nutrient solution. In case of major pathogens, Bacillus cereus and Staphylococcus aureus were detected in all sample with the exception of nutrient solution. Meantime, Escherichia coli, Listeria monocytogenes, E.coli O157 and Salmonella spp. were not detected. For airborne bacteria, soilculture farms showed less contamination than nutriculture farms. A piece of glass and can was confirmed asphysical hazards. Heavy metal(Cd, Pb, Cu, Cr, Hg, Zn, Ni and As) and pesticide residues as chemical hazards were detected, but their levels were lower than the regulation limit. These results demonstrate that potential hazards on harvesting stage of tomato fam were exposed. Therefore, proper management is needed to prevent biological hazards due to cross-contamination, while physical and chemical hazards were in appropriate levels based on GAP criteria.

• Journal of agriculture & life science
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• v.44 no.6
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• pp.121-132
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• 2010

Soybean farms in Changnyeong were selected for hazard analysis to establish the Good Agricultural Practices (GAP) model of soybean, and physical, chemical(heavy metal) and biological(sanitary indications, foodborne pathogens) hazard analysis for cultivation environment (soil, water) was carried out. First, bow which is able to be mixed in soil and water was confirmed as physical hazard. Levels (Cd:0.01~0.103, Cu:0.001~6.036, As:0.006~3.045, Hg:ND~0.041, Pb:0.003~3.952, $Cr^{+6}$:0.007~0.496, Zn:0.001~66.500, Ni:0.003~18.010) of heavy metals in soil and water were appropriate for GAP criteria. In biological hazard, APC and coliform in soil were detected at the levels of $6.0{\pm}0.3$ and $3.6{\pm}1.6$ log CFU/g, and levels of water were $3.5{\pm}0.7$ and $1.9{\pm}0.7$ log CFU/mL, while E. coli wasn't detected in all sample. However, coliform in water wasn't appropriate for criteria, and E. coli O157 was detected about 22% in some farms, so it needs ways to prevent contamination by human and animals excrements. In conclusion, it needs proper management to prevent cross-contamination of hazards although physical and chemical hazard level were appropriate for GAP criteria while biological hazard wasn't.

• Korean Journal of Soil Science and Fertilizer
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• v.31 no.1
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• pp.25-32
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• 1998

To characterize the growth environment, inorganic composition and morphological chracteristics of leaves of Korean tea plant, soil and tea leaf samples were collected from 15 locations and analyzed. The chemical characteristics of soils were in range of pH 4.09~6.15, OM 23.9~72.6g/kg, available phosphate less than 300mg/kg, K $0.8{\sim}2.5cmol^+/kg$, Na $tr{\sim}0.17cmol^+/kg$, Ca $1.0{\sim}6.2cmol^+/kg$, and Mg $0.3{\sim}2.1cmol^+/kg$. The contents of Ni. Cr, Zn. Cu, Pb, and Cd were at the level less than natural content in upland soil. Most of the sample soils were sandy loamy and loamy texture. The native tea plants were mainly grown in bamboo thicket or in forest. The leaf sizes of tea plants were $6.85{\pm}1.75{\times}2.6{\pm}0.5cm$, lateral vein number $14.2{\pm}2.7$, and crenated number $58.5{\pm}11.2$, and the leaf color was thin to dark green. The contents of $NH_4{^+}$, $Na^+$, $K^+$, $Mg^{2+}$ and $Ca^{2+}$ in tea leaves were in range of 30.5~47.7, 45.5~164.5, 16,998~25,431, 1.590~2,392 and 1,085~1,958mg/kg, respectively. The contents of $F^-$, $Cl^-$, $NO_3{^-}$, $PO_4{^{3-}}$ and $SO_4{^{2-}}$ were in range of 21.2~63.2, 126.4~257.9, 108.5~185.9, 1,270~1.819, and $954{\sim}1,670mg/kg$, respectively. The leaf size of native tea plant grown widlly in Shunchun Changchun-ri, Hwasun Ssangbongsa, Kuryoi Chonunsa, Bosong Daewonsa and Namhae Boriam was as large as those of Yabukita. Japan cultiver, grown at Kangjin Jangwon tea field.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.1-9
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• 2022

The effect of sediments in a waste dumping area on marine organisms was evaluated using sediment toxicity tests with a benthic amphipod (Monocorophium acherusicum) and bioluminescent bacterium (Vibrio fischeri) in accordance with the Korean Standard Method for Marine Wastes (KSMMW). Nine sites in the East Sea-Byeong, East Sea-Jeong, and Yellow Sea-Byeong areas were sampled from 2016 to 2019. The test results showed that the relative average survival rate (benthic amphipods) and relative luminescence inhibition rate (luminescent bacteria) were below 30%, which were judged to be "non-toxic." However, in the t-test, a total of 12 benthic amphipod samples (6, 1, 1, and 4 in 2016, 2017, 2018, and 2019, respectively) were significantly different (p<0.05) from the control samples. To identify the source of toxicity on benthic amphipods, a simple linear regression analysis was performed between the levels of eight heavy metals (Cr, As, Ni, Cd, Cu, Pb, Zn, and Hg) in sediments and the relative average survival rate. The results indicated that Cr had the highest contribution to the toxicity of benthic amphipods (p = 0.000, R2 = 0.355). In addition, Cr was detected at the highest concentration at the DB-85 station and exceeded the Marine Environment Standards every year. Although the sediments were determined as "not toxic" according to the ecotoxicity criteria of the KSMMW, the results of the statistical significance tests and toxicity identification evaluation indicated that the toxic effect was not acceptable. Therefore, revising the criteria for determining the toxic effect by deriving a reference value through quantitative risk assessment using species sensitivity distribution curves is necessary in the future.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

• Economic and Environmental Geology
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• v.41 no.4
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• pp.405-425
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• 2008

In order to investigate the amounts of trace elements flowing into reservoir, and to elucidate the relationship between trace element mobility and fraction size, the stream water and sediment samples were collected from thirty-two sites of the 3rd or 4th order stream within watershed surrounding the Juam reservoir. Chemical analyses of trace elements (As, Cd, Cr, Cu, Ni, Pb and Zn) for all samples were completed, and additionally cationi and anion for stream water samples. Considering the distribution of rocks and contamination sources in watershed, the eight stream sediments were selected from typical sites representing study areas, and we determined the concentrations of trace elements according to size fractions ($2\;mm{\sim}200\;{\mu}m$, $200{\sim}100\;{\mu}m$, $100{\sim}50\;{\mu}m$, $50{\sim}20\;{\mu}m$ and < $20\;{\mu}m$). The correlation relationships between concentrations and size fractions of stream sediments were important to identify the hydro-geochemical behavior of trace elements that flow into Juam reservoir. Stream waters showed four water types (Ca-Mg-$HCO_3$, Ca-Na-$HCO_3$-Cl, Ca-Na-$HCO_3-SO_4$, Ca-Na-$HCO_3$) depending on pollution sources such as coal mine, metal mine, farm-land and dwellings. Concentrations of trace elements increased clearly with the decrease in size fractions of stream sediments. Concentrations of Cu, Pb and Zn increased dramatically in silt size (< $20\;{\mu}m$) fraction, while As had high concentrations in sand size ($2\;mm{\sim}100\;{\mu}m$) fraction in downstream sediments of metal mines. These indicate that Cu, Zn, and Pb moved into Juam reservoir easily in the adsorbed form on silt size grain in sediments, and As was transported as As-bearing mineral facies, resulting in its less chance to reach into Juam reservoir.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.25 no.3
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• pp.380-391
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• 2015

Objectives: The objective of this study is to assess airborne particulate matter pollution and its effect on health of residents living near Ansim Briquette Fuel Complex and its vicinities. Also, this study measured and analyzed the concentration of TSP, $PM_{10}$, $PM_{2.5}$, and heavy metals which influences on the environmental and respiratory disease in Ansim Briquette Fuel Complex, Daegu, Korea. Methods: In this study, we analyzed various environmental pollutants such as particulate matter and heavy metals from Ansim Briquette Fuel Complex that adversely affected local residents's health. In particular, we verified the concentration distribution and characteristics of exposure for TSP, $PM_{10}$, and $PM_{2.5}$ among particulate matters, and heavy metals(Cd, Cr, Cu, Mn, Ni, Pb, Fe, Zn, and Mg). In that regard, the official test method on air pollution in Korea for analysis of particulate matter and heavy metal in atmosphere were conducted. The large capacity air sampling method by the official test method on air pollution in Korea were applied for sampling of heavy metals in atmosphere. In addition, we evaluated the concentration of seasonal environmental pollutants for each point of residence in Ansim Briquette Fuel Complex and surrounding area. The sampling measured periods for air pollutants were from August 11, 2013 to February 21, 2014. Furthermore, we measured and analyzed the seasonal concentrations(summer, autumn and winter). Results: The average concentration for TSP, $PM_{10}$, and $PM_{2.5}$ by direct influence area at Ansim Briquette Fuel Complex were 1.7, 1.4 and 1.9 times higher than reference region. In analysis results of seasonal concentrations for particulate matter in four direct influence and reference area, concentration levels for winter were generally somewhat higher than concentrations for summer and autumn. The average concentrations for Cd, Cr, Mn, Ni, Pb, Fe, and Zn in direct influence area at Ansim Briquette Fuel Complex were $0.0008{\pm}0.0004{\mu}g/Sm^3$, $0.0141{\pm}0.0163{\mu}g/Sm^3$, $0.0248{\pm}0.0059{\mu}g/Sm^3$, $0.0026{\pm}0.0011{\mu}g/Sm^3$, $0.0272{\pm}0.0084{\mu}g/Sm^3$, $0.4855{\pm}0.1862{\mu}g/Sm^3$, and $0.3068{\pm}0.0631{\mu}g/Sm^3$, respectively. In particularly, the average concentrations for Cd, Cr, Mn, Ni, Pb, Fe, and Zn in direct influence area at Ansim Briquette Fuel Complex were 1.9, 3.6, 2.1, 1.9, 1.4, 2.6, and 1.2 times higher than reference area, respectively. The continuous monitoring and management were required for some heavy metals such as Cr and Ni. Moreover, the average concentration in winter for particulate matter in direct influence area at Ansim Briquette Fuel Complex were generally higher than concentrations in summer and autumn. Also, average concentrations for TSP, $PM_{10}$, and $PM_{2.5}$ were from 1.5 to 2.0 times, 1.2 to 1.8 times, and 1.1 to 2.3 times higher than reference area, respectively. In results for seasonal atmospheric environment, TSP, $PM_{10}$, $PM_{2.5}$, and heavy metal concentrations in direct influence area were higher than reference area. Especially, the concentrations in C station were a high level in comparison with other area. Conclusions: In the results, some particulate matters and heavy metals were relatively high concentration, in order to understand the environmental pollution level and health effect in surrounding area at Ansim Briquette Fuel Complex. The concentration of some heavy metals emitted from direct influence area at Ansim Briquette Fuel Complex were relatively higher than reference area. In particular, average concentration for heavy metals in this study were higher than average concentrations in air quality monitoring station for heavy metal for 7 years in Deagu metropolitan region. Especially, the residents near Ansim Briquette Fuel Complex may be exposed to the pollutants(TSP, $PM_{10}$, $PM_{2.5}$, and heavy metals, etc) emitted from the factories in Ansim Briquette Fuel Complex.

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