• 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.

• Korean Journal of Mineralogy and Petrology
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• v.35 no.2
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• pp.125-140
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• 2022

The Xiquegou Pb-Zn deposit is located at the Qingchengzi orefield which is one of the largest Pb-Zn mineralized zone in the northeast of China. The geology of this deposit consists of Archean granulite, Paleoproterozoinc migmatitic granite, Paleo-Mesoproterozoic sodic granite, Paleoproterozoic Liaohe group, Mesozoic diorite and Mesozoic monzoritic granite. The Xiquegou deposit which is a Triassic magma-hydrothermal type deposit occurs as vein ore filled fractures along fault zone in unit 3 (dolomitic marble and schist) of Dashiqiao formation of the Paleoproterozoic Liaohe group. Xiquegou Pb-Zn deposit consists of quartz, apatite, calcite, pyrite, arsenopyrite, pyrrhotite, marcasite, sphalerite, chalcopyrite, stannite, galena, tetrahedrite, electrum, argentite, native silver and pyrargyrite. Wallrock alteration of this deposit contains silicification, pyritization, dolomitization, chloritization and sericitization. Based on mineral petrography and paragenesis, dolomites from this deposit are classified two type (1. dolomite (D₀) as wallrock, 2. dolomite (D₁) as wallrock alteration in Pb-Zn mineralization quartz vein ore). The structural formulars of dolomites are determined to be Ca_1.03-1.01Mg_0.95-0.83Fe_0.12-0.02Mn_0.02-0.00(CO₃)₂(D₀) and Ca_1.16-1.00Mg_0.79-0.44Fe_0.53-0.13Mn_0.03-0.00As_0.01-0.00(CO₃)₂(D₁), respectively. It means that dolomites from the Xiquegou deposit have higher content of trace elements compared to the theoretical composition of dolomite. The dolomite (D₁) from quartz vein ore has higher content of these trace elements (FeO, PbO, Sb₂O₅ and As₂O₅) than dolomite (D₀) from wallrock. Dolomites correspond to Ferroan dolomite (D₀), and ankerite and Ferroan dolomite (D₁), respectively. The structural formular of chlorite from quartz vein ore is (Mg_1.65-1.08Fe_2.94-2.50Mn_0.01-0.00Zn_0.01-0.00Ni_0.01-0.00Cr_0.02-0.00V_0.01-0.00Hf_0.01-0.00Pb_0.01-0.00Cu_0.01-0.00As_0.03-0.00Ca_0.02-0.01Al_1.68-1.61)_5.77-5.73(Si_2.84-2.76Al_1.24-1.16)_4.00O₁₀(OH)₈. It indicated that chlorite of quartz vein ore is similar with theoretical chlorite and corresponds to Fe-rich chlorite. Compositional variations in chlorite from quartz vein ore are caused by mainly octahedral Fe²⁺ <-> Mg²⁺ (Mn²⁺) substitution and partly phengitic or Tschermark substitution (Al^3+,VI+Al^3+,IV <-> (Fe²⁺ 또는 Mg²⁺)^VI+(Si⁴⁺)^IV).

• 한국해양학회지
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• v.27 no.4
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• pp.277-289
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• 1992

Kyeonggi Bay, a macrotidal coastal embayment in the Yellow Sea coast of central korea, is fringed by vastly developed tidal flats. About 400 surface sediment samples were collected from the intertidal and subtidal zones of Kyeonggi Bay for a study of the sediment distribution pattern and the surface sediment characteristics of this environment. The kyeonggi Bay surface sediment becomes progressively finer in the shoreward direction, from offshore sand to shoreward silty sand and sandy silt. This shoreward-fining trend is repeated again on the tidal flat and, as a consequence, a grain-size break occurs near the low-water line which separates the intertidal area from the subtidal one. The intertidal and subtidal sediments differ from each other in textural characteristics such as mean grain size and skewness and this can be interpreted to result from differences in hydraulic energy and morphology between the two environments. The mineral and chemical compositions of the Kyeonggi Bay sediments are largely controlled by the sediment grain size. Smectite was nearly absent in the clay mineral assemblage of Kyeonggi Bay sediment. The contents of Co, Cu and Ni were high in the Banweol tidal flat, which suggests a continuous process of accumulation of these metals. the intertidal environment appears to respond rapidly to artificial coastal modifications, the effects of which should be taken into consideration when planning a dam construction or coastal reclamation.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.3
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• pp.404-409
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• 2012

In order to obtain optimum mixing conditions with animal cadaver residue and sawdust for composting using rendering treatment method for agricultural recycling, changes of chemical characteristics and compost quality after composting were investigated. Initial mixing ratios with animal cadaver residue and sawdust were adjusted 100 : 0, 50 : 50 and 30 : 70. Temperature, pH, contents of ammonia and carbon dioxide were rapidly increased in 3 days and then decreased with time. Organic matter content was similar in all conditions. In mixing ratio of 50 : 50, the compost quality was satisfied with compost depending on official standard for product fertilizer. Thus, the optimum mixing ratio of animal cadaver residue and sawdust were 50 : 50.

• 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.

• Economic and Environmental Geology
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• v.2 no.4
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• pp.23-71
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• 1969

Sediment samples were taken at about half-mile intervals from all the inajor rivers draining the St. Austell granite mass. The minus 80 mesh(B.S.S.) fraction of each sample was analysed, using semiquantitative methods, for sodium, potassium, lithium, phosphorus, nickel, chromium, tin, tungsten, arsenic copper, zinc and lead. The work was carried out with the view to gaining further information as to the geographical distribution of such different granite facies as might axist, and to investigate the geochemical dispersion of these elements with relation to mineralisation in this area. The sesults confirm Exley's suggestion that the mass consists of two major granite intrusions, the earlier undifferentiated one is joined on the west by a later differentiated intrutive. During the work grid deviation maps proved particularly useful in obtaining data concerning the nature of the granite but frequency diagrams were not particularly helpful. All the known lode areas were associated with stream sediments containing anomalously high concentrations of lode metals and it is concluded that these high concentrations are due premarily to lode material transferred to the streams in the form of tailings lost during milling operations.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.24 no.4
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• pp.547-555
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• 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.