• 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.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.1
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• pp.33-41
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• 2001

Enormous volumes of mining wastes from the abandoned and closed mines are disposed without a proper treatment in the upper Okdong River basin at Southeastern part of Kangwon Province. Erosion of these wastes contaminates soil, surface water, and sediments with heavy metals. Objectives of this research were to fractionate heavy metals in the mine tailing stored in the Sangdong Tungsten tailing dams and to assess the potential pollution index of each metal fraction. Tailing samples were collected from tailing dams at different depth and analyzed for physical and chemical properties. pH of tailings ranged from 7.3 to 7.9. Contents of total N and organic matter were in the ranges of 3.2~5.5%, and 1.3~9.1%, respectively. Heavy metals in the tailings were higher in the newly constructed tailing dam than those in the old dam. Total concentrations of metals in the tailings were in the orders of Zn > Cu > Pb > Ni > Cd, exceeded the corrective action level of the Soil Environment Conservation Law and higher than the natural abundance levels reported from uncontaminated soils. Relative distribution of heavy metal fractions was residual > organic > reducible > carbonate > adsorbed, reversing the degree of metal bioavailability. Mobile fractions of metals were relatively small compared to the total concentrations. Distribution of metals in the tailing dam profiles was metal specific. Concentrations of Cu at the surface of tailing dams were higher than those at the bottom. Pollution index (PI) values of each fraction of metals were ranged from 4.27 to 8.51 based on total concentrations. PI values of mobile fractions were lower than those of immobile fractions. Results on metal fractions and PI values of the tailing samples indicate that tailing samples were contaminated with heavy metals and had potential to cause a detrimental effects on soil and water environment in the lower part of the stream. A prompt countermeasure to prevent surface of tailings in the dams from water and wind erosions is urgently needed.

• Korean Journal of Environmental Agriculture
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• v.34 no.1
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• pp.6-13
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• 2015

BACKGROUND: Most of the tailings have been left without any management in abandoned metalliferous mines and have become the main source of heavy metal contamination for agricultural soils and crops in the these areas. METHODS AND RESULTS: This experiment was carried out to investigate the assessment of the heavy metal contamination in paddy soils located on downstream of the closed metalliferous mine. The average total concentrations of cadmium (Cd), copper (Cu), lead (Pb), zinc (Zn), and arsenic (As) in paddy soils were 8.88, 56.7, 809, 754, and 37.9 mg/kg, respectively. Specially, the average concentrations of Cd, Pb and Zn were higher than those of warning criteria for soil contamination(4 mg/kg for Cd, 200 mg/kg for Pb, and 300 mg/kg for Zn) in agricultural soil established by Soil Environmental Conservation Act in Korea. The proportions of 0.1 M HCl extractable Cd, Cu, Pb, Zn, and As concentration to total concentration of these heavy metals in paddy soils were 27.7, 21.3, 35.1, 13.8 and 10.5%, respectively. The pollution index of these five metals in paddy soils ranged from 0.42 to 11.92. Also, the enrichment factor (EFc) of heavy metals in paddy soils were in the order as Cd>Pb>Zn>Cu>As, and the enrichment factor in paddy soil varied considerably among the sampling sites. The geoaccumulation index (Igeo) of heavy metals in soils were in the order as Cd>Pb>Zn>Cu>As, specially, the average geoaccumulation index of Cd, Pb, and Zn (Igeo 2.49~3.10) were relatively higher than that of other metals in paddy soils. CONCLUSION: Based on the pollution index, enrichment factor, and geoaccumulation index for heavy metal in paddy soils located on downstream of closed metalliferous mine, the main contaminants are mine waste materials and mine drainage including mine activity.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1227-1240
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• 2014

Abandoned mines often cause environmental problems, such as alteration of landscape, metal contamination, and landslides due to a heavy rainfall. Geotechnical and rheological tests were performed on waste materials corrected from Imgi waste rock dump, located in Busan Metropolitan City. Debris flow mobility was examined with the help of 1-D BING model which was often simulated in both subaerial and subaqueous environments. To determine flow curve, we used a vane-penetrated rheometer. The shear stress (${\tau}$)-shear rate (${\dot{\gamma}}$) and viscosity(${\eta}$)-shear rate (${\dot{\gamma}}$) relationships were plotted using a shear stress control mode. Well-known rheological models, such as Bingham, bilinear, Herschel-Bulkley, Power-law, and Papanastasiou concepts, were compared to the rheological data. From the test results, we found that the tested waste materials exhibited a typical shear shinning behavior in ${\tau}$-${\dot{\gamma}}$ and and ${\eta}$-${\dot{\gamma}}$ plots, but the Bingham behavior is often observed when the water contents increased. The test results show that experimental data are in good agreement with rheological models in the post-failure stage during shearing. Based on the rheological properties (i.e., Bingham yield stress and viscosity as a function of the volumetric concentration of sediment) of waste materials, initial flowing shape (5 m, 10 m, and 15 m) and yield stress (100 Pa, 200 Pa, 300 Pa, and 500 Pa) were input to simulate the debris flow motion. As a result, the runout distance and front velocity of debris flow are in inverse propositional to yield stress. In particular, when the yield stress is less than 500 Pa, most of failed masses can flow into the stream, resulting in a water contamination.

• Economic and Environmental Geology
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• v.38 no.4 s.173
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• pp.451-462
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• 2005

In order to examine the extent of environmental contamination at abandoned Samsanjeil Cu mines in Kosung-kun, Kyeongsangnam-do, we have investigated the contaminations and mobility of toxic trace elements from mine wastes including about 280,000 tonnages of tailings by chemical experiments (total extraction, partial extraction by 0.1N HCI and sequential extraction procedure). Total concentrations of trace elements showed that Cu, As, Co, Zn, Pb, and Cd concentrations in tailings were 14.0, 3.6, 3.1, 2.1, 2.1 and 1.6 times greater than those in background soil, respectively. From the proportion of metals bound to the exchangeable and carbonate fractions, the comparative mobility of metals decrease in order of $Zn(29.0\%)>Cu(12.3\%)Pb(9.6\%)>Cd(3.0\%)>As=Co(0.0\%)$. Based on the concentrations, chemical speciations of tailings, waste rock and nearby soil, it was revealed that Cu and Zn were the most possible elements to contaminate the surrounding environment in Samsanjeil mine area. In addition, the tailings had total trace metal concentrations below Dutch guideline values except Cu, and they might not affect adverse impact on environment.

• Economic and Environmental Geology
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• v.48 no.4
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• pp.337-349
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• 2015

This study has focused on investigation of correlation for As and heavy metals in paddy soil and rice crops sampled in the vicinity of the abandoned Munmyung Au-Ag mine. Soil samples extracted by various methods including aqua regia, 1 M $MgCl_2$, 0.01 M $CaCl_2$ and 0.05 M EDTA were analyzed for As and heavy metals (Cd, Cu, Pb and Zn). Rice grain samples grown on the soils were also analyzed for the same elements to evaluate the relationships between soils and rice crops. According to soil extraction methods, As and heavy metal contents in the soils were decreased in the order of aqua regia > 0.01 M $CaCl_2$ > 1 M $MgCl_2$ > 0.05 M EDTA. In addition to correlation analysis, statistically significant correlation with the four extraction methods (p<0.01) were found in the soil and rice samples. As calculation of biological accumulation coefficients (BACs) of the rice crops for As and heavy metals, the BACs for Cd, Zn and Cu were relatively higher than those for As and Pb. This study also carried out a stepwise multiple linear regression analysis to identify the dominant factors influencing metal extraction rates of the paddy soils. Furthermore, daily intakes of As and heavy metals from regularly consumed the rice grain (287 g/day) grown on the contaminated soils by the mining activities were estimated, and found that Cd and As intakes from the rice reached up to 73.7% and 51.8% for maximum allowance levels of trace elements suggested by WHO, respectively. Therefore, long-term consumption of the rice poses potential health problems to residents around the mine, although no adverse health effects have yet been observed.

• Economic and Environmental Geology
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• v.37 no.1
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• pp.73-86
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• 2004

In order to estimate the post-ingestion bioavailability of heavy metals and to assess the risk of adverse health effects on human exposure to toxic heavy metals, environmental geochemical surveys were undertaken around the Dogok Au-Ag-Cu and the Hwacheon Au-Ag-Pb-Zn mine sites. Human risk assessment of toxic heavy metals was performed with the results of the SBET(simple bioavailability extraction test) analysis for soil and chemical analytical data for crop plant and water. Arsenic and other heavy metals were highly elevated in tailings from the Dogok(218 As mg/kg, 90.2 Cd mg/kg, 3,053 Cu mg/kg, 9,473 Pb mg/kg, 14,500 Zn mg/kg) and the Hwacheon(72 As mg/kg, 12.4 Cd mg/kg. 578 Pb mg/kg, 1,304 Zn mg/kg) mines. These significant concentrations can impact on soils and waters around the tailing dumps. The quantities of As, Cd and Zn extracted from paddy soils in the Hwacheon mine using the SBET analysis were 55.4%, 20.8% and 26.4% bioavailability, respectively, and for farmland soils in the Dogok mine, 40.8%, 37.6% and 33.0% bioavailability, respectively. From the results of human risk assessment, HI(Hazard Index) value exceeded 1.0 for As in the Hwacheon mine and for Cd in the Dogok mine. Thus, toxic risks for As and Cd exist via exposure(ingestion) of contaminated soil, water and rice grain in these mine sites. The cancer risk for As by the consumption of rice and groundwater in the Hwacheon mine area was 8E-4 and 1E-4, respectively. This risk level exceeds the acceptable risk(1 in 100,000) for regulatory purpose. Therefore, regular ingestion of locally grown rice and ground-water by the local population can pose a potential health threat due to long-term arsenic exposure.

• Economic and Environmental Geology
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• v.36 no.6
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• pp.469-480
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• 2003

Laboratory leaching experiment study carried out to estimate a extent of heavy metals that could be leached out when acid rain(pH 5.0-3.0) and strong acidic solution(pH 2.5-1.0) reacted with tailings and contaminated soils from abandoned metal mines. In slightly to moderately acid conditions(pH 5.0-3.0), As, Pb and Zn dissolutions became significantly increased with decreased pH in tailing, while dissolution of these elements was very limited in contaminated soil. These results suggested that moderately acid rainwater leaches Pb, As and Zn from the tailings, while these elements would remain fixed in contaminated soil. In the pH range of 2.5-1.0(strongly acid condition), Zn, Cd and Cu concentrations of leachate rapidly increased with decreased pH in contaminated soil, while Pb, As and Co dissolutions became importantly increased in tailings. The experimental solubility of Zn. Cd and Cu was very low even at very low pH values(up to pH 1), except for CY4(Cheongyang mine). These can result from an incomplete dissolution or the presence of less soluble mineral phases. So, the solubility of heavy metals depends not only on the pH values of leachate but also on the speciation of metals associated with contaminated soils and tailings. The relative mobility of each element within failings at the pH 5.0-3.0 of the reaction solution was in the order of Pb>Zn>Cd>Co=Cu>As. In case of pH 2.5-1.0 of the reaction solution, the relative mobility of each element within contaminated soils and tailings were in the order of Zn＞Cd>Cu>Co>Pb=As for contaminated soils, and Pb>Zn>Cd>hs>Co>Cu for tailings. The obtained results could be useful for assessing the environmental effects and setting up the restoration plan in the areas.