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Econ. Environ. Geol. 2022; 55(4): 339-352

Published online August 30, 2022

https://doi.org/10.9719/EEG.2022.55.4.339

© THE KOREAN SOCIETY OF ECONOMIC AND ENVIRONMENTAL GEOLOGY

Geochemical Occurrence Characteristics of Geogenic Heavy Metals in Korea Evaluated Using Geochemical Map Data

Joo Sung Ahn, Seung-Jun Youm*, Yong-Chan Cho, Gil-Jae Yim, Sang-Woo Ji, Jung-Hwa Lee, Pyeong-Koo Lee, Jeong-Ho Lee, Seong-Cheon Shin

Korea Institute of Geoscience and Mineral Resources, Daejeon 34132, Republic of Korea

Received: August 11, 2022; Revised: August 22, 2022; Accepted: August 22, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided original work is properly cited.

Abstract

As environmental criteria items are increased or strengthened, cases of heavy metal contamination by geogenic origin are increasing, and the need to distinguish between natural and anthropogenic origins in soil or groundwater exceeding the standard is increasing. In this study, geochemical occurrences of geogenic heavy metals were identified through statistical processing of the national geochemical map data and evaluation of geochemical characteristics of regions with high geoaccumulation indices. Cobalt, Cr, Cu, Ni, Pb, V, and Zn were targeted for which the national geochemical maps were prepared, and Co, Cr, Ni, and V derived from ultrabasic or ultramafic rocks were classified as factor 1. Copper, Pb and Zn of non-ferrous sulfide origin were classified as factor 2. In particular, enrichment of heavy metals by factor 1 occurs mainly in the serpentine distribution areas of the Chungcheong region, and there is a risk of contamination in neighboring areas. In the case of factor 2, geogenic occurrence is concerned not only in non-ferrous metal mineralization areas such as Taebacksan and Gyeongnam mineralization zones, but also in Au-Ag mineralization areas distributed nationwide.

Keywords heavy metals, geogenic origin, ultrabasic rocks, non-ferrous sulfides, geochemical map

전국 지화학도 자료를 이용한 지질기원 중금속의 지화학적 발생특성

안주성 · 염승준* · 조용찬 · 임길재 · 지상우 · 이정화 · 이평구 · 이정호 · 신성천

한국지질자원연구원

요 약

환경 기준 항목이 증가하거나 강화되면서 지질기원에 의한 중금속 오염사례가 증가하고 있으며, 토양이나 지하수의 기준치 초과양상에서 자연적 기원인지 인위적 기원인지 구분해야 할 필요성이 높아지고 있다. 본 연구에서는 전국 지화학도 자료에 대한 통계적 처리와 높은 지질축적지수 분포 지역의 지화학적 특성을 평가하여 중금속 원소들의 지질기원 발생요인을 규명하였다. 지화학도가 작성된 Co, Cr, Cu, Ni, Pb, V, Zn 등을 대상으로 하였으며, 초염기성암 또는 초고철질암에서 기원한 Co, Cr, Ni, V이 요인 1로, 비철금속 황화광물에 기인한 Cu, Pb, Zn가 요인 2로 구분되어졌다. 특히 충청지역의 사문암체 분포지역에서 요인 1에 의한 중금속 지질기원 부화현상이 주로 나타나며 이를 포함한 인근지역에서도 오염 위험이 있다. 요인 2의 경우 태백산 및 경남 광화대 등지의 비철금속 광화지역 뿐만 아니라 국내의 전반적인 금-은 광화대 지역에서도 지질기원 부화현상이 우려된다.

주요어 중금속, 지질기원, 초염기성암, 비철금속 황화광물, 지화학도

Article

Research Paper

Econ. Environ. Geol. 2022; 55(4): 339-352

Published online August 30, 2022 https://doi.org/10.9719/EEG.2022.55.4.339

Copyright © THE KOREAN SOCIETY OF ECONOMIC AND ENVIRONMENTAL GEOLOGY.

Geochemical Occurrence Characteristics of Geogenic Heavy Metals in Korea Evaluated Using Geochemical Map Data

Joo Sung Ahn, Seung-Jun Youm*, Yong-Chan Cho, Gil-Jae Yim, Sang-Woo Ji, Jung-Hwa Lee, Pyeong-Koo Lee, Jeong-Ho Lee, Seong-Cheon Shin

Korea Institute of Geoscience and Mineral Resources, Daejeon 34132, Republic of Korea

Received: August 11, 2022; Revised: August 22, 2022; Accepted: August 22, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided original work is properly cited.

Abstract

As environmental criteria items are increased or strengthened, cases of heavy metal contamination by geogenic origin are increasing, and the need to distinguish between natural and anthropogenic origins in soil or groundwater exceeding the standard is increasing. In this study, geochemical occurrences of geogenic heavy metals were identified through statistical processing of the national geochemical map data and evaluation of geochemical characteristics of regions with high geoaccumulation indices. Cobalt, Cr, Cu, Ni, Pb, V, and Zn were targeted for which the national geochemical maps were prepared, and Co, Cr, Ni, and V derived from ultrabasic or ultramafic rocks were classified as factor 1. Copper, Pb and Zn of non-ferrous sulfide origin were classified as factor 2. In particular, enrichment of heavy metals by factor 1 occurs mainly in the serpentine distribution areas of the Chungcheong region, and there is a risk of contamination in neighboring areas. In the case of factor 2, geogenic occurrence is concerned not only in non-ferrous metal mineralization areas such as Taebacksan and Gyeongnam mineralization zones, but also in Au-Ag mineralization areas distributed nationwide.

Keywords heavy metals, geogenic origin, ultrabasic rocks, non-ferrous sulfides, geochemical map

전국 지화학도 자료를 이용한 지질기원 중금속의 지화학적 발생특성

안주성 · 염승준* · 조용찬 · 임길재 · 지상우 · 이정화 · 이평구 · 이정호 · 신성천

한국지질자원연구원

Received: August 11, 2022; Revised: August 22, 2022; Accepted: August 22, 2022

요 약

환경 기준 항목이 증가하거나 강화되면서 지질기원에 의한 중금속 오염사례가 증가하고 있으며, 토양이나 지하수의 기준치 초과양상에서 자연적 기원인지 인위적 기원인지 구분해야 할 필요성이 높아지고 있다. 본 연구에서는 전국 지화학도 자료에 대한 통계적 처리와 높은 지질축적지수 분포 지역의 지화학적 특성을 평가하여 중금속 원소들의 지질기원 발생요인을 규명하였다. 지화학도가 작성된 Co, Cr, Cu, Ni, Pb, V, Zn 등을 대상으로 하였으며, 초염기성암 또는 초고철질암에서 기원한 Co, Cr, Ni, V이 요인 1로, 비철금속 황화광물에 기인한 Cu, Pb, Zn가 요인 2로 구분되어졌다. 특히 충청지역의 사문암체 분포지역에서 요인 1에 의한 중금속 지질기원 부화현상이 주로 나타나며 이를 포함한 인근지역에서도 오염 위험이 있다. 요인 2의 경우 태백산 및 경남 광화대 등지의 비철금속 광화지역 뿐만 아니라 국내의 전반적인 금-은 광화대 지역에서도 지질기원 부화현상이 우려된다.

주요어 중금속, 지질기원, 초염기성암, 비철금속 황화광물, 지화학도

    Fig 1.

    Figure 1.Stream distributions and sampling locations of the Geochemical Atlas of Korea (KIGAM, 2007).
    Economic and Environmental Geology 2022; 55: 339-352https://doi.org/10.9719/EEG.2022.55.4.339

    Fig 2.

    Figure 2.Boxplots of heavy metal concentrations of the Geochemical Atlas of Korea (KIGAM, 2007).
    Economic and Environmental Geology 2022; 55: 339-352https://doi.org/10.9719/EEG.2022.55.4.339

    Fig 3.

    Figure 3.Spatial distributions of the heavy metals in the stream sediments of the Korea (redrawn from KIGAM(2007)).
    Economic and Environmental Geology 2022; 55: 339-352https://doi.org/10.9719/EEG.2022.55.4.339

    Fig 4.

    Figure 4.Dendrogram of the selected elements.
    Economic and Environmental Geology 2022; 55: 339-352https://doi.org/10.9719/EEG.2022.55.4.339

    Fig 5.

    Figure 5.Spatial distribution of geoaccumulation index (Igeo) for each heavy metal.
    Economic and Environmental Geology 2022; 55: 339-352https://doi.org/10.9719/EEG.2022.55.4.339

    Fig 6.

    Figure 6.Spatial distribution of averaged geoaccumulation index (Igeo_averaged) for the Factor-1 and Factor–2 elements.
    Economic and Environmental Geology 2022; 55: 339-352https://doi.org/10.9719/EEG.2022.55.4.339

    Fig 7.

    Figure 7.Sampling points marked on topographic map at the time of sampling in the Bonghwa-gun area with Igeo_averaged for the Factor-2 greater than 3.0 (SC41, 43, 44, 45GB samples).
    Economic and Environmental Geology 2022; 55: 339-352https://doi.org/10.9719/EEG.2022.55.4.339

    Fig 8.

    Figure 8.Spatial representation of factor scores of the principal component analysis.
    Economic and Environmental Geology 2022; 55: 339-352https://doi.org/10.9719/EEG.2022.55.4.339

    Table 1 . Selected element concentrations of the Geochemical Atlas of Korea (KIGAM, 2007; mg/kg except for the major component in %).

    nminQ25meanmedianQ75Q90maxstdUpper Continental Crust*
    CaO23,5420.110.731.661.181.892.9953.12.235.5
    Fe2O323,5430.304.485.945.717.138.4951.02.186.28
    K2O23,5430.082.603.083.043.504.017.770.742.4
    MgO23,5430.040.911.511.331.822.4218.01.033.7
    MnO23,5390.010.080.120.100.130.187.770.110.10
    TiO223,5410.050.680.850.810.951.158.960.330.68
    Co15,1420.199.0114.113.117.522.63378.4811.6
    Cr15,1411.5346.083.071.61041401,50062.935
    Cu23,5021.0016.628.023.132.545.02,10029.214.3
    Li23,5464.9431.047.842.758.076.657425.422
    Ni23,4650.2914.824.621.431.042.049215.918.6
    Pb23,4155.2021.627.226.531.036.01,36015.217
    V23,5482.1049.071.566.886.01101,00036.153
    Zn15,1392.1178.513910714921221,10033552

    n: number of samples; min: minimum; max: maximum; Q25, Q75, and Q90: 25th, 75th, and 90th percentiles of the data set, respectively; std: standard deviation;.

    *Wedepohl (1995).


    Table 2 . Pearson’s correlation between the selected elements.

    CaO Fe2O3K2OMgOMnOTiO2CoCrCuLiNiPbV
    Fe2O3.127**
    K2O-.246**-.335**
    MgO.483**.431**-.314**
    MnO.102**.284**-.140**.092**
    TiO2.052**.660**-.291**.268**.143**
    Co.101**.565**-.288**.405**.212**.359**
    Cr.021**.346**-.156**.420**.010.216**.514**
    Cu.046**.205**-.023**.143**.129**.104**.164**.120**
    Li-.042**.036**.153**.045**.009.014*.056**-.010.105**
    Ni.013*.375**-.097**.418**.055**.218**.481**.604**.244**.098**
    Pb.050**.119**.053**.033**.126**.016*.058**.023**.203**.037**.106**
    V.093**.688**-.376**.343**.150**.562**.423**.267**.222**.033**.362**.083**
    Zn.095**.121**-.046**.032**.396**-.005.075**.009.163**.018*.016.573**.020*

    ** Correlation is significant at the 0.01 level (2-tailed).

    * Correlation is significant at the 0.05 level (2-tailed).

    Bold values represent significant correlations..


    Table 3 . Results of the principal component analysis on the selected elements.

    Factor-1Factor-2Factor-3
    CaO.175.164.556
    Fe2O3.761.195.284
    K2O-.363.020-.628
    MgO.657.039.270
    MnO.096.555.300
    TiO2.582.007.334
    Co.750.102.033
    Cr.715-.063-.263
    Cu.309.355-.242
    Li.103.096-.376
    Ni.752.041-.349
    Pb.030.774-.178
    V.695.080.230
    Zn-.038.877.044
    Eigen value3.9991.7841.405
    Explained variance (%)28.56312.74110.036
    Explained cumulative variance (%)28.56341.30451.340

    Extraction method : principal component analysis.

    Rotation method : Varimax with Kaiser normalization.

    Bold values represent dominant elements in each factor..


    Table 4 . Samples with greater than 2.0 of Igeo_averaged for the Factor-1 elements.

    Sample IDAddressIgeo_averaged
    YS92CNChugye-ri, Yugu-eup, Gongju-si2.751
    YS93CNChugye-ri, Yugu-eup, Gongju-si2.646
    YW156GNCheonsang-ri, Beomseo-eup, Ulju-gun2.434
    SR106CBUngyo-ri, Cheongcheon-myeon, Goesan-gun2.400
    BN169JNEundeok-ri, Gyeombaek-myeon, Boseong-gun2.304
    BE24CBSongpyeong-ri, Hoein-myeon, Boeun-gun2.264
    HS97CNCheonggwang-ri, Guhang-myeon, Hongseong-gun2.178
    JW75CNDonghae-ri, Yugu-eup, Gongju-si2.112

    Igeo_averaged = [Igeo_Co + Igeo_Cr + Igeo_Ni + Igeo_V]/4.


    Table 5 . Samples with greather than 3.0 of Igeo_averaged for the Factor-2 elements.

    Sample IDAddressIgeo_averagedNote
    PC88GWDaesang-ri, Pyeongchang-eup, Pyeongchang-gun5.400
    CW98GNWeolgye-ri, Dong-eup, Changwon-si5.088Guryong mine
    DS96CBYulji-ri, Susan-myeon, Jecheon-si4.442Geumpoong mine
    SC44GBGalsan-ri, Jaesan-myeon, Bonghwa-gun4.391Sanmak mine
    AW11GGGahak-dong, Gwangmyeong-si4.277Siheung mine
    GS85CNGurae-ri, Boksu-myeon, Geumsan-gun4.152
    SC45GBGalsan-ri, Jaesan-myeon, Bonghwa-gun3.306Janggun, Ilweol, Sanmak, Eunjeom mines
    SC43GBGalsan-ri, Jaesan-myeon, Bonghwa-gun3.282
    SC41GBGalsan-ri, Jaesan-myeon, Bonghwa-gun3.239
    JS156GWPunggog-ri, Gagok-myeon, Samcheok-si3.1732nd Yeonhwa mine
    JJ132JBSin-ri, Sanggwan-myeon, Wanju_Gun3.154

    Igeo_averaged = [Igeo_Cu + Igeo_Pb + Igeo_Zn]/3.

    Note : nearest non-ferrous metal mines developed.


    KSEEG
    Apr 30, 2024 Vol.57 No.2, pp. 107~280

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