Heavy metal speciation with prediction model for heavy metal mobility and risk assessment in mine-affected soils

Authors
Ahn, YongtaeYun, Hyun-ShikPandi, KalimuthuPark, SanghyunJi, MinkyuChoi, Jaeyoung
Issue Date
2020-01
Publisher
SPRINGER HEIDELBERG
Citation
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, v.27, no.3, pp.3213 - 3223
Abstract
Heavy metals from mines affect the soil and groundwater, and cause and severely impact on the health of local residents. The soil samples were characterized for the distribution and by the chemical speciation method, and then estimated the human health risks of the two mineaffected soils after stabilization process.. Two extraction techniques (Tessier and Wenzel methods) were applied to fractionate metals, such as arsenic (As) and zinc (Zn), to quantify the chemical status of metals in the soils. The mobility of As and Zn was predicted using the ASTM test and sequential extraction (Tessier and Wenzel) method results. The correlation coefficients of As and Zn mobility prediction using Tessier and Wenzel Fraction 1 were 0.920 and 0.815, respectively. The sum of fractions F1 + F2 + F3 showed the highest correlation coefficients value and F value for mobility prediction of both As and Zn. The hazardous indices (HI) for non-carcinogenic risk and carcinogenic risk (CR) to humans were evaluated according to the pseudo-total concentrations of metal in soils. The CR values of carcinogenic for As were within the ranges from 1.38 x 10(-4) to 1.25 x 10(-3) and 3.71 x 10(-4) to 3.35 x 10(-3) for both Young Dong (YD) and Dea San (DS), respectively. The HI for non-carcinogenic risk was the highest for As in the YD (2.77) and DS (7.46) soils, which covered approximately 96 and 84% of HI, respectively. In summary, the contribution of As to risk from heavy metals was dominant.
Keywords
TRACE-METALS; SURFACE SEDIMENTS; POLLUTION; WATER; BIOAVAILABILITY; RIVER; CONTAMINATION; SIZE; TRACE-METALS; SURFACE SEDIMENTS; POLLUTION; WATER; BIOAVAILABILITY; RIVER; CONTAMINATION; SIZE; Heavy metals; Mobility prediction; Risk assessment; Mine-affected soil; Sequential extraction method; Arsenic; Zinc
ISSN
0944-1344
URI
https://pubs.kist.re.kr/handle/201004/119121
DOI
10.1007/s11356-019-06922-0
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KIST Article > 2020
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