Influence of sediment grain size and land use on the distributions of heavy metals in sediments of the han river basin in korea and the assessment of anthropogenic pollution

Tien M. Lai, Wonkyo Lee, Jin Hur, Younghun Kim, In Ae Huh, Hyun Sang Shin, Chan Kook Kim, Jong Hyun Lee

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38 Scopus citations

Abstract

The influence of sediment grain size and land use was examined on the distribution of Cr, Ni, Zn, Pb, Cd, Cu, As, and Hg in the sediments collected from 19 subbasins of the Han River Basin, Korea. The degree of anthropogenic pollution of the heavy metals was also evaluated using the enrichment factor and geoaccumulation index based on local geochemical background concentrations. Except for Zn and Al, all the metals investigated showed significant correlations with the fine silt fraction of the sediments, suggesting that grain size distribution may contribute to the enrichment of the metals. Close association of the metal concentrations with a percentage of urban area in the subbasin was exhibited only for Cd, Cu, Hg, and Pb. The two pollution indices revealed that most of the sediments could be classified into a category of "unpolluted to moderately polluted," except for a subbasin with the highest percentage of urban area, which was highly polluted with Cu, Hg, and Pb. No relationship was observed between agricultural land use and the enrichment of metals. Principal component analysis showed that a combination of grain size distribution and percent urban area were responsible for 55 % of the variance of the metal distribution. Cluster analysis revealed that the sources of As might be different from the other metals. Multiple regression analyses based on fine silt fraction and percent urban area resulted in a good estimation of the concentrations of Cd, Cu, Hg, and Pb (r > 0.7, p < 0.005).

Original languageEnglish
Article number1609
JournalWater, Air, and Soil Pollution
Volume224
Issue number7
DOIs
StatePublished - Jul 2013

Keywords

  • Enrichment factor
  • Geochemical background
  • Land use
  • Metal pollution
  • Multivariate statistical analyses
  • River sediments

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