Assessment of enrichment factors and grain size influence on the metal distribution in riverbed sediments (Anllons River, NW Spain)

被引:47
作者
Devesa-Rey, Rosa [1 ]
Diaz-Fierros, Francisco [1 ]
Barral, Maria T. [1 ]
机构
[1] USC, Dept Edafol & Quim Agr, Fac Farm, Santiago De Compostela 15782, Spain
关键词
Metals; Non-geogenic; Sediments; Enrichment factor; Pseudo-sands; Grain size; HEAVY-METALS; ORGANIC-MATTER; SURFICIAL SEDIMENTS; BED SEDIMENTS; IRON-OXIDES; POLLUTION; BIOAVAILABILITY; ELEMENTS; GALICIA; SURFACE;
D O I
10.1007/s10661-010-1742-7
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The metals distribution in the bed sediments of the Anllns River was studied, with special emphasis on the evaluation of the metal distribution as a function of the granulometric fraction chosen for the analysis. Statistical significant differences between the distribution of K, Ca, Cr, Mn, As, Rb, Sr and Nb in the bulk (< 2 mm) and fine fraction (< 63 mu m) were not found. Fe, Ni, Cu, Ga, Zr, Zn and Pb commonly appear in higher concentrations in the fine fraction, whereas Ti appears in higher concentrations in the bulk fraction. In general, it was observed that contamination phenomena tend to equalise the concentrations of both fractions, and this was mainly explained as the result of two processes. First, the formation of coatings over sands and, second, the formation of large aggregates (pseudo-sands) at sites located over basic rocks, whose chemical behaviour is closer to that of clays and could be responsible for significant adsorption processes. Normalisation techniques to evaluate contamination were applied by testing Nb, Sr, Rb or Ga as normaliser elements and by using crustal or shale average values for background concentrations. The most satisfactory result was obtained when using shale average values and Ga as the normaliser element. Arsenic was identified as the main contaminant of the basin, exceeding in all cases the low-effect reference values proposed by sediment quality guidelines and in two cases the medium-effect reference values. These sites were identified by multivariate techniques, which allow differentiating site 10 as affected by anthropogenic inputs related to past mining activities.
引用
收藏
页码:371 / 388
页数:18
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