Metal leachability and anthropogenic signal in roadside soils estimated from sequential extraction and stable lead isotopes

被引:67
作者
Bäckström, M [1 ]
Karlsson, S [1 ]
Allard, B [1 ]
机构
[1] Univ Orebro, Man Technol Environm Res Ctr, Orebro, Sweden
关键词
anthropogenic signal; lead; lead isotopes; roadside soils; tungsten;
D O I
10.1023/B:EMAS.0000003572.40515.31
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Several roadside soil samples were collected at two field sites in Sweden. They were analysed for total elemental content (using both ICP-MS and XRF) and stable lead isotopes. Extraction with deicing salt solution and sequential extraction were performed in order to elucidate the potential mobility due to the use of deicing agents. The total concentrations of elements, especially lead, have decreased and lead is presently almost at background concentrations (15 - 51 ppm for surface samples). However, the isotopic signature indicates that old gasoline lead still is left at the site constructed prior to 1975. The field site constructed in 1992 showed, however, no Pb-206/Pb-207 ratio below 1.14. Only minor amounts were leached using deicing salt solutions; for lead only 0.29%, on average, was extracted indicating that the mobile fraction already was released. Sequential extraction indicated that lead mainly was associated with reducible (34.4%) and oxidisable (35.4%) fractions. Exchangable and acid soluble fractions contained 20.3% while 10.0% was found in the residual fraction. The salt extraction released, however, very low concentrations indicating that most in fraction 1 is acid soluble (e.g. carbonates). Tungsten was also found at high concentrations indicating a possible impact from studded tires. For tungsten the following composition was obtained: residual (48.0%) > oxidisable (47.6%) > reducible (3.3%) > exchangeable/ acid soluble (1.1%). From the isotopic studies it was also suggested that the order for incorporating anthropogenic lead into soils is exchangeable/ carbonates > (hydr) oxides > organic matter > residual. The multivariate technique principal component analysis (PCA) seems promising for evaluating large sequential extraction datasets.
引用
收藏
页码:135 / 160
页数:26
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