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    Digitale Medien
    Digitale Medien
    Oxford, UK : Blackwell Science Ltd
    European journal of soil science 54 (2003), S. 0 
    ISSN: 1365-2389
    Quelle: Blackwell Publishing Journal Backfiles 1879-2005
    Thema: Geologie und Paläontologie , Land- und Forstwirtschaft, Gartenbau, Fischereiwirtschaft, Hauswirtschaft
    Notizen: Risk assessment of heavy metals in soil requires an estimate of the concentrations in the soil solution. In spite of the numerous studies on the distribution of Cd and Zn in soil, few measurements of the distribution coefficient in situ, Kd, have been reported. We determined the Kd of soils contaminated with Cd and Zn by measuring metal concentrations in the soil and in the soil solution and attempted to predict them from other soil variables by regression. Soil pH explained most of the variation in logKd (R2 = 0.55 for Cd and 0.70 for Zn). Introducing organic carbon content or cation exchange capacity (CEC) as second explanatory variable improved the prediction (R2 = 0.67 for Cd and 0.72 for Zn), but these regression models, however, left more than a factor of 10 of uncertainty in the predicted Kd. This large degree of uncertainty may partly be due to the variable degree of metal fixation in contaminated soils. The labile metal content was measured by isotopic dilution (E value). The E value ranged from 18 to 92% of the total metal content for Cd and from 5 to 68% for Zn. The prediction of Kd improved when metals in solution were assumed to be in equilibrium with the labile metal pool instead of the total metal pool. It seems necessary therefore to discriminate between ‘labile’ and ‘fixed’ pools to predict Kd for Cd and Zn in field contaminated soils accurately. Dilute salt extracts (e.g. 0.01 m CaCl2) can mimic soil solution and are unlikely to extract metals from the fixed pool. Concentrations of Cd and Zn in the soil solution were predicted from the concentrations of Cd and Zn in a 0.01 m CaCl2 extract. These predictions were better correlated with the observations for field contaminated soils than the predictions based on the regression equations relating logKd to soil properties (pH, CEC and organic C).
    Materialart: Digitale Medien
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
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