Abstract
Different fractions of Ni, Zn, Cu and Pb were determined in metal-spiked forest soils derived from four parent materials using three extractants (H2O, CaCl2 and diethylenetriaminepentaacetic acid (DTPA)). It is important to determine how parent materials and soil properties affect the retention of these metals in order to predict their behavior and act accordingly in the event of accidental spillage, for example. The extraction of fractions was not sequential (before carrying out the extractions, the soil samples were divided into three parts), so the CaCl2 fraction also included the H2O one, and the DTPA fraction contained the other two. With the results, we developed models to predict the extraction of each fraction employing the physicochemical characteristics of the soil (e.g., pH, organic matter content and texture values) and the amount of metal added. The objective of this work was to determine how the properties of the soil would influence the fractioning of the metals considered, and through these characteristics create models to predict the behavior of each metal fraction. We found correlations between the different fractions of Ni and Zn, suggesting that there are soil properties that condition the retention of both metals. Pb and Cu showed different behavior than Zn or Ni, since the proportions extracted by H2O and CaCl2 were much lower. Regarding the DTPA fraction, unlike the case of Ni or Zn, the extraction of Cu and Pb was more homogeneous; they did not show great variation in different soils, even when considering the results of extraction in limestone soils. This may be due to the fact that the soil properties do not exert an important effect on their availability, or these two metals are considerably sensitive to the effect of pH, and no differences were observed because the extraction of the DTPA fraction was conducted with a buffered solution. For each fraction of metal used, we obtained a model with R2 always greater than 0.65. Considering these results, we can conclude that it is possible to predict Zn, Ni, Cu and Pb availability in soils developed on different parent materials. This can be achieved by identifying some basic soil characteristics and applying the developed equations.
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