Concentration of the mobile forms (MF) of heavy metals (HM) in soils is one of major parameters, determined at soil-chemical monitoring of natural environment. Participating in migration processes, these forms are responsible to potential danger of soil, plant, groundwater pollution. Therefore there is a need of the forecast methods development of HM mobilization due to the natural and man-induced factors.
The aim of the present study is the modelling of variations of MF contents of Mn, Zn, Pb, Cu, Co, Cr, Ni depending on the main soil and geochemical parameters. For quantitative description of these relationships multivariate regression analysis was applied.
The derived equations incorporate acid-base conditions, redox status, organic matter content, bulk amounts of each element as the factors. The texture factor was not taken into account as we have studied only loamy soils which occupy extensive areas within the investigated region.
Soils of background landscapes in southern taiga of the Smolensk-Moscow Upland were our first study object. This area has physiographic conditions typical for Non-Chernozemic centre of the Russian plain. The second object were soils of forest-steppe in the Middle Povolzh`e: the Volga Upland and the Trans-Volga Lowland. TStatistical samples included he genetic horizons of following soils: sod-podzolic with different degree of gleyzation, sod (humus) soils, dark gray forest, gray forest, podzolized and leached chernozems, meadow, meadow alluvial.
The total content of metals was determined by the quantitative spectral method, the MF - by atomic absorption - in 1n HCl extract. The hydrochloric acid extracts a total potential supply of HM (including sorbed by hydroxides), which in extreme conditions can exert an negative influence on the environment. Application of 1n HCl is promising for soil-chemical monitoring owing to high information capacity and possibility to compare with the results of other researchers.
The multivariable regression models were obtained as the second order polynom of the factors taken into account, or of their square roots; models also comprise coupled products of the factors. The chosen type of models is in accordance with the available information - its volume, details and accuracy, and has small number of parameters and variables.
Interpretation of received equations allowed to evaluate the "sign" and the degree of the influence of the factors under consideration upon concentrations of the HM mobile forms. In forest landscapes the MF for the most elements have direct positive relation with bulk concentrations. Cu and Pb are the exceptions; for Cu inverse relation between the MF contents and above mentioned parameters is typical, while for Pb it is absent.
The impact of organic matter is indirect, and is revealed via redox conditions and soil genesis. In oxidative conditions the MF concentrations of Mn, Zn, Pb, Ni (the elements are arranged in a decreasing sequence according to the correlation degree) and organic matter display positive correlation. Under reductive conditions the positive correlation remains only for Pb, whereas for other elements the relation becomes negative. The last situation is typical for Cr, Co in all the cases.
The influence of redox conditions (availability or absence of gley) on the contents of the HM mobile forms is evident for Ni and Mn (positive correlation in reductive conditions). For the other elements it is displayed indirectly, through concentrations of Fe mobile forms. In this case direct positive correlation for all elements, except Co, is observed. The results of regression analysis demonstrated the minor importance of pH conditions.
In forest-steppe landscapes, organic matter plays the leading role in Mn, Zn and Pb (in a smaller degree) mobilization; an increase of the pH of the soil solution results in the growth of Zn and Mn mobile forms concentrations and in the decrease of those for Pb. Content of the Cr mobile forms is controlled by its bulk concentration and by Í of the soil solution. The behaviour of Ni depends on a combination of all the factors considered.