The importance of using soil series-based geochemical background values when calculating the enrichment factor in agricultural areas

The enrichment factor (EF) is one of the most commonly used indices for determining the source of air, water and soil pollution. However, concerns have been raised about the accuracy of the EF results because the formula leaves the choice of background value to the researcher's discretion. The EF was used in this study to assess the validity of such concerns and to determine heavy metal enrichment in five soil profiles with different parent materials (alluvial, colluvial, and quartzite). Moreover, the upper continental crust (UCC) and specific local background values (sub-horizons) were used as the geochemical backgrounds. When UCC values were applied, the soils were moderately enriched in Cr (2.59), Zn (3.54), Pb (4.50) and Ni (4.69), and significantly enriched in Cu (5.09), Cd (6.54) and As (6.64). Using the sub-horizons of the soil profiles as a background value, it was found that the soils had "moderate enrichment" by As (2.59) and "minimally enrichment" by Cu (0.86), Ni (1.01), Cd (1.11), Zn (1.23), Cr (1.30), and Pb (1.50). As a result, the UCC reported an inaccurate conclusion indicating that soils were 3.84 times more heavily polluted than they were. In addition, the statistical analyses performed in this study (Pearson correlation analysis and principal component analysis) revealed that the percentage of clay in the soil horizons and the cation exchange capacity had strong positive relationships (r ≥ 0.670, p < 0.05) with certain heavy metals (Al, Zn, Cr, Ni, Pb and Cd). These findings indicated that sampling from the "lowest horizons" or "parent materials" of the soil series would yield the most accurate results in determining the geochemical background values in agricultural areas.

A GIS based method for soil mapping in Sardinia, Italy: a geomatic approach

A new project was recently initiated for the realization of the "Land Unit and Soil Capability Map of Sardinia" at a scale of 1:50,000 to support land use planning. In this study, we outline the general structure of the project and the methods used in the activities that have been thus far conducted. A GIS approach was used. We used the soil-landscape paradigm for the prediction of soil classes and their spatial distribution or the prediction of soil properties based on landscape features. The work is divided into two main phases. In the first phase, the available digital data on land cover, geology and topography were processed and classified according to their influence on weathering processes and soil properties. The methods used in the interpretation are based on consolidated and generalized knowledge about the influence of geology, topography and land cover on soil properties. The existing soil data (areal and point data) were collected, reviewed, validated and standardized according to international and national guidelines. Point data considered to be usable were input into a specific database created for the project. Using expert interpretation, all digital data were merged to produce a first draft of the Land Unit Map. During the second phase, this map will be implemented with the existing soil data and verified in the field if also needed with new soil data collection, and the final Land Unit Map will be produced. The Land Unit and Soil Capability Map will be produced by classifying the land units using a reference matching table of land capability classes created for this project.