The importance of using soil series-based geochemical background values when calculating the enrichment factor in agricultural areas
- 6 June 2023
- journal article
- research article
- Published by Springer Nature in Environmental Geochemistry and Health
- Vol. 45 (8) , 6215-6230
Abstract
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.Keywords
Funding Information
- Çukurova University Research Projects Unit (FDK-2019-11716)
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