عنوان مقاله [English]
Background and objectives: Considering progressive growth of industry and technology, the accumulation of environmental contaminants, especially heavy metals (HMs) in the soil is of increasing worldwide concern about the probable soil pollution risks. The perception of pollutants spatial distribution pattern and recognition of factors which control this pattern and identification of probable sources of pollution, are the most important purposes in the environmental pollution studies. The present study was conducted to achieve to useful information to distinguish the role of natural sources from the human ones, using modeling the spatial variability pattern of heavy metals pollution load index in the Zanjan Zinc Industrial Town area.
Materials and methods: In the present study, 85 topsoil samples (0-20 cm) using a regular grid sampling pattern were collected. The total (Nitric-acid extractable) contents of Zn, Pb, Cd, Ni and Cu were measured for each soil sample using atomic absorption spectroscopy. Assessing the soil pollution risk with selected HMs, contamination factor was calculated. Accordingly, sampling locations were classified into the different soil contamination classes. In order to simultaneous assessment of the status of overall soil pollution by the pollutant elements, pollution load index (PLI) of studied heavy metals was calculated. Afterwards, PLI was considered as an environmental variable which its values at un-sampled locations were interpolated using ordinary kriging method.
Results: Comparing the measured HMs contents with their maximum permissible limits in the soil showed that the studied soils are polluted with Zn, Pb and Cd, but non-polluted with Ni and Cu. The total concentration of Zn, Pb and Cd in the soil showed a great degree of variability, indicated by large coefficients of variation (CV) from 140.5 % of Cd to 185.6 % of Pb. These elevated CVs may indicate that these elements’ distribution in the studied area is influenced by an anthropogenic source. In contrast, the relatively low calculated CVs for Ni (78.1 %) and Cu (80.3 %) may imply that natural sources are responsible for these elements’ distribution in the studied soils. Classification of observations according to the contamination factor of studied heavy metals showed that most of sampling points occurred in the very high contamination class regarding Zn and Pb (65.9 % and 68.2 %, respectively) and in the medium contamination class regarding Cd, Cu and Ni (57.7, 51.8 and 68.2 %, respectively). Mapping the spatial variability of heavy metals pollution load index showed that areas with highest pollution contents occurred in the contiguity of Zinc Town.
Conclusion: Totally, industrial activities related to Zn production caused to simultaneous entrance of several heavy metals to the adjacent soils and lead to degradation of the lands in studied area. Considering the low efficiency of single-element maps for HMs to reflect the overall soil quality in relation to environmental contaminants, modeling of the spatial variability of PLI may provide the good perception of the contaminants' spatial distribution and their effects on soil quality.