Numeral Analysis of Soil Pollution Distribution of Heavy Metals in Anguran Area, Zanjan

Document Type : Research Article

Authors

• S. Abdollahi
• M. A. Delavar
• P. Shekari

10.22067/jsw.v1391i0.16932

Abstract

Increasing soil pollution due to heavy metals is a major concern of present day soil research. This study conducted to know intensity and spatial pattern of soil heavy metals pollution in a 10,000 ha area of Anguran region near Zanjan. A number of 315 surface (0-10 cm) samples collected at nodes of a 500 meter equilateral grid. Beside HNO3-extracted Pb, Cu, Ni, Cd and Zn content, EC, pH, OC and CaCO3 of the samples were determined. To classify data in taxonomic space, a fuzzy c-means with extragrades clustering algorithm ran on the data using several fuzziness exponents (Φ). Plausible fuzzy clusters obtained at Φ=1.3. To find eight as the optimal number of classes from a 2-10 assemblage, fuzziness validation functions F, H, and S were used. Scrutiny of class centroids and membership values revealed that though number of variables was not numerous, the algorithm clustered data sensitively. Spatial distribution of classes mapped through geostatistical analysis of membership values. Though extragrade class embraced extreme values, still all centroids of regular classes showed severe pollution. Most polluted classes C, E, F and H located at center to southeast, while A, B, D and G covered northern and western parts of the study area. Extragrade class widely spread in the area that confirmed interspersed outliers among all others. Major part of extragrade class lied across southeastern part of the area. Results of the study showed that numerical classification of soil pollution is rather realistic, thus provides a pragmatic approach to the problem.

Keywords

• Algorithm
• Fuzzy clustering
• Dandi
• Extragrade

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