Abstract
The spatial distribution of soil physicochemical characteristics and four heavy metals (Mn, Fe, Zn, and Cu) in the semi-arid climatic region of Neyshabur plain in Northeast of Iran was investigated and identified soil pollution hotspots zone using Moran’s I and GIS techniques. The geostatistical techniques, Pearson’s correlation matrix, and spatial autocorrelation were used to locate the pollution sources and concentration. Geostatistical interpolation techniques determined the spatial distribution of heavy metals. The mean values of Iron (Fe), Manganese (Mn), Zink (Zn), Copper (Cu) were 2.31, 7.18, 2.84, 1.16 mg/kg, respectively. The routs comes of the spatial statistical method have established the gravity of pollutions and their anthropogenic impact based on spatial changes in contamination levels. The genesis of the pollution process was influenced by natural factors (e.g., the high soil shale, the sandstone, the calcareous and the metamorphic parents and the background values) as well as by anthropogenic factors (e.g., waste disposal, extraction from mines of distinct mineral ores and high, unmanaged practices of fertilizer). Although nearly all the monitoring classes of land use suffered from contamination by heavy metals, farmland was the most contaminated. This evidence will help land use planners and environmental menace administrators to promote environmentally sound economic expansion policies.
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Keshavarzi, A., Bhunia, G.S., Shit, P.K., Ertunç, G., Zeraatpisheh, M. (2022). Spatial Pattern Analysis and Identifying Soil Pollution Hotspots Using Local Moran's I and GIS at a Regional Scale in Northeast of Iran. In: Shit, P.K., Adhikary, P.P., Bhunia, G.S., Sengupta, D. (eds) Soil Health and Environmental Sustainability. Environmental Science and Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-09270-1_12
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