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Article

Spatial Distribution Characteristics of Heavy Metals in Surface Soil of Xilinguole Coal Mining Area Based on Semivariogram

1
College of Desert Control Science and Engineering, Inner Mongolia Agricultural University, Hohhot 010011, China
2
College of Grassland, Resources and Environment, Inner Mongolia Agriculture University, Hohhot 010011, China
3
Inner Mongolia Autonomous Region Grassland Survey and Planning Institute, Hohhot 010020, China
*
Author to whom correspondence should be addressed.
Academic Editors: Wolfgang Kainz and Christos Chalkias
ISPRS Int. J. Geo-Inf. 2021, 10(5), 290; https://doi.org/10.3390/ijgi10050290
Received: 10 February 2021 / Revised: 22 April 2021 / Accepted: 1 May 2021 / Published: 2 May 2021
(This article belongs to the Special Issue GIS-Based Analysis for Quality of Life and Environmental Monitoring)
Heavy metal pollution is a major environmental problem facing humankind. Locating the source and distribution of heavy metal pollutants around mines can provide a scientific basis for environmental control. The structure effect and random effect of a semivariogram can be used to determine the reason for spatial differences in the heavy metal content in surface soil, and the coefficient of variation and regression analysis can be used to confirm that the verification accuracy meets the geostatistical requirements. According to the maximum difference method, the content of heavy metals in the surface soil of the mining area is higher than that of the surroundings, and Cu and Zn levels are higher than the background values for Inner Mongolia. In the present case, Zn, Mn, Pb, Cr, Ni, and Cu levels exceeded the background values for the surroundings of the study area by 65.10%, 53.72%, 52.17%, 46.24%, 33.08%, and 29.49%, respectively. The results show that human activities play a decisive role in the spatial distribution of heavy metals, leading to their spatial distribution in the form of “core periphery”. This distribution pattern was significantly affected by the slope, NDVI value, and the distance from the mining area, but the spatial distribution of Pb was significantly related to high-grade roads. The research methods and conclusions have reference significance for the sources and spatial distribution characteristics of heavy metal pollution in similar mining areas and provide a target for the prevention and control of environmental pollution in the study area. View Full-Text
Keywords: maximum difference method; semivariogram; kriging interpolation; spatial variability; opencast mine area; heavy metals maximum difference method; semivariogram; kriging interpolation; spatial variability; opencast mine area; heavy metals
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MDPI and ACS Style

Chen, G.; Yang, Y.; Liu, X.; Wang, M. Spatial Distribution Characteristics of Heavy Metals in Surface Soil of Xilinguole Coal Mining Area Based on Semivariogram. ISPRS Int. J. Geo-Inf. 2021, 10, 290. https://doi.org/10.3390/ijgi10050290

AMA Style

Chen G, Yang Y, Liu X, Wang M. Spatial Distribution Characteristics of Heavy Metals in Surface Soil of Xilinguole Coal Mining Area Based on Semivariogram. ISPRS International Journal of Geo-Information. 2021; 10(5):290. https://doi.org/10.3390/ijgi10050290

Chicago/Turabian Style

Chen, Guoqing, Yong Yang, Xinyao Liu, and Mingjiu Wang. 2021. "Spatial Distribution Characteristics of Heavy Metals in Surface Soil of Xilinguole Coal Mining Area Based on Semivariogram" ISPRS International Journal of Geo-Information 10, no. 5: 290. https://doi.org/10.3390/ijgi10050290

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