Geospatial and Correlation Analysis of Heavy Metal Distribution on the Territory of Integrated Steel and Mining Company Qarmet JSC

Yryszhan Zhakypbek, Kanay Rysbekov (), Vasyl Lozynskyi (), Sergey Mikhalovsky, Ruslan Salmurzauly, Yerkezhan Begimzhanova, Gulmira Kezembayeva, Bakhytzhan Yelikbayev and Assel Sankabayeva
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Yryszhan Zhakypbek: Mining and Metallurgical Institute Named After O.A. Baikonurov, Satbayev University, Almaty 050013, Kazakhstan
Kanay Rysbekov: Mining and Metallurgical Institute Named After O.A. Baikonurov, Satbayev University, Almaty 050013, Kazakhstan
Vasyl Lozynskyi: Department of Mining Engineering and Education, Dnipro University of Technology, 49005 Dnipro, Ukraine
Sergey Mikhalovsky: ANAMAD Ltd., Brighton BN1 9SB, UK
Ruslan Salmurzauly: Space Technology and Remote Sensing Center, Al-Farabi Kazakh National University, Almaty 050040, Kazakhstan
Yerkezhan Begimzhanova: Mining and Metallurgical Institute Named After O.A. Baikonurov, Satbayev University, Almaty 050013, Kazakhstan
Gulmira Kezembayeva: Mining and Metallurgical Institute Named After O.A. Baikonurov, Satbayev University, Almaty 050013, Kazakhstan
Bakhytzhan Yelikbayev: Mining and Metallurgical Institute Named After O.A. Baikonurov, Satbayev University, Almaty 050013, Kazakhstan
Assel Sankabayeva: Mining and Metallurgical Institute Named After O.A. Baikonurov, Satbayev University, Almaty 050013, Kazakhstan

Sustainability, 2025, vol. 17, issue 15, 1-19

Abstract: This paper provides geospatial and correlation analysis of heavy metal distribution in the soil cover of the city of Temirtau and its industrial zones. Based on 25 soil samples taken in 2024, concentrations of nine heavy metals (As, Pb, Zn, Cu, Ni, Co, Mn, Cr, Ba) were determined using X-ray fluorescence analysis. Spatial data interpolation was performed using the Kriging method in the ArcGIS Pro environment. The results showed the presence of localized extreme pollution zones, primarily near the Qarmet JSC metallurgical plant. The most significant exceedances of maximum permissible concentrations (MPC), up to 348× MPC for Cr, 160× MPC for Zn, and 72× MPC for As, were recorded at individual locations. Correlation analysis revealed a moderate positive relationship between several elements, particularly Mn and Cu (r = 0.64). Comparison of the spatial distribution of pollution with population data allowed for the assessment of potential environmental risks. This research emphasizes the need to implement systematic monitoring, sustainable land management practices, ecological maps, and preventive measures to reduce the long-term impact of heavy metals on ecosystems and public health, and to promote environmental sustainability in industrial regions.

Keywords: geospatial analysis; correlation analysis; heavy metals; sustainable land management; interpolations; pollution (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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