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The Spatial Distribution and Influencing Factors of Heavy Metals in Soil in Xinjiang, China

Author

Listed:
  • Youwen Li

    (Xinjiang Biomass Solid Waste Resources Technology and Engineering Center, College of Chemistry and Environmental Science, Kashi University, Kashi 844000, China)

  • Jiangpeng Xue

    (Xinjiang Biomass Solid Waste Resources Technology and Engineering Center, College of Chemistry and Environmental Science, Kashi University, Kashi 844000, China)

  • Jixiang Cai

    (Xinjiang Biomass Solid Waste Resources Technology and Engineering Center, College of Chemistry and Environmental Science, Kashi University, Kashi 844000, China)

  • Yucai Zhang

    (Xinjiang Biomass Solid Waste Resources Technology and Engineering Center, College of Chemistry and Environmental Science, Kashi University, Kashi 844000, China)

  • Feixing Li

    (Xinjiang Biomass Solid Waste Resources Technology and Engineering Center, College of Chemistry and Environmental Science, Kashi University, Kashi 844000, China)

  • Xianghao Zha

    (Xinjiang Biomass Solid Waste Resources Technology and Engineering Center, College of Chemistry and Environmental Science, Kashi University, Kashi 844000, China)

  • Guodong Fang

    (Xinjiang Biomass Solid Waste Resources Technology and Engineering Center, College of Chemistry and Environmental Science, Kashi University, Kashi 844000, China
    Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China)

Abstract

Heavy metal pollution has been a problem of concern in soil ecology in recent decades. This study investigated the spatial distribution of heavy metals and their pollution levels in the soil of Xinjiang, based on the data of heavy metals published in the literature in the past five years, by using a geostatistical method, pollution index method, and geographic information system (GIS)-based spatial analysis. Additionally, the effects of five economic development indicators, such as population and industrial activities on the accumulation of heavy metals in soil, were explored by correlation analysis. The results showed that the average contents of Cd, Cr, Cu, Ni, Pb, and Zn in the soils were 2.858, 1.062, 1.194, 1.159, 1.192, and 1.086 times higher than the background values in Xinjiang, respectively. The semi-variance functions indicated that the Cd and Pb block gold coefficients of soils were greater than 25% and less than 50%, with an obvious spatial correlation. The spatial patterns showed that the high values of Cd, Cr, Cu, Ni, Pb, and Zn were mainly distributed in Karamay, Changji, Tacheng, and Kashi areas, with an overall decreasing trend from north to south, and the pollution index showed that the pollution of heavy metal Cd in soil was the most serious. Furthermore, Karamay, Changji, and Kashi areas were at heavy pollution levels. Correlation analysis showed that heavy metal Pb in the soil was significantly positively correlated with the agricultural GDP in Xinjiang, while Cd was correlated significantly and positively with comprehensive energy consumption and more significantly with industrial GDP. Thus, this study could provide a scientific basis for local evaluation of soil environmental quality and prevention and control of soil heavy metal pollution, which is of great significance for understanding the impact of human activities.

Suggested Citation

  • Youwen Li & Jiangpeng Xue & Jixiang Cai & Yucai Zhang & Feixing Li & Xianghao Zha & Guodong Fang, 2023. "The Spatial Distribution and Influencing Factors of Heavy Metals in Soil in Xinjiang, China," Sustainability, MDPI, vol. 15(23), pages 1-14, November.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:23:p:16379-:d:1289662
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    References listed on IDEAS

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    1. Liu Jin & Zongqi Wang & Xiaohong Chen, 2022. "Spatial Distribution Characteristics and Influencing Factors of Traditional Villages on the Tibetan Plateau in China," IJERPH, MDPI, vol. 19(20), pages 1-19, October.
    2. Jiaojiao Bian & Wanxu Chen & Jie Zeng, 2022. "Spatial Distribution Characteristics and Influencing Factors of Traditional Villages in China," IJERPH, MDPI, vol. 19(8), pages 1-18, April.
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