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Potential Risk Recognition of Agricultural Land Based on Agglomeration Characteristics of Pollution-Related Enterprises: A Case Study on the Black Soil Region in Northeast China

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  • Xiaofeng Zhao

    (Comprehensive Survey Command Center for Natural Resources, China Geological Survey, Beijing 100055, China
    School of Earth Science and Resources, China University of Geosciences (Beijing), Beijing 100083, China
    Key Laboratory of Coupling Process and Effect of Natural Resources Elements, Beijing 100055, China
    These authors contributed equally to this work.)

  • Changhe Wei

    (School of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038, China
    These authors contributed equally to this work.)

  • Jiufen Liu

    (Comprehensive Survey Command Center for Natural Resources, China Geological Survey, Beijing 100055, China
    School of Earth Science and Resources, China University of Geosciences (Beijing), Beijing 100083, China
    Key Laboratory of Coupling Process and Effect of Natural Resources Elements, Beijing 100055, China)

  • Xiaohuang Liu

    (Comprehensive Survey Command Center for Natural Resources, China Geological Survey, Beijing 100055, China
    Key Laboratory of Coupling Process and Effect of Natural Resources Elements, Beijing 100055, China)

  • Xiaoming Wan

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Mei Lei

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Shaobin Wang

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

The black soil region in Northeast China serves as a ballast for food security. However, the presence of scattered polluting enterprises poses a threat to the safety of the surrounding soil and agricultural products. In this study, the distribution patterns and agglomeration features of key industrial enterprises in Northeast China were elucidated through multi-source geographical big data and geographic information system (GIS) spatial analysis. Subsequently, the risk areas were extracted based on their potential impact on the soil environmental quality of the surrounding agricultural lands. The results revealed that pollution-related enterprises were widely distributed but locally clustered in the black soil area. The dominant industries were chemical manufacturing, petroleum processing, coking, and non-ferrous metal mining. The study found that the agricultural land area affected by polluting enterprises was 43,396.13 km 2 , with the majority being at a low-risk level (83.42%). High-risk areas (1646.62 km 2 ) were mostly aggregated west of Hulunbuir, east of Xilingol, and in most of Chifeng. These areas were primarily affected by the non-ferrous metal mining industry. Other high-risk hotspots were mainly influenced by the chemical manufacturing and metal processing industries. The emissions from industrial and mining enterprises are important heavy metals in the agricultural lands in this region. However, it is important to note that there are other sources of pollution as well. These results may contribute to future investigations on soil environmental quality and pollution source control in the black soil region in Northeast China.

Suggested Citation

  • Xiaofeng Zhao & Changhe Wei & Jiufen Liu & Xiaohuang Liu & Xiaoming Wan & Mei Lei & Shaobin Wang, 2024. "Potential Risk Recognition of Agricultural Land Based on Agglomeration Characteristics of Pollution-Related Enterprises: A Case Study on the Black Soil Region in Northeast China," Sustainability, MDPI, vol. 16(1), pages 1-20, January.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:1:p:417-:d:1312401
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    References listed on IDEAS

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    1. D. Y. Jayasinghe & C. L. Jayasinghe, 2022. "An Investigation into Adult Human Height Distributions Using Kernel Density Estimation," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 79-105, May.
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