Journal of Soils and Sediments

, Volume 19, Issue 2, pp 629–640 | Cite as

Spatial network analysis of surface soil pollution from heavy metals and some other elements: a case study of the Baotou region of China

  • Xiaodan Han
  • Huajiao LiEmail author
  • Meixia Su
  • Pengli An
Soils, Sec 2 • Global Change, Environ Risk Assess, Sustainable Land Use • Research Article



With the development of heavy industry, urban soil suffers serious pollution, which threatens the sustainable development of cities. Understanding the spatial distribution characteristics of surface soil pollution aids in pollution prevention and control and promotes sustainable development.

Materials and methods

We use China’s Baotou as an example. Based on the data of 2820 sampling points in main urban areas and some suburban areas of Baotou, we constructed a relationship network model for sampling points in surface soil by using the complex network method. We combined the network method with spatial geographic information to analyze the spatial agglomeration characteristics of the surface soil pollution in Baotou China.

Results and discussion

Sampling points at Dalahai Village (including 506D, 538B, and 538D) and Hayenaobao Village (including 509C, 541A, and 541C), Puerhantu Town within the Kundulun District have the most serious pollution problems, and they are all concentrated in the tailings dam. Sampling points 328D and 544A are scattered in the Leng Community, Kunhe Town, Kundulun District and Changhan Village, Haringer Township, Jiuyuan District, but they have a close co-anomaly relationship with the tailings dam. We suggest that these areas should be unified to give priority to pollution control. There is an obvious difference for Al2O3, B, Hg, and U, which are abnormal in the power plant ash storage pools, but normal at the tailings dam. Consequently, pollution control for power plant ash storage pools needs to be different from pollution control at the tailings dam. Sampling points at the Fengying Community (including 580A and 580B), Kunhe Town, Kundulun District, and Gaoyoufang Village (579D and 643B), Rare Earth Road, Qingshan District as well as other sampling points upstream of the Kundulun River have a close co-anomaly relationship with the tailings dam. It is necessary to strengthen the purification treatment of sewage upstream of the Kundulun River to reduce the spread of pollutants.


These results provide a theoretical basis for the government to formulate specific cross-regional collaborative governance measures.


Complex network Geochemistry elements Pollution assessment Spatial distribution Surface soil pollution Urban soil 



The authors would like to express their gratitude to Haizhong An, Xiaoqi Sun, and Xueyong Liu, who provided valuable suggestion. The authors would also like to thank AJE-American Journal Experts for their professional suggestions regarding the language usage, spelling, and grammar of this paper.

Funding information

This research is supported by grants from the National Natural Science Foundation of China (Grant No. 41701121), the Beijing Youth Talents Funds (2017000020124G190) and the Fundamental Research Funds for the Central Universities (Grant No. 2-9-2017-041).


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.China University of GeosciencesBeijingChina
  2. 2.Key Laboratory of Carrying Capacity Assessment for Resource and EnvironmentMinistry of Land and ResourcesBeijingChina
  3. 3.Geological Survey Institute of Inner Mongolia Autonomous RegionHohhotChina

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