Environmental Science and Pollution Research

, Volume 25, Issue 21, pp 21106–21117 | Cite as

Source identification and spatial distribution of metals in soils in a typical area of the lower Yellow River, eastern China

  • Jianshu Lv
  • Yuanhe Yu
Research Article


In this study, 234 soil samples were recently collected from Gaoqing County (a typical area of the lower Yellow River) to determine the contents of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn. Multivariate statistical analyses such as correlation analysis, principal components analysis, and one-way ANOVA were applied to identify the source of metals in the soil. Geostatistical methods were used to analyze the spatial structure and distribution of the metals. The results indicated that the mean contents of all metals exceeded the background value of the lower Yellow River, especially for As, Cu, and Hg (1.23, 1.20, and 1.29 times that of the BV, respectively), indicating that these metals were enriched in the study area to different degrees. The results derived from multivariate analysis suggested that As, Cd, Cr, Cu, Ni, Pb, and Zn were mainly controlled by the combination of human activities and soil parent material, and the human activities included industrial emissions, traffic emissions, and agricultural practices. In addition, Hg mainly originated from anthropogenic inputs, such as textile printing, plastics processing, and petrochemical engineering. The contents of metals in different types of land use and parent materials are clearly different. The mean content for eight elements in urban construction land was significantly higher than that of the other land use types; in addition to Hg, the mean content of the other elements was the highest in the lacustrine deposit. The elements of As, Cd, Cr, Cu, Ni, Pb, and Zn had similar hotspots in the urban area, indicating the significant human influence. In addition, these seven metals showed high values in the southeast lacustrine deposit area. The high-value areas of Hg were concentrated in the southwest and northeast study area, which were consistent with the spatial pattern of the industrial sites.


Metals Soil Multivariate statistical analysis Geostatistics Sources identification Spatial distribution 


Funding information

This study was jointly supported by the National Natural Science Foundation of China (No.41601549, 41701604), Natural Science Foundation of Shandong Province (No.ZR2016DQ11), and Open Foundation of Estuarine and Coastal State Key Laboratory (SKLEC-KF201710).


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Copyright information

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

Authors and Affiliations

  1. 1.College of Geography and EnvironmentShandong Normal UniversityJinanChina
  2. 2.State Key Laboratory of Estuarine and Coastal ResearchEast China Normal UniversityShanghaiChina

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