Literature DB >> 29770936

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

Jianshu Lv1,2, Yuanhe Yu3.   

Abstract

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.

Entities:  

Keywords:  Geostatistics; Metals; Multivariate statistical analysis; Soil; Sources identification; Spatial distribution

Mesh:

Substances:

Year:  2018        PMID: 29770936     DOI: 10.1007/s11356-018-2256-z

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  38 in total

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Journal:  J Hazard Mater       Date:  2009-02-07       Impact factor: 10.588

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Journal:  Environ Pollut       Date:  2009-06-13       Impact factor: 8.071

5.  Assessment of heavy metal contamination in the sediments from the Yellow River Wetland National Nature Reserve (the Sanmenxia section), China.

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Journal:  Environ Sci Pollut Res Int       Date:  2015-01-07       Impact factor: 4.223

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Journal:  Environ Sci Pollut Res Int       Date:  2015-03-04       Impact factor: 4.223

7.  Distribution, sources and contamination assessment of heavy metals in surface sediments of the South Yellow Sea and northern part of the East China Sea.

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Journal:  Mar Pollut Bull       Date:  2017-07-08       Impact factor: 5.553

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Authors:  Jianxing Zhu; Qiufeng Wang; Haili Yu; Meiling Li; Nianpeng He
Journal:  Chemosphere       Date:  2016-08-30       Impact factor: 7.086

9.  Spatial distribution, risk assessment and source identification of heavy metals in sediments of the Yangtze River Estuary, China.

Authors:  Deming Han; Jinping Cheng; Xianfeng Hu; Zhenyi Jiang; Lei Mo; Hao Xu; Yuning Ma; Xiaojia Chen; Heling Wang
Journal:  Mar Pollut Bull       Date:  2016-12-08       Impact factor: 5.553

10.  Transfer of metals from soil to vegetables in an area near a smelter in Nanning, China.

Authors:  Yu-Jing Cui; Yong-Guan Zhu; Ri-Hong Zhai; Deng-Yun Chen; Yi-Zhong Huang; Yi Qiu; Jian-Zhong Liang
Journal:  Environ Int       Date:  2004-08       Impact factor: 9.621

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  1 in total

1.  Identifying potentially contaminated areas with MaxEnt model for petrochemical industry in China.

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Journal:  Environ Sci Pollut Res Int       Date:  2022-03-18       Impact factor: 5.190

  1 in total

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