Literature DB >> 28478597

Multivariate statistical and lead isotopic analyses approach to identify heavy metal sources in topsoil from the industrial zone of Beijing Capital Iron and Steel Factory.

Guangxu Zhu1,2, Qingjun Guo3, Huayun Xiao4, Tongbin Chen5, Jun Yang5.   

Abstract

Heavy metals are considered toxic to humans and ecosystems. In the present study, heavy metal concentration in soil was investigated using the single pollution index (PIi), the integrated Nemerow pollution index (PIN), and the geoaccumulation index (Igeo) to determine metal accumulation and its pollution status at the abandoned site of the Capital Iron and Steel Factory in Beijing and its surrounding area. Multivariate statistical (principal component analysis and correlation analysis), geostatistical analysis (ArcGIS tool), combined with stable Pb isotopic ratios, were applied to explore the characteristics of heavy metal pollution and the possible sources of pollutants. The results indicated that heavy metal elements show different degrees of accumulation in the study area, the observed trend of the enrichment factors, and the geoaccumulation index was Hg > Cd > Zn > Cr > Pb > Cu ≈ As > Ni. Hg, Cd, Zn, and Cr were the dominant elements that influenced soil quality in the study area. The Nemerow index method indicated that all of the heavy metals caused serious pollution except Ni. Multivariate statistical analysis indicated that Cd, Zn, Cu, and Pb show obvious correlation and have higher loads on the same principal component, suggesting that they had the same sources, which are related to industrial activities and vehicle emissions. The spatial distribution maps based on ordinary kriging showed that high concentrations of heavy metals were located in the local factory area and in the southeast-northwest part of the study region, corresponding with the predominant wind directions. Analyses of lead isotopes confirmed that Pb in the study soils is predominantly derived from three Pb sources: dust generated during steel production, coal combustion, and the natural background. Moreover, the ternary mixture model based on lead isotope analysis indicates that lead in the study soils originates mainly from anthropogenic sources, which contribute much more than the natural sources. Our study could not only reveal the overall situation of heavy metal contamination, but also identify the specific pollution sources.

Entities:  

Keywords:  Heavy metal; Multivariate statistical analysis; Pb isotopes; Pollution assessment; Soil; Sources identification

Mesh:

Substances:

Year:  2017        PMID: 28478597     DOI: 10.1007/s11356-017-9055-9

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


  34 in total

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Journal:  Water Sci Technol       Date:  2007       Impact factor: 1.915

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Journal:  Environ Pollut       Date:  2011-09-07       Impact factor: 8.071

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8.  Source apportionment and health risk assessment of heavy metals in soil for a township in Jiangsu Province, China.

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9.  Soil heavy metal contamination related to roasted stone coal slag: a study based on geostatistical and multivariate analyses.

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10.  Identifying natural and anthropogenic sources of metals in urban and rural soils using GIS-based data, PCA, and spatial interpolation.

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Journal:  Environ Pollut       Date:  2009-04-10       Impact factor: 8.071

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  7 in total

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3.  Temporal-spatial trends in potentially toxic trace element pollution in farmland soil in the major grain-producing regions of China.

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5.  Pollution Levels and Risk Assessment of Heavy Metals in the Soil of a Landfill Site: A Case Study in Lhasa, Tibet.

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6.  Evaluation of the phytoremediation potential of dominant plant species growing in a chromium salt-producing factory wasteland, China.

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7.  Lead Emissions and Population Vulnerability in the Detroit Metropolitan Area, 2006-2013: Impact of Pollution, Housing Age and Neighborhood Racial Isolation and Poverty on Blood Lead in Children.

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  7 in total

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