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Source identification and spatial distribution of metals in soils in a typical area of the lower Yellow River, eastern China.
Environ Sci Pollut Res Int. 2018 Jul; 25(21):21106-21117.ES

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.

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Authors+Show Affiliations

Lv J
College of Geography and Environment, Shandong Normal University, Jinan, 250014, China. lvjianshu@126.com. State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, 200062, China. lvjianshu@126.com.
Yu Y
College of Geography and Environment, Shandong Normal University, Jinan, 250014, China.

MeSH

AgricultureChinaEnvironmental MonitoringEnvironmental PollutionIndustryMetalsMultivariate AnalysisPrincipal Component AnalysisRiversSoilSoil Pollutants

Pub Type(s)

Journal Article

Language

eng

PubMed ID

29770936

Citation

Lv, Jianshu, and Yuanhe Yu. "Source Identification and Spatial Distribution of Metals in Soils in a Typical Area of the Lower Yellow River, Eastern China." Environmental Science and Pollution Research International, vol. 25, no. 21, 2018, pp. 21106-21117.
Lv J, Yu Y. Source identification and spatial distribution of metals in soils in a typical area of the lower Yellow River, eastern China. Environ Sci Pollut Res Int. 2018;25(21):21106-21117.
Lv, J., & Yu, Y. (2018). Source identification and spatial distribution of metals in soils in a typical area of the lower Yellow River, eastern China. Environmental Science and Pollution Research International, 25(21), 21106-21117. https://doi.org/10.1007/s11356-018-2256-z
Lv J, Yu Y. Source Identification and Spatial Distribution of Metals in Soils in a Typical Area of the Lower Yellow River, Eastern China. Environ Sci Pollut Res Int. 2018;25(21):21106-21117. PubMed PMID: 29770936.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Source identification and spatial distribution of metals in soils in a typical area of the lower Yellow River, eastern China. AU - Lv,Jianshu, AU - Yu,Yuanhe, Y1 - 2018/05/16/ PY - 2018/01/30/received PY - 2018/05/07/accepted PY - 2018/5/18/pubmed PY - 2019/5/30/medline PY - 2018/5/18/entrez KW - Geostatistics KW - Metals KW - Multivariate statistical analysis KW - Soil KW - Sources identification KW - Spatial distribution SP - 21106 EP - 21117 JF - Environmental science and pollution research international JO - Environ Sci Pollut Res Int VL - 25 IS - 21 N2 - 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. SN - 1614-7499 UR - https://www.unboundmedicine.com/medline/citation/29770936/Source_identification_and_spatial_distribution_of_metals_in_soils_in_a_typical_area_of_the_lower_Yellow_River_eastern_China_ DB - PRIME DP - Unbound Medicine ER -