Application of multivariate statistical approach to identify heavy metal sources in sediment and waters: a case study in Yangzhong, China
Abstract Multivariate statistical approach is used to identify the sources of heavy metals (Bi, Cd, Co, Cr, Mn, Pb, U, V, and Zn) in surface water and freshly deposited riverine sediment samples in Yangzhong city, China. The metal concentration data for the water and sediment samples are reported in...
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Gespeichert in:
| Autor*in: |
Zhou, Jian [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2007 |
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| Systematik: |
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| Anmerkung: |
© Springer-Verlag 2007 |
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| Übergeordnetes Werk: |
Enthalten in: Environmental geology - Springer-Verlag, 1975, 54(2007), 2 vom: 28. Juni, Seite 373-380 |
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| Übergeordnetes Werk: |
volume:54 ; year:2007 ; number:2 ; day:28 ; month:06 ; pages:373-380 |
| Links: |
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| DOI / URN: |
10.1007/s00254-007-0824-5 |
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OLC207441353X |
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| 520 | |a Abstract Multivariate statistical approach is used to identify the sources of heavy metals (Bi, Cd, Co, Cr, Mn, Pb, U, V, and Zn) in surface water and freshly deposited riverine sediment samples in Yangzhong city, China. The metal concentration data for the water and sediment samples are reported in terms of basic statistical parameters and metal-to-metal correlations. In both surface water and sediment samples, significant correlations are observed between some metals. Principal component analysis and cluster analysis distinguishes factors of lithogenic and anthropogenic origin. Bismuth, Cd, Co, and Pb (Co only for water samples) contents are controlled by the regional lithogenic high background factor; Co, Mn, U, and V (Co only for sediment samples) are interpreted to be mainly inherited from soil parent materials, while Cr, Zn, and Mn in the two kinds of samples are recognized as the tracer of industrial pollution. Obvious similarity between factor loadings of the two kinds of samples is observed, evidencing that metal variability in the two kinds of samples is controlled by the same sources. Statistical analysis agrees with discussion based on background value and field survey of point-source pollutant affected sediment, making this statistical discussion more convincing. | ||
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10.1007/s00254-007-0824-5 doi (DE-627)OLC207441353X (DE-He213)s00254-007-0824-5-p DE-627 ger DE-627 rakwb eng 330 550 VZ 550 VZ 13 ssgn TE 3140 VZ rvk Zhou, Jian verfasserin aut Application of multivariate statistical approach to identify heavy metal sources in sediment and waters: a case study in Yangzhong, China 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2007 Abstract Multivariate statistical approach is used to identify the sources of heavy metals (Bi, Cd, Co, Cr, Mn, Pb, U, V, and Zn) in surface water and freshly deposited riverine sediment samples in Yangzhong city, China. The metal concentration data for the water and sediment samples are reported in terms of basic statistical parameters and metal-to-metal correlations. In both surface water and sediment samples, significant correlations are observed between some metals. Principal component analysis and cluster analysis distinguishes factors of lithogenic and anthropogenic origin. Bismuth, Cd, Co, and Pb (Co only for water samples) contents are controlled by the regional lithogenic high background factor; Co, Mn, U, and V (Co only for sediment samples) are interpreted to be mainly inherited from soil parent materials, while Cr, Zn, and Mn in the two kinds of samples are recognized as the tracer of industrial pollution. Obvious similarity between factor loadings of the two kinds of samples is observed, evidencing that metal variability in the two kinds of samples is controlled by the same sources. Statistical analysis agrees with discussion based on background value and field survey of point-source pollutant affected sediment, making this statistical discussion more convincing. Sediment Sample Inductively Couple Plasma Mass Spectrometry Riverine Sediment Potential Toxic Element Multivariate Statistical Approach Ma, Dongsheng aut Pan, Jiayong aut Nie, Wenming aut Wu, Kai aut Enthalten in Environmental geology Springer-Verlag, 1975 54(2007), 2 vom: 28. Juni, Seite 373-380 (DE-627)129421634 (DE-600)190352-4 (DE-576)014797453 0943-0105 nnns volume:54 year:2007 number:2 day:28 month:06 pages:373-380 https://doi.org/10.1007/s00254-007-0824-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_22 GBV_ILN_30 GBV_ILN_40 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_267 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2018 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4277 GBV_ILN_4309 TE 3140 AR 54 2007 2 28 06 373-380 |
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10.1007/s00254-007-0824-5 doi (DE-627)OLC207441353X (DE-He213)s00254-007-0824-5-p DE-627 ger DE-627 rakwb eng 330 550 VZ 550 VZ 13 ssgn TE 3140 VZ rvk Zhou, Jian verfasserin aut Application of multivariate statistical approach to identify heavy metal sources in sediment and waters: a case study in Yangzhong, China 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2007 Abstract Multivariate statistical approach is used to identify the sources of heavy metals (Bi, Cd, Co, Cr, Mn, Pb, U, V, and Zn) in surface water and freshly deposited riverine sediment samples in Yangzhong city, China. The metal concentration data for the water and sediment samples are reported in terms of basic statistical parameters and metal-to-metal correlations. In both surface water and sediment samples, significant correlations are observed between some metals. Principal component analysis and cluster analysis distinguishes factors of lithogenic and anthropogenic origin. Bismuth, Cd, Co, and Pb (Co only for water samples) contents are controlled by the regional lithogenic high background factor; Co, Mn, U, and V (Co only for sediment samples) are interpreted to be mainly inherited from soil parent materials, while Cr, Zn, and Mn in the two kinds of samples are recognized as the tracer of industrial pollution. Obvious similarity between factor loadings of the two kinds of samples is observed, evidencing that metal variability in the two kinds of samples is controlled by the same sources. Statistical analysis agrees with discussion based on background value and field survey of point-source pollutant affected sediment, making this statistical discussion more convincing. Sediment Sample Inductively Couple Plasma Mass Spectrometry Riverine Sediment Potential Toxic Element Multivariate Statistical Approach Ma, Dongsheng aut Pan, Jiayong aut Nie, Wenming aut Wu, Kai aut Enthalten in Environmental geology Springer-Verlag, 1975 54(2007), 2 vom: 28. Juni, Seite 373-380 (DE-627)129421634 (DE-600)190352-4 (DE-576)014797453 0943-0105 nnns volume:54 year:2007 number:2 day:28 month:06 pages:373-380 https://doi.org/10.1007/s00254-007-0824-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_22 GBV_ILN_30 GBV_ILN_40 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_267 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2018 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4277 GBV_ILN_4309 TE 3140 AR 54 2007 2 28 06 373-380 |
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10.1007/s00254-007-0824-5 doi (DE-627)OLC207441353X (DE-He213)s00254-007-0824-5-p DE-627 ger DE-627 rakwb eng 330 550 VZ 550 VZ 13 ssgn TE 3140 VZ rvk Zhou, Jian verfasserin aut Application of multivariate statistical approach to identify heavy metal sources in sediment and waters: a case study in Yangzhong, China 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2007 Abstract Multivariate statistical approach is used to identify the sources of heavy metals (Bi, Cd, Co, Cr, Mn, Pb, U, V, and Zn) in surface water and freshly deposited riverine sediment samples in Yangzhong city, China. The metal concentration data for the water and sediment samples are reported in terms of basic statistical parameters and metal-to-metal correlations. In both surface water and sediment samples, significant correlations are observed between some metals. Principal component analysis and cluster analysis distinguishes factors of lithogenic and anthropogenic origin. Bismuth, Cd, Co, and Pb (Co only for water samples) contents are controlled by the regional lithogenic high background factor; Co, Mn, U, and V (Co only for sediment samples) are interpreted to be mainly inherited from soil parent materials, while Cr, Zn, and Mn in the two kinds of samples are recognized as the tracer of industrial pollution. Obvious similarity between factor loadings of the two kinds of samples is observed, evidencing that metal variability in the two kinds of samples is controlled by the same sources. Statistical analysis agrees with discussion based on background value and field survey of point-source pollutant affected sediment, making this statistical discussion more convincing. Sediment Sample Inductively Couple Plasma Mass Spectrometry Riverine Sediment Potential Toxic Element Multivariate Statistical Approach Ma, Dongsheng aut Pan, Jiayong aut Nie, Wenming aut Wu, Kai aut Enthalten in Environmental geology Springer-Verlag, 1975 54(2007), 2 vom: 28. Juni, Seite 373-380 (DE-627)129421634 (DE-600)190352-4 (DE-576)014797453 0943-0105 nnns volume:54 year:2007 number:2 day:28 month:06 pages:373-380 https://doi.org/10.1007/s00254-007-0824-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_22 GBV_ILN_30 GBV_ILN_40 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_267 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2018 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4277 GBV_ILN_4309 TE 3140 AR 54 2007 2 28 06 373-380 |
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10.1007/s00254-007-0824-5 doi (DE-627)OLC207441353X (DE-He213)s00254-007-0824-5-p DE-627 ger DE-627 rakwb eng 330 550 VZ 550 VZ 13 ssgn TE 3140 VZ rvk Zhou, Jian verfasserin aut Application of multivariate statistical approach to identify heavy metal sources in sediment and waters: a case study in Yangzhong, China 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2007 Abstract Multivariate statistical approach is used to identify the sources of heavy metals (Bi, Cd, Co, Cr, Mn, Pb, U, V, and Zn) in surface water and freshly deposited riverine sediment samples in Yangzhong city, China. The metal concentration data for the water and sediment samples are reported in terms of basic statistical parameters and metal-to-metal correlations. In both surface water and sediment samples, significant correlations are observed between some metals. Principal component analysis and cluster analysis distinguishes factors of lithogenic and anthropogenic origin. Bismuth, Cd, Co, and Pb (Co only for water samples) contents are controlled by the regional lithogenic high background factor; Co, Mn, U, and V (Co only for sediment samples) are interpreted to be mainly inherited from soil parent materials, while Cr, Zn, and Mn in the two kinds of samples are recognized as the tracer of industrial pollution. Obvious similarity between factor loadings of the two kinds of samples is observed, evidencing that metal variability in the two kinds of samples is controlled by the same sources. Statistical analysis agrees with discussion based on background value and field survey of point-source pollutant affected sediment, making this statistical discussion more convincing. Sediment Sample Inductively Couple Plasma Mass Spectrometry Riverine Sediment Potential Toxic Element Multivariate Statistical Approach Ma, Dongsheng aut Pan, Jiayong aut Nie, Wenming aut Wu, Kai aut Enthalten in Environmental geology Springer-Verlag, 1975 54(2007), 2 vom: 28. Juni, Seite 373-380 (DE-627)129421634 (DE-600)190352-4 (DE-576)014797453 0943-0105 nnns volume:54 year:2007 number:2 day:28 month:06 pages:373-380 https://doi.org/10.1007/s00254-007-0824-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_22 GBV_ILN_30 GBV_ILN_40 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_267 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2018 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4277 GBV_ILN_4309 TE 3140 AR 54 2007 2 28 06 373-380 |
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10.1007/s00254-007-0824-5 doi (DE-627)OLC207441353X (DE-He213)s00254-007-0824-5-p DE-627 ger DE-627 rakwb eng 330 550 VZ 550 VZ 13 ssgn TE 3140 VZ rvk Zhou, Jian verfasserin aut Application of multivariate statistical approach to identify heavy metal sources in sediment and waters: a case study in Yangzhong, China 2007 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2007 Abstract Multivariate statistical approach is used to identify the sources of heavy metals (Bi, Cd, Co, Cr, Mn, Pb, U, V, and Zn) in surface water and freshly deposited riverine sediment samples in Yangzhong city, China. The metal concentration data for the water and sediment samples are reported in terms of basic statistical parameters and metal-to-metal correlations. In both surface water and sediment samples, significant correlations are observed between some metals. Principal component analysis and cluster analysis distinguishes factors of lithogenic and anthropogenic origin. Bismuth, Cd, Co, and Pb (Co only for water samples) contents are controlled by the regional lithogenic high background factor; Co, Mn, U, and V (Co only for sediment samples) are interpreted to be mainly inherited from soil parent materials, while Cr, Zn, and Mn in the two kinds of samples are recognized as the tracer of industrial pollution. Obvious similarity between factor loadings of the two kinds of samples is observed, evidencing that metal variability in the two kinds of samples is controlled by the same sources. Statistical analysis agrees with discussion based on background value and field survey of point-source pollutant affected sediment, making this statistical discussion more convincing. Sediment Sample Inductively Couple Plasma Mass Spectrometry Riverine Sediment Potential Toxic Element Multivariate Statistical Approach Ma, Dongsheng aut Pan, Jiayong aut Nie, Wenming aut Wu, Kai aut Enthalten in Environmental geology Springer-Verlag, 1975 54(2007), 2 vom: 28. Juni, Seite 373-380 (DE-627)129421634 (DE-600)190352-4 (DE-576)014797453 0943-0105 nnns volume:54 year:2007 number:2 day:28 month:06 pages:373-380 https://doi.org/10.1007/s00254-007-0824-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_22 GBV_ILN_30 GBV_ILN_40 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_267 GBV_ILN_2006 GBV_ILN_2010 GBV_ILN_2014 GBV_ILN_2018 GBV_ILN_2027 GBV_ILN_4012 GBV_ILN_4277 GBV_ILN_4309 TE 3140 AR 54 2007 2 28 06 373-380 |
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Application of multivariate statistical approach to identify heavy metal sources in sediment and waters: a case study in Yangzhong, China |
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Abstract Multivariate statistical approach is used to identify the sources of heavy metals (Bi, Cd, Co, Cr, Mn, Pb, U, V, and Zn) in surface water and freshly deposited riverine sediment samples in Yangzhong city, China. The metal concentration data for the water and sediment samples are reported in terms of basic statistical parameters and metal-to-metal correlations. In both surface water and sediment samples, significant correlations are observed between some metals. Principal component analysis and cluster analysis distinguishes factors of lithogenic and anthropogenic origin. Bismuth, Cd, Co, and Pb (Co only for water samples) contents are controlled by the regional lithogenic high background factor; Co, Mn, U, and V (Co only for sediment samples) are interpreted to be mainly inherited from soil parent materials, while Cr, Zn, and Mn in the two kinds of samples are recognized as the tracer of industrial pollution. Obvious similarity between factor loadings of the two kinds of samples is observed, evidencing that metal variability in the two kinds of samples is controlled by the same sources. Statistical analysis agrees with discussion based on background value and field survey of point-source pollutant affected sediment, making this statistical discussion more convincing. © Springer-Verlag 2007 |
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Abstract Multivariate statistical approach is used to identify the sources of heavy metals (Bi, Cd, Co, Cr, Mn, Pb, U, V, and Zn) in surface water and freshly deposited riverine sediment samples in Yangzhong city, China. The metal concentration data for the water and sediment samples are reported in terms of basic statistical parameters and metal-to-metal correlations. In both surface water and sediment samples, significant correlations are observed between some metals. Principal component analysis and cluster analysis distinguishes factors of lithogenic and anthropogenic origin. Bismuth, Cd, Co, and Pb (Co only for water samples) contents are controlled by the regional lithogenic high background factor; Co, Mn, U, and V (Co only for sediment samples) are interpreted to be mainly inherited from soil parent materials, while Cr, Zn, and Mn in the two kinds of samples are recognized as the tracer of industrial pollution. Obvious similarity between factor loadings of the two kinds of samples is observed, evidencing that metal variability in the two kinds of samples is controlled by the same sources. Statistical analysis agrees with discussion based on background value and field survey of point-source pollutant affected sediment, making this statistical discussion more convincing. © Springer-Verlag 2007 |
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Abstract Multivariate statistical approach is used to identify the sources of heavy metals (Bi, Cd, Co, Cr, Mn, Pb, U, V, and Zn) in surface water and freshly deposited riverine sediment samples in Yangzhong city, China. The metal concentration data for the water and sediment samples are reported in terms of basic statistical parameters and metal-to-metal correlations. In both surface water and sediment samples, significant correlations are observed between some metals. Principal component analysis and cluster analysis distinguishes factors of lithogenic and anthropogenic origin. Bismuth, Cd, Co, and Pb (Co only for water samples) contents are controlled by the regional lithogenic high background factor; Co, Mn, U, and V (Co only for sediment samples) are interpreted to be mainly inherited from soil parent materials, while Cr, Zn, and Mn in the two kinds of samples are recognized as the tracer of industrial pollution. Obvious similarity between factor loadings of the two kinds of samples is observed, evidencing that metal variability in the two kinds of samples is controlled by the same sources. Statistical analysis agrees with discussion based on background value and field survey of point-source pollutant affected sediment, making this statistical discussion more convincing. © Springer-Verlag 2007 |
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