Social-Ecological Patterns of Soil Heavy Metals Based on a Self-Organizing Map (SOM): A Case Study in Beijing, China
Identifieur interne : 000152 ( Pmc/Curation ); précédent : 000151; suivant : 000153Social-Ecological Patterns of Soil Heavy Metals Based on a Self-Organizing Map (SOM): A Case Study in Beijing, China
Auteurs : Binwu Wang [République populaire de Chine] ; Hong Li ; Danfeng SunSource :
- International Journal of Environmental Research and Public Health [ 1661-7827 ] ; 2014.
Abstract
The regional management of trace elements in soils requires understanding the interaction between the natural system and human socio-economic activities. In this study, a social-ecological patterns of heavy metals (SEPHM) approach was proposed to identify the heavy metal concentration patterns and processes in different ecoregions of Beijing (China) based on a self-organizing map (SOM). Potential ecological risk index (RI) values of Cr, Ni, Zn, Hg, Cu, As, Cd and Pb were calculated for 1,018 surface soil samples. These data were averaged in accordance with 253 communities and/or towns, and compared with demographic, agriculture structure, geomorphology, climate, land use/cover, and soil-forming parent material to discover the SEPHM. Multivariate statistical techniques were further applied to interpret the control factors of each SEPHM. SOM application clustered the 253 towns into nine groups on the map size of 12 × 7 plane (quantization error 1.809; topographic error, 0.0079). The distribution characteristics and Spearman rank correlation coefficients of RIs were strongly associated with the population density, vegetation index, industrial and mining land percent and road density. The RIs were relatively high in which towns in a highly urbanized area with large human population density exist, while low RIs occurred in mountainous and high vegetation cover areas. The resulting dataset identifies the SEPHM of Beijing and links the apparent results of RIs to driving factors, thus serving as an excellent data source to inform policy makers for legislative and land management actions.
Url:
DOI: 10.3390/ijerph110403618
PubMed: 24690947
PubMed Central: 4025005
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<front><div type="abstract" xml:lang="en"><p>The regional management of trace elements in soils requires understanding the interaction between the natural system and human socio-economic activities. In this study, a social-ecological patterns of heavy metals (SEPHM) approach was proposed to identify the heavy metal concentration patterns and processes in different ecoregions of Beijing (China) based on a self-organizing map (SOM). Potential ecological risk index (RI) values of Cr, Ni, Zn, Hg, Cu, As, Cd and Pb were calculated for 1,018 surface soil samples. These data were averaged in accordance with 253 communities and/or towns, and compared with demographic, agriculture structure, geomorphology, climate, land use/cover, and soil-forming parent material to discover the SEPHM. Multivariate statistical techniques were further applied to interpret the control factors of each SEPHM. SOM application clustered the 253 towns into nine groups on the map size of 12 × 7 plane (quantization error 1.809; topographic error, 0.0079). The distribution characteristics and Spearman rank correlation coefficients of RIs were strongly associated with the population density, vegetation index, industrial and mining land percent and road density. The RIs were relatively high in which towns in a highly urbanized area with large human population density exist, while low RIs occurred in mountainous and high vegetation cover areas. The resulting dataset identifies the SEPHM of Beijing and links the apparent results of RIs to driving factors, thus serving as an excellent data source to inform policy makers for legislative and land management actions.</p>
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<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Int J Environ Res Public Health</journal-id>
<journal-id journal-id-type="iso-abbrev">Int J Environ Res Public Health</journal-id>
<journal-id journal-id-type="publisher-id">ijerph</journal-id>
<journal-title-group><journal-title>International Journal of Environmental Research and Public Health</journal-title>
</journal-title-group>
<issn pub-type="ppub">1661-7827</issn>
<issn pub-type="epub">1660-4601</issn>
<publisher><publisher-name>MDPI</publisher-name>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">24690947</article-id>
<article-id pub-id-type="pmc">4025005</article-id>
<article-id pub-id-type="doi">10.3390/ijerph110403618</article-id>
<article-id pub-id-type="publisher-id">ijerph-11-03618</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Article</subject>
</subj-group>
</article-categories>
<title-group><article-title>Social-Ecological Patterns of Soil Heavy Metals Based on a Self-Organizing Map (SOM): A Case Study in Beijing, China</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Wang</surname>
<given-names>Binwu</given-names>
</name>
<xref ref-type="aff" rid="af1-ijerph-11-03618">1</xref>
<xref ref-type="aff" rid="af2-ijerph-11-03618">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Li</surname>
<given-names>Hong</given-names>
</name>
<xref ref-type="aff" rid="af3-ijerph-11-03618">3</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Sun</surname>
<given-names>Danfeng</given-names>
</name>
<xref ref-type="aff" rid="af1-ijerph-11-03618">1</xref>
<xref rid="c1-ijerph-11-03618" ref-type="corresp">2*</xref>
</contrib>
</contrib-group>
<aff id="af1-ijerph-11-03618"><label>1</label>
College of Resources and Environmental Sciences, China Agricultural University, No. 2 Yuan Ming Yuan west Road, Beijing 100193, China; E-Mail:<email>binw_w@cau.edu.cn</email>
</aff>
<aff id="af2-ijerph-11-03618"><label>2</label>
Key Laboratory of Agricultural Land Quality, Ministry of Land and Resources, No. 2 Yuan Ming Yuan west Road, Beijing 100193, China</aff>
<aff id="af3-ijerph-11-03618"><label>3</label>
Institute of Agricultural Integrated Development, Beijing Academy of Agriculture and Forestry Sciences, No. 9 Shu Guang Hua Yuan Middle Road, Beijing 100097, China; E-Mail:<email>lihsdf@sina.com</email>
</aff>
<author-notes><corresp id="c1-ijerph-11-03618"><label>*</label>
Author to whom correspondence should be addressed; E-Mail: <email>sundf@cau.edu.cn</email>
; Tel./Fax: +86-10-6273-3869.</corresp>
</author-notes>
<pub-date pub-type="epub"><day>31</day>
<month>3</month>
<year>2014</year>
</pub-date>
<pub-date pub-type="ppub"><month>4</month>
<year>2014</year>
</pub-date>
<volume>11</volume>
<issue>4</issue>
<fpage>3618</fpage>
<lpage>3638</lpage>
<history><date date-type="received"><day>20</day>
<month>2</month>
<year>2014</year>
</date>
<date date-type="rev-recd"><day>18</day>
<month>3</month>
<year>2014</year>
</date>
<date date-type="accepted"><day>19</day>
<month>3</month>
<year>2014</year>
</date>
</history>
<permissions><copyright-statement>© 2014 by the authors; licensee MDPI, Basel, Switzerland.</copyright-statement>
<copyright-year>2014</copyright-year>
<license><license-p><pmc-comment>CREATIVE COMMONS</pmc-comment>
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/3.0/">http://creativecommons.org/licenses/by/3.0/</ext-link>
).</license-p>
</license>
</permissions>
<abstract><p>The regional management of trace elements in soils requires understanding the interaction between the natural system and human socio-economic activities. In this study, a social-ecological patterns of heavy metals (SEPHM) approach was proposed to identify the heavy metal concentration patterns and processes in different ecoregions of Beijing (China) based on a self-organizing map (SOM). Potential ecological risk index (RI) values of Cr, Ni, Zn, Hg, Cu, As, Cd and Pb were calculated for 1,018 surface soil samples. These data were averaged in accordance with 253 communities and/or towns, and compared with demographic, agriculture structure, geomorphology, climate, land use/cover, and soil-forming parent material to discover the SEPHM. Multivariate statistical techniques were further applied to interpret the control factors of each SEPHM. SOM application clustered the 253 towns into nine groups on the map size of 12 × 7 plane (quantization error 1.809; topographic error, 0.0079). The distribution characteristics and Spearman rank correlation coefficients of RIs were strongly associated with the population density, vegetation index, industrial and mining land percent and road density. The RIs were relatively high in which towns in a highly urbanized area with large human population density exist, while low RIs occurred in mountainous and high vegetation cover areas. The resulting dataset identifies the SEPHM of Beijing and links the apparent results of RIs to driving factors, thus serving as an excellent data source to inform policy makers for legislative and land management actions.</p>
</abstract>
<kwd-group><kwd>social-ecological patterns</kwd>
<kwd>soil heavy metals management</kwd>
<kwd>geographical information system</kwd>
<kwd>self-organizing map</kwd>
<kwd>Beijing</kwd>
</kwd-group>
</article-meta>
</front>
</pmc>
</record>
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