Heavy-Metal Distribution in River Waters and Sediments around a "Firefly Village", Shikoku, Japan: Application of Multivariate Analysis
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- ANAZAWA Katsuro
- Department of Earth and Environmental Sciences, Faculty of Science, Kagoshima University
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- KAIDA Yasuhiko
- National Institute of Advanced Industrial Science and Technology, Kyushu
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- SHINOMURA Yoshinori
- Graduate School of Frontier Sciences, University of Tokyo
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- TOMIYASU Takashi
- Department of Earth and Environmental Sciences, Faculty of Science, Kagoshima University
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- SAKAMOTO Hayao
- Department of Earth and Environmental Sciences, Faculty of Science, Kagoshima University
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Description
River water and sediment samples were collected at the same site in a vicinity of an abandoned mine, and the concentrations of major elements and heavy metals were determined. The chemical correlations were observed by principal component analysis (PCA), and the samples were classified by cluster analysis (CA) based on the PCA scores. The PCA results presented a macroscopic viewpoint of covariance structure, i.e., the chemical elements could be classified into three groups: 1) major elements and heavy metals in the river water, 2) Cd, Fe and Mn in the sediments, and 3) Cu and Zn in the sediments. The CA results implied a similarity of chemical compositions in most parts of the study area, except the ranges close to the abandoned copper mine. At the mixing location of mining water with natural river water, major elements and cadmium showed simple physical mixing (conservative mixing). Other heavy metals (Cu, Fe, Mn and Zn) showed the massive precipitation at the mixing event. The PCA structure was mainly interpreted in terms of the mixing process between mining water and diluted natural river water.
Journal
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- Analytical Sciences
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Analytical Sciences 20 (1), 79-84, 2004
The Japan Society for Analytical Chemistry
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Details 詳細情報について
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- CRID
- 1390282679233879680
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- NII Article ID
- 130004440824
- 30013458899
- 10011942392
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- NII Book ID
- AA10500785
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- COI
- 1:CAS:528:DC%2BD2cXmvFWjtQ%3D%3D
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- ISSN
- 13482246
- 09106340
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- NDL BIB ID
- 6810122
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- PubMed
- 14753261
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL Search
- Crossref
- PubMed
- CiNii Articles
- OpenAIRE
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- Abstract License Flag
- Disallowed