Assessment of Heavy Metal Contamination in the Sediments of the Shuangtaizi Estuary Using Multivariate Statistical Techniques. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Li, Chen; Sun, Menghan; Song, Chengwen; Tao, Ping; Yin, Yanyan; Shao, Mihua
• Is Part Of: Soil & sediment contamination. Volume 26:Issue 1(2017)
• Page Start: 45
• Page End: 58
• Publication Date: 2017-01-02
• Subjects: Estuary -- sediment -- heavy metals -- cluster analysis -- principal component analysis; Soil pollution -- Periodicals; Soil protection -- Periodicals; 628.5505
• DOI: 10.1080/15320383.2017.1245710
• Languages: English
• ISSNs: 1532-0383

Abstract

ABSTRACT: In order to assess heavy metal pollution of sediment samples collected from Shuangtaizi estuary, contamination factor (CF) and multivariate statistical analyses, including principal component analysis (PCA), cluster analysis (CA) and correlation analysis, are carried out in this paper. CF confirms that Pb, Cu and Hg concentrations are very low and all fall within the range of background, while Zn and Cd demonstrate moderate contamination (in A10, A13, A15, A16 and A17 sites) and very high contamination (in A10, A13, A15 and A17 sites), respectively. The PCA indicates that four significant principal components (PCs) are extracted, explaining 88.959% of total variance, which suggests that Pb, Cu and Zn are mainly associated with organic carbon (OC). The result from CA is consistent with that obtained from PCA, classifying that the heavy metals in two clusters derive from different sources. Correlation analysis supports the conclusions from PCA and CA, elucidating the relationships between heavy metals and particle sizes of the sediments.