Identification of Heavy Metals Contamination at Bushehr Mangroves | ||
| محیط شناسی | ||
| Article 3, Volume 38, Issue 3, December 2012, Pages 27-36 PDF (2.73 M) | ||
| DOI: 10.22059/jes.2012.29146 | ||
| Authors | ||
| Ali Davari; Afshin Danehkar; Nematolah Khorasani; Arash Javanshir | ||
| Abstract | ||
| Mangrove trees occur along the coastal areas of Bushehr province, south Iran and these plants have been used in traditional medicine and fodder for centuries. Heavy metals are known to pose a potential threat to terrestrial and aquatic biota. However, little is known on the levels of heavy metals found in mangrove in Iran. To understand levels of heavy metals and identified heavy metal source, we used mathematical methods. Principal components analysis (PCA) is a multivariate statistical technique capable of discerning patterns in large environmental datasets. Typically, PCA has been used to examine the spatial variability of contaminants. However, it has also been used to discriminate between contaminant sources and to identify key variables for environmental monitoring purposes. Surface mangrove sediments (0–10 cm) collected from three mangrove sites in Bushehr, northern Persian Gulf were sampled for metal contamination analysis in April 2009. The concentrations ranged (in µg g-1 dry weight): Al, 1795-30240; Fe,6425-51530; Cd, 0.6-3.45; Cu, 14.1-98.28; Ni, 14.1-204.54; Pb, 34.15-191.6; V, 57.38-825.26 and Zn, 44.91–306.15; respectively. Reducing the in?uence of grain size using granulometric normalisation mean that other factors affecting metal variability, including mineralogy, anthropogenic sources and oil pollution, could be identi?ed and interpreted more clearly. | ||
| Keywords | ||
| Bushehr Province; Mangrove forest; Normalisation; PCA; Sediment | ||
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