Multivariate Statistics and Heavy Metals Contamination in Beach Sediments from The Sakarya Canyon, Turkey


Yalçın M. G. , Simsek G., Bilge Ocak S., Yalçın F., Kalayci Y., Karaman M. E.

ASIAN JOURNAL OF CHEMISTRY, vol.25, no.4, pp.2059-2066, 2013 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 25 Issue: 4
  • Publication Date: 2013
  • Doi Number: 10.14233/ajchem.2013.13309
  • Journal Name: ASIAN JOURNAL OF CHEMISTRY
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.2059-2066
  • Keywords: Heavy metal, Multivariate statistic, Beach sand, Multivariate, Sakarya Canyon, BLACK-SEA, TURKISH COAST, MARINE-ALGAE, GEOCHEMISTRY, PONTIDES, ANATOLIA, ELEMENTS, ORIGIN, MERSIN, SHELF

Abstract

The aim of the study is to determine heavy metal contents and their possible origins that represent the variability of The Sakarya Canyon coastal sediments. In addition to determine the source of heavy metals (natural and anthropogenic), simple and multivariate statistical analyses were applied to the samples. In all the samples, ignition loss ratio is between 0.01-0.09. 47.26 % of the samples, which have 0.5-0.25 mm, show very good sorting. G10, G19, G20 and G21 reflect the conditions of the irregular sedimentary environment. The heavy metals, Fe, Mg, Ti, Cr, Zn, Pb and Cu, are considered to come from near regions according to frequency histograms. By principal component analysis (PCA; factor 1: 40.911 %; factor 2: 21.558 %; factor 3: 13.548 %) and cluster analysis, heavy metals were formed three (3) groups. According to hierarchical cluster analysis, Q-type cluster at the similarity level of 50 % form three (3) different groups and they show the same features during pollution. These results reveal that they are highly reliable data for statistical data of model summary (according to the value R-2 = 100) and Anova 21 explanation value. According to maximum abundances As:G4; Ni:G7; Mg, Ti, Mn, Fe, V, Cr, Co, Nb:G13; Cu, Zr, Sn:G20; Al, Zn, Ga, Cd, Pb:G22 stations showed the highest anomaly. Influence of anthropogenic can be constituted in this region coming from port wastes, mining operations, road pollution, urban wastes and industrial wastes.