Assessment of heavy metal enrichment factors and the degree of contamination in marine sediments from Tamaki Estuary, Auckland, New Zealand

Abstract

Eight sediment cores recovered from Tamaki Estuary were analysed for Cu, Pb, Zn, and Cd using downward cored sub-samples. The results indicate a significant upward enrichment in heavy metals with the highest concentrations found in the uppermost 0-10 cm layer. Assessment of heavy metal pollution in marine sediments requires knowledge of pre-anthropogenic metal concentrations to act as a reference against which measured values can be compared. Pristine values for the cored sediments were determined from flat "base-line" metal trends evident in lower core samples. Various methods for calculating metal enrichment and contamination factors are reviewed in detail and a modified and more robust version of the procedure for calculating the degree of contamination is proposed. The revised procedure allows the incorporation of a flexible range of pollutants, including various organic species, and the degree of contamination is expressed as an average ratio rather than an absolute summation number. Comparative data for normalized enrichment factors and the modified degree of contamination show that Tamaki Estuary sediments have suffered significant systematic heavy metal contamination following catchment urbanization. Compared to baseline values the uppermost sediment layers show four-fold enrichment averaged across eight cores and four analysed metals.

Assessment of heavy metal contamination in the sediments from the Yellow River Wetland National Nature Reserve (the Sanmenxia section), China

“…where C n is the measured concentration of the heavy metal in the sediment, constant 1.5 is the background matrix correction factor due to lithogenic effects (Abrahim and Parker 2008;Çevik et al 2009;Qian et al 2005), B n is the geochemical local background levels (LBLs) of Henan Province (EMC 1990) (Table 1), and n is the number of analyzed elements.…”

“…Toxicity weight 1 was assigned for Cr, Zn, and Mn; 2 was assigned for Cu, 5 for Pb, and 300 for Cd (Singh et al 2002). The contamination levels may be classified descriptively for increasing I geo (Forstner et al 1993) and mC d (Abrahim and Parker 2008) values, and the sediment classification is given for the SPI values (Singh et al 2002) listed in Table 2. When PLI index is more than 1, it means that metal pollution exists; otherwise, there is no pollution (Varol 2011).…”

“…Only the mean values of Cu at the SC site (20.5 mg kg −1 ), Cd at the DHW site (0.05 mg kg −1 ) and NC site (0.07 mg kg −1 ), Zn at the NC site (52.2 mg kg − 1 ) and DHW site (62.8 mg kg −1 ), and all the concentrations of Cr detected at seven sampling sites are approximately equal to the LBLs. Forstner et al (1993) b Abrahim and Parker (2008) c Singh et al (2002) To investigate and determine possible sources of heavy metals in the sediments, statistical analysis of Spearman correlation with two-tailed test was performed using the software package SPSS 19.0. Table 3 shows that the relationships between Cu and Cr (r=0.654), between Cu and Mn (r=0.762), between Cr and Pb (r=0.605), and between Cd and Zn (r= 0.596) are significant (P<0.01), and the clear-cut correlation (P<0.05) also exists between Cu and Pb (r=0.520) and between Mn and Zn (r=0.448).…”

Assessment of trace element contamination in sediment cores from the Pearl River and estuary, South China: geochemical and multivariate analysis approaches

“…In view of these conflicting features, selecting an appropriate background value is essential for obtaining reliable EFs. Other research has also shown that EF values will change considerably with different baseline values (Abrahim and Parker 2008;Celis-Hernandez et al 2013). Consequently, it is more logical and appropriate to use the UCCEC for normalization than to use regional background values or the UCW.…”

Temporal variations and bioaccumulation of heavy metals in different Suaeda salsa marshes of the Yellow River estuary, China

“…Various hydrological processes and sediment physicochemical properties significantly influence the biochemical processes of heavy metals in marshes. There has been intensely increasing interest in understanding the pollution of heavy metals in coastal marsh due to the great influences of human activities (Li et al 2000(Li et al , 2007Caeiro et al 2005;Abrahim and Parker 2008;Bai et al 2011Bai et al , 2012Xiao et al 2013). Exploring heavy metal accumulation in plants for the remediation (or phytoremediation) of coastal environment is of great significance (Chaney et al 1997;Deng et al 2004).…”