International Journal of Marine Science, 2017, Vol.7, No.13, 114-124
116
1.2 Sampling and analysis
A total of 36 recent surface sediment samples (0-10 cm depth) were collected during summer 2015 from the
near-shore zone using plastic spatula. Sediments were transported cooled in polyethylene bags. In the laboratory,
sediments were dried to constant weight, disaggregated and fractionated through stainless sieves. Because most
bioavailable metals were principally associated with fine grains (Salomons and Forstner, 1984), the ˂ 63µm
fraction was used for this study.
A mixture of concentrated nitric, percholoric and hydrofluoric acid (3:2:1 in volume) were added to about 0.5 g of
each sediment samples in Teflon cups, and left for 12 hours before complete digestion at 100ºC (Oregioni and
Aston, 1984). The residue was diluted to 25 ml with deionized water, and filtered using Whatman filter paper. The
resulted solution was analyzed for metals using atomic absorption spectrophotometer (AAS, GBC 932A). The
results were obtained in µg/g. For quality control, all reagents and chemicals were of high analytical grads.
Glassware was soaked in 10% nitric acid and rinsed with distilled water prior to use. Samples were measured
against acid blank. For accuracy, the method was verified by analysis of replicate measurements for the studied
metals in a sample of sediments. A satisfactory performance was obtained within the precision range of 6.2-14.8%
for all studied metals.
1.3 Statistical analysis
The results were subjected to one-way analysis of variance (ANOVA) to test significant differences between sites.
Assumption of homogeneity (Batlett’s test) and normality (Shapiro-Wilk test) of data were assessed prior to
ANOVA, then Duncan’s multiple range test was used to further determine the position of the variance. For
multivariate analysis, Pearson’s correlation and principal component analysis (PCA) were conducted. Statistical
analysis was carried out using software packages SPSS 18.0 for windows.
1.4 Assessment of sediments quality
To interpret and assess the status of metal contamination in sediments, metal levels were compared to the
background levels of heavy metals recorded by Hanna (1992) in sediments of the Red Sea (collected during 1943),
and with the global standard shale values (Forstner and Wittmann, 1979). The contamination condition was also
evaluated by metal assessment indices: contamination factor (CF), metal pollution load index (MPI), Enrichment
factor (EF) and geo-accumulation index (I
geo
). These indices were widely used to describe the contamination
condition of surface sediments in aquatic environment (Chen et al., 2007).
The contamination factor (CF) is the ratio obtained by dividing the concentration of each heavy metal in the
sediments (C
heavy metal
) by the concentration in the background (C
background
). In our study, the mean results of Hanna
(1992) for sediments collected from the Red Sea during 1943 were used for calculating the background values:
=
/
The overall effect of heavy metals in sediments was estimated by metal pollution load index (MPI) that proposed
by Tomlinson et al. (1980). The MPI is a simple comparative way obtained from the mutual effects of all studied
metals with respect to the background values and calculated from the formula:
= (
……
)
/
EF was efficiently used to differentiate between naturally and anthropogenic source of metals. Where metals (M)
were normalized to the textural characteristics of the sediments according to the formula:
= ( / )
/( / )
According to Zhang and Liu (2002), the heavy metals are largely from natural sources (crustal materials) when the
EF below 1.5 (i.e. 0.5 ≤ EF ≤1.5), but when EF value is greater than 1.5 (EF ˃ 1.5), the significant portion of
heavy metals originated from anthropogenic sources.
