Analysis of heavy metal contamination in surface sediments of Iskenderun Bay, Turkey

As a result of technological development, heavy metal pollution has become a threat to life. Many adverse effects of metal pollution on the aquatic environment have been identified. Heavy metal pollution in the aquatic environment derives from natural sources such as air, soil, and dissolved mineral rocks (Adamu et al. 2015; Skordas et al. 2015), as well as anthropogenic sources such as domestic, industrial, and agricultural effluents (Wei & Yang 2010; Mohiuddin et al. 2010).

The discharge, storage, and precipitation of heavy metals occur in marine and oceanic sediments (Fujita et al. 2014; Machado et al. 2016). Sediments are a good indicator of heavy metals from anthropogenic sources due to the hydrophobic properties of the latter and their tendency to accumulate with precipitation. Sediment analysis provides information on total accumulation (Anderson Abel et al. 2016). Sedimentation is very important for the accumulation of heavy metals in the hydrological cycle in the aquatic environment. Heavy metals are not completely immobilized in the surface sediment, which is a biological, physicochemical, hydrological, and geological interaction area in a complex system. Instead, they migrate and sometimes accumulate (Dhanakumar et al. 2015; Chen et al. 2019).

In order to determine metal contamination sources in the aquatic environment, it is important to examine changes in natural and anthropogenic trace elements (Bing et al. 2013). For this purpose, indices such as the enrichment factor (EF), the contamination factor (CF), and the geoaccumulation index (Igeo) are employed to identify whether metals originate from natural geological structures, and the potential ecological risk index RI is frequently used to assess the ecological risk (Yang et al. 2014; Bing et al. 2013; Long et al. 2006; Hou et al. 2013). The RI is commonly preferred along with principal component analysis (PCA) and cluster analysis (CA) to characterize pollutant emissions (Huang et al. 2018).

Pollution has become a serious issue in countries bordering the Mediterranean Sea. The semi-enclosed structure of this ecosystem and the increase in population density along the Mediterranean coastline have caused considerable water pollution. In order to mitigate this problem, a comprehensive pollution prevention and control program (Mediterranean Action Plan), organized and supported by the United Nations and various international agencies, has been implemented by the Mediterranean countries since 1975. A number of researchers have reported that many trace metals, from either natural or anthropogenic sources, enter the Mediterranean Sea in different parts of this ecosystem (Cubadda et al. 2001).

Previous studies investigated the presence and effects of heavy metals on seawater and sediment in Iskenderun Bay (Türkmen & Aras 2011) focusing on sediment and benthos (Dural and Göksu 2006; Türkmen & Aras 2011), marine algae (Olgunoğlu & Polat 2007), aquatic vertebrates (Kargın et al. 2006; Kalay et al. 1999), and aquatic invertebrates (Duysak et al. 2013; Duysak & Ersoy 2014).

The objectives of this study were to determine the accumulation and distribution of ten heavy metals (i.e. Cu, Pb, Zn, Ni, Mn, Fe, As, Cd, Cr and Hg) in sediments collected from eight sites located in different regions of Iskenderun Bay. Furthermore, we calculated the contamination factor, the pollution load index, and the potential ecological risk index (RI) to determine whether the source of pollution was natural or anthropogenic.

Two-period sampling was performed to cover the Iskenderun, Yumurtalık, and Arsuz regions in the northern and southern parts of the study area, i.e. Iskenderun Bay (Fig. 1).

Figure 1

Surface sediment samples were collected at the selected sites in the study area on 8 April 2018 and 8 June 2019, using a van Veen grab sampler (Table 1). Samples were homogenized and placed in plastic bags before being transferred to Petri dishes pre-washed with acid and RO purified water in the laboratory. Samples in Petri dishes were then dried at 60°C for 24 h. The concentrations of Cu, Pb, Zn, Ni, Mn, Fe, As, Cd, Cr, and Hg were measured in the digested phase by inductively coupled plasma mass spectrometry (ICP-MS; ACME Analytical Labs, Vancouver, BC, Canada). The prepared sample was digested with a modified aqua regia solution with equal parts of concentrated HCl, HNO₃, and DI H₂O for 1 h in a heating block. The sample was made up to volume with dilute HCl. Quality control was performed using duplicates, blanks, and internal standard reference material (DS 9) obtained from ACME Analytical Labs. The values obtained (mg kg⁻¹) from the analysis of this sample were as follows:

Two indices, EF and CF, were used to assess metal accumulation in the sediment. The former is calculated by dividing the current metal/Al weight ratio by the background metal/Al ratio (Acevedo-Figueroa et al. 2006; Çevik et al. 2009; Vrhovnik et al. 2013). In this way, the anthropogenic effect can be determined by detecting an increase exceeding the background value. The obtained values were evaluated according to the procedure described by Sutherland (2000): EF < 2, EF = 2–5, EF = 5–20, EF = 20–40, and EF > 40 indicate no, moderate, significant, very high, and excessive enrichment, respectively. Further, CF is the ratio of the current metal content in the existing sediment to the normal permissible concentration levels. Thus, metal enrichment in the sediment is assessed. CF was calculated according to the method employed by Håkanson (1980), and CF < 1, 1 ≤ CF < 3, 3 ≤ CF < 6, and CF > 6 indicate low, moderate, high, and very high contamination, respectively.

To determine environmental quality of the sediment, an integrated Pollution Load Index (PLI) was used, according to Suresh et al. (2011): PLI=(CF1×CF2×…CFn)1/n PLI = {(C{F_1} \times C{F_2} \times \ldots C{F_n})^{1/n}} where CF is the contamination factor and n is the number of elements used. A PLI value of 0 indicates a clean area, while a value of up to 1 indicates pollution. The RI defined by Håkanson (1980) was used to draw inferences about the toxic effects of metals. The RI values for each metal ( Eri E_r^i ) and an integrated value for all metals are interpreted as follows: Eri<40, 40≤Eri<80, 80≤Eri<160, 160≤Eri<320, and Eri≥320 E_r^i < 40,\,40 \le E_r^i < 80,\,80 \le E_r^i < 160,\,160 \le E_r^i < 320,\,{\rm{and}}\,E_r^i \ge 320 indicate low, moderate, significant, high, and very high potential ecological risk, respectively. It is calculated using the following formula presented by Håkanson (1980): Eri=Cfi×Tfi E_r^i = C_f^i \times T_f^i where Tfi T_f^i is the toxicity coefficient for a single metal, and Cfi C_f^i is the ratio between the metal content in the sediment at a given site and the background concentration levels. Depending on the toxicity, the corresponding coefficients are as follows: Hg = 40, Cd = 30, As = 10, Cu = Pb = Ni = 5, Cr = 2, and Zn = 1 (Guo et al. 2010).

Further, the RI is calculated as follows: RI=∑Eri RI = \sum {E_r^i} and RI < 150, 150 ≤ RI < 300, 300 ≤ RI < 600, and RI ≥ 600 indicate low, moderate, significant, and very high ecological risk, respectively.

In addition, Pearson’s correlation analysis was used to analyze the relationships between the variables. Further, CA was used to determine the distance between the variables. PCA was employed to identify the main sources of variation between the study sites in the bay.