el-amier, et al.,

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Bioscience Research Print ISSN: 1811-9506 Online ISSN: 2218-3973

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RESEARCH ARTICLE BIOSCIENCE RESEARCH, 2018 15(3): 2626-2639. OPEN ACCESS

Ecological Risk Assessment of Heavy Metal Pollution in Top soil of Mediterranean Coast: A Case Study of Mareotis Coast, Egypt

Yasser A. El-Amier1*; Suliman M. Alghanem2 and Muhammad A. El-Alfy3

1Botany Department, Faculty of Science, Mansoura University, Mansoura, Egypt 2Biology Department, Faculty of Science, Tabuk University, Tabuk, Kingdom of Saudi Arabia 3Marine Pollution Department, National Institute of Oceanography and Fisheries, Egypt *Correspondence: [email protected] Accepted: 04 Aug. 2018 Published online: 30 Sep. 2018

The present study was conducted in Mediterranean coastal area to determine the soil contamination by heavy metals as well as their accumulation using halophytes. Sixteen sites were selected along the study area, topsoil samples and plant species were taken and then transferred to the laboratory for metal analyses. Results revealed that the order of metal concentration in total and available form of the soil was as follow; Fe > Pb > Cr > Ni > Cd > Co. The average concentration of Cd and Pb are within the Canadian soil quality guidelines (CSQG) and European Union Standards (EU) limits, but more than those for average upper earth crust (AUEC). While Ni, Co and Cr are more than the limits of CSQG and AUEC. The contamination factor of heavy metals is decreased in the following order: Cd > Cr > Pb > Ni > Co > Fe and the enrichment factors of studied metals showed that their sources were from anthropogenic impacts. The anthropogenic factors could lead to potential environmental risk as indicated by the contamination degree and the Geo-accumulation index (Igeo) results of heavy metals. On the other hand, the maximum metal concentrations of Fe, Pb and Cd were found in Atriplex portulacoides, whereas Ni and Co were related to Halocnemum strobilaceum, respectively. On the basis of the BAF values, the studied plant species could be considered as hyperaccumulators for Fe, Pb, Cd and Co (BAF values >1) except Ni. Further observations should be considered to apply these halophyte species as remediators in different applied sectors.

Keywords: Heavy metals, Soil contamination, Mareotis coast, Halophytes, Phytoaccumulation.

INTRODUCTION

Heavy metals are important environmental pollutants threatening the health of human populations, which can be dispersed and accumulated in plants and animals, and taken in by humans through consumption as well as natural ecosystems (Wang and Zhang, 2012; Ntakirutimana et al., 2013). Soils are important components of our terrestrial environment and have a significant impact on the structure and

function of land ecosystems, which provides nutrients to living organisms, and act as a storehouse for a variety of environmental pollutants (Xu et al., 2017).

In recent years the modernization of industry and the presence of intensive human activities increase human exposure to heavy metals (Sun et al., 2010). At the long-term input of metals could result in a decreased buffering capacity of soil and groundwater contamination (Krishna and Govil,

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El-Amier, et al., Ecological Risk Assessment of Heavy Metal

Bioscience Research, 2018 volume 15(3):2626-2639 2627

2008) as well as posed adverse effect on human health. So heavy metals contamination has been a worldwide environmental concern with its potential ecological effect (Liu et al., 2009). Moreover, the investigation of soil metal distribution and their influencing factors in topsoil could offer an ideal means to monitor and assess the pollution of the soil itself and the overall environmental quality as reflected in soils (Li et al., 2009).

Phytoremediation is promising economic effective biotechnology that uses plants for the cleaning of polluted water and soil, as well as it is suitable when the pollutants cover a large area. Phytoremediation can be used for inorganic and organic contaminants present in the soil, air, and water (Chibuike and Obiora, 2014; Sytar et al., 2016). The mechanisms of soil remediation contaminated by heavy metals can be achieved through several categories of phytoremediation such as phytoextraction, phytodegradation, phytostabilization, and phytovolatilization. Phytoextraction is the most common form of phytoremediation, which involves the accumulation of heavy metals in the roots, stems, leaves, and inflorescences of phytoremediation plants (Dixit et al., 2015).

The coastal zones of Egypt suffer from a number of serious problems including unplanned development, land subsidence, excessive erosion rates, water logging, salt water intrusion, soil salinization and ecosystem degradation (El-Raey, 1997; Eid and El-Marsafawy, 2002). A review of

the literature shows that a great number of studies of heavy metal pollution in soil have been carried out in Egypt during the last 10 years to understand their impact on terrestrial ecosystems such as El-Bady (2014), Shokr et al., (2016), El-Amier et al., (2017) and El-Alfy et al., (2017). The main goals of this study were; quantification of heavy metal pollution levels of soil in the coastal region, Egypt, to assess the ecological risks posed by these contaminated soil and evaluate the phyto-accumulation of heavy metals by some wild plants. MATERIALS AND METHODS

Description of the study area The Mediterranean coastal land of Egypt has

a narrow coastal belt that stretches between Sallum (on the Libyan borders) eastward to Rafah (on the Palestinian borders) for about 970 km with a normal width ranging between 20- 25 km in a north-south direction (Figure 1). Ecologically, the Mediterranean coast of Egypt can be divided into three sections: 1) the western section (Mareoits coast) extends from Sallum to Abu Qir for about 550 km, it is a thin belt of land parallel to the Mediterranean Sea. Its average width, from sea landward, is about 20 km and it is bordered by Lake Mariut on the east, 2) the middle section (Deltaic coast) runs from Abu Qir to Port Said for about 180 km and 3) the eastern section (Sinai Northern coast) stretches from Port Said to Rafah for about 240 km (Zahran et al., 1990).

Figure 1: A map showing the study area and the sampling sites



The selected area is located between 29° 66' - 28° 90' Easting longitude (El-Ajami) and 31° 3' - 30° 85' Northern latitude (Ras El-Hekma). The sampled sites are distributed in two governorates of Egypt, namely: Alexandria and Marsa Matruh (Figure 1).

The soils of the western Mediterranean coastal land of Egypt are fine and essentially alluvial. They are derived from two main sources. The first is Maruit tableland (inland plateau), composed essentially of limestone alternating with strata of limestone and shale, and the second source is beach deposits composed of calcareous oolitic grains (Harga, 1967). The climate of the northwestern coastal zone is that of the arid Mediterranean, where the stress conditions of drought caused by scarcity of rain and high solar radiation are somewhat tempered by the maritime influence on the atmospheric relative humidity and temperature (Ayyad and Ghabbur, 1986).

Soil sampling and analyses Sixteen surface soil samples (0–20cm depth)

were collected from each site (triplicates) using a Van-Veen grab coated with polyethylene. Soil texture and organic matter content were determined according to Piper (1947), while calcium carbonate content was determined according to Jackson (1962). The soil solution of (1:5) was prepared and electrical conductivity and pH values were determined by a portable meter (Model Corning, NY 14831 USA) (Jackson, 1962). The samples were dried in the oven at 70 °C and sieved using 0.75 mm plastic sieve. For metal analysis, soil digestion for about two hours in a mixture of 3:2:1 HNO3, HClO4, and HF acids, respectively to detect the heavy metal contamination in the soil samples (Oregioni and Astone, 1984).

Risk assessment

Enrichment factor (EF): Enrichment Factor is considered as an

effective tool to evaluate the magnitude of contaminants in the environment. Iron (Fe) was chosen as the controlling element (Seshan et al., 2010).

Enrichment Factor=Ctracemetal / Cbackground Where, C is the concentration of metal.

Contamination factor (CF): The CF is the ratio calculated by dividing the

concentration of each metal in the sediment by

the baseline or background value (Tomilson et al., 1980). Contamination Factor (CF) = C metal / C background

Degree of contamination (DC): The Degree of contamination (Dc) is defined

as the sum of all contamination factors for a given site (Hakanson, 1980):

DC= ∑ 𝐶𝐹𝑛𝑖=1 i

where CF is the single contamination factor and n is the count of the elements present.

Ecological risk assessment: The ecological risk was assessed using two

indices; pollution load index as equation 1 and potential ecological risk index as equations (2 & 3).

𝑃𝐿𝐼 = (𝐶𝑓1 ∗ 𝐶𝑓2 ∗ 𝐶𝑓3 … … . . 𝐶𝑓𝑛) 1/𝑛 𝐸𝑟 = 𝑇𝑟 ∗ 𝐶𝑓

RI = ∑ 𝐸𝑟

𝑛

1

where Er is the single index of the ecological risk factor, and n is the count of the heavy metal species, Tr = toxic response factor suggested by Hakanson (1980) for five metals Cd (30), Co (5), Pb (5), Ni (5) and Cr (2).

Geo-accumulation index: An index of geo-accumulation (Igeo) was

originally defined by Muller (1969) to determine and define the metal contamination in sediments by comparing current concentrations with pre-industrial levels.

𝐼𝑔𝑒𝑜 = 𝐿𝑜𝑔2 (𝐶𝑛

1.5𝐵𝑛)

Where, Cn: metal concentration in sediments, Bn: geochemical background value in average shale of element n and 1.5 is the background matrix correction.

Plant sampling and analyses Four halophytes species were collected at full

maturity stage during June 2017, nomenclature and identification of plant species were carried out according to Boulos (1999 - 2005). All plants were washed and cleaned with tap water, oven dried at

50 ∘C, and ground into powder with an electric grinder. For metal analyses, 0.1 g (dry weight) of plant samples was added to Teflon beakers and digested with HNO3/H2O2 (3:1, v/v) at 70 to 90 °C during which temperatures were raised to approximately 95°C until evolution of nitrous gas had stopped and the digest became quite clear. The digests were diluted with distilled water up to



a known volume (Allen et al., 1974). Fe, Cd, Co, Ni, and Pb were estimated using Atomic Absorption Spectrometer (A Perkin-Elemer, Model 2380, USA).

Phytoremediation efficiency The bioaccumulation factor (BAF) determines

the ability of a plant to uptake a metal from soils using the following equations:

𝐵𝐴𝐹𝑠ℎ𝑜𝑜𝑡 = 𝐶𝑠ℎ𝑜𝑜𝑡/𝐶𝑠𝑜𝑖𝑙 Where C shoot and C soil represent the metal

concentrations in the shoots and soil, respectively (Yoon et al., 2006).

Statistical analyses The analysis of soil samples and heavy metal

of plant were done in triplicates and the data are presented as a mean ± standard deviation. Pearson correlation coefficients were calculated to analyze the correlation between heavy metals in plant and soil. RESULTS AND DISCUSSION

Soil

Physiochemical parameters: The soil is a thin, unconsolidated layer with a

variable amount of mineral and organic material. Soil characteristics are sensitive to changes in the

environment and are therefore used as indicators of the ecosystem (Boluda et al., 2011). The availability and ecological toxicity risks of heavy metals depend on various soil physiochemical factors such as the pH, particle size, degree of aeration and microbial activity (Chibuike and Obiora, 2014).

Table 1 summarizes the physiochemical properties of the soil. Harter (1983) reported that soil pH is the major factor affecting soil quality, microorganism activity and physical condition of the soil. The pH was observed at all sites ranged from 7.7 to 8.25 with a mean value of 7.99. In alkaline soil, metals tend to form metal mineral phosphates and carbonates which are insoluble, whereas, in acidic soil, metals are more soluble and more bioavailable in the soil solution (Sandrin and Hoffman 2007; Egbenda et al., 2015). Electrical conductivity (EC) expresses ion contents of the solution and thus give a clear idea of salinity in the soil (Fuller et al., 1995). EC value in all sites ranged between 1.28 and 0.34 ds.m-1 (Table 1).The highest EC values due to the all sites nearby sea and sea water intrusion from the Mediterranean Sea (Osman and Kloas, 2010; El-Amier et al., 2017).The soil texture in all sites is formed mainly of coarse fraction (sand) and partly of fine fractions (silt and clay), the sand contents ranging from 61.5 (Site 2) to 80.72 % (Site 12).

Table 1: Soil analysis collected from the Mareotis coast.

Site no. Soil texture %

CaCO3 % SOM % pH EC ds.m-1 Sand Silt Clay

1 73.3 15.5 11.2 2.60 2.08 8.03 2.74

2 61.5 23.6 14.9 2.12 2.79 7.79 2.41

3 76.9 14.9 8.2 3.09 1.22 8.21 1.86

4 62.3 23.5 14.2 2.19 2.68 7.83 1.79

5 76.4 14.8 8.8 2.97 1.36 8.18 2.51

6 73.8 15.6 10.6 2.65 1.86 8.07 1.72

7 77.62 14.2 8.18 2.20 1.63 8.08 2.41

8 74.82 14.5 10.68 2.00 2.08 7.98 2.65

9 76.22 14.2 9.58 2.13 1.77 8.06 2.09

10 79.02 13.8 7.18 2.57 1.12 8.21 1.60

11 61.92 22.8 15.28 1.44 2.94 7.70 1.28

12 80.72 13.5 5.78 4.27 0.96 8.25 1.82

13 76.95 12.6 10.46 2.80 2.12 7.86 2.23

14 76.25 12.9 10.86 2.74 2.08 7.81 1.63

15 68.35 20.5 11.16 3.05 2.48 7.73 1.79

16 79.85 12.6 7.56 3.51 1.65 7.97 1.72

Average 73.50 16.22 10.29 2.65 1.93 7.99 2.02

± SD 6.42 3.96 2.74 0.67 0.60 0.18 0.43 EC: Electrical conductivity; SOM: Soil organic matter



The soil organic matter (SOM) was found highest in site 11 (2.94%), while it was lowest in site 12 (0.96%) (Table 1). Significant negative correlation between SOM and soil textures was recorded (Zhang et al., 2016), as well as, SOM has been shown to decrease heavy metal availability through immobilization of these metals (Yi et al., 2007). According to Odoemelam and Ajunwa (2008) reported SOM content of < 2.0 % as low. The main reason for such low levels of SOM is the poor silt and clay contents of soils (Sollins et al., 1996; El-Amier et al., 2017). The carbonate content (CaCO3) ranged from 1.44 to 3.51 % revealing the nature of the studied soils, which play role in soil structure, colour and neutralize soil acidity. However, these levels are higher than those reported by El-Amier et al., (2017) excluding CaCO3 less, but similar to the levels observed in other studies (Serag, 1999; Hegazy et al., 2008; Zahran and El-Amier, 2013).

Heavy metals in soil Soil pollution with heavy metals has been

attracting more and more interests. The sewage irrigation, use of pesticide and fertilizer containing heavy metals and atmospheric pollutant deposition caused the heavy metal enrichment in the soil. Soil microorganisms cannot degrade heavy metal pollutants making it difficult to eliminate soil contaminants in the short-term (Jia et al., 2018).

The range of total heavy metals in mg.kg-1 for Fe (477.67 - 1239.46), Co (3.83- 11.98), Cd (8.11-16.57), Pb (22.42-48), Ni (22.65-126.65) and Cr (17.55-378.98) with mean values of 7.16, 0.27, 0.86, 4.20, 2.56 and 3.56 for each respectively as shown in Table (2). While this range for the available metals in mg.kg-1 was as follow; for Fe (4.13 - 10.72), Co (0.13 – 0.39 ), Cd (0.73 - 1), Pb (3.71 -4.91 ), Ni (1.97 -3.07 ) and Cr (2.88 – 4.12) with mean values of 7.16 , 0.27 , 0.86 , 4.20 , 2.56 and 3.56 for each respectively as shown in Table (3). The order of metals abundance in total and available form in the top soil of Mareotis coast was as follow; Fe > Pb > Cr > Ni > Cd > Co.

The average total concentration of Cd and Pb are within the CSQG and EU limits more than those for AUEC, after Wedepohl (1995) of 11.6 and 0.1 for Cd and Pb respectively. Average values of Ni and Cr are more than the limits of CSQG and AUEC. While the average values of Co are within the limits.

Although most natural soils contain less than 1 mg kg-1 cadmium from the weathering of parent materials, those developed on black shales and

those associated with mineralized deposits can have much higher levels (Alloway, 1995). Cadmium is distributed in the marine environment at low concentrations but when being accumulated may act as a poison to humans (Stankovic et al., 2011).

High concentrations of lead are related to higher depositions from vehicular emissions along the international coastal road. When lead is deposited in soil from anthropogenic sources, it does not biodegrade or decay and is not rapidly absorbed by plants, so it remains in the soil at elevated levels. Lead is toxic to humans, and poisoning can occur either through ingestion of lead or by breathing in lead dust (Steffan et al., 2018). While, Natural emissions are from wind resuspension, sea salt, and biogenic sources. Werkenthin et al., (2014) revealed that potential contribution of traffic to Pb and Cd contamination in roadside soils. In fact, traffic is generally believed to be the major source of Pb and Cd in soils.

The Cr and Ni content of topsoil may increase due to pollution from various sources of which attributed to industrial wastes, this is agreed with Li et al., (2012). Lago-Vila et al., (2015) revealed that Ni and Cr are potentially toxic elements. Where the occurrence of cobalt in the earth's surface varies greatly. This element does not exist in its natural form and is encountered only in meteorites. An increased amount of cobalt occurs as a result of industrial pollution (Barałkiewicz and Siepak, 1999).

Risk assessment From the results of EF, the source of metals in

the studied area seem to be from anthropogenic activities as EF > 2 (Liaghati et al., 2003). The enrichment value for studied metals take the order of; Cd > Cr > Pb > Ni > Co. Cadmium is more abundant than other metals, this agrees with El-Amier et al., (2017); whereas Co showed the lowest appearance (Table 4).

The EF varied from 1320.86 to 3965.69 and 53.59 to 216.88 for Cd and Pb (extremely high enrichment in all sites), respectively.



Table 2: Total heavy metal contents of the topsoil sampled in the Mareotis coast.

Site no. Heavy metal (mg.kg-1)

Fe Cd Pb Ni Cr Co

1 609.64 10.68 45.77 76.15 238.44 7.88

2 698.46 8.25 39.51 114.34 257.64 11.62

3 522.31 11.32 48 126.65 333.1 5.55

4 567.19 8.11 41.46 76.54 124.5 9.17

5 477.67 12.04 22.42 105.72 17.55 3.83

6 654.51 12.7 27.56 118.59 33.48 10.42

7 880.13 10.76 45.83 76.38 363.1 8.06

8 968.96 13.49 39.57 114.57 378.98 11.8

9 998.46 11.39 39.04 110.28 276.06 5.73

10 1054.97 9.98 33.73 76.76 94.65 9.35

11 942.23 12.11 35.45 105.95 147.54 4.01

12 1164.94 9.78 42.58 55.5 294.21 10.6

13 1150.63 10.84 26.13 76.6 62.42 8.24

14 1239.46 16.57 32.2 22.65 32.23 11.98

15 1063.31 11.47 39.09 110.5 41.38 5.91

16 1108.19 10.06 33.78 76.99 119.22 9.53

Average 881.32 11.22 37.01 90.26 175.91 8.36

Av. shale 47200 0.3 20 68 90 19

CSQG - 40 - 70 50 64

(EU, 2002) - - - 300 75 150

AUEC 30890 11.6 0.1 17 18.6 35 Average shale, after Turekian and Wedepohl (1961) -Average upper earth crust (AUEC), after Wedepohl (1995)-CSQG of Agricultural soil: Canadian soil quality guidelines, 2007, EU, 2002: European Union Standards

Table 3: Available heavy metal contents of the topsoil sampled in the Mareotis coast.

Site no. Available heavy metal (mg.kg-1)

Fe Co Cd Pb Ni Cr

1 5.27 0.26 0.79 4.29 1.97 3.79

2 6.04 0.38 0.99 3.71 2.96 3.96

3 4.52 0.18 0.83 4.50 2.85 2.88

4 4.90 0.30 0.73 3.89 1.98 3.63

5 4.13 0.13 0.89 4.09 2.74 2.95

6 5.66 0.34 0.94 4.91 3.07 4.12

7 7.61 0.26 0.79 4.30 1.98 3.80

8 8.38 0.38 0.99 3.71 2.96 3.96

9 6.85 0.19 0.84 4.51 2.85 2.89

10 7.24 0.30 0.73 3.90 1.99 3.64

11 6.47 0.13 0.89 4.09 2.74 2.96

12 8.00 0.35 0.94 4.92 3.07 4.12

13 9.95 0.27 0.80 4.31 1.98 3.80

14 10.72 0.39 1.00 3.72 2.97 3.97

15 9.19 0.19 0.84 4.51 2.86 2.89

16 9.58 0.31 0.74 3.90 1.99 3.64

Average 7.16 0.27 0.86 4.20 2.56 3.56

± SD 2.03 0.09 0.09 0.40 0.47 0.48



Table 4. The Enrichment factor (EF) of heavy metals in the topsoil of Mareotis coast.

Site no. Fe Cd Pb Ni Cr Co

1 1 2756.25 177.18 86.70 205.12 32.11

2 1 1858.37 133.50 113.63 193.45 41.33

3 1 3409.88 216.88 168.31 334.46 26.40

4 1 2249.64 172.51 93.67 115.12 40.16

5 1 3965.69 110.77 153.63 19.27 19.92

6 1 3052.87 99.37 125.77 26.83 39.55

7 1 1923.47 122.89 60.24 216.36 22.75

8 1 2190.42 96.38 82.07 205.12 30.25

9 1 1794.79 92.28 76.67 145.00 14.26

10 1 1488.37 75.46 50.50 47.05 22.02

11 1 2022.12 88.79 78.05 82.12 10.57

12 1 1320.86 86.26 33.07 132.45 22.60

13 1 1482.23 53.59 46.21 28.45 17.79

14 1 2103.35 61.31 12.68 13.64 24.01

15 1 1697.17 86.76 72.13 20.41 13.81

16 1 1428.25 71.94 48.22 56.42 21.36

Mean 1 2171.48 109.12 81.35 115.08 24.93

The EF of Ni varied from 12.68 to 168.31 and showed significant enrichment in sites 12 and 14 and extremely high enrichment in other sites. For Cr, EF varied from 13.64 to 334.46 and showed significant enrichment in sites 5 and 14; very high enrichment in sites 6 and 15 and extremely high enrichment in other sites.

The EF of Co ranged between 10.57 and 41.33 and revealed significant enrichment in sites 5, 9, 11, 13 and 15; extremely high enrichment in sites 2 and 4 and very high enrichment in other sites (Table 4). The increase of EF approved the increase of anthropogenic activities according to Sutherland (2000).

Anthropogenic source of heavy metals which have an enrichment factor ≥ 2 is may be attributable to a wide range of potential effects of the coastal ecosystems, mainly from the point and non-point sources of pollution. Storm water runoff from hinterland and from sewage, industrial, irrigation, and urban runoff are the main sources of heavy metals in the studied deposits (El-Sorogy and Attiah, 2015). Yuan et al., (2014) suggested that Pb and Cd in the topsoil were strongly influenced by anthropogenic or chemical industry activities, while Ni and Cr mainly originated from the natural parent materials of the soils.

To study the level of metal contamination, CF calculation is very benefited (Tomlinson et al., 1980). The ranges of CF for metals are (0.01-0.03), (27.03-55.23), (1.12-2.40), (0.33-1.86),

(0.20-4.21) and (0.20-0.63) for Fe, Cd, Pb, Ni, Cr and Co, respectively (Table 5). The CF showed low contamination for Fe and Co, very high contamination for Cd and moderate contamination of Pb in all sites. For Ni, it varied between low contamination in sites 12 and 14 and moderate contamination in all other sites. Finally, for Cr, it varied from low contamination in sites 5, 6, 13, 14 and 15; moderate contamination in sites 1, 2 and 16 and considerable contamination in other sites (Table 5). The average calculated CF of heavy metals is decreased in the following order: Cd > Cr > Pb > Ni > Co > Fe.

Pollution load index (PLI) is used to calculate the extents of pollution of heavy metals as described by Tomlinson et al., (1980). In the study area, it ranged between no pollution (PLI < 1) in sites 4, 5, 6, 10, 11, 13, 14 and 15 (Table 5). While it indicates progressive deterioration in other sites as PLI > 1. The results of the contamination degree are very high in all sites where (DC > 24). The results of the potential ecological risk factor (Er), risks of heavy metals are ordered as follow; Cd > Pb > Cu > Zn. RI index indicated that there was a very high ecological risk (RI > 600) in all stations (Table 6). This is may be attributed to urbanization and different industrial activities distributed along the study area.



Table 5. The contamination factors (CF), pollution load index (PLI) and degree of contamination (DC) of heavy metals in the topsoil of Mareotis coast.

Site no. CF PLI DC

Fe Cd Pb Ni Cr Co

1 0.01 35.60 2.29 1.12 2.65 0.41 1.04 42.09

2 0.01 27.50 1.98 1.68 2.86 0.61 1.15 34.65

3 0.01 37.73 2.40 1.86 3.70 0.29 1.12 46.00

4 0.01 27.03 2.07 1.13 1.38 0.48 0.89 32.11

5 0.01 40.13 1.12 1.55 0.20 0.20 0.55 43.22

6 0.01 42.33 1.38 1.74 0.37 0.55 0.81 46.39

7 0.02 35.87 2.29 1.12 4.03 0.42 1.20 43.76

8 0.02 44.97 1.98 1.68 4.21 0.62 1.42 53.48

9 0.02 37.97 1.95 1.62 3.07 0.30 1.15 44.93

10 0.02 33.27 1.69 1.13 1.05 0.49 0.95 37.65

11 0.02 40.37 1.77 1.56 1.64 0.21 0.96 45.57

12 0.02 32.60 2.13 0.82 3.27 0.56 1.17 39.40

13 0.02 36.13 1.31 1.13 0.69 0.43 0.85 39.72

14 0.03 55.23 1.61 0.33 0.36 0.63 0.75 58.19

15 0.02 38.23 1.95 1.63 0.46 0.31 0.86 42.61

16 0.02 33.53 1.69 1.13 1.32 0.50 1.00 38.20

Mean 0.02 37.41 1.85 1.33 1.95 0.44 1.07 43.00

Table 6. Ecological risk factor (Er) and ecological risk index (RI) of heavy metals in the topsoil of

Mareotis coast.

Site no. Er RI

Cd Pb Ni Cr Co

1 1068 11.44 5.60 5.30 2.07 1092.41

2 825 9.88 8.41 5.73 3.06 852.07

3 1132 12.00 9.31 7.40 1.46 1162.18

4 811 10.37 5.63 2.77 2.41 832.17

5 1204 5.61 7.77 0.39 1.01 1218.78

6 1270 6.89 8.72 0.74 2.74 1289.10

7 1076 11.46 5.62 8.07 2.12 1103.26

8 1349 9.89 8.42 8.42 3.11 1378.84

9 1139 9.76 8.11 6.13 1.51 1164.51

10 998 8.43 5.64 2.10 2.46 1016.64

11 1211 8.86 7.79 3.28 1.06 1231.99

12 978 10.65 4.08 6.54 2.79 1002.05

13 1084 6.53 5.63 1.39 2.17 1099.72

14 1657 8.05 1.67 0.72 3.15 1670.58

15 1147 9.77 8.13 0.92 1.56 1167.37

16 1006 8.45 5.66 2.65 2.51 1025.26

Mean 1122.19 9.25 6.64 3.91 2.20 1144.18



Figure 2. The geo-accumulation index (Igeo) of heavy metals in the topsoil of Mareotis coast. The Igeo is used to evaluate the degree of

anthropogenic or geogenic accumulated pollutant loads and is used most often because it tends to be much more accurate than the other indices (Banat et al., 2005). The distribution of geo-accumulation index is described in Figure 2. The order of Igeo is; Cd > Pb > Co > Cr > Ni.

The Igeo index indicated unpolluted category (Igeo ≤ 0) for all metals in all sites except for Cd which indicated moderate polluted category (1 < Igeo ≤ 2) as defined by Buccolieri et al., (2006).

Plants

Heavy metal concentrations in plants: Phytoremediation is an aspect of

bioremediation that uses plants for the treatment of polluted soils. The ions of metals stored in the roots and shoots of plants (Chibuike and Obiora, 2014). Table 7 shows slight variations in the concentration of heavy metals between the studied plant, but Co and Ni show considerable differences. A general trend for HMs uptake in the shoot are in this order of magnitude Fe > Pb > Ni > Cd >Co. The uptake and accumulation of contaminants vary from plant to plant and also from species to species within a genus.

In the present study, the highest mean concentrations of Fe, Pb, and Cd (31.25, 6.07 and 1.76 mg.kg-1) were found in Atriplex portulacoides, while the lowest concentration (21.85, 4.88 and 1.45 mg.kg-1) was in Halocnemum strobilaceum, Suaeda pruinosa and Atriplex semibaccata, respectively (Table 7). Fe is the fourth most

abundant element in the lithosphere. However, their bioavailability in pH and aerobic environments is limited due to the low solubility of oxidized ferric form in aerobic environments (Samaranayake et al., 2012; Rout and Sahoo, 2015). Iron is an essential nutrient for plants where it plays important roles in metabolism and plant cell wall (Morrissey and Guerinot, 2009). Cd and Pb are phytotoxic in nature. It influences the plant growth adversely by affecting the leaves and root growth, inhibits water and nutrient uptake as well as inhibit the enzymatic activities and resulted in reduce production (Correa et al., 2006; Lai et al., 2012).

The accumulation of chemical elements in plants depends not only on their absolute content in the soil but also on the level of soil fertility, pH, reductive-oxidative conditions and organic matter content (Husson, 2013). The minimum concentration of nickel and cobalt (1.69 and 0.91 mg kg-1) was related to Atriplex portulacoides, and its maximum values of (2.52 and 1.33 mg kg-1) were associated to Halocnemum strobilaceum, respectively (Table 7). Ni is an essential micronutrient for plant growth and development (Eskew et al., 1983). However, excess Ni becomes toxic which destroys photosynthesis and membrane functions, inhibits seed germination, plant growth and development, and markedly decreases the yields of plants (Parlak, 2016). Similarity, Co is an essential component of several enzymes and co-enzymes. It has been shown to affect growth and metabolism of plants depending on the concentration and status of Co in soil (Vijayarengan and Dhanavel, 2005).



Metal accumulation efficiency: To evaluate the metal accumulation in plants,

the bioaccumulation factor (BAF) was calculated

to measure the ability of a plant body to accumulate metals from soil (Sivakoff and Gardiner, 2017).

Table 7. Heavy metals concentrations (mg.kg-1) and bioaccumulation factor in tissues of wild halophytes collected from different sampling sites of the study area.

Plant species Heavy metal (mg.kg-1)

Fe Pb Cd Ni Co

Atripex portulacoides Conc. 31.25 6.07 1.76 1.96 0.91

BAF 4.37 1.44 2.06 0.77 3.33

Atriplex semibaccata Conc. 25.92 5.61 1.45 2.26 1.06

BAF 3.62 1.34 1.69 0.88 3.91

Halocnemum strobilaceum

Conc. 21.85 5.45 1.72 2.52 1.33

BAF 3.05 1.30 2.00 0.98 4.87

Suaeda pruinosa Conc. 23.11 4.88 1.50 2.31 1.11

BAF 3.23 1.16 1.75 0.90 4.09

Table 8. Simple linear correlation coefficients (r) between heavy metals in studied halophytes and

soil.

Heavy metals in soil

Heavy metals in studied halophytes

Fe Pb Cd Ni Co

Atriplex portulacoides

Fe 0.769** 0.108 0.690** 0.769** 0.947**

Pb 0.126 0.008 0.030 0.116 -0.113

Cd 0.336* -0.094 0.334* 0.336* -0.065

Ni 0.128 -0.077 0.050 0.308* -0.114

Co -0.024 0.030 -0.078 -0.024 0.109

Atriplex semibaccata

Fe 0.909** 0.153 0.769** 0.708** 0.690**

Pb 0.182 0.069 0.136 0.008 0.030

Cd 0.079 -0.234 0.536** -0.094 -0.134

Ni 0.064 -0.071 0.328* -0.077 0.050

Co 0.344* -0.101 -0.024 0.030 -0.078

Halocnemum strobilaceum

Fe 0.769** 0.108 0.947** 0.728** 0.896**

Pb 0.129 0.018 -0.313* 0.076 -0.146

Cd 0.436** -0.094 -0.065 0.024 -0.015

Ni 0.128 -0.077 -0.114 0.028 -0.013

Co -0.024 0.030 0.109 0.003 0.120

Suaeda pruinosa

Fe 0.769** 0.146 0.653** 0.832** 0.653**

Co -0.024 0.024 -0.101 0.317* -0.101

Cd 0.122 -0.019 0.434** 0.113 -0.234*

Pb 0.136 -0.073 0.069 0.167 0.069

Ni 0.328* 0.121 -0.071 0.101 -0.071

**Correlation is significant at the 0.01 level (2-tailed).

*Correlation is significant at the 0.05 level (2-tailed).



BAF greater than one indicates that a particular element is accumulated by plant species from soil (Yoon et al., 2006; Serbula et al., 2013). In the present study, the highest BAF (4.37) and the lowest (0.77) was observed in Atriplex portulacoides in addition, most halophytic plants had a BAF value for Fe, Pb, Cd, and Co were >1, except BAF of Ni were ˂1 (Table 7). El-Amier et al. (2017) reported that the BAF values for Fe, Pb, Ni, Co, and Cd were <1 for halophytic plants (Atriplex halimus, Limoniastrum monopetalum, Limonium pruinosum, Suaeda maritima, Suaeda pruinosa and Zygophyllum aegyptium). On the basis of the BAF values, the studied plant species could be considered as hyperaccumulator for Fe, Pb, Cd, and Co (BAF values >1) except Ni. In the view of the above-mentioned data, different plant species showed a variation in metal accumulation and the uptake of metal ions was affected by the metal species and plant parts (Juste and Mench, 1992), pH, soil organic matter, age of plant, and plant physiology (Khan et al., 2015; El-Amier et al., 2017).

Correlations in plants and soil: The relationships between heavy metals

concentrations in soil and halophytes were analyzed by Pearson’s correlation coefficient and the results are shown in Table 8. The high correlation coefficient (near +1 or -1) means a good relation between two factors, and its concentration around zero means no relationship between them, as well as according to Rakesh and Raju (2013), R2 > 0.7 (strongly correlated); 0.5≤ R2 ≥ 0.7 (moderate correlation). On this basis, we can observe that strong positive correlation between Fe in soil with Fe, Cd, Ni and Co in studied halophytes except Cd and Co in Suaeda pruinosa showed moderate positive correlations. This strong positive relationship shows that heavy metals are closely linked, indicating their common origin. Cd in soil showed moderate positive correlations with Cd in A. semibaccata, while the other correlations are weak (Table 8).

CONCLUSION It could be concluded that different

anthropogenic activities distributed along the coastline (Mareotis coast) effect on the marine environment as indicated from used indices. Also, the used halophyte species proved the efficiency to reduce metal concentrations from contaminated environments. Therefore some species as Atriplex portulacoides could be used in the remediation

process in different fields. CONFLICT OF INTEREST The authors declared that present study was performed in absence of any conflict of interest. ACKNOWLEGEMENT The researchers are gratefully thankful for Mansoura University, National Institute of Oceanography & Fisheries and Tabuk University for the support. AUTHOR CONTRIBUTIONS All authors contributed equally in all parts of this study.

Copyrights: © 2017 @ author (s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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