Speciation and Mobility of Lead, Chromium and Zinc in Soils of Abis Region, Egypt

Introduction

Soils are the reservoir for many harmful constituents, (elemental and biological), including heavy metals. Total elemental content of soils is useful for many geochemical applications but often the speciation of these metals is more of an interest agriculturally in terms of what is biologically extractable (Cottenie et al., 1980). Speciation is defined as the identification and quantification of the different, defined species, forms, or phases in which an element occurs (Tack and Verloo, 1995) and is essentially a function of the mineralogy and chemistry of the soil sample examined (Tessier et al., 1979). Quantification is typically done using chemical solutions of varying but specific strengths and reactivity to release metals from the different fractions of the examined soil (Ryan et al., 2008). In terms of bioavailability, various species of metals are more biologically available in the ecosystem (Nelson and Donkin, 1985). Bioavailability and the mobility of metals are also related to each other, then higher concentration of mobile toxic metals in the soil which increases the potential for plant uptake, and animal/human consumption (Ratuzny et al., 2009). Heavy metals are included in soil minerals as well as bound to different phases of soil particles by a variety of mechanisms. Moreover, soil properties such as contents of organic matter, carbonates and oxides influence the heavy metal mobility (Kabata-Pendias and Pendias, 2001). It is widely recognized that to assess the environmental impact of soil pollution, the determination of the metal speciation will give more information about the potential for release of contaminants and further derived processes of migration and toxicity (Usero et al., 1998). Therefore, in geo-environmental studies of risk assessment, chemical partitioning among the various geochemical phases is more useful than measurements of total heavy metals contents (Quevauviller et al., 1996). There is no information available in the literature on heavy metals speciation, mobility, availability and toxicity in soils of Abis region in Egypt. Herein, the objectives of this study were aimed at determining the speciation and mobility of Pb, Cr and Zn metals in the top soil of this area.

MATERIAL AND METHODS

Site description and soil samples

Thestudied area is located between 31^o 00' to 31^o 30' N and 29^o30' to 30^o 30'E at the north western delta fringes south of Mariut Lake which named Abis (Map 1). It covers parts of Alexandria and El-Behira Governorates with total area about 40000 Fed. Forty one surface (0-35 cm) soil samples representing the studied area were taken as shown in Map 2. The soil analysis for pH ,EC , CaCO₃ %, soluble cations, soluble anions and particle size distribution  were carried out using the methods described by Page et al. (1982) as presented (Yehia et al, 2014). Also, the organic matter was determined using Walkley-Black wet combustion method (Tan, 1996). The statistical characterization of soil samplesare presented inTable (1).

Map (1): The general location of the study area

Map 2: The soil sample locations of the study area

Total heavy metals measurement

Total concentrations of heavy metals (Pb, Cr, and Zn) were determined by wet digestion in soil according to (Page et al., 1982); 1 g of collected surface soil was placed in a Teflon crucible 5 mL HNO₃, 10 mL HF and 12 mL HClO₄ were added in to the soil and oscillated for 10 h then under constant temperature (80°C). After the sample was almost dried, 10 mL nitric acid (1:1) was added to dissolve the solids continually. The dissolved soil sample was transferred constantly to 50 mL volumetric flask to determine the total contents of  the tested metals in soils.

Estimating forms of the tested heavy metals

Sequential extraction procedure was carried out using 2.0 g soil was involved to the five following steps (Tessier et al., 1979; Tessier et al., 1980):

1. Water soluble:

Samples of finely grounded air-dried soil were transferred top shaking bottle followed by 16 ml of deionized water and samples were shaken on a reciprocating shaker for 1 h. The suspension was centrifuged for 30 minutes and then the supernatant was filtered through whatman 42 filter papers.  

2. Exchangeable fraction:                                                                      

The same soil sample was placed in contact with a high ionic strength solution, in order to release the so-called exchangeable fraction of metal by altering the sorption–desorption superficial processes. In this step 16 ml of 1 M NH₄OAc (pH=7) were added to the sample and the supernatant was shaken for 2 h.                                                                                      

3. Fraction bound to carbonate:                                                           

The fraction of metal bound to carbonates, present in the sample, may be selectively labialized by varying the pH of the sample itself with a slightly acidic extraction solution. 16 ml of 1 M of CH₃COONa, plus CH₃COOH (pH= 5) were added to the residue obtained from the former extraction, and the suspension was shaken for 5 h.                                           

 4. Fraction bound to iron and manganese oxides:    

The residue from fraction 3 was extracted under mild reducing conditions of 13.9g of hydroxylamine hydrochloride (NH₂OH·HCl) was dissolved in 500mL distilled water to prepare 0.4M NH₂OH·HCl. The residue was extracted with 20mL 0.4M NH₂OH·HCl in 25% (v/v) acetic acid with agitation at 96°C in a water bath for 6 hours. The extracted metals solution was decanted from the residual soil which was used for the next extraction.                                                                 

5. Fraction bound to organic matter and to sulphides:                         

The residue from fraction 4 was oxidized as follows: 6mL 0.02M HNO₃ and 10mL 30% (v/v) hydrogen peroxide was added to the residue from fraction 4. The mixture was heated to 85°C in a water bath for 2 hours with occasional agitation and allowed to cool down. Another 6mL of 30% hydrogen peroxide, adjusted to pH 2 with HNO₃, was then added. The mixture was heated again at 85°C for 3h with occasional agitation and allowed to cool down. Then, 10mL of 3.2M ammonium acetate in 20% (v/v) nitric acid was added, followed by dilution to a final volume of 50 mL with de-ionized water.                                                

6. Residual fraction:                                                                             

It is the metal fraction present as scatter within the crystal lattice of the rocks and minerals that constitutes the soil. It was calculated from the difference between the concentration of total metal and the sum of the first four fractions.

After each extraction, the suspension was subjected to centrifugation for 20 min at 4000 rpm. The solution was separated, while the precipitate was washed with10 ml of high purity water and centrifuged again for 5 min. The washing water then was added to the supernatant, while the precipitate was used for the subsequent extractions. The extracts were diluted to 50 ml by distilled water and analyzed for the selected heavy metals by atomic absorption spectrometer (Analytike Jena,Germany)®.  

Classic statistical analysis and Kriging maps

The important information about variables is provided by descriptive statistics using the Statistical Package for Social Science (SYSTAT) version 12.0. Measures of tendency of variables were determined by mean and median as well as computing the dispersion of a variable in variance, standard deviation, Coefficient of Variation (CV) and range (Cen et al., 2006). Geostatistical analyses of any parameter readings were calculated for their semivariogram. A semivariogram indicates autocorrelation as a function of distance (semivariance versus distance separation) to plot spatial variability (Shibusawa, 1998). It’s components which include fitted model type, nugget variance (C0), structural variance sill (C0+C), range (A), Residual Sum of Square (RSS), coefficient (r²) and proportion (C0/[C+C]) were calculated by Geostatistical analysis software through GS⁺ Geostatistics for the Environmental Science (Gamma Design Software, Version 9, LLC Plainwell, Michigan). Variability has been identified as spatial, temporal and predictive. Spatial variability of total heavy metal contents was obtained in this study to monitor difference in maps of this measured parameter. These data were interpolated using ArcGIS 10.1 through spatial analysis extension on semivariogram results for Geostatistical Software (GS⁺).                                                               

Results and Discussion

1. Characterization of the studied soils

The minimum, maximum and average values of main physical and chemical properties of soil are shown in Table 1. The data show that the studied soils are characterized by sandy loam to sandy clay loam texture in most samples. Data of total soluble salts, as expressed by the electrical conductivity and sodium adsorption ratio indicate that most of the studied soils are characterized by their moderate to high EC and SAR values.  The EC values ranged between 0.77 and 10.91 dS/m, SAR values being in the range from 2.05 to16.00 dSm^-1, total carbonate content ranged between 2 and 34%. pH values ranged between7.92 and 8.83. The amounts of sand, silt and clay varied from 47.70 to 83.04, 2.00 to 17.74 and 8.96 to 44.00%, respectively.

Table (1). Statistical parameters of the estimated properties and total heavy metals of the soil samples

SD: standard deviation; CV: Variation coefficient; Var: Variance

2. Total concentrations of Pb, Cr and Zn in soil

The concentration of heavy metals in the soils of Abis area was determined and the statistical parameters of the estimated total heavy metals in the soil samples are presented in Table 1. The mean concentrations of  Pb, Cr and Zn were 25.64, 21.20, 85.18 mgkg^-1, respectively. High metal concentrations in the soils were found for Zn, while Cr had the least concentrations. The mean values of the heavy metal contents can be ranked in the order of Zn >Pb >Cr (Table 1). According to Jones and Jarvis (1981), processes of metal mobilization-immobilization are affected by a variety of soil properties. To examine this influence, data from this study were statistically analyzed to illustrate the relationship among total content of heavy metals, EC, pH, organic matter, clay, sand and silt are listed in Table 2. A positive correlation was recorded between Zn and clay (r= 0.358*). Also, a negative correlation between total Zn and sand (r=-0.404**) was observed. Geostatistical analyses of total heavy metals were presented according to its semivariogram. As mentioned in material and method, semivariogram has different components and the variograms of total Cr, Pb and Zn were prepared as shown in Fig. 1., Fig.2 and Fig.3. The classification approach using raster calculator, which was available in the spatial analyst for calculating the total Pb, Cr and Zn and calculated maps were produced. The classification technique of manual, which was introduced by ArcGIS software, was selected to visual variability as groups. This study decided to zone the area into 5 zones which could be manageable and also easy to compare.

Fig (1) : Isotropic semivariogram of total Cr, Exponential model  (C0= 35.3; C0+C = 271.5; Ao= 12970; R²= 0.976; RSS = 665)

Fig(2): Isotropic semivariogram of total Pb, Spherical model, (C0= 7.10; C0+C = 130.4; Ao= 2150; R²= 0.008; RSS = 1190)

Fig(3): Isotropic semivariogram of total Zn, Gaussian model (C0= 210; C0+C = 799.5; Ao= 5530; R²= 0.87; RSS = 52595)

Map 3 shows the distribution of total Pb in the soil representing the study area using weighted average. It is clear that, total Pb is variable and ranged from 23 to 32 mg kg^-1 soil. The dominant total Pb class was 23 to 25 mg kg^-1soil covered about 29.17% of the area and mostly found in the northern part of the study area and is found in Alexandria Governorate. Also another dominant class had 26-27 mg kg^-1 covered about 38.16 % and mostly found in Behira Governorate.

Total Cr ranged from 0.2 to 43 and classified into five classes as shown in Map 4. The dominant classes had 25 to 31 mg/kg soil and covered about 27.06% of the area and mostly found in El Behira Governorate. Also, another dominant class had 20 to 24 mg kg^-1 soil covered about 30.63% of the area and found in Alexandria Governorate.

 Total Zn contents ranged from 48 to 130 mg kg^-1 soil and classified into five classes as shown in Map 5. The dominant classes had 48 to 68 mg kg^-1 soil and covered about 32.07% of the area and mostly found in Alexandria governorate. The class which had the higher content of Zn (120 to 130 mg kg^-1) was found in Behira governorate and covered about 9.65% of the area.

Table (2): The correlation coefficients between total heavy metals and some properties of the soil samples

       *Significant at 5% level,        

        **Significant at 1% level                                                                                                

Map (3): Distribution of total Pb in the top soil of Abis area

Map (4): Distribution of total Cr in the top soil of Abis area 

     Map (5): Distribution of total Zn in the top soil of Abis area

However, total heavy metals contents were found to be in the permissible limits reference values of heavy metals for agricultural soils according to the FAO (2001). The values of the limits reference of Zn, Pb and Cr were 300, 100, 100 mgkg^-1 soil, respectively.

 3. Geochemical fractions of Pb, Cr, and Zn in soil

Metal chemical speciation carried out by sequential extraction is essential to the metal mobility (Tessier et al, 1979). The obtained results (Tables 3 and 4) showed that the amounts of heavy metals extracted from each fraction vary widely. The order of mobility of the metals considering their abundance in the fractions is: soluble+ exchangeable > bound to carbonate > bound to oxides > bound to organics > residuals (Tessier et al, 1979). Oxides exist as nodules and cement between particles. These oxides hold trace metals and can be mobilized under reducing and acidic conditions. The organic phase is relatively stable in nature but can be mobilized under strong oxidizing conditions due to degradation of organic matter (Haung et al., 2007).

3.1. Fractionation of Pb

The statistical parameters of Pb fractions and their percentages of the total extracted are presented in Tables 3 and 4, respectively. The dominant fraction for lead in soils of Abis area was the residual fraction. This chemical form was closely followed by the exchangeable fraction. The partitioning of Pb varied among all the fractions. More than 80% of Pb (Table 4) was held in the residual form, which indicates the bioavailability potential of Pb. The stability of metals bound to sediments as inorganic compounds (metal oxides, hydroxides, carbonate and sulphides) is controlled primarily by the pH system (Poulton et al., 1988). The order of the partitioning of Pb in the soils of Abis area is F6>F2>F3>F4> F5>F1. This agrees with those found by Ramirez et al., (2005), who reported that Pb was mostly associated with the residual fraction.

3.2. Fractionation of Cr

Chromium is mostly abundant in residual fraction (Tables 3 and 4). The abundance of Cr in residual phase ranged between 0.06 to 43.88 mg kg^-1 soil with a mean of 15.58 mg kg^-1 soil (Table 3) and 65.63 % of total (Table 4) .The calcium carbonate fraction is the second in abundance after the residual fraction, the range was from0.22 to 7.41mg kg^-1 with a mean value of 2.70 mg kg^-1 soil and the abundance was 18.04% of total. Abundance of Cr in other geochemical phases was very low. This means that Cr was less mobile in this environment.

3.3. Fractionation of Zn

   Zinc is mostly abundant in residual fraction in the range from 37.68 to 135.24mg kg^-1 with a mean value of 79.13 mg kg^-1 soil (Table 3) and 91.33% of total (Table 4) while in the oxide fraction, the range of Zn was from 1.06 to 9.13mg kg^-1 with a mean value of 2.69 mg kg^-1 soil (Table 3) and the abundance was 3.66% of total. Abundance of Zn in other fractions was low. Also, Zn in this environment was less mobile since the metals which were mostly abundant occurred in the Residual fraction. This is in agreement with the data repected by Zerbe et al., (1999).

Table (3): Range, mean, standard deviation (SD) of heavy metals in different  geochemical fractions of soil samples

F1: Soluble- fraction; F2: Exchangeable fraction; F3: Carbonate fraction F4: Fe+Mn-oxide fraction; F5: Organic matter fraction;

 F6: Residual fraction 

Table (4): Range, mean, standard deviation (SD) of heavy metals (% of total) in different geochemical fractions of soil samples

 F1: Soluble- fraction; F2: Exchangeable fraction; F3: Carbonate fraction F4: Fe+Mn-oxide fraction;  F5: Organic matter

   fraction; F6: Residual fraction