Environ Geochem Health (2009) 31:717–726 DOI 10.1007/s10653-009-9250-9
ORIGINAL PAPER
Metal distribution in urban soil around steel industry beside Queen Alia Airport, Jordan Omar A. Al-Khashman Æ Reyad A. Shawabkeh
Received: 26 September 2007 / Accepted: 11 February 2009 / Published online: 5 March 2009 Ó Springer Science+Business Media B.V. 2009
Abstract The objective of this study was to assess the extent and severity of metal contamination in urban soil around Queen Alia Airport, Jordan. Thirty-two soil samples were collected around steel manufacturing plants located in the Al-Jiza area, south Jordan, around the Queen Alia Airport. The samples were obtained at two depths, 0–10 and 10–20 cm, and were analyzed by atomic absorption spectrophotometry for lead (Pb), zinc (Zn), cadmium (Cd), iron (Fe), copper (Cu) and chromium (Cr) levels. The physicochemical factors believed to affect the mobility of metals in the soil of the study area were also examined, including pH, electrical conductivity, total organic matter, calcium carbonate (CaCO3) content and cation exchange capacity. The high concentrations of Pb, Zn and Cd in the soil samples were found to be related to anthropogenic sources, such as the steel manufacturing
Capsule: Metals concentrations in the surface and sub-surface soils around steel manufacturing plants in southern Jordan have been studied and compared with metals in urban soils. O. A. Al-Khashman (&) Department of Environmental Engineering, College of Mining and Environmental Engineering, Al-Hussein Bin Talal University, P.O. Box 20, Ma’an, Jordan e-mail:
[email protected] R. A. Shawabkeh Department of Chemical Engineering, Mutah University, Al-Karak 61710, Jordan
plants, agriculture and traffic emissions, with the highest concentrations of these metals close to the site of the steel plants; in contrast the concentration of Cr was low in the soil sampled close to the steel plants. The metals were concentrated in the surface soil, and concentrations decreased with increasing depth, reflecting the physical properties of the soil and its alkaline pH. The mineralogical composition of the topsoil, identified by X-ray diffraction, was predominantly quartz, calcite, dolomite and minor minerals, such as gypsum and clay minerals. Metal concentrations were compared using one-way analysis of variance (ANOVA) to compute the statistical significance of the mean. The results of the ANOVA showed significant differences between sites for Pb, Cd and Cu, but no significant differences for the remaining metals tested. Factor analysis revealed that polluted soil occurs predominantly at sites around the steel plants and that there is no significant variation in the characteristics of the unpolluted soil, which are uniform in the study area. Keywords Factor analysis Jordan Metals Steel industry Soil pollution
Introduction Metals, which are released into the biosphere by both natural processes and human activities and
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predominately transferred as chemical compounds or particulate matter in the atmosphere (Gunter and Komarnicki 2005), are considered to be one of the main sources of environmental pollution. The increased levels of metals that accumulate in the soil and affect nearby ecosystems primarily originate from anthropogenic activities (Tu¨zen 2003). The contribution of metals to environmental pollution from industrial, agricultural and mining processes as well as automobile emissions have been the subject of many studies and research in recent years (Ndiokwere 1984). It has become evident that the mobilization of metals into the atmosphere as a result of anthropogenic activities is an important process in the geochemical cycling of heavy metals. This is acutely evident in urban areas where various stationary and mobile sources release large quantities of heavy metals into the atmosphere, soil and vegetation, resulting in concentrations that exceed natural levels (Nriagu 1989; Hewitt and Candy 1990; Olajire and Ayodele 1997; Jaradat and Momani 1999; De Kimble and Morel 2000; Bilos et al. 2001; Matos et al. 2001; Manta et al. 2002; Charlesworth et al. 2003; Tu¨zen 2003; AlKhashman 2004, 2007; Banat et al. 2005; Bin Chen et al. 2005; Al-Khashman and Shawabkeh 2006). The sources of potentially toxic metals in soil are both natural, such as the weathering of primary minerals (Kumar et al. 2005), and anthropogenic in origin, such as mining, industrial processes, energy production, agriculture, industry, vehicle exhausts, waste disposal and coal combustion (Chon et al. 1995; Chen et al. 1997; Wong and Mak 1997; Martin et al. 1998; Li et al. 2001; Gray et al. 2003; Bin Chen et al. 2005; Biasioli et al. 2006). The presence of metals in the soils of urban areas have been a subject of great concern due to their non- biodegradable nature and long biological halflives within the human body. Most of these metals have an adverse effect on human health at high concentrations, especially on the health of children (Crnkovic et al. 2006). The main objectives of the investigation reported here were: 1.
2.
to determine the concentrations of specific metals, such as lead (Pb), zinc (Zn), cadmium (Cd), iron (Fe), copper (Cu) and manganese (Mn), and the extent of their distribution in soil within the study area, to study the chemical and mineralogical forms of these metals in the soil samples.
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Materials and methods The study area The study area is located in the southern part of Amman, capital of Jordan. The steel manufacturing plant is located 2 km west of the desert highway and about 5 km west of Queen Alia International Airport. This plant, which was established in 1993 as a stateowned enterprise, plays a significant role in the local economy and is a major employer in the area. The study area has a typical Mediterranean climate characterized by hot, dry summers and cool, rainy winters. The annual mean minimum temperature in January is 2.1°C and in July, 25.9°C (Department of Meteorology 2005). The plant is located in the desert area of Jordan, which is about 768 m a.s.l. (Fig. 1). The surrounding area is essentially rural, consisting of open areas with scattered houses at distances varying from 300 to 500 m from the plant. Rainfall occurs only in the winter season, which extends from November to April, and annual precipitation is around 133 mm. The prevailing wind direction is from westerly to northwesterly. Evaporation in the study area is high, and the relative humidity ranges from 33 to 61%, with the minimum relative humidity occurring in May and themaximum occurring in December. The investigated area is located in the northwest part of the Arabian plate, with most of Jordan situated within the stable part of the plate. Upper cretaceous carbonaceous facies dominate the central part of country, whereas ancient basement (pre-Cambrian) and Cambrian Nubian sandstone dominate the southern part. Basalt desert in the northeast and the rift valley form Jordan’s western borders. The sandy facies within the carbonate rock increase in the south of the country (Bender 1974). Sample collection Thirty-two composite samples were collected in a grid system around the steel plant in the desert area at two depths, 0–10 and 10–20 cm (Fig. 2). Additional samples were collected near the steel plant and a few more at greater distances. Stones and foreign objects were removed by hand. All of the samples were collected using a stainless steel spatula and kept in plastic bags for not more than 24 h before the start of analytical procedures. Particle size distribution was
Environ Geochem Health (2009) 31:717–726
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Fig. 1 Location map of the studied area
Fig. 2 The location of the sampling sites
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determined by a hydrometer method (Gee and Bauder 1986; Madrid et al. 2002). Soil chemistry properties were determined by standard procedures (Page et al. 1982; Madrid et al. 2002). The pH was determined with a 1:2.5 soil-to-solution ratio, electrical conductivity (EC) in a 1:5 extract and calcium carbonate equivalent by a manometric method. The percentage of the organic matter in the soil samples was measured by the titration method based on the oxidation of organic matter by K2Cr2O7. The values of cation exchange capacity (CEC) were obtained by calculations based on exchangeable cation contents determined after 5-g samples (\63 lm soil fraction) had been treated with a sodium and ammonium acetate solution (Hesse 1972; Banat et al. 2005). Analytical methods Following collection, the soil samples were transferred to a quartz crucible and dried to constant weight at 105°C for about 4 h. The dried samples were then sieved through a 2-mm plastic sieve to remove gravelsized materials (Li et al. 2001; Madrid et al. 2002; Manta et al. 2002). Accurately weighted 2-g sieved samples were then digested overnight with 10 ml concentrated HNO3 solution in a test tube, ultrasonicated for 1 h and heated in a test tube heater for 2 h at 90°C. The solution was then cooled, filtered into 25-ml polyethylene volumetric flasks through 0.45lm filters and diluted to mark with a 1% HNO3 solution. The extracts were kept in polyethylene bottles in a refrigerator at 5°C. Blanks were prepared in a similar manner. Metal concentrations were determined using a Shimadzu atomic absorption spectrophotometer (model AA-6200; Shimadzu, Kyoto, Japan). All of the standard solutions were prepared from analytical grade compounds (Merck,
Whitehouse Station, NJ). For Fe, Cu, Cd, Pb, Zn and Mn, six standard solutions of different concentrations were prepared in 2 M HNO3 within the linear concentration range for measurement purposes. The calibration curves were prepared for each metal by least square fitting and shown by analysis of NBS standards to be better than ±10% (Jaradat and Momani 1999). Reference soil was collected 1000 m west of the steel plant since the prevailing wind direction was westerly to northwesterly. All glassware was cleaned initially with soap, washed and soaked in 10% HNO3 (v/v) overnight to remove any contamination by metals, then washed thoroughly with distilled water and rinsed with de-ionized water. Soil mineralogy was determined by powder X-ray diffraction, with CuKa radiation filtered by Ni, scanning at 18/min in the range of 2h from 3 to 65°.
Results and discussion Physico-chemical parameters The physico-chemical characteristics of soil samples in terms of pH, EC, total organic matter (TOM) and calcium carbonate (CaCO3) contents and CEC are given in Table 1. The soil was of the vertisol type (Simonson 1962). The sieve and hydrometer analysis of soil samples showed that the grain-size particles were composed of 30.7% sand, 41.4% clay and 27.9% silt, representing a clay–loam texture. The rocks were wholly sedimentary. The bed rock ranged in age from Turonian (Upper Cretaceous) to Eocene (Lower Tertiary), and the mantling superficial deposits were from Pleistocene to recent age. The study area was dominated by basalt and the Pleistocene deposits, and mainly consisted of
Table 1 Descriptive parameters of the 32 soil samples at two depths Parameters
Sample depth: 0–10 cm Median
pH EC (ls/cm)
Mean
Sample depth: 10–20 cm SD
Range
7.53
7.53
0.83
5.33–8.33
Median
Mean
SD
Range
7.44
7.47
0.84
5.52–8.25
225.00
225.00
36.30
193.00–328.00
213.00
215.00
33.60
169.00–284.00
TOM (%)
1.58
1.59
0.35
0.95–2.31
1.09
1.10
0.31
0.55–1.75
CaCO3 (%)
9.26
9.29
4.18
4.52–18.62
9.54
9.55
1.60
7.63–13.52
97.00
98.00
8.12
71.00–132.00
64.00
66.00
11.80
47.00–102.00
CEC (meq/100 g)
EC, Electrical conductivity; TOM, total organic matter; CEC, cation exchange capacity; SD, standard deviation
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distance depending on the particle size. The concentration of these metals in any soil can vary greatly according to the strength and direction of the wind, type of soil, composition, CEC and pH. Lead concentrations in the upper soil (0–10 cm) samples ranged from 20.5 to 117 mg/kg dry soil, with the median concentration being 60.31 mg/kg dry soil. The highest Pb value, 117 mg/kg dry soil, was found in the upper soil samples collected from the eastern side of the entrance of the steel plant (Fig. 3), while the lowest Pb concentration (20.5 mg/kg dry soil) was found in the upper reference soil samples. The high Pb concentration can be attributed to the burning of fossil fuels and traffic ( Carreras and Pignata 2002; Banat et al. 2005; Al-Khashman 2007).
70 60
mg/kg dry soil
yellow to brown loess-like silt, residual calcareous bedrock and clay. The soil was rich in iron oxides, with a thickness of 0.5–1.5 m (Bender 1974). The prominent E–W Siwaqa fault is one of the most distinctive E–W faults in the country and crosses the study area N–S, E–W and NW–SE (Bender 1974). The Qatrana graben is located in the southwestern part of the Siwaqa area; it is oriented N–S and extends 7 km northwards from the study area. The pH ranged from 5.33 to 8.33, indicating that most of the samples were slightly alkaline. The highest value of pH was found in samples taken on the west side of the factory and was associated with carbonate materials. The lowest value of pH was found in samples collected near the parking lot. High EC values were found in samples collected close to the steel plant. CaCO3 contents of the soil samples varied from 4.52 to 18.62%, with an average value of 9.55%. The organic matter of the soil affects the color and increases the CEC. The TOM ranged from 0.55 to 2.31%, with a mean value of 1.59%. The highest values of organic matter were found in samples taken from the eastern side of the investigated area; however, the distribution pattern of organic matter reflected the variable distribution of plants, grass and vegetation cover in the investigated area. The CEC of the soil samples ranged from 47 to 132 meq/100 g, with a mean value of 98 meq/100 g.
50 40 0-10 cm 30
10-20 cm
20 10
Total metal concentrations 0
Metal concentrations in soil samples collected at both depths (Table 2) were generally low. The metals originating from industrial activities were distributed in soil through atmospheric deposition within specific
Pb
Zn
Cd
Fe
Cu
Cr
Metals
Fig. 3 Mean values of metal concentrations in the soil samples
Table 2 Metal contents of the 32 soil samples at two depths Metals
Metal contents of soil samples (mg/kg) 0–10 cm
10–20 cm
Median
Mean
SD
Range
Median
Pb
60.31
60.20
10.30
20.50–117.00
26.00
Zn
50.90
51.43
9.37
7.5–87.0
25.30
Cd
5.77
6.55
1.29
2.5–1.50
2.13
Fe
47.63
47.82
16.03
14.1–103.2
Mean
SD
Range
26.00
8.71
9.00–60.00
25.70
5.61
3.70–43.00
2.33
1.05
0.91–6.80
12.70
12.72
4.15
4.38–28.30
Cu
3.02
3.02
1.08
1.43–9.72
1.83
1.91
0.82
0.63–4.82
Cr
16.95
17.23
9.40
0.95–39.0
5.31
5.38
3.63
0.45–11.00
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from the entrance to the factory beside the parking lot. However, higher levels were also observed due to the influence of the steel plant and motorized traffic in the factory. The highest Cu value (9.72 mg/kg dry soil) was observed in samples collected east and northeast of the steel plant. Agricultural soils receive metals mainly from chemical fertilizers, manure, pesticides, wastewater and other scattered diffuse pollution sources, such as vehicle emissions, industries and waste incineration (Carreras and Pignata 2002; Biasioli et al. 2006; Al-Khashman 2007). The geographical distribution of Cu in the study area is mainly dominated by the emissions from the steel plant. However, the lowest value of Cu was measured in the lower part of the soil (10–20 cm; 0.63 mg/kg dry soil) (Fig. 3). A significant correlation was found
The mean values of Pb were much lower than those in samples from Palermo, Torino, London, Aberdeen, an urban playground in Hong Kong, central Jordan and southern Jordan (Table 3). There were highly significant correlations between metals at all sampling points, such as Pb versus Zn and Cd (R2 = 0.87, 0.74, respectively) (Table 4). Iron is one of the principle elements in the Earth’s crust and is mainly associated with coarse atmospheric particles. If associated with other sources, it is generally deposited in the neighborhood of the emission sources (Carreras and Pignata 2002; Berg et al. 1995). In the study area, higher levels were observed to the east of the steel factory (103.2 mg/kg dry soil), but the lowest value of Fe was observed in the upper part of soil. The sample was collected 60 m away
Table 3 Comparison of mean concentrations of metals in urban soil samples from different sites in the world Sample site
Mean concentration (mg/kg) Pb
Palermo Hong Kong
Zn
Cd
References Fe
Cu
Cr
253.00
151.00
–
–
77.00
39.00
Manta et al. (2002)
95.00
125.00
–
–
23.30
23.00
Li et al. (2004)
Torino
149.00
183.00
–
–
90.00
191.00
Madrid
161.00
210.00
–
–
72.00
75.00 23.90
Aberdeen
94.40
58.50
–
–
27.00
London
294.00
183.00
–
–
73.00
Nanjing
104.00
96.00
–
–
104.00
–
– 97.00
Biasioli et al. (2006) De Miguel et al. (1998) Paterson et al. (1996) Thornton (1991) Lu et al. (2003)
Central Jordan
62.17
146.94
4.98
–
83.93
Banat et al. (2005)
South Jordan
55.00
44.51
5.00
24.18
2.89
22.18
Al-Khashman and Shawabkeh (2006)
This study (0–10 cm)
60.20
51.43
6.55
47.82
3.02
17.32
Present study
Table 4 Statistical variation (analysis of variance) between metals and soil samples Parameter
Sum of squares between groups
df
Mean square between groups
pH
1.642
2
0.434
EC
65449.662
2
26244.663
Pb
1375.135
2
577.917
Zn
248.124
2
129.437
Cd
22.046
2
11.578
Fe
36.418
2
Cr
278.421
2
Cu
1.338
2
0.677
Sum of square within groups 3.546
df
Observed a
59
0.436
1.017
0.310
52041.732
0.485
0.325
17326.739
59
216.544
4.323
0.021*
14356.669
59
312.564
0.561
0.514
1013.326
59
18.652
5.440
0.014*
14.315
3487.387
59
56.234
0.270
0.264
143.127
14432.161
59
260.141
0.439
0.321
123.317
59
2.145
0.314
0.0314
F revealed variation of the group averages/expected variation of the group averages
123
Fa
59
401740.5
* Statistically signifcant difference between samples at P \ 0.05 a
Mean square within groups
Environ Geochem Health (2009) 31:717–726
723
Table 5 Correlation matrix between metals in urban samples Pb
Zn
Cd
Fe
Cu
Cr
Pb Zn
0.870
Cd
0.000 0.731
0.742
0.000
0.000
0.592
0.593
0.000
0.000
0.000
Cu
0.752
0.602
0.701
0.000
0.001
0.000
0.002
Cr
0.719
0.721
0.669
0.422
0.125
0.001
0.000
0.000
0.002
0.000
Fe
0.623 0.591
Cells show the Pearson correlation coefficient (above) and the corresponding P value (below)
between Cu and Cd (R2 = 0.70) (Table 5), although both Cu and Cd may also originate from the bedrock contribution. These results indicate that industrial activities were the main source of metals in our soil samples. Cadmium is emitted into the atmosphere from both natural sources, mainly basaltic rocks, and anthropogenic sources. Metal production (drying of Zn concentrates and roasting, smelting, and refining of ores) is the largest source of anthropogenic atmospheric Cd emissions, followed by waste incineration, the production of batteries, fossil fuel combustion and the generation of dust by industrial processes, such as
steelmaking (Yamagata 1970). Cadmium was generally found at lower in concentrations than the other metals (Fig. 4). As mentioned, Zn was the predominant metal found in the soil samples, followed by Zn (median value 10–50 mg/kg dry soil). There was a significant correlation between Zn and Cd (R2 = 0.74). Zinc particles may be derived from industrial sources, with the abrasion of tires of motor vehicles a possible second source (Ellis and Revitt 1982; Beckwith et al. 1985; Garty et al. 1996; Adriano 2001; Carreras and Pignata 2002; Al-Khashman 2004). There were no correlations between metal concentrations and the pH, EC, CEC or TOM content of the soil samples. Owing to the narrow range of pH (5.33–8.33) in the soil, these parameters have limited effect on metal mobility and distribution. Mineralogical composition The mineral components of the topsoil are dominated by quartz, carbonates (calcite and dolomite) as major minerals with clay minerals and gypsum as minor minerals (Fig. 5). Quartz grains are the most common primary mineral cretaceous and tertiary deposits from natural processes during the weathering of igneous and sedimentary rocks. Calcite is one of the most common and widespread minerals; it occurs as a secondary mineral and results from carbonate rocks in the study area. Gypsum is associated with carbonate rocks as a minor mineral.
25
Statistical analyses and data treatment
mg/kg dry soil
20
15
0-10 cm
10
10-20 cm 5
0 Pb
Zn
Cd
Fe
Cu
Cr
Metals
Fig. 4 Mean values of metal concentrations in a reference soil sample
Statistical analyses were performed with SPSS for Windows ver. 10.0.5 (SPSS, Chicago IL). Data were log transformed prior to principle component analysis (PCA) to reduce the influence of high data values (Moller et al. 2005). The PCA was conducted using factor extraction with an eigenvalue [1 after varimax rotation. Metal concentrations were compared using one-way ANOVA to compute the statistical significance of the mean. The analyses revealed significant between-site differences (P \ 0.05; Chen et al. 1997) in the concentrations of Pb, Cd and Cu, but no significant differences were found for the other metals tested (Table 4). The inter-element relationships provided interesting information on the source and distribution of the
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Fig. 5 X-ray powder diffraction pattern of a selected soil sample
metals in the soil samples. Pearson’s correlation coefficient can be used to measure the degree of correlation between the logarithms of the metal data (Garcia and Millan 1998). These correlation coefficients are shown in Table 5. Lead and Zn are well correlated (R2 = 0.87), indicating common contamination sources. On the other hand, there are significant correlation coefficients between metals in all sampling points, such as Pb vs. Zn and Cd (R2 = 0.87, 0.74, respectively). Chromium shows a good correlation with Pb and Zn (R2 = 0.71, 0.72, respectively), and there are significant correlations between metals in all soil samples, such as Zn and Cu (R2 = 0.60). The metals in the soil samples do not, however, correlate with physico-chemical parameters, such as pH, TOM and CEC. Factor analysis was used to explore associations that would provide information on the distribution and source of metal pollution. Eigenvalues for the PCA were computed and the principle component rotated by the varimax method. The factor loadings are presented in Table 6. Factor 1, accounting for 39.85% of the total variance, showed high loadings on the elements Pb, Zn and Cd and indicated the influence of local anthropogenic activities. This was corroborated by results from soil samples that showed increased metal levels downwind. Similar results were obtained by Garcia and Millan 1998. Factor 2 (about 11.71% of the variance) comprised the effect of natural soil characteristics and smaller anthropogenic effects, such as those from traffic and agriculture (Moller
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Table 6 Factor loadings for varimax rotated PCA of metal data in soil samples Parameters
Factor 1
Factor 2
pH
-0.281
-0.421
0.841a
EC
-0.224
0.413
0.714a
0.321
-0.315
0.702a
0.231
0.552
0.115
-0.152
0.165
0.774a
TOM CaCO3 CEC
Factor 3
Pb
a
0.713
0.401
-0.214
Zn
0.755a
0.279
-0.147
a
Cd
0.692
0.174
Fe
0.121
0.758a
-0.213
Cu
0.514
0.602
-0.154
Cr
0.189
0.541
-0.234
Eigenvalue
4.122
1.287
1.126
% variance
39.852
11.708
10.247
% cumulative
39.852
51.605
61.846
a
0.235
Factor loadings [0.70
et al. 2005; Biasioli et al. 2006). Factor 3 (10.25% of the total variance), determined by the soil characteristics, such as pH, conductivity, CEC and organic matter, was not significant. These results suggest that the steel plant is the most important source of pollutants in the area investigated.
Conclusions This study of soil samples from the southwestern part of Queen Alia Airport area revealed a distinct
Environ Geochem Health (2009) 31:717–726
accumulation of metal pollutants. The soil consists mainly of yellow to brown loess-like silt, residual calcareous bedrock and clay. The highest metal concentrations were found on the eastern side of the steel factory, i.e. downwind and beside the desert highway. No significant variations were found in pH values between the soil samples, likely due to the buffering effect of carbonate. The non-clay mineralogical composition of the topsoil samples identified by X-ray diffraction was predominantly quartz, calcite, dolomite and minor minerals, such as gypsum and clay minerals. In terms of median concentration values, the order of metals present in the soil samples, from highest to lowest, was Pb [ Zn [ Fe [ Cr [ Cd [ Cu. The distribution of the metal concentrations in the soil indicate that this area has been affected by industrialization in general and by the presence of the steel processing plant in particular, leading to a high accumulation of heavy metals compared with the natural background levels. Soils from other large cities, such as London, Hong Kong and Madrid, also show higher concentrations of metals in their topsoil. In terms of health risks, bioavailability and metal mobility can be stated to be of minor significance in our study area.
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