HEAVY METAL DISTRIBUTION IN VALLEY SEDIMENTS IN WADI AL-KARAK CATCHMENT AREA, SOUTH JORDAN TAYEL EL-HASAN1∗ and ANWAR JIRIES1 1 Department of Chemistry, Faculty of Science, Mu’tah University, Al-Karak – Jordan (∗ author for correspondence, fax: + 962-6-4654061; e-mail:
[email protected])
(Received 8 June 2000; accepted in revised form 23 February 2001)
Abstract. Valley sediments samples collected from the major and minor valleys of Al-Karak catchment area (southern Jordan) were leached with hot dilute HCl and analysed for their heavy metals content. The results of leachable metal concentrations indicated the absence of anomalous values for metal occurrences. However, appreciable contamination of the sediments with Cu, Zn, Pb, Cd and Cr was observed. Using an index of pollution the extent of contamination was better delineated. The geographical distribution of the samples showed higher Cu, Zn, Pb, Cd and Cr concentrations mainly around heavily inhabited areas indicating an anthropogenic source of contamination. Lithological influence indicated from the anomalies of Fe and Mn was found to be very low. Key words: anthropogenic, arid regions, environmental indicator, heavy metals, pollution index, stream sediments
1. Introduction Valley sediments have been used as an exploration technique in various climates and geological environments, (Hawkes and Webb, 1962; Beeson, 1984; Saffarini and Lahawani, 1992; Lombard et al., 1999). Multi-elemental valley sediment geochemical survey was conducted in the Jordanian basement, (BRGM, 1994). Sediments, which are an important part of the ecosystem, act as storage for heavy metals, where large portions of the metallic substances are ultimately incorporated in their composition (Rolfe and Edgiston, 1973). Once the pollutants reach the valley sediments through surface runoff, heavy metals are either adsorbed on sediment surface, or transported along the water flow path of the valleys, some fractions will be incorporated into the plants depending on the geochemical conditions of the ecosystem. Heavy metals are natural constituents in nature, usually occurring in low concentration under normal conditions. Anthropogenic activities can cause elevated levels of these metals in various parts of the ecosystems. Heavy metals of river sediments in hydrological systems are more sensitive than dissolved concentrations as indicators of contamination (Gaiero et al., 1997). In the Karak area, several investigations were carried out on heavy metal contamination. Hussain et al. (2000) reported elevated levels of heavy metals in sediEnvironmental Geochemistry and Health 23: 105–116, 2001. © 2001 Kluwer Academic Publishers. Printed in the Netherlands.
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ments, plants, and treated wastewater produced from a University laboratory. They also reported elevated levels of heavy metals in sediments affected by wastewater produced from Karak wastewater treatment plants. The objectives of the present study were to determine heavy metals concentrations in sediments from major valleys in an arid climatic condition, such as Al-Karak region (Jordan), which are potentially contaminated by anthropogenic activities. This study aims to establish base-line data for a zone (Wadi Al-Karak) that lies at a fault and encompasses at some sampling sites affected by multi-human activities. As such, metal contents in the sediments of the study area may be due to the occurrence of the fault and/or due to human sources and are verified by the use of Index of Pollution. 2. Study Area The investigated area is located in the central part of Jordan covering more than 150 km2 of Al-Karak province Figure 1. The lithology of the area is characterised by outcrops of Lower-Cretaceous sandstone (Kurnub sandstone Fm.), overlain by Upper-Cretaceous carbonate formations. The latter can be divided into a lower part (Ajloun Limestone), which is compressed (Naur; Fuheis; Hummar; Shuayb; and Wadi Es- Sir Fms.). An upper part (Belqa Limestone) is composed of Um-Ghudran; Amman silicified; Al-Hisa phosphorite; and Muwaqqar Fms (Powell, 1988). Large areas are covered by red soils along the banks of the valleys as a result of many landslides. The upper parts of the upper Cretaceous formations that are exposed at higher elevation are highly weathered and dominated by caliche. Highly weathered basaltic dykes of Miocene age are intruded in the above formations along the NW – SE Al-Karak fault zone. Structurally, several faults were reported in the investigated area, where the main valleys lie along the main fault systems. The regional fault system (Al-Karak – Al-Faiha) is striking NW–SE across the area. Another minor fault exists striking NNW–SSW and E–W along which the main tributaries course exists (Bender, 1974). The valleys of the area are relatively young with V-shaped morphology and steep escarpments along their paths. Jordan has a Mediterranean climate; the average rainfall is around 300 mm yr−1 , falling only during the winter season, starting in November and ending in March. No surface runoff exists in the summer period; therefore, flushing of the pollutants into the drainage by rainfall is discounted as the sampling period in the end of the summer season. 3. Experimental Fifty valley sediment samples were collected during September–November (1999) from the main valleys of Wadi Al-Karak catchment area Figure 1. The samples
HEAVY METAL DISTRIBUTION IN VALLEY SEDIMENTS
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Figure 1. Location map with sampling sites.
were obtained from the middle of the valleys to eliminate the influence of sediments from the flanks of the valleys. Samples were collected and stored in plastic bags until the time of analysis. Seven background samples (H1–H7) were collected from the hubs of large segment of the main valleys, they are not included in the statistical interpretation. Sediment samples were dried at 85◦ C to a constant weight. All
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dried samples were sieved and the portion < 150 µm (− 100 mesh) was analysed since it was proven to be the best size for arid and semi-arid regions (Saffarini and Lahwani, 1992; and FOREGS, 1998). Two extraction methods were used and the best results were yielded by the hot extraction with dilute HCl (1 : 3). This method was described by Beeson (1974) and used successfully in arid regions (Saffarini and Lahawani, 1992). One gram of sediment was accurately weighed, digested with 10 ml (1 : 3) dilute HCl solution in a test tube, heated at 90◦ C for 2 h, shacken vigorously every 10 min. The final extracts were filtered into 25-ml polyethylene volumetric flasks through 0.45 µm filters. The supernatant content of heavy metals (Fe, Cu, Mn, Zn, Pb, Cd, Cr and Ni) were determined using a flame atomic absorption spectrophotometer (Smith-Heftie 11 model 757 AA) with deuterium lamp background correction. Quality control was done for Cd, Fe, Zn, Mn, Cu, Ni, Pb and Cr using (Merck ICP4) standard solutions. The errors were within 95% confidence level.
4. Results and Discussion Heavy metal concentrations of all samples of Wadi Al-Karak catchments area are given in (Table I) and for each major segment in (Table II). Although faults might concentrate heavy metals along their planes, no correlation between the major faults and heavy metals distribution was observed in the study area. However, considerable variation in heavy metal concentrations between different segments was observed. The higher concentrations were detected around highly populated areas, and heavy traffic, such as around Karak city and Wadi Twal of (90,000 inhabitants). Of all the heavy metals determined, iron exhibits high values all over the study area and can be attributed to the soils of the investigated area, which are characterised by high iron contents mainly as poorly crystallised Fe-oxides (Younis et al., 1999). Basalt can be a rich source of some heavy metals such as Fe, Cu and Cr. The basaltic dyke showed no influence in the investigated area as it is highly weathered and located at the western edge of the study area. Other heavy metals such as Zn and Pb showed higher concentrations in valleys such as Wadi Al-Karak (around Karak city), Wadi Twal, and a part of Wadi AlThania adjacent to Karak city than other segments of the investigated area. The highest Zn and Pb concentrations exist along Wadi Twal. This might be due to the presence of the Karak municipal industrial area (mainly automobile maintenance) in the upper valley, besides the two major oil exchange service stations situated down the valley. A threshold was calculated using the equation (reported in a similar work in Jordan, Saffarini and Lahawani, 1992). Threshold = X + 2σ where X is the mean, σ is the standard deviation.
(1)
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TABLE I Heavy metals concentrations of samples in the study area (all are in ppm) Samples
Fe
Cu
Mn
Zn
Pb
Cd
Cr
Ni
KGS-1 KGS-2 KGS-3 KGS-4 KGS-5 KGS-6 KGS-7 KGS-8 KGS-11 KGS-12 KGS-13 KGS-14 KGS-15 KGS-16 KGS-17∗ KGS-18 KGS-19∗ KGS-21 KGS-22∗ KGS-23 KGS-24∗ KGS-25 KGS-26∗ KGS-27∗ KGS-28 KGS-29 KGS-31 KGS-32∗ KGS-33∗ KGS-37∗ KGS-38 KGS-39 KGS-40∗ KGS-42∗ KGS-43 KGS-44 KGS-46 KGS-47
18515 20958 18997 13303 10859 8013 8193 5298 7689 9908 6546 6447 10381 8497 7742 8902 9596 9300 4942 7150 5046 11104 7346 6751 10802 11434 8800 7689 7940 6997 7652 10446 7997 7404 10260 16140 21179 15978
14.01 15.01 13.96 17.5 21.02 18.03 35.47 27.99 20.47 12.51 8 23.99 14.97 13.99 7.49 11 11.5 11 7.49 12.9 6.99 12.51 8.99 10 9.5 10.49 10 10.98 5.49 3.5 8 11 9.5 12.51 11.51 10.49 17.98 11.98
469.88 501.2 467.69 321.56 269.72 215.85 197.34 95.34 95.46 192.73 165.63 257.35 131.95 220 192.42 190.81 244.05 219.91 235.5 145.27 180.5 137.89 342.64 257.35 219.04 308.56 362.49 259 231.18 166.33 253.4 318.87 236.41 70.54 244.74 395.76 533.97 408.43
62 57.5 54.8 86.5 125.6 125.2 164.9 108.5 109.8 75.1 69 186.9 92.3 88.5 45 69.5 73.5 78 53.4 96.5 51.5 50.5 33 56 42 36.9 39 76.9 22.5 37 20.5 43 22.5 96.1 88.1 57 66.4 63.9
22.5 24 25.9 15 28 40.6 33 16 47.4 16 13.5 58 23 22.5 12.5 21 16.5 29 10.5 18.5 19 13 9.5 17 17.5 15 21.5 10 16 19.5 11 18 15.5 11.5 19 15 24.5 12.5
3 3 2.49 3 9.01 4.01 9.99 7.5 6.49 6.51 5.5 7.5 2 1.5 2.05 4.5 2.5 0.5 n 5.5 2 n 2 1 n n 1 1 n 1 n 1 n 0.5 1.5 2.5 1.5 2.5
45 45 34.9 60 40 35.1 79.9 100 35 25 15 50 44.9 30 15 25 25 30 15 15 20 30 10 20 10 20 15 20 5 5 5 5 5 60 40 35 45 39.9
35.53 36.01 40.89 39.01 34.53 27.54 44.96 44.98 28.96 26.02 20.49 40.98 34.94 21.99 21.48 25.01 16.99 32 30.45 28.5 18.98 32.51 26.98 31.01 26.01 33.45 9 17.97 4.99 17.49 21 12.99 20.99 29.52 29.03 34.98 42.46 37.45
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TABLE I continued Samples
Fe
Cu
Mn
Zn
Pb
Cd
Cr
Ni
KGS-48 KGS-50 KGS-51 KGS-52 KGS-53 KGS-54 KGS-55 KGS-56 KGS-57 KGS-58 KGS-59 KGS-60 Hub-1 Hub-2 Hub-3 Hub-4 Hub-5 Hub-6 Hub-7
9084 11234 8653 11395 9744 3746 16610 9241 17504 20317 7841 15319 7950 6334 12743 11150 7153 7835 3590
21.46 16.98 16.51 12.99 21.49 6.49 13.97 10.49 12.5 15.97 13.98 13.97 9.81 13.47 28.93 12.0 13.73 13.46 7.48
248.05 320.55 234.59 264.39 220.87 330.67 428.97 270.73 488.6 566.59 154.81 373.75 415.0 401.1 295.6 370.5 247.6 181.0 109.7
101.8 73.9 70.5 70 101.4 19.5 40.9 123.9 65.5 52.4 103.9 70.9 42.5 71.4 133.6 55.0 66.5 79.9 24.9
17 20.5 16 10 26.5 21.5 19 24 20 21.5 14.5 24.0 23.0 14.0 14.4 12.0 11.1 17.5 n
1.5 1 1 5.5 4.5 3.5 2 3.5 5 2.49 6.49 2.99 3.0 2.5 6.0 1.5 1.0 3.5 n
59.9 39.9 30 25 55 10 29.9 20 40 34.9 40 25 25.0 45.0 65.0 45.0 24.0 45.0 5.0
39.93 36.95 33.51 27.99 27.98 23.48 23.94 23.98 34.51 31.45 30.46 30.94 25.5 17.0 21.9 28.0 19.5 24.9 13.5
∗ Samples used for ABS calculations. n: not detected.
Few samples exceeded this threshold indicating the absence of anomalous metallic occurrences within the vicinity of the investigated area. However, for the purpose of environmental evaluation of the heavy metals distribution in the investigated area, the method of calculating the index of pollution (IP) was used (Chester et al., 1985). The prime step of this method is the assigning of the ABS (artificial background samples), which were chosen based on the following criteria; first the valley from which ABS sample was chosen must have sufficient number of samples to assess the effect of pollutants input. Secondly the individual sample should show lower heavy metal concentrations relative to other samples, (Chester et al., 1985). The chosen ABS samples are shown in (Table I). The new threshold was then calculated using the following equation: Threshold = X(ABS) + 2σ(ABS)
(2)
where X(ABS) is the mean of ABS samples, σ(ABS) is the standard deviation of ABS samples.
HEAVY METAL DISTRIBUTION IN VALLEY SEDIMENTS
TABLE II Average Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn concentration (in µgg−1 ) from main segments of the investigated area Concentration (µgg−1 ) Max Mean
Heavy Metal
Min
Cd Cr Cu Fe Mn Ni Pb Zn
W. Safafa (Site) 0.50 2.50 5.0 60.0 10.4 17.98 7404.0 21179.0 70.5 533.97 12.99 42.46 11.5 24.50 43.0 96.10
1.58 37.48 12.58 14229.4 327.9 31.1 16.8 69.1
Cd Cr Cu Fe Mn Ni Pb Zn
W. Al-Thania (Site) 1.0 5.5 10.0 59.9 6.5 21.5 3746.0 20317.0 220.87 566.6 23.48 39.9 10.0 26.5 19.5 123.9
3.2 34.5 14.9 11752.8 337.4 30.4 19.6 72.0
Cd Cr Cu Fe Mn Ni Pb Zn
W. Al- Karak (Site) 0.0 5.5 5.0 30.0 3.5 12.5 4942.0 11434.0 137.9 362.5 5.0 33.5 9.5 29.0 20.5 96.5
0.9 15.0 9.1 8063.3 243.6 23.4 16.2 47.7
Cd Cr Cu Fe Mn Ni
W. Twal (Site) 2.5 10.0 34.9 55.0 14.0 20.4 5298.0 20958.0 95.5 501.2 27.5 45.0
5.3 23.6 7.7 13017.0 317.3 37.9
111
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TABLE II continued Heavy Metal Pb Zn
Min
Concentration (µgg−1 ) Max Mean
15.0 54.8
40.6 164.9
25.6 98.1
Cd Cr Cu Fe Mn Ni Pb Zn
W. Shanawar (Site) 2.5 6.5 25.0 40.0 11.0 13.9 7878.0 15319.0 218.9 373.8 13.9 30.94 9.5 24.0 34.4 103.9
Cd Cr Cu Fe Mn Ni Pb Zn
Around Al-Karak City (Site) 1.5 7.5 4.5 15.0 50.0 30.7 7.5 23.9 14.5 6447.0 10381.0 8172.9 131.9 257.4 192.9 20.5 40.9 27.8 12.5 58.0 27.6 45.0 186.9 95.2
4.1 28.8 12.6 10414.5 248.1 25.9 19.0 79.5
Finally, the IP was then calculated by using the following equation. IP = Conc. E/(X(ABS) + 2σ(ABS) )
(3)
where Conc. E is the concentration of any element in the sample, and the (X(ABS) + 2σ(ABS) ) is the ABS threshold of that element. Whenever IP > 1.0 this indicates that additional pollutant input has been introduced to the sample. The distribution of IP values that are > 1.0 through the investigated area is shown graphically in Figure 2. Fe and Mn show random distribution along Wadi Safsafa, Wadi Shanawer, Wadi Twal and Wadi Al-Thania. This observation indicates a non-point source input of these metals, and confirms that the Fe and Mn presence is related to the large quantity of soil in the samples as these valleys are surrounded by red soils exposures (Yunis et al., 1999; and ElHasan and Lataifah, In press). Copper, Zn, Pb, Cd and Cr distribution was limited to Wadi Twal, as well as a segment of Wadi Al-Karak around Karak city, and the part
HEAVY METAL DISTRIBUTION IN VALLEY SEDIMENTS
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Figure 2. The distribution of samples that have IP > 1.0 for each element all over the study area.
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TABLE III Correlation coefficient matrix for all heavy metals in the study area
Fe Cu Mn Zn Pb Cd Cr Ni
Fe
Cu
Mn
Zn
Pb
Cd
Cr
Ni
1 0.12 0.89 −0.15 0.02 −0.07 0.20 0.38
1 −0.06 0.77 0.53 0.64 0.84 0.68
1 −0.37 −0.04 −0.18 −0.04 0.25
1 0.63 0.69 0.66 0.49
1 0.46 0.28 0.27
1 0.49 0.37
1 0.76
1
95% confidence level, and (n = 50).
of Wadi Al-Thania that is near Karak city. Ni shows no indication of pollutant input all over the study area. Therefore, two groups of heavy metals were confirmed by testing the significant correlation coefficient between all heavy metals (Table III). The first group consists of Fe and Mn, and the second compresses Cu, Zn, Pb, Cd and Cr. A strong relationship between Fe and Mn with other heavy metals in sedimentary processes, due to their high absorbance capacity, has been reported by many workers (e.g. Kinniburgh et al., 1976; Edwards and Benjamin, 1989; Rahner et al., 1993; Brooks and Herman, 1998). Such a relationship was not in the investigated area, which might indicate that the enrichment of heavy metals (Cu, Zn, Pb, Cd and Cr) is related to something else other than sedimentary processes or lithological factors, most probably anthropogenic input, which is confirmed by IP distribution, (Figure 2). A one-way ANOVA has been used to compute the statistical significance of the differences between means of each heavy metal concentration with in each Wadi (Table IV). The difference between the average concentrations between the investigated valleys was significant for Fe, Zn, Pb, Cd, Cr and Ni. No significant variation was observed for Cu and Mn. However, there is no significant occurrence of metal deposits in these elements in the lithology of the study area, thus the main source of these elements in the investigated area would originate from anthropogenic sources. This was confirmed by the use of multiple comparison between the different valleys. The main significance in variation was mainly due to Wadi Twal which is located to the west of Karak city where anthropogenic activities are highest.
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HEAVY METAL DISTRIBUTION IN VALLEY SEDIMENTS
TABLE IV Statistical analysis (one-way ANOVA) results of the heavy metals in samples collected from five main valleys of the investigated area showing different relationships between each segment and between each metal within these segments Heavy metal
Sum of squares between groups
df
Mean square between groups
Sum of squares within groups
df
Mean square between groups
F
Observe α
Fe Cu Mn Zn Pb Cd Cr Ni
88154.892 2695.204 75567.444 14079.629 493.590 116.768 8829.114 1230.903
4 4 4 4 4 4 4 4
22038.723 673.801 18891.861 3519.907 123.398 29.192 2207.279 307.726
267261.108 19451.794 502337.909 29230.857 1234.117 134.389 8767.911 2517.777
37 38 38 38 38 38 38 38
7223.273 511.889 13219.419 769.233 32.477 3.537 230.735 66.257
3.051 1.316 1.429 4.576 3.800 8.254 9.566 4.644
0.029∗ 0.281 0.243 0.004∗ 0.011∗ 0.000∗ 0.000∗ 0.004∗
∗ Significant difference between the sites.
5. Conclusions The results of the present investigation indicate the absence of ore deposits containing Fe, Cu, Mn, Zn, Pb, Cd, Cr and Ni since no economic anomalies were detected. The results of the investigations of heavy metal either concentrations or distribution in the study area can be used as reference baseline data values for further studies. The use of the I.P. technique indicates pollutant inputs of Cu, Zn, Pb, Cd and Cr and the distribution of these contaminated samples relates to heavily inhabited areas, thus, indicating the anthropogenic source of contamination.
Acknowledgements The authors are deeply thankful to Mr. Mufeed Batarsah and Mohammad Bustangi for their help in the analytical procedures. As well as the authors would like to express their thanks to the Department of Chemistry, Mu’tah University for providing the AAS instrument.
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