J. Glob. Innov. Agric. Soc. Sci., 2014, 2(4): 158-162. ISSN (Online): 2311-3839; ISSN (Print): 2312-5225 DOI: 10.17957/JGIASS/2.4.460 http://www.jgiass.com

QUANTIFICATION OF THE HEAVY METALS IN THE AGRICULTURAL OF MARDAN DISTRICT, ,

Nida Gul1,*, Mohammad Tahir Shah1, Sardar Khan2 and Said Muhammad3

1 National Centre of Excellence in , University of Peshawar, Pakistan 2Department of Environmental Sciences, University of Peshawar, Pakistan 3Department of Earth and Environmental Sciences, COMSATS, Abottabad, Pakistan * Corresponding author’s e-mail: [email protected]

Soil samples were collected from Mardan district, Khyber Pakhtunkhwa, Pakistan and were analyzed for physico-chemical parameters (pH, EC, SOM), major cations (Na, K, Ca, Mg, Fe, Mn) and heavy metals (Cu, Pb, Zn, Ni, Cr, Cd, As) concentrations using atomic absorption spectrometer. Based on concentration values, the major cations was found in order of Na> Ca >Fe> K > Mg >Mn. Increasing order of the heavy metal concentrations were as Zn > Cr > Ni > Cu >Pb> As > Cd. The enhanced values of heavy metals in the studied soils could be due to sulfide and mafic in the soils of the study area. Metal concentrations were used to quantify pollution contamination factors (CFs) and pollution load index (PLI). It can be concluded from this classification that soils of the study area are polluted with some of the heavy metals. Keywords: major cations, heavy metals, contamination factor, pollution load index

INTRODUCTION MATERIALS AND METHODS

Soil is an important part of the nature. The presence of Study Area Profile: Mardan district is among the major major cations and heavy metals, soil organic matter (SOM), districts of the Khyber Pakhtunkhwa province of Pakistan. It air, moist and biological species result in complex is located about 14km northeast of Peshawar, Khyber phenomena. All the important biochemical cycles operate in Pakhtunkhwa. Mardan district can be divided into two parts, its upper most layers, where solar energy trapped in the northern hilly area and southwestern plain area, which is biomass is converted to organics on decomposition best known for agriculture. The major crops grown in the (Mckenzie and Susan, 2004). Soil also plays a significant district are wheat, sugar cane, tobacco, maize, rice, rape role in waste disposal and recycling of different nutrients seed and mustered (DCR, 1998).The important fruits grown and pollutants among different mediums and human’s food in the district are orange, plum, peach, apricot, pear, lechi, chain (Chen et al. 1997; Folinsbee, 1993). rare mango and apple. The main source of irrigational water The presence and nature of various elements and soil quality is the canals. The upper Swat canal irrigates most part of the mainly depends on the chemical composition of the parent district and lower Swat canal irrigates south-western part of rock, physical conditions and organic content of soil the district. The other sources are tube wells and lift (Drewery and Paton, 2005; Reynold et al. 2007; Shukla et irrigation (DCR, 1998). al. 2006). However, anthropogenic inputs from industries and agricultural products have become the predominant Soil Sampling and Analysis: Soil samples were collected sources of heavy metals (Heavy metals) in the soils (Wild, randomly from different agricultural fields of the Mardan 1996; Mico´ et al. 2006). district. Each sample of about 1kg was taken up to a depth Interaction between natural and anthropogenic sources has of 30 cm by an auger and stored in polyethylene bag. All the made source identification more difficult and ambiguous soil samples were properly labeled in the field and the (Facchinelli et al. 2001). These elevated concentrations of coordinates of each sample were recorded. These samples heavy metals may results in phytotoxicity and food chain were transferred to the laboratory of the disruption on one hand and can hindered the availability of National Centre of Excellence in Geology, University of essential nutrients on the other hand (Wang et al. 2006; Peshawar for experimental work. Soil samples, collected Alam et al. 2001; Michaud et al. 2008; Khan et al. 2008). Present study was based on the hypothesis that the geogenic during field, were air dried and were pulverized to 200 as well as anthropogenic inputs could enhance the levels of mesh. These soil samples were than dried overnight at 110 different major cations and heavy metals in the soils of ˚C in the oven.For measuring physical parameters, each soil Mardan district. Therefore the study was aimed; 1) to sample was mixed with deionized water in a ratio of 1:4 measure the level of different major cations and heavy (w/v) (Das and Maiti, 2008). The electric conductivity (EC) metals to quantify pollution 2) to apply different statistical and pH were determined by conductivity meter and pH techniques to identify the possible sources and grouping of meter respectively. The soil organic matter (SOM) was heavy metals. determined by the method of Konnen et al. (2002). 158 Gul, Shah, Khan & Muhammad

Table 1: Physio-chemical parameters of the soils of Mardan Pollution load index (PLI) district Pollution load index was measured by the following a Parameter Range Mean ±Std dev equation of Usero et al. pH 5.9-8.1 7.6 ±0.4 b -1 (2000); EC (µScm ) 209-510 287±64 SOMc (%) 0.50-6.00 2.26 ±1 PLI = (CF1× CF2× CF3×……….CFn) 1/n a Standard deviation; bElectrical conductivity; cSoil organic matter

th Table 2: Major cations and heavy metals concentrations in the Value of PLI being as a n root of the product of nCF. The soils of Mardan district results were compared with that reported by Rashed (2010). Element Range Mean ±Std dev Bohn,s limit CFa Statistical Analysis: The statistical parameters such as Major Cations ( gkg-1) range, mean and standard deviation were determined by Ca 9-140 61.1±46 25 3.4 using Excel 2007. Statistical analysis like interelemental Mg 0.8 – 14.5 9.8±5 15 5.3 correlation and factor analysis (FA) and cluster analysis Na 59-115 98 ±12 15 8.8 (CA) were carried out, using SPSS version 17. K 9.8-34 26 ±7 15 2.1 Fe 11.6-35 25 ±7 57.7 0.6 RESULTS AND DISCUSSION Mn 0.5-11 1.4 ±2 1 1.8 Heavy Metals ( mgkg-1) Cu 12-45 28 ±7 20 1.4 Physico-chemical Parameters Concentrations in Soil Pb 4-56 27 ±8 10 2.7 Samples: Table 1 summarizes the pH, EC and SOM values Zn 4-275 96 ±54 50 1.9 in the soils samples. Mean values of pH, EC and SOM were Ni 20-81 49 ±15 40 1.2 found as 7.6, 287 µScm-1 and 2.3% respectively. Low pH Cr 25-84 60 ±14 20 3.0 values in some samples could be due to the presence of Cd 0.15-3.06 2.33 ±0.5 0.06 38.8 sulfide bearing phases, especially pyrite while the high As 1.55-26.13 5.14 ±4 10 0.5 values could be attributed to the presence of calcite and PLIb 2.3 a b dolomite in the studied soils as these minerals are Contamination Factor; Pollution Load Index abundantly present in the sedimentary and mafic-ultramafic For the determination of major cations (Ca, Mg, Na and K) rocks exposed in the catchment areas from where the soils and heavy metals (Fe, Mn, Cu, Pb, Zn, Ni, Cr and Cd) 1 g of are eroded out (Hussain et al., 1984; Pouge and Hussain, each soil sample was taken in separate Typhlon beaker and 1986; Rafiq and Jan, 1989). Relatively high EC in the soil was digested according to procedure adopted by Gupta et al. samples could be due to the saline nature of the soils of (1996). In these solutions major cations (Ca, Mg, Na and K) Mardan district. The mean values of EC and SOM were and heavy metals (Fe, Mn, Cu, Pb, Zn, Ni, Cr and Cd) were however, found lower than the contaminated soils of determined using Perkin Elmer 700 atomic absorption northern parts of Pakistan (Muhammad et al. 2011). spectrometer under the standardized instrumental conditions. The reference standards, G2, AGVI and W-2 Major Cations and Heavy Metals: Descriptive summary of were used for calculating the precision. 95% confidence major cations and heavy metals is given in Table 2. Mean concentrations of the Ca, Mg, Na, K, Fe, Mn were 61.1gkg- level was attained for the analysis. 1 1 1 1 1 1 For the determination of arsenic (As), 5g of soil sample was , 9.8 gkg- , 98 gkg- , 26 gkg- , 25 gkg- and 1.4 gkg- digested in an acid mixture prepared according to procedure respectively. Major cations concentrations were found in the adopted by Abollino et al. (2002). The concentration of As order of Na > Ca >K> Fe > Mg >Mn. These elements were was determined by using mercury hydride system (MHS) found higher as compared to the normal agricultural soils fitted with Perkin Elmer 700 atomic absorption spectrometer reported by Bohn et al. (2001). Elevated level of Ca and Mg under the standardized instrumental conditions. may be due to the weathering of limestone and dolomite, and the addition of phosphate fertilizers. Higher values of Quantification of Soil Pollution Na content could be due to high concentrations of salts that Contamination factor (CF): For heavy metals, CF values have been built up in the soils due to high rate of were determined through following equation; evaporation of water contributed by the Swat River through irrigational means. The water logging and salinity remained CF = [C] heavy metal / [C] background the problem for long time in the area which has greatly affected the agricultural soils of the area. The elevated Where [C] heavy metal means the concentrations of heavy content of K could be due to the decomposition of feldspar, metals in contaminated soils while, [C] background denotes contributed to the studied soils by the granite rocks of their concentrations in uncontaminated or referenced soils alkaline province exposed in the northern parts of Mardan (Rashed, 2010; Khan et al. 2008). As in the present study district. Contents of Fe were found within the limit referenced soil sample were not collected so here safe limits suggested by Bohn et al. (2001) for the normal agricultural for these heavy metals suggested by Bohn et al. (2001) were soils (Table 2). used for CF values calculation (Bohn et al. 2001). The Mean concentrations of Cu, Pb, Zn, Ni, Cr, Cd and As were -1 -1 -1 -1 -1 results were compared with those of Muller (1969). 28 mgkg , 27 mgkg , 96 mgkg , 49 mgkg , 60 mgkg , 159 Quantification of the heavy metals in the agricultural soils

Table 3: Inter elemental correlation among the physio-chemical parameters of the studied soils pH EC SOM Ca Mg Na K Fe Mn Cu Pb Zn Ni Cr Cd As pH 1 -0.348* -0.014 0.065 0.485* -0.179 -0.217 -0.335 -0.065 0.169 -0.071 0.096 0.131 0.282 0.643** 0.074 EC 1 0.22 -0.2 0.065 0.046 0.313 0.204 0.106 0.313 0.504** -0.023 0.32 0.231 -0.284 -0.163 SOM 1 -0.157 0.233 0.235 0.317 0.316 -0.096 0.131 -0.125 -0.043 0.089 0.126 0.088 -0.008 Ca 1 -0.021 -0.238 -0.196 0.127 -0.035 -0.112 -0.164 -0.231 -0.124 0.045 -0.075 0.061 Mg 1 -0.2 0.199 0.460** -0.304 0.464** 0.205 -0.065 0.445** 0.448** 0.491** 0.092 Na 1 0.214 -0.069 0.236 -0.298 -0.127 0.179 -0.314 -0.301 -0.162 -0.019 K 1 0.154 -0.590** -0.084 0.294 -0.105 0.124 -0.033 -0.123 -0.102 Fe 1 0.028 0.383* 0.092 -0.244 0.304 0.305 -0.085 -0.018 Mn 1 0.116 -0.241 0.095 -0.19 -0.039 -0.204 -0.125 Cu 1 0.184 0.136 0.819** 0.868** 0.196 0.108 Pb 1 -0.03 0.256 0.133 0.342 -0.025 Zn 1 -0.127 -0.042 0.05 0.017 Ni 0.850** 0.213 0.205 Cd 1 0.257 0.074 Cr 1 0.127 As 1 *. Correlation is significant at the 0.05 level (2-tailed); **. Correlation is significant at the 0.01 level (2-tailed).

Mardan district could be the main cause of the Ni and Cr contents in the soils.

Pollution Quantification Contamination factor (CF): Table 2 summarizes the CF values for major cations and heavy metals. The Ca, Mg, Na, K, Fe and Mn in the soils were found with CF values of 3.4,

5.3, 8.8, 2.1, 0.6, and 1.8, respectively. Order of the CF Figure 1: Cluster analysis result for heavy metals by using values was Na > Mg > Ca > K >Mn> Fe. Based on Muller ward method classification major cations concentrations in the soils were classified as Ca; moderate to highly polluted, Mg and Na; Table 4: Factor analysis results for heavy metals in soils of highly polluted, K and Mn; moderately polluted, Fe; weakly Mardan district polluted. F1 F2 F3 Similarly for heavy metal concentrations, CF values were Cu 0.919 0.092 0.215 Pb 0.097 0.831 -0.125 1.4, 2.7, 1.9, 1.2, 3.0, 38.8 and 0.5 for Cu, Pb, Zn, Ni, Cr, Zn -0.112 -0.015 0.912 Cd and As respectively (Table 2). The CF values were in the Ni 0.936 0.166 -0.028 order of Cd > Cr >Pb> Zn > Cu > Ni > As. Based on Muller Cr 0.948 0.099 0.042 classification heavy metals were classified as Cu and Zn; Cd 0.131 0.789 0.198 moderately polluted, Pb and Cr; moderate to highly As 0.167 0.042 0.381 polluted, Cd; highly polluted, As; weakly polluted, Ni; Eigen value 2.685 1.36 1.08 without significant pollution. It can be concluded from this % of Variance 38.351 19.433 15.43 classification that soils of the study area are almost heavily Cumulative % 38.351 57.784 73.214 polluted with major cations and heavy metals. 2.33 mgkg-1, 5.14 mgkg-1, respectively (Table 2). Increasing order of these heavy metals concentrations were found in Pollution load index (PLI): Based on CF values, PLI was the order of Zn > Cr > Ni > Cu >Pb> As > Cd. Few soil calculated for the soils of Mardan district. High PLI value samples showed high Cu content (>20gkg-1) in comparison (2.3) indicated that the soils of the Mardan district are to the normal agricultural soils (Bohn et al. 2001). However, highly polluted which may threaten the food chain and soil almost all the soil samples were having high contents of Pb, biology in the area (Table 2). Zn, Ni and Cr in comparison with the normal agricultural soils of Bohn et al. (2001) (Table ii). Arsenic contents in the Statistical analysis studied soil samples were found within the permisible limit Inter elemental correlation: Significant positive of 9 mgkg-1(Kabata-Pendias and Pendias, 2001). The correlations were observed between pairs such as pH-Cd (r enhanced values of Cu, Pb and Zn in the studied soils can be = 0.643), EC-Pb (r = 0.504), Mg- Fe(r = 0.460), Mg-Cu (r = attributed to the sulfide seams in the area (Watling, 2006), 0.464), Mg-Ni (r = 0.445), Mg-Cr (r = 0.448), Mg-Cd (r = while weathered material contributed by the mafic and 0.491), Cu-Ni (r = 0.819), Cu-Cr (r = 0.868) and Ni-Cd (r = ultramafic rocks exposed in the north-western part of 0.850) (Table 3).

160 Gul, Shah, Khan & Muhammad

Factor analysis (FA): To further elaborate the relationship Alam, S., S. Kamei, and S. Kawai. 2001. Effect of iron between the heavy metals, FA was applied to the data. deficiency on the chemical composition of the xylem According to the results three factors were extracted from sap of barley. Soil Sci. Plant. Nutr. 47: 643-649. the whole data set. The FA results are summarized in Table Bohn, H.L., B. L. McNeal, and G.A. O’Connor. 2001. Soil 4. chemistry, 3rd Ed. John Wiley and Sons, Inc. New Factor 1.contributed 38.351 % to the total variance with York. loading on Cu (0.919), Ni (0.938) and Cr (0.948) (Table 4). Chen, T.B., J.W.C. Wong, H.Y. Zhou, and M.H. Wong. All the three heavy metals also showed significant 1997. Assessment of trace metal distribution and association among themselves and also with Mg and Fe contamination in surface soil of Hong Kong. Environ. during inter elemental correlation (Table 3). Pollut. 96: 61-68. Factor 2.contributed 19.433 % to the total variance with Cui, Y., Y. G. Zhu, R. Zhai, Y. Huang, Y. Qiu, and J. high loading on Pb (0.831) and Cd (0.789). Stronger Liang. 2005. Exposure to metal mixtures and human correlation was also observed between Cd and Mg. Again health impacts in a contaminated area in Nanning, the stronger correlation suggests the natural sources for . Environ. Int. 31: 784-790. these metals in the studied soils. Das, M., and S.K. Maiti. 2008. Comparison between Factor 3.had contributed 15.43 % to the total variance. The availability of heavy metals in dry and wetland tailing only element with loading in this factor was Zn (0.912). The of an abandoned copper tailing pond. Environ. Monit. high loading from only one metal indicates some Asses. 137: 343-350. anthropogenic inputs in the soils of Mardan district. District Census Report of Mardan District (DCR), 1998. Facchinelli, A., E. Sacchi, and L. Mallen. 2001. Multivariate Cluster analysis (CA): To further investigate the sources of statistical and GIS based approach to identify heavy heavy metals in the soils of the study area, CA was metal sources in soils. Environ. Pollut. 114: 313-324. performed in agreement with FA. As a result of CA, two Folinsbee L. J. 1993. Human health effects of air pollution. major clusters were obtained, cluster 1 and cluster 2 (Fig. 1). Environ. Health. Persp. 100: 45-46. Cluster 1 was made of the elements which were present in Gallego, J. L. R., A. Ordonez, and J. Loredo. 2002. the F1andF2 (Cu, Pb, Ni, Cr and Cd). This shows the Investigation of trace element sources from an geogenic input as most of the sulfide and mafic minerals industrialized area (Aviles, northern Spain) using (i.e., pyroxene, olivine and amphibole) posses the strong multivariate statistical methods. Environ. Int. 27: 589- correlation of these metals Cluster 2 was consisted of only 596. Zn, the metal presented in the F3. The major anthropogenic Gupta, S.K., M. K. Vollmer, and R. Krebs. 1996. The factors for the enhanced values of Zn could be the use of importance of mobile, mobilisable and pseudo total phosphate fertilizers and pesticides application on heavy metal heavy metal fractions in soil for three-level agricultural fields of the study area. risk assessment and risk management.Sci. Total. Environ. 178: 11-20. CONCLUSION Husain, S.S., T. Khan, H, Dawwod, and I. Khan. 1984. A The elevated concentrations of major cations and heavy note on Kot-Parang Ghar mélange and associated metals in the agricultural soils of the Mardan District could occurences. Geol. Bull. Univ. Peshawar. 17: be the result of both geogenic and anthropogenic inputs. 61-68. Saline conditions in the past, mafic rocks and fertilizers Khan, S., Q. Cao, Y. M. Zheng, Y. Z. Huang, and Y. G. Zh. have greatly influenced the soils chemistry. From cluster 2008. 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