Speciation and evaluation of Arsenic in surface water and groundwater samples: A multivariate case study

ARTICLE IN PRESS Ecotoxicology and Environmental Safety 73 (2010) 914–923

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Speciation and evaluation of Arsenic in surface water and groundwater samples: A multivariate case study Jameel Ahmed Baig a,n, Tasneem Gul Kazi a,1, Abdul Qadir Shah a,1, Ghulam Abbas Kandhro a, Hassan Imran Afridi a,1, Mohammad Balal Arain b, Muhammad Khan Jamali c, Nusrat Jalbani d,2 a

Centre of Excellence in Analytical Chemistry University of Sindh, Jamshoro 76080, Pakistan Department of Mathematics and Natural Sciences, NED, University of Karachi, Pakistan c Degree College Usta Muhammad, Usta Muhammad, Balochistan d Pakistan Council for Scientific and Industrial Research, Karachi 75280, Pakistan b

a r t i c l e in f o

a b s t r a c t

Article history: Received 11 September 2009 Received in revised form 5 January 2010 Accepted 7 January 2010 Available online 3 April 2010

The principal object of the current study was to estimate total arsenic and its inorganic speciation in different origins of surface water (n =480) and groundwater (n = 240) of Sindh, Pakistan. This study provided a description based on the evaluation of physico-chemical parameters of collected water samples and possible distribution of As with respect to its speciation. The concentration of total inorganic As (iAs) and its species (As3 + and As5 + ) for the surface and underground water was reported in terms of basic statistical parameters, principal component analysis, cluster analysis, metal-to-metal correlations and linear regression analyses. The chemical correlations were observed by PCA, which were used to classify the samples by CA, based on the PCA scores. Standard addition method confirmed the accuracy; the recoveries of As3 + and iAs were found to be 4 98%. The concentration of As5 + in the water samples was calculated by the difference of the total inorganic arsenic and As3 + . The results revealed that the groundwater of the understudied area was more contaminated as compared to the surface water samples. The mean concentration of As3 + and As5 + in the surface water and groundwater samples were in the range 3.0 to 18.3 and 8.74–352 mg/L, respectively. & 2010 Elsevier Inc. All rights reserved.

Keywords: As speciation Surface water Groundwater Cluster analysis Principal component analysis

1. Introduction The metals and metalloids in natural systems were originated from both anthropogenic and geological sources. Arsenic (As) is a metalloid present in different environmental and biological systems (soil, sediment, water and food stuffs). In drinking water, it predominantly occurs as inorganic (As3 + and As5 + ) and organic forms (methyl and dimethyl arsenic compounds) (Smedley and Kinniburgh, 2002; Baig et al., 2009a,b,c). The underdeveloped countries have been suffering from water contamination due to disordered industrial growth. In many parts of the world, groundwater is contaminated with As (Mandal and Suzuki, 2002; Chowdhury et al., 2000). Arsenic is recognized as carcinogenic (class A), causing skin, lungs, and bladder cancers (NTP, 2002; Yoshida et al., 2004; Hughes, 2002). These effects are

n

Corresponding author. Fax: + 92 22 2771560. E-mail addresses: [email protected] (J. Ahmed Baig), [email protected] (T. Gul Kazi), [email protected] (A. Qadir Shah), [email protected] (H. Imran Afridi), [email protected] (M. Balal Arain), [email protected] (M. Khan Jamali), [email protected] (N. Jalbani). 1 Fax: + 92 22 2771560. 2 Fax: + 92 218141847. 0147-6513/$ - see front matter & 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.ecoenv.2010.01.002

primarily due to the consumption of arsenic-contaminated drinking waters (Kazi et al., 2009). The World Health Organization (WHO) and United State Environmental Protection Agency (US EPA) have revised the maximum contaminant level of As in drinking water as 10 mg/L (WHO, 1996; EPA, 2001). Highly As contaminated (450 mg/L) groundwater has been reported in various parts of the world (Mukherjee and Bhattacharya, 2001; Bhattacharya et al., 2002; Smedley et al., 2002; Focazio et al., 2000; Chowdhury et al., 2000). In Pakistan researchers and agencies (Pakistan Council of Research in Water Resources ‘PCRWR’ and UNICEF) have reported the level of As4100 mg/L in groundwater (Tahir, 2000; Nickson et al., 2007; Farooqi et al., 2007; Kahlown, et al., 2002). Deaths of more than 40 people were reported in Hyderabad city, Pakistan, in 2004 due to contamination of municipal treated water with lake water containing high level of As and other toxic metals (Arain et al., 2008). In general, inorganic As compounds are much more hazardous than organic As compounds. Recently Vega et al., 2001 reported that the toxicity order of arsenicals is as follows: iAs3 + 4organic As3 + 4organic As5 + 4iAs5 + (Arain et al., 2009; Michon et al., 2007). In view of these facts, the speciation of As is very important for the assessment of toxicological and environmental impacts of As. Moreover, it is necessary to develop sensitive and precise

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methods to identify and quantify inorganic As species in water, because of their bioavailability, and physiological and toxicological effects (Zhang et al., 2004; Hirata and Toshimitsu, 2005; Murata et al., 2005; Wang and Mulligan, 2006, Hu et al., 2008). Several analytical techniques have been used for the speciation of As including inductively coupled plasma atomic emission spectrometry (ICP–AES), inductively coupled plasma mass spectrometry (ICP–MS), high performance liquid chromatography (HPLC), electroanalytical techniques and different hyphenated coupled techniques (Wu et al., 2000; Garcia-Sanchea et al., 2001; Ferreira et al., 2002; Jitaru et al., 2004; Coelho et al., 2005; Gregori et al., 2005). However, the direct determination of As species by atomic absorption spectrometry is difficult (Kile et al., 2007). Thus, scientists have made it possible by applying sample pre-treatment procedures including solvent extraction, solid phase extraction, co-precipitation and cloud point extraction, prior to the determination step (Elci et al., 2008; Tuzen et al., 2009; Trung et al., 2001; Gil et al., 2007; Chakravarty et al., 2002; Jitmanee et al., 2005). The co-precipitation method using APDC was frequently applied to determine As3 + in natural water, a selective macromolecule for co-precipitation of inorganic As3 + (Zhang et al., 2007a,b; Big et al., 2009c). The species of the different oxidation state of As was separated at the time of sample pretreatment by solid phase separation in natural water samples by electrothermal atomic absorption spectrometry (Ferguson et al., 2005; Murata et al., 2005; Hu et al., 2008). It was reported in our previous work that the surface water and groundwater of the southern part of Pakistan, which are highly contaminated with As, are frequently used for domestic and agricultural purposes (Arain et al., 2008; Baig et al., 2009b). Thus, the evaluation of As speciation and its correlation with other physico-chemical parameters were very decisive. The aim of the present work is to determine the total arsenic (AsT), total inorganic arsenic (iAs), and arsenic species (As3 + and As5 + ) in surface water and groundwater samples collected during 2007–2008 from Khairpur Mir’s, Pakistan. Mutual relationships of As species with different physico-chemical parameters of water samples were also investigated. The iAs was determined by SPE using TiO2 as the adsorbent, while As3 + was co-precipitated with PbPDC. In the present study, a large data set obtained during the two years was subjected to different multivariate statistical techniques (PCA and CA) to extract information about the similarities or dissimilarities between sampling sites and identification of water quality variables responsible for groundwater contamination. 2. Materials and methods 2.1. Sampling sites The surface water and groundwater samples were collected from 60 sampling sites of different origins, on alternate months in 2007–2008, from eight taluks (sub-districts) of the district Khairpur, situated in the north east of Sindh province of Pakistan with the help of global positioning system (GPS) as shown in Fig. 1. The study areas are situated on the east bank of the Indus River, composed of quaternary alluvial-deltaic sediments derived from Himalayan rocks. The understudied district lies in between Latitude 261 00 –271 450 and Longitude 681 00 –701 150 . It is a semiarid and subtropical continental climate and temperatures ranged from 12 to 50 1C. The district has an area of 15,910 sq km.

915

2 L polyethylene plastic bottles cleaned with metal-free soap, rinsed many times with distilled water and finally soaked in 10% nitric acid for 24 h, and finally rinsed with ultrapure water. All water samples were stored in an insulated cooler containing ice and delivered on the same day to the laboratory and all samples were kept at 4 1C until processing and analysis (Gong et al., 2002). In the field, we measured water temperature, electrical conductivity (EC), total dissolved solids (TDS), salinity and pH. The pH was measured by the pH meter (781-pH meter, Metrohm) and TSDS, EC and salinity by the Conductivity meter (InoLab conduc. 720, Germany). The analyses of As3 + and iAs were accomplished on the same day to avoid risk of transformation of species as reported elsewhere (Gong et al., 2002). Different water quality parameters, their units and methods of analysis are summarized in Table 1. The physico-chemical parameters were determined by standard methods (Tamasi et al., 2004; APHA, 1998). Total alkalinity was determined by acid titration using methyl-orange. Total hardness as Ca2 + hardness was measured by EDTA complexometric titration using Erichromeblack-T and Calcon as indicators at pH 10 and 12, respectively, with an analytical error o 2% (Eaton et al., 1995). The analytical data quality was ensured through careful standardization, procedural blank measurements, and spiked and duplicate samples. The ionic charge balance of each sample was within 7 5%. The laboratory also participated in regular national program on analytical quality control (AQC). Basic statistics of the 2-year data set on surface water and groundwater quality is summarized in Table 2. 2.3. Reagents and materials The ultrapure water obtained from ELGA lab water system (Bucks, UK) was used for experimental work. The extracting solutions were prepared from analytical grade reagents and were checked for possible trace metal contamination. The standard solutions of the above-mentioned elements were prepared on a daily basis by diluting appropriate aliquots of a 1000 mg/L certified standard solution obtained from Fluka Kamica (Buchs, Switzerland) of corresponding metal ions. Ammonium pyrrolidinedithiocarbamate (APDC, Fluka) was used as the chelating agent to form the hydrophobic metal complexes. A 0.1% (w/v) of APDC solution was prepared by dissolving a suitable amount of APDC in DDW. All chemicals and reagents were of analytical grade, Merck (Darmstadt, Germany) and were checked for possible trace metal contamination. Titanium (IV) dioxide (Merck 99%, 0.5 mm) was used as a sorbent. The stock standard solutions of chemical modifiers of Mg(NO3)2, (5000 mg/L) were prepared from Mg(NO3)2 (Merck) and Pd (3000 mg/L) was prepared from Pd 99.99% Aldrich (Milwaukee, WI, USA). Working solution of modifiers was prepared by diluting 10 mL of each stock solution in 100 mL. The certified reference material SRM 1643e (water) was purchased from National Institute of standards and Technology (NIST), Giathersburg, MD, USA. 2.4. Apparatus WIROWKA Laboratoryjna type WE-1, nr-6933 centrifuge (speed range 0–6000 rpm, timer 0–60 min, 220/50 Hz, Mechanika Phecyzyjna, Poland) was used for centrifugation. Mechanical shaker (Gallankamp, England) was used for shaking. The measurement of electrical conductivity (EC) and total dissolved solids (TDS) in water samples was analyzed by using a conductometer (InoLab conduc. 720, Germany); pH was measured by a pH meter (781-pH meter, Metrohm). A global positioning system (iFinder GPS, Lowrance, Mexico) was used for sampling locations. The determination of As in extracts and digests was carried out by means of a double beam Perkin-Elmer atomic absorption spectrometer model 700 (Norwalk, CT, USA) equipped with the graphite furnace HGA-400, pyrocoated graphite tubes with integrated platform and an autosampler AS-800. A single element hollow cathode lamp for As was operated at 7.5 mA with a spectral bandwidth of 0.7 nm. The graphite furnace heating program was set for different steps: drying, ashing, atomization and cleaning as temperature range 1C/(ramp time in s/holding time in s) (80–120/1/30, 300–600/10/20, 2000–2100/0/5, and 2100–2400/0/2), respectively. Portions of both, standard or sample and modifier, were transferred into autosampler cups, and 20 mL [standard or sample volume 10+10 mL modifier {3 mg Pd+5 mg Mg(NO3)2}] was injected into the electrothermal graphite atomizer. 2.5. Determination of total As

2.2. Sampling and treatment The sampling network was designed to cover a wide range of whole district. The samples were collected from 8:00 AM to 1:00 PM during the 2-year study. One hundred and twenty surface water [canals (CS), river (RS) and lake (LS)] composite samples were collected using an open water grab sampler (1.5 L capacity) equipped with a simple pull-ring that allowed for sampling at various water depths of 20–30 cm, from 5 to 7 points of each station randomly. The municipal treated water (MS) and groundwater samples (tube wells (TS) and hand pumps (HS) at depths of 420 and 4 5 m, respectively) were collected simultaneously from each sampling site. To evaluate the water quality, water samples were kept in

For the determination of AsT, 200 mL of surface water (RS, CS, LS and MS) and groundwater (HS and TS) samples were pre-concentrated up to 25 mL at 70 1C on an electric hot plate, filtered, and kept at 4 1C till further analysis. For accuracy, a certified reference sample of water (SRM 1643e) was treated as described in a previous work (Arain et al., 2009; AOAC, 1995). 2.6. Determination of total inorganic arsenic The iAs was determined as slurry by using TiO2 as the adsorbent. The triplicates of each sample (100 mL) of different origins were taken in flasks and complexing

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Fig. 1. Sampling map of study area (Khairpur Mir’s district).

Table 1 Water quality parameters, abbreviations, units and analytical methods as measured during 2007–2008 for the surface water and groundwater. Parameter

Abbreviations

Units

Analytical methods

Salinity pH Electrical conductivity Total dissolved solids Total hardness Calcium hardness (Calcium) Fluoride Chloride Nitrite Nitrate Phosphate Sulphate Potassium Sodium Magnesium Iron Total arsenic Total inorganic arsenic Arsenite Arsenate

Salinity pH EC TDS T-Hard CaCO3 Ca-Hard CaCO3(Ca2 + ) F Cl  NO2 NO3 PO24  SO24  K+ Na + Mg2 + Fe AsT Asi As3 + As5 +

% pH unit S cm  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1 mg L  1

Electrometric pH meter Electrometric Gravimetric Titrimetric Titrimetric Ion chromatography Ion chromatography Ion chromatography Ion chromatography Ion chromatography Ion chromatography FAAS FAAS FAAS GFAAS GFAAS GFAAS GFAAS Estimate

agent TiO2 (20 mg) was added, separately, then the pH 2 was adjusted with 0.5 M HCl (Zhang et al., 2007a). The flasks were placed inside the ultrasonic water bath and were subjected to ultrasonic energy at 35 kHz for 10 min at room temperature. Then the sample solutions were centrifuged to separate the precipitates and slurry was made by adding 5 mL of ultrapure water after being subjected to an ultrasonic bath for 2 min. Then the slurry with the modifier was injected into a graphite tube by an autosampler. The same procedure was applied for blank.

2.8. Estimation of As5 + The concentration of As5 + could not be determined directly by the above analytical procedure, but their concentrations were given by the difference between the iAs and As5 + .

2.9. Statistical evaluation

2.7. Determination of As3 + The triplicates of each sample (100 mL) of different origins of surface water and groundwater were placed in a beaker; pH was adjusted to 3.0 with 1.0 M HCl. Then 1.5 mL of 1% (w/v) APDC (chelating agent) and 1.0 mL of 0.4% (w/v) Pb(NO3)2 solution were added and stirred for 15 min with a mechanical shaker (Zhang et al., 2007a). After that the sample solutions were centrifuged, the residual solid phase was dissolved in 1.0 M HNO3 and diluted to 5.0 mL with deionized water. Then 10 mL of sample solution with 10 mL of modifiers was injected into the electrothermal atomizer (Results are shown in Table 2).

All mathematical and statistical computations were made using Excel 2003 (Microsoft Offices) and STATISTICA 6 (StatSoft, Inc.s). The resulted data of arsenic species and different parameters were subjected to different multivariate techniques (cluster analysis and principal component analysis). The Cluster analysis (CA) technique is an unsupervised classification procedure that involves measuring either the distance or the similarity between objects to be clustered. In hierarchical clustering, clusters are formed sequentially by starting with the most similar pair of objects and forming higher clusters step by step. Hierarchical agglomerative CA was performed on the normalized data set (mean of observations over the whole period) by means of Ward’s method using squared Euclidean distances as a measure of similarity (Jalbani et al., 2007).

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0.5 7.48 1.99 763 21.3 17.6 769 15.8 372 1.01 124 2.01 21.8 0.79 205 2.36 68.3 65.2 25.4 39.8 1.2 8.4 9.82 3350 61.8 45.4 1888 31.1 760 1.60 325 9.22 97.3 5.00 594 3.8 361 352 114 238 0.0 7.0 0.35 153 6.8 4.45 190 6.90 80.0 0.40 93.0 0.43 4.91 0.47 43.0 0.5 9.20 8.74 2.80 5.90 0.8 7.9 2.8 1111 62.0 29.8 745 25.6 508 2.2 431 3.4 40.9 0.6 877 1.80 53.8 51.6 22.7 28.63 0.0 7.3 0.34 347 31.1 14.1 395 6.90 364 1.10 149 1.30 15.5 0.57 478 0.22 6.40 6.06 2.54 3.51 0.0 7.5 0.54 456 46.5 20.6 499 23.2 613 1.8 204 1.73 32.1 0.85 733 0.30 8.30 8.05 3.38 4.66 0.0 7.1 0.12 285 22.7 11.2 291 0.54 282 0.5 120 0.86 9.93 0.47 230 0.14 5.00 4.70 1.90 2.70 1.1 7.4 1.25 390 36 16.5 282 20.2 331 1.30 319 1.24 19.3 0.58 411 0.32 12.0 11.30 5.09 6.22 1.8 8.20 9.22 940 151 73.1 800 61.0 420 2.60 851 8.03 97.6 0.80 951 0.70 18.3 17.75 5.68 12.07 0.5 7.10 0.29 153 6.0 1.3 165 4.6 200 0.40 102 0.43 8.8 0.47 92 0.11 10.0 4.60 1.93 2.35 0.0 7.2 0.40 188 25.9 10.9 211 4.3 248 0.5 119 0.5 6.4 0.59 144 0.17 4.0 3.9 2.3 1.6 0.0 7.5 0.49 188 39.1 13.1 225 5.7 288 0.6 179 0.8 8.4 0.7 201 0.21 5.3 5.2 3.0 2.2 0.1 7.27 0.38 486 21.9 10.8 326 7.3 348 0.9 206 1.4 16.8 0.48 240 0.22 6.1 5.8 2.6 3.3

mg L  1

mS cm  1 mg L  1

– 6.5–8.5 0.40 1000 100 50 200 12 – 1.5 250 3 50 – 250 0.3 10 – – – Salinity pH a EC b TDS b Ca++ b Mg++ b Na + b + K b HCO3 b  F b Cl  b NO2 b NO3 b PO34  b SO24  b Fe c AsT c Asi c As3 + c As5 +

%

0.0 7.1 0.30 369 17.8 8.6 280 4.6 316 0.4 170 0.4 12.6 0.4 179 0.11 4.2 4.1 2.1 2.0

0.1 7.6 0.45 678 26.4 13.2 370 11.4 388 1.1 275 1.9 24.9 0.6 338 0.32 8.0 7.6 3.2 4.4

0.0 7.1 0.34 190 8.20 6.8 191 3.0 179 0.47 135 0.4 5.2 0.52 107 0.14 3.0 2.9 1.3 1.1

Max Min Mean Max Min

n= 120

WHO recommended values

Unit

0.0 7.2 0.8 370 8.6 12.7 490 6.8 282 1.0 152 1.1 12.6 0.5 695 0.30 9.2 8.7 3.1 5.6

1.5 8.5 5.2 1943 137 49.1 976 37.6 782 5.0 900 5.3 74.1 0.7 1120 3.25 163 148 71.2 77.19

Max Min Mean Max Min Max Min Mean Max Min

nS= 120 n= 120

Mean

LS RS CS

The analyzed data of underground water samples were also performed through principal component analysis (PCA). The PCA is designed to transform the original variables into new, uncorrelated variables (axes), called the principal components, which are linear combinations of the original variables. The new axes lie along the directions of maximum variance. PCA provides an objective way of finding indices of this type so that the variation in the data can be accounted for as concisely as possible (Sarbu and Pop, 2005). PC provides information on the most meaningful parameters, which describes a whole data set affording data reduction with minimum loss of original information (Helena et al., 2000; Arain et al., 2009). The principal component (PC) can be expressed as

2.10. Analytical performance

Parameter

Table 2 Ranges of analytical data of the ground and surface water samples in district Khairpur Mir’s, Sindh, Pakistan.

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where z is the component score, a is the component loading, x the measured value of variable, i is the component number, j the sample number and m the total number of variables.

Mean

n= 120 n= 120

n =240

TS(20–100 m) MS

HS(5–20 m)

Mean

J. Ahmed Baig et al. / Ecotoxicology and Environmental Safety 73 (2010) 914–923

zij ¼ ai1 x1j þ ai2 x2j þ ai3 x3j þ . . . þ aim xmj

The calibration and standard addition graphs were obtained for As3 + and total iAs, determined by electrothermal atomic absorption spectrometry. The mean and standard deviation, for n= 6 of the slopes of the standard calibration graph corresponding to As3 + and total iAs, were 0.1767 0.004 and 0.236 7 0.006 mg/L, respectively. The linear range of the calibration graph ranged from the quantification limit up to 20 mg/L for As. The limit of detection (LOD) and limit of quantification (LOQ) were defined as 3 s m  1 and 10 s m  1, respectively, where s is the standard deviation corresponding to 10 blank injections and m is the slope of the calibration graph. The LOD values were 0.05 and 0.22 mg/L and LOQ 0.12 and 0.63 mg/L for As3 + and total iAs, respectively. Due to lake certified reference material for As speciation, the accuracy of the methodologies was performed in replicate three sub-samples of a canal water sample by spiking standard solutions of each species at three concentration levels, as shown in Table 3. The %recoveries for the spiked samples were calculated as follows: % recovery ¼

½Cafterspiking Cbeforespiking  100 Cspiked

The recoveries for As3 + and iAs were generally greater than 98% (Table 3). A good agreement was obtained between the added and measured analyte concentration. These results confirm the validity of the proposed method. The presented method could be applied successfully for the separation, pre-concentration and speciation of trace amounts of inorganic arsenic species in different origins of surface water and groundwater samples. For total Fe and As, the accuracy was checked by using standard reference material SRM 1643e (Table 3). The paired t-test was calculated for n 1=5 degrees of freedom, texp (0.12) and (0.18) for total As and Fe, respectively, were less than the texperiment (2.57) at a confidence interval of 95% (Table 3), indicating no difference between found values and certified values. Potassium, sodium, magnesium and iron were determined by flame atomic absorption spectrophotometer ‘FAAS’ (AAnalyst 700 AAS, PerkinElmer) with limit of detection (LOD) of 14.0, 5.52, 17.7 and 69.2 mg/L, respectively. However, fluoride, chloride, nitrate, nitrite, phosphate and sulphate concentrations were determined by ion chromatography (Metrohm 838 Advanced Sample Processor with chemical suppression) with LOD of 2.2, 1.3, 1.5, 1.4, 0.9 and 2.8 mg/L, respectively. For the validation of ions, ionic balances were calculated (Baig et al., 2009b) and the average ion balance 2.52% with two outliers of 4.8 and  4.2% was established, for which no explanation is impending; the mean balance is 1.2%.

3. Results and discussion 3.1. Physico-chemical parameters In surface water, the temperature showed a very characteristic annual cycle, with higher values during the summer (30–49 1C) and lower values in the winter season (12–28 1C). The results of physico-chemical parameters of surface water (CS, RS, LS and MS) and groundwater (HS and TS) samples are presented in Table 2. The analysis of the collected samples reveals some level of compliance with regulated standards (WHO) for drinking water and the significant deviations were equally noticed. The pH values fluctuated between 7.1 and 8.2 in surface water whereas in groundwater samples it was found in the range of 7.0–8.50 (Table 2), which were fall within the WHO regulated values for drinking water. TDS and EC in surface water (MS, LS, RS and CS) were found to be in the range of 153–940 mg/L and 0.12–9.22 mS/ cm, respectively. The EC values exceeding the WHO guidelines for

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Table 3 The results for tests of addition/recovery for As3 + and total iAs determination in canal water samples (n= 6). Added conc. (mg/l)

Species

Mean7 Std (mg/l)

% recovery

3.50 7 0.60 5.94 7 0.75 8.43 7 0.84 13.4 7 0.65 4.30 7 0.78 6.7 7 0.85 9.27 7 0.82 14.23 71.14

– 99.1 98.6 98.9 – 98.4 98.8 98.5

pffiffiffi Found values x 8 ts= n

% recovery (% RSD)

tExperiment

58.97 1.65 96.87 2.85

97.4 (2.56) 98.6 (1.32)

As3 +

0.00 2.5 5.0 10.0 0.00 2.5 5.0 10.0

iAs

Element

Certified value of SRM 1643e

Validation for total As and Fe 60.457 0.72 AsT Fe 98.17 1.40 tcritical = 2.26 at 95% confidence limit, (n =6)

drinking water (Table 2) was attributed to the high salinity (1.2–1.8 mg/L) and soluble electrolytes in LS water samples (Kazi et al., 2009). The levels of TDS and EC in groundwater were varied from 153 to3350 mg/L and from 0.35 to 9.82 mS/cm, respectively. Alkalinity was found in the range of 179–613 and 282–786 mg/L in surface water and groundwater samples, respectively. In groundwater, the concentrations of Na + , K + , Ca2 + and Mg2 + were found in the range of 190–1888, 6.80–37.6, 6.80–628 and 4.45–49.1 mg/L, respectively. The range of SO24  was observed in groundwater samples as 43–1120 mg/L, while Cl  ranged from 93.0 to 900 mg/L. The average values of NO2 , NO3 and PO34  in groundwater were observed as 3.40, 37.0 and 70.0 mg/L, respectively. However, in surface water, Na + and Ca2 + ranged from 191 to 800 and 6.02–46.5 mg/L, respectively, and Cl  concentration reached up to 851 mg/L. The levels of NO2 and PO34  were observed to be o10 mg/L, while the concentrations of NO3 and SO24  were found in the range of 5.20–97.3 and 92.0–733 mg/L, respectively (Table 2). In all surface water and groundwater samples the F  levels were within the WHO permissible level (1.5 mg/L), whereas in LS and TS, it was observed to be 42.0 mg/L (Table 2). The physical parameters of water (EC and TDS) are significantly correlated with cations and anions (Ca2 + , K + , NO2 , NO3 and PO34  ) in groundwater samples (Table 4), which might be the result of ion exchange and solubilization in the aquifer (Baig et al., 2009b; Lopez et al., 1999). However, in surface water EC and TDS have strong correlation with cations and anions except for F  , Cl  and SO24  (Table 4). In groundwater the Fe concentration was found in the range of 0.3–3.8 mg/L while it was within the WHO recommended level in surface water except in lake water samples (Table 2).

3.2. Total arsenic and iron Cluster analysis (CA) was applied on a data set of total As and Fe content in six sampling origins of surface water and groundwater, to identify spatial similarity and dissimilarity for grouping of sampling origins. The resulted dendrogram (Fig. 2) grouped all the six sampling into three statistically significant clusters, as sampling origin (LS) and (RS, CS, MS) have low mutual dissimilarities as compared to sampling origins (TS, HS), has 14% of total dissimilarity, The dendrogram elucidated the abnormality of the sampling origin LS, which was grouped as cluster 1, receiving As from contaminant effluents from nonpoint sources, i.e., agricultural, industrial and domestic activities

0.12 0.18

(Arain et al., 2008). Besides cluster 1, the mutual dissimilarity among other sampling origins of groundwater made as cluster 2 (RS, CS and MS) and cluster 3 (TS and HS) corresponds to the relatively moderate contaminated, low contaminated and high contaminated regions, respectively. It was concluded that for rapid measurement of As contamination in water, only one site in each cluster may serve as good in spatial assessment of the whole data set. It is evident that the CA technique is helpful in offering reliable classification of different origins of surface water and groundwater in an adequate manner. Thus, the number of sampling origins and cost in the monitoring network will be reduced without losing any significance of the outcome. This approach is consistent with the literature reported research (Kim et al., 2005; Arain et al., 2009). The concentration of total As distributed in groundwater samples of district Khairpur (Pakistan) varied from 5.0 to 361 mg/L, while it ranged from 3.0 to 18.3 mg/L in surface water (Table 2). On the other hand in groundwater, the total Fe concentration was found in the range of 0.3–3.8 mg/L, while it was within the WHO recommended level in all surface water origins except for lake water samples (Table 2). The average concentration of total As in surface water samples was found to be 8.0 mg/L, which is lower than the reported values (Smedley and Kinniburgh, 2002; Baig et al., 2009b). The concentration of total As was found to be higher in LS than the WHO permissible level (10 mg/L), which might be due to the natural processes, i.e., extensive evaporation of water due to high temperature and low rate of rainfall enhanced the amount of salts, trace and toxic elements in the Lake (Arain et al., 2008; Baig et al., 2009b). The other possible factors are frequent use of pesticides and insecticides in agricultural lands as well as use of untreated wastewater sewage sludge as agricultural fertilizer (Arain et al., 2008; Baig et al., 2009b; Arain et al., 2009; Torres and Ishiga, 2003). The average content of total As was found to be 54.2 mg/L in groundwater samples of the understudied areas, higher than the permissible limit of WHO but less than other countries as reported elsewhere (Smedley and Kinniburgh, 2002a; Smedley et al., 2002b). It was also reported that the high total As concentrations were observed in shallow groundwater while low total As concentrations prevail in deep groundwater; our results are consistent with other studies (Focazio et al., 2000; Ravenscroft et al., 2005). It may be due to the non-point sources, i.e., agricultural, industrial and domestic activities (Arain et al., 2008, 2009; Baig et al., 2009b). There are other reports (Kazi et al., 2009; Mukherjee and Bhattacharya, 2001; Bhattacharya et al., 2002;

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Table 4 Linear correlation coefficient matrix for different physico-chemical parameters, Fe and As species. TDS

Ca++

Mg++

Na +

K+

HCO3

F

Cl 

NO2

NO3

PO34 

SO24 

AsT

Asi

As3 +

As5 +

Groundwater (n=480) EC 0.40 TDS 0.40 0.98 ++ 0.37 0.89 Ca ++ 0.70 0.36 Mg 0.42 0.03 Na + 0.40 0.93 K+ HCO3 0.26 0.02 0.58 0.08 F 0.56 0.45 Cl   0.42 0.86 NO2  0.49 0.94 NO3 3 0.57 0.94 PO4 0.35  0.11 SO24  0.29 0.78 AsT Asi  0.26  0.35  0.27  0.36 As3 +  0.19  0.35 As5 + Fe  0.29  0.31

0.86 0.31 0.01 0.87 0.01 0.01 0.39 0.81 0.93 0.93  0.08 0.75  0.38  0.39  0.39  0.33

0.36 0.06 0.84  0.02 0.03 0.41 0.74 0.74 0.78 0.18 0.77  0.36  0.37  0.28  0.38

0.59 0.38 0.32 0.50 0.84 0.41 0.40 0.52 0.20 0.39  0.14  0.14  0.05  0.18

0.10 0.37 0.34 0.55 0.21 0.04 0.15  0.07 0.12  0.25  0.26  0.12  0.32

0.12 0.11 0.46 0.87 0.89 0.86  0.07 0.89  0.23  0.25  0.23  0.22

0.08 0.28 0.18 0.10 0.18  0.09 0.15  0.18  0.17  0.18  0.14

0.48 0.08 0.14 0.21  0.04  0.05 0.11 0.12 0.15 0.09

0.44 0.49 0.57  0.07 0.46  0.22  0.22  0.21  0.19

0.79 0.81  0.15 0.61  0.50  0.51  0.55  0.40

0.97  0.15 0.77  0.29  0.30  0.29  0.27

 0.11 0.73  0.37  0.37  0.35  0.34

0.07  0.03  0.04 0.14  0.16

 0.04  0.06 0.03 0.62

1.00 0.87 0.93

0.86 0.94

0.64

Surface water (n= 300) EC 0.76 TDS 0.69 0.99 0.69 0.67 Ca++ ++ 0.69 0.89 Mg 0.75 0.95 Na + + 0.57 0.75 K 0.47 0.77 HCO3 0.16 0.10 F 0.22 0.07 Cl  NO2 0.63 0.92  0.67 0.94 NO3 3 0.60 0.91 PO4 2 0.32 0.20 SO4 0.55 0.68 AsT 0.54 0.77 Asi 0.56 0.79 As3 + 0.36 0.51 As5 + Fe 0.61 0.85

0.61 0.90 0.94 0.74 0.80 0.09 0.06 0.93 0.94 0.91 0.13 0.65 0.80 0.82 0.55 0.87

0.64 0.66 0.57 0.51 0.39 0.02 0.56 0.60 0.59 0.40 0.51 0.47 0.49 0.21 0.59

0.92 0.75 0.68 0.22 0.11 0.87 0.86 0.89 0.28 0.69 0.80 0.81 0.52 0.88

0.76 0.73 0.16 0.15 0.89 0.92 0.89 0.27 0.70 0.81 0.83 0.53 0.89

0.51 0.40 0.07 0.75 0.81 0.78 0.04 0.95 0.60 0.61 0.37 0.67

0.29 0.03 0.68 0.70 0.65 0.03 0.41 0.70 0.71 0.45 0.77

 0.09  0.02 0.17 0.03 0.02 0.34 0.17 0.17 0.00 0.24

0.21 0.01 0.19 0.16 0.00 0.17 0.17 0.27 0.10

0.89 0.97 0.09 0.61 0.82 0.84 0.64 0.85

0.91 0.18 0.74 0.73 0.76 0.47 0.82

0.21 0.67 0.79 0.81 0.57 0.84

0.10 0.06 0.06  0.05 0.11

0.47 0.48 0.22 0.61

1.00 0.87 0.95

0.86 0.96

0.69

pH

EC

(Dlink/Dmax)*100

Significant at 5% level, r 40.649.

120

3.3. Inorganic arsenic (iAs)

100

Inorganic metal oxides have been applied as solid sorbent, such as aluminum oxide, cobalt oxide and titanium dioxide (TiO2). With its high surface area TiO2 was chosen in pre-treatment procedures for the present study (Zhang et al., 2004). Therefore, it is used for the determination of iAs. The concentration of iAs was found to be 2–7% lower than the total As (Table 2), indicating the lesser availability of organic As in surface water and groundwater (Thirunavukkarasu et al., 2002). The concentrations of iAs in six studied origins were obtained in increasing order as follows: RS oCSoMSoLSoTSoHS (Table 2).

80 60 40 20 0 Lake

River

Canal Municipal Tube well

Hand pump

Fig. 2. Dendrogram showing clustering of different origins of surface water and groundwater according to distribution of As species.

Smedley and Kinniburgh, 2002b; Focazio et al., 2000) where a similar approach has successfully been applied in water quality programs.

3.4. Inorganic arsenic species Arsenic speciation in groundwater is an important factor in determining mobilization, toxicity, and general water chemistry. The redox As species are unstable in natural waters because of the transformation between As3 + and As5 + , due to the organic matrices, redox potential (Eh) and pH (McCleskey et al., 2004). Arsenic is most problematic in the environment because of its relative mobility over a wide range of redox conditions. pH is the most important factor controlling As speciation. Under oxidizing conditions As5 + (H2AsO4 ) is dominant at low pH (opH 6.9),

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Table 5 Analytical results for surface and groundwater samples and comparison with literature values. Samples

Concentration (mg/l) As3 +

As5 +

Asi

AsT

2.30 71.25 2.60 72.50 2.54 7 2.60 5.09 72.36 25.4 7 81.5 22.7 7 93.7

1.60 3.30 3.51 6.22 39.8 28.63

3.90 7 1.20 5.80 7 1.90 6.06 7 1.60 11.30 7 2.80 65.2 7 70.3 51.6 7 62.6

4.07 1.60 6.107 2.15 6.407 1.75 12.07 2.20 68.3 782.5 53.8 793.4

0.54 70.03 nd nd nd nd 0.026 0.82 0.11 70.01 0.32 70.01 nd nd 1.22 7 0.07 0.89 70.06

1.02 nd nd nd nd 0.13 0.55 0.547 0.03 0.657 0.02 nd nd 2.84 70.09 1.207 0.04

1.56 7 0.05 nd nd nd nd nd nd nd nd nd nd nd nd

nd 235 45 72 30.0 0.16 1.37 0.657 0.03 0.977 0.04 143.8 7 176.9 74.4 763.7 nd nd

Our results River water Canal water Municipal water Lake water Hand pump Tube well Literature values River (Gregori et al., 2005) Shallow groundwater (Farooqi et al., 2007) Middle depth groundwater (Farooqi et al., 2007) Deep groundwater (Farooqi et al., 2007) Rain water (Farooqi et al., 2007) Manza-Karabuki River (Sano and Kikawada, 2008) Yu River (Sano and Kikawada, 2008) Tap water (Tuzen et al., 2009) River water (Tuzen et al., 2009) Groundwater (Pandey et al., 2006) Surface water (Pandey et al., 2006) Lake water (Hu et al., 2008) Tap water (Hu et al., 2008) nd= not determined.

while at higher pH, HAsO24  becomes dominant (H3AsO4 and AsO34  may be present in extremely acidic and alkaline conditions, respectively). Under reducing conditions at pH less than about pH 9.2, the uncharged arsenite species H3AsO3 will predominate (Smedley and Kinniburgh, 2002a). To avoid such speculation, the surface water and groundwater samples were delivered on the same sampling day to the laboratory for precise and accurate determination of As3 + and As5 + (Gong et al., 2002). It was incorporated with these evidence and the resulting data are presented in Table 2. The As3 + concentrations were in the ranges 2.1–3.2, 1.3–3.0, 1.93–5.68 and 1.90–3.38 mg/L in water samples of CS, RS, LS and MS, respectively (Table 2). The LS water has a high level of As3 + (Maeda, 1994), which is more toxic and mobile than As5 + (Baig et al., 2009c; Arain et al., 2009; Viraraghavan, et al., 1999). It is because of its ability to form a complex with certain co-enzymes associated with biological activity and dissolved organic water in natural water (Jiang, 2001). Thus, it might be tracheae bronchitis, rhinitis, pharyngitis, shortness of breath, nasal congestions and black foot disease (Liu, 2004; Liu et al., 2006). A strong linear correlation coefficient was observed between the concentrations of inorganic As species and different physico-chemical parameters (TDS, EC, Mg2 + , Na + , NO2 , NO3 , PO34  ) and Fe contents in surface water (Table 4), indicating the possible contamination caused by both natural and anthropogenic sources (Arain et al., 2008; Jamali et al., 2007). The As3 + was observed as 3.1–71.2 and 2.80–114 mg/L in the TS and HS samples, respectively. It was observed that in most of the groundwater (TS and HS) samples, the contamination of As5 + was prominent as compared to As3 + (Table 2). It is reported in the literature that the elevated level of As5 + in groundwater under oxidizing condition is characterized by high contents of SO24  ( 4250 mg/L) and pH 47.5 (Smedley et al., 2002b; Singh, 2006). Such processes are considered to have been responsible for the release of As in oxidizing quaternary sedimentary aquifers in the study area (Smedley et al., 2002b). The concentrations of As3 + and As5 + in groundwater were strongly correlated with Fe concentrations (Table 4). It is reported in the literature that

reductive desorption of As5 + is due to dissolution of iron oxides, and/or changes the mineral structure producing conditions where adsorption is no longer possible (Smedley and Kinniburgh, 2002). Thus, the source of the inorganic As species might be due to the pyretic material or black shale occurring in the underlying geological strata (Thornton and Farago, 1997). The elevated concentrations of As3 + and As5 + were more likely to be found in domestic HS with short screens set in proximity to the upper confine aquifer as compared to deep groundwater (Tables 2 and 5). The obtained results of the present study and the literature reported values (Gregori et al., 2005; Farooqi et al., 2007; Sano and Kikawada, 2008; Tuzen et al., 2009; Pandey et al., 2006) of As species in surface water and groundwater samples are shown in Table 5. Our results for AsT, iAs, As3 + and As5 + were comparable to those reported in the literature for groundwater while a high value of all As species is observed in surface water samples, but the difference is not significant (p 40.05). All this provide evidence that anthropogenic and geological environment plays a key role in the distribution of studied inorganic As species in water bodies of understudy areas and makes a significant contribution to the total intake of inorganic As. The determination of iAs intake was based on the sum of iAs ingested from drinking water, consumed by a normal adult during the 24-h period. In district of Khairpur most of the population of rural area depends on groundwater, and the consumption of drinking water is approximately 4 L containing450 mg iAs/L. Thus, the total consumption of iAs is over 200 mg compared to an estimated daily intake of 12–14 mg iAs from diets of the North American population (Yost et al., 1998). Therefore, chronic exposure to iAs may give rise to several health effects including gastrointestinal and respiratory tract disorders, and also disorders in the skin, liver, cardiovascular system, hematopoietic system, nervous system, etc in the understudied areas. The earliest reports date back to the latter part of the 19th century when the onset of skin effects (including pigmentation changes, hyperkerotosis and skin cancers) was linked to the consumption of As in medicines and drinking water (Crecelius, 1974).

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3.5. Principal component analysis 1

Table 6 Loadings of experimental variables (19) on significant principal components for groundwater of district Khairpur Mir’s. Variables

PC1

PC2

PC3

pH EC TDS Ca2 + Mg2 + Na + K+ HCO3 F Cl  NO2 NO3 PO24  SO4 AsT Asi As3 + As5 + Fe Eigenvalue % Total variance Cumulative %

0.798 0.907 0.952 0.272 0.724 0.898 0.564 0.898 0.799 0.827 0.944 0.933  0.195 0.787  0.483  0.483  0.424  0.499  0.034 9.53 50.0 50.2

0.180 0.091  0.128 0.813 0.508  0.117 0.490 0.353 0.196  0.073 0.234 0.086  0.158  0.006 0.861 0.864 0.865 0.750 0.883 5.06 26.6 76.8

0.233  0.018 0.261  0.128  0.100 0.165  0.005 0.103  0.254  0.289  0.091  0.147 0.919 0.370 0.008 0.009 0.151  0.182 0.379 1.54 8.20 85.0

Asi As3+ AsT As5+

0.75

Fe

Ca2+ 2+ K+ Mg HCO32F- NO pH NO3- EC

F2 (26.64 %)

0.5 0.25 0

SO4ClTDS Na+

PO4-

-0.25 -0.5 -0.75 -1 -1

-0.75

-0.5

-0.25 0 0.25 F1 (50.17 %)

0.5

0.75

1

5 Faiz Ganj

4 3 F2 (26.64 %)

Due to the high concentration of As in groundwater samples of the understudied area, principal component analysis was also applied to the normalized data sets of groundwater (19 variables) separately for 24 different sampling sites (n=240). The first component (PC1) accounted for over 50.17% of the total variance in the data set of the groundwater; in other words, the physical parameters, major cations, anions, Fe and As species in the solution demonstrate similar behavior in the groundwater samples (Table 6). From a macroscopic point of view all the physico-chemical parameters behave similarly, i.e. high concentration of major elements as well as As species in the main body of whole groundwater, except in few cases where the variation in pollution loading has some temporal effects. Strong positive loadings on EC, TDS, NO2 and NO3 were observed, whereas a negative loading on PO34  indicates the role of anthropogenic contamination. The anthropogenic pollution is mainly due to the discharge of fertilizer and pesticides as a regular source throughout the year. However, there is no available data on the use of arsenical pesticides or industrial chemicals in the understudy area. But, it is reported by WWF—Pakistan (2007) that about 5.6 million tonnes of fertilizer and 70 thousand tonnes of pesticides are consumed in the country every year. Their use is increasing annually at a rate of about 6%. Pesticides, mostly insecticides, sprayed on the crops (cotton, wheat, maize, sugarcane and rice) mix with the irrigation water, which leaches through the soil and enters groundwater aquifers (Nickson et al., 2007). The trend obtained was also supported by the analysis of the results on the raw data set. The second component (PC2), explaining 26.6% of the total variance, has strong positive loadings for Fe and As species, thus basically representing the elements of the pollution group. The third component (PC3) of PCA shows that only 8.20% of the total variation has positive loading of PO34  and SO24  . The high values of Fe, TAs, iAs, As3 + , As5 + , major cations and anions in underground water samples are above the permissible limit of WHO values for drinking water (WHO, 2004). The above observation is clearly shown Fig. 3a and b, which shows the characteristics of samples and helps to understand their spatial distribution. It is evident that samples distributed in

Khairpur

2 Kotdigi 1

Gambat

0 -1

Nara Kingri -2 Sobhodaro

Thari Mir Wah

-3 -3

-2

-1

0

1

2

3

4

5

6

7

8

F1 (50.17 %) Fig. 3. Plots of PCA (a) scores for combined data set groundwater samples and (b) scores for distribution of Fe, As species and water quality parameters in subdistrict of Khairpur Mir’s.

the upper right quadrant are more enriched with pH, EC, Ca2 + , Mg2 + , K + , HCO3 , F  , NO2 and NO3 while those in the lower right quadrant are less enriched with TDS, Na + , Cl  and SO24 as shown in Fig. 3a. The samples distributed in the other two quadrants (upper and lower left) are enriched with Fe, As species and PO34  to a lesser extent. The scores plot (PC1 and PC2) for the groundwater samples (Fig. 3b) shows high distribution of Fe, As species and other water quality parameters in groundwater samples of Gambat sub-district as appeared in the upper right quadrant. However, Thari Mirwah sub-district falls in the lower right quadrant indicating the 2nd most polluted sub-district with respect to Fe, As species and other water quality parameters. The upper and lower left quadrants show the mixed distribution in groundwater samples of Khairpur, Faiz Ganj, Kotdigi, Kingri, Nara and Sobhodiro. The high level of As species in water is due to dissolution of arsenic compounds coming from Himalaya through the Indus river and settled down over the years and then introduced into groundwater by geothermal, geo hydrological and bio geo chemical factors (Yost et al., 1998; Smedley et al., 2002b; Singh, 2006). It may be due the As containing insecticides and herbicides used for agriculture purposes and from seepages from hazardous waste sites (Smedley and Kinniburgh, 2002a).

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4. Conclusions The speciation analysis provided more information about toxicity, bioavailability and mobility of different As species in surface water and groundwater samples. In this study, hierarchical CA grouped the sampling sources into three clusters of similar characteristics, reflecting the water quality characteristics. The multivariate techniques (PCA and CA) were successfully applied to the proposed procedures based on solid phase extraction for As3 + while iAs by Pb-PDC co-precipitation and TiO2 based slurry methods. These methodologies offer a simple, rapid, sensitive, inexpensive and non-polluting alternative to other separation/ pre-concentration techniques. The PCA yielded two significant (eigenvalue41) PCs accounting for more than 99.75% of the total variance of the combined data set of six origins of surface water and groundwater. From these results it may convincingly be presumed that the contamination in surface water samples might be due to anthropogenic contamination resulting from soil weathering, agricultural run-off, leaching from solid waste disposal sites, and domestic and industrial wastewater disposal. In undergroundwater samples, the domestic HS (shallow aquifer) were more contaminated with inorganic As species as compared to TS (deep aquifer). This suggested that further studies should be focused on the bio-accumulation of As speciation in aquatic biota and hazards associated with their consumption.

Acknowledgments This work was supported by Higher Education Commission (HEC), Islamabad (Grant no. 20–1246/R&D/9). We are grateful to Young Welfare Society Mughalabad (YWSM) and Indus Resource Center (IRC) Khairpur Mir’s Pakistan for their assistance in sampling. The authors thank two anonymous reviewers for their help in reviewing and helpful advice on the structure of the research article. References AOAC, 1995. Association of official analytical chemists, Official Methods of Analysis 16th Ed. AOAC International, Gaithersburg, Maryland. APHA, 1998. American Public Health Association, Standard Methods for the Examination of Water and Wastewater 20th Ed. APHA, American Water Works Association, and Water Pollution Control Federation, Washington, DC. Arain, M.B., Kazi, T.G., Baig, J.A., Jamali, M.K., Afridi, H.I., Shah, A.Q., Jalbani, N., Sarfraz, R.A., 2009. Determination of arsenic levels in lake water, sediment, and foodstuff from selected area of Sindh, Pakistan: estimation of daily dietary intake. Food Chem. Toxicol. l47, 242–248. Arain, M.B., Kazi, T.G., Jamali, M.K., Jalbani, N., Afridi, H.I., Shah, A., 2008. Total dissolved and bioavailable elements in water and sediment samples and their accumulation in Oreochromis mossambicus of polluted Manchar Lake. Chemosphere 70, 1845–1856. Baig, J.A., Kazi, T.G., Arain, M.B., Shah, A.Q., Afridi, H.I., Kandhro, G.A., Sarfraz, R.A., Jamali, M.K., Khan, S., 2009a. Arsenic fractionation in sediments of different origins using BCR sequential and single extraction methods. J. Hazard. Mater. 167, 745–751. Baig, J.A., Kazi, T.G., Arain, M.B., Afridi, H.I., Kandhro, G.A., Sarfraz, R.A., Jamali, M.K., Shah, A.Q., 2009b. Evaluation of arsenic and other physico-chemical parameters of surface and ground water of Jamshoro, Pakistan. J. Hazard. Mater. 166, 662–669. Baig, J.A., Kazi, T.G., Shah, A.Q., Arain, M.B., Afridi, H.I., Kandhro, G.A., Khan, S., 2009c. Optimization of cloud point extraction and solid phase extraction methods for speciation of arsenic in natural water using multivariate technique. Anal. Chim. Acta 651, 57–63. Bhattacharya, P., Jacks, G., Ahmed, K.M., Khan, A.A., Routh, J., 2002. Arsenic in groundwater of the Bengal delta plain aquifers in Bangladesh. Bull. Environ. Contam. Toxicol. 69, 528–545. Chakravarty, S., Dureja, V., Bhattacharyya, G., Maity, S., Bhattacharjee, S., 2002. Removal of arsenic from groundwater using low cost ferruginous manganese ore. Water Res. 36, 625–632. Chowdhury, U.K., Biswas, B.K., Chowdhury, T.R., Samanta, G., Mandal, B.K., Basu, G.C., Chanda, C.R., Lodh, D., Saha, K.C., Mukherjee, S.K., Roy, S., Kabir, S., Quamruzzaman, Q., Chakraborti, D., 2000. Groundwater arsenic contamination in Bangladesh and West Bengal, India. Environ. Health Perspect. 108, 393–397.

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