Safety Evaluation, Health Risk Assessment and its Source Appointment in Drinking Water

Procured from Water Purification Plants of Faisalabad, Punjab, Pakistan

Saud Khalid, Muhammad Atif Randhawa, Aamir Shehzad, Shahid Masood, Muhammad Shamoon, Nida Kanwal

and Rana Muhammad Adil

Faculty of Food Nutrition and Home Sciences, National Institute of Food Science & Technology, University of

Agriculture, Faisalabad, Pakistan

Corresponding Author: Saud Khalid, Faculty of Food Nutrition and Home Sciences, National Institute of Food

Science & Technology, University of Agriculture, Faisalabad, Pakistan

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ABSTRACT

United Nations Development Program (UNDP) and Pakistan Safe Drinking Water Act (PSDWA) acknowledge

adequate access to potable water as a basic necessity of human beings. To provide ample assess of adequate water to

its inhabitants, Government of Pakistan (GOP) designed a project titled “Clean Drinking Water for All (CDWA)” in

which it was decided to install water purification plants in each Union Council of Pakistan. Current study was

designed to assess the safety status of drinking water of water purification plants of Faisalabad, Punjab, Pakistan.

The study was further planned to identify potential sources of contamination and to direct policy makers for direct

future investments. It concluded that factors like defective/leaked taps, presence of garbage and standing water

beside sampling sites were among the common sources of microbial contamination across the study sites. On the

other hand, 73% of sampling sites were classified as ‘high risk’ for microbial contamination.Among heavy metals,

drinking water was found to be heavily contaminated with Pb and Fe.However, Cd wasn’t detected across the study

site. Based on heavy metals concentration, chronic daily intake (CDI) and hazard quotient (HQ) was calculated. The

values of CDI were in the order of Fe>Cu>Zn>Mn>Pb>Cr>Ni>Zn>Cd.The values of HQ were <1for all heavy

metals in all samples indicating no health risk. Furthermore, multivariate statistical analysis like one-way ANOVA,

inter-metal correlation, cluster analysis and principal component analysis results revealed that anthropogenic

pollution and geochemical background were the major sources of heavy metals contamination in drinking water.

Key words: Drinking water, heavy metals, microbial contamination, risk assessment, Pakistan

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INTRODUCTION

Water is vital requisite but it has to be potable to allow secure consumption. Ground water and surface water are the

two main sources of drinking water. Raw water obtained through these two sources is prone to wide variety of

pollutants. These pollutants threaten all forms of life, in general. Such pollutants can be countered in two ways;

either by enhancing the efficiency of water treatment plants or by improving the quality status of existing water

purification plants. The first path is more technical and is opted by research institutes and universities, for instance.

The second path is strategic one as it requires input of policy makers and allocation of capital by the state.

Regardless of the approach undertaken, the status of water quality should be monitored periodically in order to

protect public health.

Majority of population in Pakistan is exposed to polluted water which may cause a multitude of water borne

diseases. WWF (2007) reported that drinking water supplied by municipalities to the public in Pakistan is mostly

contaminated with pathogens or toxic chemicals. Adding to this, Bhutta et al.(2002) reported that drinking water in

densely populated areas of Pakistan like Karachi, Lahore, Rawalpindi, Peshawar, Faisalabad, Qasur, Sialkot and

Gujrat cannot be recommended for human consumption due to contamination caused by various anthropogenic

activities. Main cause of prevalence of water borne diseases in Pakistan includes contamination of drinking water

with industrial wastes as well as municipal sewage and lack of water disinfection practices cum quality monitoring

of treatment plants (Hashmi et al., 2009). A study conducted in 23 major cities of Pakistan concluded that water

quality of 84-89% of water sources throughout the country is below the recommended standard for drinking purpose

(PCRWR, 2008). Due to lack of documentation practices and maintenance of records in hospitals, it is very difficult

to quantify exactly the water borne diseases in Pakistan (Aziz, 2005). The diseases related to consumption of unsafe

drinking water includes hepatitis, cholera, dysentery, cryptosporidiosis, giardiasis, and typhoid. Adding to this, all of

these diseases accounts for one third of all deaths in Pakistan (WB-SCEA, 2006). The situation gets worse with

water-borne diseases like hepatitis, typhoid fever, gastroenteritis, dysentery, cholera, E. coli diarrhea, rotavirus

diarrhea, malaria, giardiasis and intestinal worms every year with the onset of monsoon rains in summer (July to

August) due to lack of control measures and effective prevention (Qasim, 2008).

Access to safe and clean drinking water is one of the basic necessities of human beings. According to millennium

development goals of United Nations Industrial Development Organization (UNIDO), half of world population

should have sustainable access to safe drinking water by 2015 (UNDP, 2000). Government of Pakistan has showed

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its commitment to provide adequate and sustainable access of safe drinking water to people of Pakistan and to meet

millennium development goals of UNDP (GOP, 2005). As per national drinking water policy, adequate access to

safe and clean drinking water is a basic right of every citizen of Pakistan (GOP, 2009). To meet these targets, a

program entitled “Clean Drinking Water for All (CDWA)” was designed by Ministry of Environment, Government

of Pakistan under its Medium Term Development Framework. The aim of program was to notably improve water

and sanitation coverage and quality. Under this project, it was decided to install water purification plants of different

capacities (500/1000/2000 gallons/hour) in each Union Council of Pakistan. It was estimated that one purification

plant would serve 2-20% of each Union Council’s population, which on average have 20,000 inhabitants. The

program generated criticism later-on. It was argued that due to lack of communication and ill planning, the program

has failed to achieve its objectives of improving water quality status of the country by installing water treatment

facilities, country-wide. Under CDWA project, it was decided to install 6,584 water treatment plants all across

Pakistan. However, only 1,139 water purification plants are installed so far all across Pakistan (Anonymous, 2011).

Keeping in view the generated criticism, current study is designed to assess the status of existing water purification

plants of Faisalabad, Punjab, Pakistan. It is feared that level of heavy metals in drinking water might reach alarming

level owing to industrial significance of the study area. Therefore, the study aims at determining concentration of

heavy metals in drinking water and its potential health risk assessment. Multivariate statistical analysis and risk

priority matrix is used to identify sources of heavy metals and microbial contamination respectively, as well as to

identify priorities for policy makers for direct future investments in water purification plants of Faisalabad, Punjab,

Pakistan.

MATERIALS AND METHODS

Study area description

Safety assessment of water purification plants covers the inspection of those plants that are installed by Government

of Pakistan for the well being of inhabitants of Faisalabad. Formerly known as Layellpur, it is the third largest city

of Pakistan and is the second largest city of province Punjab (Fig. 1). Owing to its industrial importance, it is also

known as Manchester of Pakistan. Faisalabad was acknowledged as City District in 2005 and was divided into 8

autonomous twons; including Lyallpur Town, Madina Town, Iqbal Town, Jinnah Town, Chak Jhumrah Town,

Jaranwala Town, Samundri Town and Tandlianwala Town. The total number of water purification plants installed

by government in Faisalabad are 37 out of which, only 21 are functional. The number of functional water

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purification plants in Jinnah Town, Madina Town, Iqbal Town and Layellpur Town are 11, 6, 2 and 1 respectively.

There are two water purification plants installed in Chak Jhumra Town, both of which are non-functional. Moreover,

no water purification plant is installed in Samundri Town, Jaranwala Town and Tandlianwala Town.

Survey design

Safety assessment of water purification plants covers the inspection of those plants that are installed by Government

of Pakistan for the well being of inhabitants of Faisalabad. While procuring samples, care is taken to analyze no less

than 50% of functional water purification plants from each Town of Faisalabad. For this purpose, 6 samples were

procured from Jinnah Town, 3 from Madina Town and 1 each from Layellpur-Town as-well-as from Iqbal- Town.

Each sample was encoded using two English letters (WS- stands for Water Sample) and a third numeric letter. The

numeric letter is specific for each water purification plant. Number of water samples that were procured from each

town are mentioned in Table 1.

Sampling plan

Water samples for physicochemical analysis were collected in PET bottles of 750 mL capacities. Un-rusted taps

were selected for collection of water samples. These taps were properly cleaned and allowed to flow for a few

minutes before collecting the samples. Before collecting the samples, the bottles were washed properly and rinsed

thoroughly several times first with water and then with distilled water.

Sanitary inspection risk survey (SIRS)

A questionnaire was adopted, by following WHO guidelines (WHO, 2012), to carry-out sanitary inspection risk

survey of selected water purification plants. The questionnaire examines physical well being of each water

purification plant. It asks 10 questions; the answer to each question may either be “yes” or “no”. Answering the

question with ‘yes’ shows the presence of risk and vice versa. Higher number of positive answers shows higher risk.

This qualitative data was then converted into quantitative one, based on the findings of risk score. It also enlightens

how to summarize the risk score from the findings of sanitary inspection risk survey. The findings of SIRS are

beneficial in pointing out the sources of microbial contamination in procured drinking water samples.

Physico-chemical and microbial analysis

Total coliform count

Totalcoliform in the drinking water samples were counted by using Galaxy, 230 colony counter usingMost Probable

Number method (MPN) as proposed by AOAC (2005).

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Water characteristics

By using digital pH meter (Inolab WTW Series 720), benchtop meter (CON-700, EUTECH) and portable

turbidimeter (TN-100/T-100, EUTECH); the pH, electrical conductivity (EC), total dissolved solids (TDS) and

turbidity were determined following APHA guidelines (APHA, 1992).

Toxic metals

Procured water samples were digested initially (Prapaisiri et al., 1988). The digested samples were then passed

through Atomic Absorption Spectrophotometer (Hitachi Polarized Zeeman AAS, Z-8200, Japan) following the

conditions as described by Horwitz, 2000. Following heavy metals were analyzed; Cadmium (Cd), Copper (Cu),

Chromium (Cr), Iron (Fe), Manganese (Mn), Nickel (Ni), Lead (Pb) and Zinc (Zn).Calibrated standards were

prepared from the commercially available stock solution (Applichem®) in the form of an aqueous solution (1000

ppm). Highly purified de-ionized water was used for the preparation of working standards. All the glass apparatus

used throughout the process of analytical work were immersed in 8N HNO3 overnight and washed with several

changes of de-ionized water prior to use.

Human health risk assessment

Chronic daily intake (CDI) indices

The CDI through water ingestion was calculated according to the modified equation from (USEPA, 2005).

CDI = (C x DI) / BW

where, C, DI and BW represent the concentration of heavy metals in water (mg/L), average daily intake rate (2

L/day) and body weight (72 kg), respectively (Muhammad et al., 2010).

Hazard quotient (HQ) indices

The hazard quotient for non-carcinogenic risk can be calculated by the following equation (USEPA, 2005):

HQ = CDI / RfD

where, according to USEPA database the oral toxicity reference dose value (RfD) is 5.0E−04, 1.5, 3.7E−02,

1.4E−01, 2.0E−02, 3.6E−02, 3.0E−01 mg/kg-day for Cd, Cr, Cu, Mn, Ni, Pb and Zn, respectively (USEPA, 2005).

The exposed population is assumed to be safe when HQ<1 (Khan et al., 2008).

Source appointment and statistical analysis

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Descriptive statistics is calculated by using Excel 2007 (Microsoft Office). The univariate and multivariate statistical

analysis such as one-way ANOVA procedure, inter-metal correlation, cluster analysis (CA) and principle component

analysis (PCA) are performed by using the SPSS software ver. 17.

RESULTS AND DISCUSSION

Sanitary inspection risk survey (SIRS)

SIRS is a component of water safety plan for community management as it provides an overview of likely threats to

water quality and is an effective tool for rapid assessment of drinking water quality (WHO, 2012). The findings of

sanitary inspection risk survey (Table 2) highlights that almost all the taps installed in government owned water

purification plants of Faisalabad are defective. Moreover, roads and/or garbage accompanies all of the water

purification plants of Faisalabad. Both of these factors are regarded as a highest source of contamination in these

purification plants. It is further noted that in 90% of water purification plants of Faisalabad, there is faulty drainage

channel. Such faulty drainage channels allow water to collect around the sampling sites. When water collects in the

surroundings areas, garbage accumulates while flies gather across the sampling sites. The presence of garbage and

flies are the potential sources of contamination in drinking water across the sampling sites. Remaining factors

including leaked pipes across sampling sites, defective concrete floor, inadequately sealed walls, access of animals

to sampling sites due to defective construction and the presence of latrines beside water purification plants; holds

negligible importance. Faulty tap as well as garbage and/or roads beside water purification plants are regarded as

serious risk in each town of Faisalabad. However, leaked pipes, accumulation of water and the presence of flies

around the sampling site are town specific problems. Leaking pipeis regarded as risk factor in Layellpur Town only

where it appeared as risk factor in all of the assessed water purification plants. Collection of water around the

sampling sites is emerged as a risk factor in Jinnah Town as well as Iqbal Town. The presence of flies around the

sampling sites is problem specific to the locality of Madina Town and Jinnah Town. Accumulation of water around

the sampling sites is the most serious problem and it leads to presence of other risk factors in the sampling sites. For

example, accumulation of water is always accompanied with garbage accumulation as well as presence of flies

around the sampling sites as it is evident from the sanitary inspection of Jinnah Town.

Physico-chemical and microbial analysis

Summary of physico-chemical and microbial parameters is summarized in Table 3a. The compliance for these

parameters with WHO standards on drinking water quality is given in Table 3b.The detailed interpretation of these

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parameters is given below:

Total coliform count

The results of present study indicate that coliform is present in more than 80% of procured water samples. The order

of coliform count per 100mL is as following; Iqbal-town(13)>Jinnah-town(11)>Madin-town(10.7)>Layellpur-

town(0).Coliform isn’t detected only in 2 samples, one sample each from Jinnah town as-well-as from Layellpur

town. Coliform was detected in all the remaining samples.

Water characteristics

pH

The pH of Jinnah town ranged from 6.7-7.9 with a mean value of 7.4. Range of pH values in Layellpur town, Iqbal

town and Madina town is 6.8-7.0, 7.3-7.5 and 6.6-7.3, respectively. Mean value for pH in these towns is 6.9, 7.4 and

7, respectively. Highest pH is observed in Jinnah town and Iqbal town (7.4), while the lowest pH is observed in

Layellpur town (6.9). However, pH in all towns of Faisalabad is in compliance with recommended value of pH as

proposed by WHO (1998).

Total dissolved solids (TDS)

Range of total dissolved solids in water samples procured from Jinnah town, Layellpur town, Madina town and Iqbal

town is 7.1-131, 150-160, 5.6-15.6 and 7.3-159 ppm, with the mean value of 60.5, 155, 10.6 and 62.1 ppm,

respectively. Observed value of TDS observed in water sample is in following order; Layellpur-town>Madina-

town>Jinnah-town>Iqbal-town. However, all the procured water samples showed cent percent compliance with

recommended value of TDS as proposed by WHO(1998).

Electrical conductance (EC)

Highest electrical conductance is observed in Layellpur town (316 µS/cm) while the lowest is observed in Madina

town (1.52 µS/cm). The order of electrical conductance in terms of its mean values is as following; Layellpur-

town(314µS/cm)>Jinnah-town(116.97µS/cm)>Madina-town(105.7µS/cm)>Iqbal-town(20.3µS/cm). Out of total

procured samples, 73% samples are in compliance with recommended value of EC as set by WHO(1998).

Turbidity

Observed range of turbidity is 0.08-0.45, 0.0-0.1, 0.37-0.47 and 0.21-0.77 NTU for Jinnah town, Layellpur town,

Iqbal town and Madina town, respectively. The order of turbidity in terms of its mean value is as following; Madina-

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town(0.43NTU)>Iqbal-town(0.42NTU)>Jinnah-town(0.25NTU)>Layellpur-town(0.05NTU). Turbidity value of all

the samples lie within the recommended values of WHO & Pak-EPA standard on drinking water quality.

Toxic metals

Cadmium (Cd)

Toxicity of Cadmium is of great concern to humans. However, Cadmium wasn’t detected in any of the procured

sample in current investigation. Mahmood & Maqbool in 2006 procured ground water samples from Chakera,

Faisalabad and found none of the sample to be contaminated with Cadmium. Similarly, Ullah et al., (2009) procured

ground water from different spots of Sialkot, Punjab and found none of the sample to be contaminated with

Cadmium.

Chromium (Cr)

In current investigation, Chromium is detected in all of the procured water samples. Only, 45% of the samples

showed concentration of Chromium within permissible limits as set by WHO and Pak-EPA. Highest Cr is observed

in Madina town i.e. 0.08 ppm. The order of Chromium detection is in following order; Layellpur-

town(0.053ppm)>Jinnah-town(0.05ppm)>Iqbal-town(0.04ppm)>Madina-town(0.038ppm).

Copper (Cu)

In current investigation, both highest and lowest concentration of Cu is observed in Iqbal town i.e. 0.58 and 0.1 ppm,

respectively. The order of Copper detection in study area is Jinnah-town(0.37ppm)>Madina-

town(0.30ppm)>Layellpur-town(0.27ppm)>Iqbal-town(0.26ppm). However, all the samples are in compliance with

recommended value of Copper as set by WHO and Pak-EPA.

Iron (Fe)

Highest concentration of Iron is observed in Jinnah town (1.64 ppm) while the lowest is observed in Madina town

(0.80 ppm). The order of iron concentration in study area is as follow; Layellpur-town(1.23ppm)>Jinnah-

town(1.20ppm)>Madina-town(1.12ppm)>Iqbal-town(1.05ppm).

Manganese (Mn)

Mean values of Manganese observed in current investigation are 0.083, 0.103, 0.06 and 0.07 ppm, for Jinnah town,

Layellpur town, Iqbal town and Madina town, respectively. Highest concentration of Manganese is observed in a

sample of Layellpur town (0.16 ppm). However, all the samples showed cent percent compliance with

recommended value for Mn in drinking water as set by WHO (1998).

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Nickel (Ni)

Highest concentration of Nickel is observed in Madina town (0.1 ppm). The order of Nickel concentration in study

area is as follow; Madina-town(0.044ppm)>Layellpur-town(0.037ppm)>Jinnah-town(0.030ppm)>Iqbal-

town(0.020ppm). Only, 36.4% samples are in compliance with WHO-standards on drinking water quality. Highest

compliance of Nickel concentration with WHO and/or Pak-EPA standard on drinking water is shown by samples

procured from Iqbal town (100%) while none of the procured sample from Layellpur town (0%) is found to be in

compliance with its respective standard.

Lead (Pb)

In current investigation, none of the procured sample is found to be in compliance with recommended concentration

of Lead in drinking water. Both highest as well as lowest concentration of Leadis observed in samples of Jinnah

town i.e. 0.14 and 0.01 ppm, respectively. In terms of mean concentration of Lead, highest concentration is observed

in Layellpur town (0.073 ppm) while the lowest is observed in Madina town as well as Iqbal town (0.067 ppm).

Zinc (Zn)

It is an essential element required by our body. However, if consumed in excess, it may compromise human health

like other trace metals. All the procured samples showed cent percent compliance with national and/or international

standards. Highest concentration of Zinc is observed in Jinnah town i.e. 0.49 ppm, while the lowest is observed in

Jinnah town as well as Layellpur town (0.16 ppm). The order of Zinc concentration in terms of its mean value is as

following; Iqbal-town(0.323ppm)>Jinnah-town(0.279ppm)>Madina-town(0.248ppm)>Layellpur-town(0.227ppm).

Human health risk assessment

Chronic daily intake (CDI) indices

Table 4 summarizes the calculated CDI values for consumption of drinking water. The results suggest that in Jinnah

town, where people consumed drinking water contaminated with heavy metals, their CDI values is in following

range; -2.80E-4-2.5E-3, 1.4E-3-1.39E-2, 8.30E-3-4.56E-2, 1.40E-3-3.30E-3, -3.0E-4-2.20E-3, 2.78E-4-3.89E-3 and

4.40E-3-1.36E-2 mg/Kg-day for Chromium, Copper, Iron, Manganese, Nickel, Lead and Zinc, respectively.

Similarly, the people in Layellpur town who consumed drinking water contaminated with heavy metals, their

calculated CDI values is in following range; 8.0E-4-1.90E-3, 4.20E-3-1.33E-2, 3.19E-2-3.78E-2, 1.90E-3-4.40E-3,

5.60E-4-1.67E-3, 1.67E-3-2.22E-3 and 4.40E-3-7.80E-3 mg/Kg-day for Chromium, Copper, Iron, Manganese,

Nickel, Lead and Zinc, respectively. In Iqbal town, the calculated CDI values for people who consumed drinking

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water contaminated with heavy metals is in following range; 8.0E-4-1.4E-3, 2.80E-3-1.61E-2, 2.44E-2-3.33E-2,

1.40E-3-1.90E-3, -3.0E-4-1.11E-3, 1.39E-3-2.22E-3 and 5.30E-3-1.14E-2 mg/Kg-day for Chromium, Copper, Iron,

Manganese, Nickel, Lead and Zinc, respectively. Similarly, the calculated CDI values for Madina town is in

following range; 0.0-2.20E-3, 2.20E-3-1.36E-2, 2.22E-2-4.47E-2, 1.40E-3-3.30E-3, 0.00-2.78E-3, 8.33E-4-3.61E-3

and 4.70E-3-9.40E-3 mg/Kg-day for Chromium, Copper, Iron, Manganese, Nickel, Lead and Zinc, respectively.

Therefore, CDI indices for heavy metals in the study area isdetected in the order of

Iron>Copper>Zinc>Manganese>Lead>Chromium>Nickel.

Hazard quotient (HQ) indices

Table 5 summarizes the hazard quotient indices of heavy metals through intake of drinking water in the study area.

In Jinnah town, the mean hazard quotient index values for Cadmium, Chromium, Copper, Manganese, Nickel, Lead

and Zinc is 9.50E-4, 2.58E-1, 1.65E-2, 4.17E-2, 5.53E-2 and 2.58E-2, respectively. The mean hazard quotient index

values for Cadmium, Chromium, Copper, Manganese, Nickel, Lead and Zinc at Layellpur town is 9.90E-4, 2.03E-1,

2.05E-2, 5.09E-2, 5.66E-2, 2.09E-2, and 7.40E-4, 1.98E-1, 1.19E-2, 2.78E-2, 5.14E-2, 2.99E-2 for Iqbal town,

respectively. Similarly, the mean hazard quotient index values at Madina town for Cadmium, Chromium, Copper,

Manganese, Nickel, Lead and Zinc for drinking water samples is 7.0E-4, 2.28E-1, 1.37E-2, 6.17E-2, 5.14E-2 and

2.29E-2, respectively. Therefore, the hazard quotient indices of heavy metals in the study area is found to be in the

order of Copper>Lead>Nickel>Zinc>Manganese>Chromium>Cadmium. The hazard quotient indices for all heavy

metals suggest no risk to local population when compared with USEPA, 2005.

Source appointment

Source appointment of microbial contamination

Risk priority matrix merges sanitary inspection data with coliform count and provides useful information on possible

sources of microbial contamination. It classifies the risks into different categories namely very high risk, high risk,

intermediate risk and low risk. Generally, improved water sources that are classified as “high” or “very high” in the

risk-priority categories should receive higher attention in terms of implementing remedial interventions than

technologies classified as “low” or “intermediate”. Table 6a and 6b concludes that about ¾ (73%) of water sites

included in the study are at high risk.However, water sites of Layellpur town aren’t in this category. 9% of water

sites are at low risk with all of them belongs to Jinnah town while 18% sites are at intermediate risk. No water

sampling site is at“very high risk” priority matrix. Results suggest that post-filtration microbial contamination across

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water sites being at high risk can be controlled by replacing the defective taps with newer ones as-well-as by

cleaning the garbage present across sampling sites.

Source appointment of selected heavy metals

One-way ANOVA procedure

Table 7b summarizes the statistical comparison for different sites using one way ANOVA procedure. It shows

significant statistical difference (P=0.000) which indicates that different sites are contributing differently to the

mean metal concentration in the water. The contribution of different sampling locations is also different within a

selected site. The heavy metals are showing different significant variation against the selected sites (Table 7a and

Figure 2). For example, in Madina town, the concentration of Nickel (P=0.0147) is significantly higher compared to

Iqbal town. Similarly, the concentration of Zinc is significantly higher (P=0.0165) in Iqbal town compared to

Layellpur town. Cadmium isn’t detected across the study area. Moreover, no significant variation is found for

Chromium (P=0.9067), Copper (0.4183), Iron (P=0.5906), Manganese (P=0.4893) and Lead (P=0.6161) in water

samples collected from different sites across the study area.

Inter-metal relationship and cluster analysis

The inter-metals relationship provides interesting information on metal sources and pathways. Table 8 summarizes

the inter-metal correlation co-efficient for water samples procured across the study area. Following heavy metals

showed significant positive correlation with each other; Cr-Fe (r=0.367), Cr-Mn (r=0.349), Fe-Mn (r=0.393) and Fe-

Zn (r=0.347). On the other hand, the correlation between Lead and Zinc is highly significant (r=0.475). Moreover,

pH is also positively correlated with Zinc at a very high level of significance (r=0.486) while EC-Ni (r=-0.346) and

Turbidity-Mn (r=-0.375) are negatively correlated with each other. The observed inter-metal relationship is further

supported by Cluster-Analysis (CA) dendogram (Figure 3). As a result from the above calculated values, some

metals do have strong significant correlation to form primary cluster pairs. The primary clusters are found for Pb-Zn,

Fe-Mn, Cr-Fe and Cr-Mn. Two clusters are observed for selected heavy metals in procured water samples.

Principle component analysis (PCA)

For qualitative evaluation of clustering behavior, PCA with varimax normalization (PCA-V) is applied for drinking

water samples and the results are revealed in Table 9. PCA of data indicates their association and grouping with

three factors in drinking water. The total variance for three factors in drinking water is 69.611%. Factor-1

contributed 28.163% to the total variance with a high loading on Chromium (r=0.780), Copper (r=0.616) and

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Manganese (r=0.648). Chromium level could have been influenced by local mining of chromite ores across Jinnah

town and Iqbal town. The other metals (Cu & Mn) are found in safe limits in drinking water samples. It means

factor-1 represents both anthropogenic pollution & geochemical background as a source of heavy metals

contamination. Factor-2 contributed 26.032% to the total variance with a high loading on Lead (r=0.776), Iron

(r=0.732) and Zinc (r=0.724). Pb, Zn and Fe levels indicated the likely influence from local Pb–Zn sulfide ores

mining in Iqbal town and from weathering of massive sulfide deposits in Layellpur town. It means that factor-2 is

also contributed by anthropogenic pollution & geochemical background. Factor-3 contributed 15.416% to the total

variance with a high loading on Nickel (r=0.904). Nickel could have been influenced by weathering of ultramafic

rocks across Madina town. It shows that factor-3 is contributed by geochemical background only.

CONCLUSION

Due to lack of maintenance and ill planning condition, of water purification plants is deteriorating day by day. Out

of proposed 103 water purification plants, only 37 are installed in Faisalabad, of which only 21 are functional. pH,

total dissolved solids and electrical conductivity is in compliance with national (Pak-EPA) as well as international

(WHO) standards on drinking water quality.However, 27.3% samples aren’t in compliance with recommended value

for turbidity in drinking water. On the other hand, coliform is detected in 81.8% samples indicating poor hygienic

condition prevailed across the study sites. Findings of sanitary inspection highlights that leaked/defective taps,

presence of garbage and standing water across sampling sites are among the common sources of microbial

contamination in drinking water. Moreover, risk priority matrix classified 73% of sampling sites as ‘high risk’ for

microbial contamination. Regarding heavy metals, drinking water is found to be heavily contaminated with Iron and

Lead however, Cadmium isn’t detected in any of the procured water sample. Compliance of heavy metals with

WHO standards on drinking water quality is 100%, 45.4%, 100%, 0%, 100%, 36.4%, 0% and 100% for Cd, Cr, Cu,

Fe, Mn, Ni, Pb and Zn, respectively. The values of CDI are in the order of Fe>Cu>Zn>Mn>Pb>Cr>Ni>Zn. The

values of HQ are <1 for all heavy metals in all samples indicating no health risk. The one-way ANOVA results

indicate that heavy metals contribution of different sites is significant (P<0.05), while Jinnah town is contributing

high level of contamination. Inter-metals correlation of selected heavy metals in drinking water shows significant

positive correlation between Pb-Zn, Fe-Mn, Cr-Fe and Cr-Mn which is also supported by CA. The PCA revealed

that both geogenic background and anthropogenic pollution are responsible for the possible contamination of

various heavy metals in drinking water of Jinnah town, Iqbal town, Layellpur town and Madina town. The statistical

Page 13 of 30

analysis provides powerful basis for identification and classification of various sources of contamination and the

correlation between heavy metals in drinking water. Finally, it is concluded that drinking water in the study area

does not pose chronic health risk. But as some of the selected heavy metals exceeded their safe levels therefore, it is

suggested that, the water from contaminated sites should not be used for drinking purpose. Moreover, Government

of Pakistan should take necessary action tominimize heavy metals contamination and to improve hygienic status of

water purification plants of Faisalabad, Punjab, Pakistan.

ACKNOWLEDGEMENT

We acknowledge the valuable contribution of Mr. Abdul Qudoos and Ms. Zil-e-Huma on equipment’s

standardization and data analysis, respectively. Mr. Abdul Qudoos is research officer at Central Hi-tech Laboratory,

University of Agriculture, Faisalabad. Ms. Zil-e-Huma is visiting lecturer at International Islamic University,

Islamabad.

REFERENCES

Anonymous, 2011. Article in-press: Clean drinking water goes down the drain [Online]. Available at

http://www.pakistantoday.com.pk/2011/02/14/news/national/clean-drinking-water-project-goes-down-the-

drain/#sthash.tb3jm1xY.JXE4q2hp.dpuf. (Verified 28 Sept. 2013).

AOAC (Association of Official Analytical Chemists), 2005. Detection and confirmed quantitation of Coliforms and

E. coli in foods. J. AOAC Int. 88:1318.

APHA (American Public Health Association), 1992. Standards methods for the examination of water and waste

water. 18th Ed. American Public Health Association; Washington DC, USA.

Bhutta, M.N., Ramzan, M., Hafeez, C.A., 2006. Ground water quality and availability in Pakistan. Biochem. 282,

22.

GOP (Government of Pakistan), 2005. National environment policy, Ministry of Environment, Government of

Pakistan [Online]. Available at http://www.environment.gov.pk/nep/policy.pdf, (Verified 17 Mar. 2013).

GOP (Government of Pakistan). 2009. National drinking water policy, Ministry of Environment, Government of

Pakistan [Online]. Available at http://epd.punjab.gov.pk/system/files/National_Drinking_Water_Policy.pdf,

(Verified 17 Mar. 2013).

Hashmi, I., Farooq, S., Qaiser, S., 2009. Chlorination and water quality monitoring within a public drinking water

supply in Rawalpindi Cantt (Westridge and Tench) area, Pakistan. Environ. Monit. Assess. 158, 393–403.

Page 14 of 30

Horwitz, W., 2000. Determination of lead, cadmium, copper, iron, magnesium, zinc in foods. (Method No. 9.1.09).

Official Method of Analysis of AOAC International. 17th Edition. AOAC International, Maryland, USA.

Khan, S., Cao, Q., Zheng, Y.M., Huang, Y.Z., Zhu, Y.G., 2008. Health risks of heavy metals in contaminated soils

and food crops irrigated with wastewater in Beijing China. Environ. Pollut. 152, 686–692.

Mahmood, S., Maqbool, A., 2006. Impacts of wastewater irrigation on water quality and on the health of local

community in Faisalabad. Pak. J. Water Res. 10, 19–22.

Muhammad, S., Shah, M.T., Khan, S., 2010. Arsenic health risk assessment in drinking water and source

apportionment using multivariate statistical techniques in Kohistan region, northern Pakistan. Food Chem.

Toxicol. 48, 2855–2864.

PCRWR (Pakistan Council for Research on Water Resources), 2008. Annual Report 2005–06, part 2 [Online].

Pakistan Council for Research in Water Resources, Islamabad, Pakistan. Available at

http://www.pcrwr.gov.pk/Annual%20Reports/New%20Annual%20Repot%202005-06_2.pdf, (Verified 12

May, 2013).

Prapaisri, P.S., Kongkachuichai, R., Prapasri, P., 1988. Acid digestion versus dry ashing for mineral analysis of

foods. J. Nutrition Assoc. Thailand. 22, 279-296.

Qasim, M., 2008. Twin cities: water-borne diseases on the rise. The NEWS, Sunday, 20 July, 2008, Pakistan.

UNDP (United Nations Development Program). 2000. Target 7, sub-target 10 of millennium development goals,

United Nations Development Program [Online]. Available at

http://www.undp.org/content/undp/en/home/mdgoverview/, (Verified 17 Mar. 2013).

US EPA (United States Environmental Protection Agency). 1992. Guidelines for Exposure Assessment, EPA/600/Z-

92/001, Risk Assessment Forum, Washington, DC.

US EPA (United States Environmental Protection Agency). 2005. Guidelines for Carcinogen Risk Assessment,

EPA/630/P-03/001F, Risk Assessment Forum, Washington, DC.

WB-SCEA (World Bank – Strategic Control Environmental Assessment). 2006. Pakistan Strategic Country

Environmental Assessment. Main report: Report no. 36946-PK World Bank. p. 1-66.

WHO (World Health Organization). 1998. Guidelines for drinking water quality, 2nd edition. Geneva, World Health

Organization.

Page 15 of 30

WHO (World Health Organization). 2012. Rapid assessment of drinking water quality: a handbook for

implementation [Online]. Available at

http://www.wssinfo.org/fileadmin/user_upload/resources/RADWQHandbookv1final.pdf, (Verified 7 Mar.

2013).

WWF (World Water Federation). 2007. Pakistan's waters at risk: water and health related issues in Pakistan and key

recommendations. WWF-Pakistan, Ferozepur Road, Lahore, Pakistan. p. 1-33.

Table 1: Number and locations of water purification plants in FaisalabadTehsil / Town Total # of

plants installed

Number of functional Plants

Number of plants from where samples were taken

Percent of samples taken out of functional plants

Chak Jhumra Town 2 0 0 -Layellpur Town 2 1 1 100%Madina Town 10 6 3 50%Iqbal Town 3 2 1 50%Jinnah Town 20 11 6 55%Tandlianwala Town 0 - - -Jaranwala Town 0 - - -Samundri Town 0 - - -Total 35 20 11

Page 16 of 30

Table 2: Summary of sanitary inspection risk data for water purification plants located in study areaSanitary inspection risk question

Jinnah town (na = 6) Layellpur town (n = 1) Iqbal town (n = 1) Madina town (n = 3) Total (n = 11)Risk frequency

Proportion Risk frequency

Proportion

Risk frequency

Proportion

Risk frequency

Proportion

Risk frequency

Proportion

Q1. Defective tap? 6 100% 1 100% 1 100% 3 100% 11 100%Q2. Leaked pipe? 2 33% 1 100% 0 0% 0 0% 2 18%Q3. Water collection

around sampling site?

5 83% 0 0% 1 100% 3 100% 10 91%

Q4. Faulty drainage channel?

1 17% 0 0% 0 0% 0 0% 1 9%

Q5. Dirty or defective floor?

0 0% 0 0% 0 0% 0 0% 0 0%

Q6. Inadequately sealed walls?

1 17% 0 0% 0 0% 0 0% 1 9%

Q7. Flies around sampling site?

4 67% 0 0% 0 0% 3 100% 7 64%

Q8. Animal's access around sampling site?

0 0% 0 0% 0 0% 1 33% 1 9%

Q9. Sewerage or laterine beside purification plant?

2 33% 0 0% 0 0% 0 0% 2 18%

Q10.

Garbage beside purification plant?

6 100% 1 100% 1 100% 3 100% 11 100%

a Number of water purification plants inspected.

Page 17 of 30

Table 3a: Summary of physico-chemical and microbial parameters in water samples collected from study areaParameter Statisti

csJinnah Town

Layellpur Town

Iqbal Town Madina Town

WHOf Pak-EPAgna = 6 n = 1 n = 1 n = 3

Total coliform count

Range 0-17 0-0 11-15 7-14 0 per 100 mL

0 per 100 mL

Mean 11 0 13 10.7Std db 5.46 0 2 2.18

pH Range 6.7-7.9 6.8-7 7.3-7.5 6.6-7.3 6.5-8.5

6.5-8.5Mean 7.4 6.9 7.4 7

Std d 0.33 0.1 0.1 0.24Total dissolved solidsc

Range 7.1-131 150-160 5.6-15.6 7.3-159 <1000 <1000Mean 60.5 155 10.6 62.1

Std d 36.43 7.07 7.07 71.48Electrical conductivityd

Range 1.8-277 312-316 18.3-22.3 1.52-312 250.0 -Mean 116.97 314 20.3 105.7Std d 87.84 2.83 2.83 158.24

Turbiditye Range 0.08-0.45 0.0-0.1 0.37-0.47 0.21-0.77 <5.0 <5.0Mean 0.25 0.05 0.42 0.43Std d 0.1 0.07 0.07 0.23

Cadmium Range 0 0 0 0 0 1.0E-2Mean 0 0 0 0

Std d 0 0 0 0Chromium Range 1.0E-2-7.0E-

23.0E-2-7.0E-2 3.0E-2-5.0E-

20.0-8.0E-2 5.0E-

25.0E-2

Mean 5.0E-2 5.3E-2 4.0E-2 3.8E-2Std d 2.0E-2 2.0E-2 1.0E-2 2.8 E-2

Copper Range 1.3E-1-5.0E-1

1.5E-1-4.8E-1 1.0E-1-5.8E-1

8.0E-2-4.9E-1

2.00 2.00

Mean 3.69E-1 2.7E-1 2.63E-1 3.04E-1Std d 1.3E-1 1.8E-1 2.7E-1 1.3E-1

Iron Range 8.80E-1-1.64 1.15-1.36 8.8E-1-1.2 8.0E-1-1.61 3.0E-1

3.0E-1Mean 1.197 1.233 1.053 1.12

Std d 2.2E-1 1.1E-1 1.6E-1 2.6E-1Manganese Range 5.0E-2-1.2E-

17.0E-2-1.6E-1 5.0E-2-7.0E-

25.0E-2-1.2E-1

1.0E-2

5.0E-2

Mean 8.3E-2 1.03E-1 6.0E-2 6.9E-2Std d 2.0E-2 5.0E-2 1E-2 2.0E-2

Nickel Range 1.0E-2-8.0E-2

2.0E-2-6.0E-2 1.0E-2-4.0E-2

0.0-1.0E-1 5.0E-1

5.0E-1

Mean 3.0E-2 3.7E-2 2.0E-2 4.4E-2Std d 3.0E-2 2.0E-2 3.0E-2 3.0E-2

Lead Range 1.0E-2-1.4E-1

6.0E-2-8.0E-2 5.0E-2-8.0E-2

3.0E-2-1.3E-1

2.0E-2

2.0E-2

Mean 7.2E-2 7.3E-2 6.7E-2 6.7E-2

Page 18 of 30

Std d 3.0E-2 1.0E-2 2.0E-2 3.0E-2Zinc Range 1.6E-1-4.9E-

11.6E-1-2.8E-1 1.9E-1-4.1E-

11.7E-1-3.4E-1

3.0 5.0

Mean 2.79E-1 2.27E-1 3.23E-1 2.48E-1Std d 8.0E-2 6.0E-2 1.1E-1 4.0E-2

a Number of water samples.b Standard deviation.c Unit of total dissolved solid was ppm (parts per million).d Unit of electrical conductivity was µS/cm (Micro Siemens per centi-meter).e Unit of turbidity was NTU (Nephalometric Turbidity Unit).

f As per the WHO (1998) guidelines for drinking water quality, 2nd edition. Geneva, World Health Organization.g As per Pakistan Environmental Protection Agency (Ministry of Environment), Government of Pakistan, 2008.

Page 19 of 30

Table 3b: Compliance for heavy metals, physico-chemical and microbial parameters in water samples collected from study area with WHO standards on drinking water quality

Parameter Jinnah town (na = 6) Layellpur town (n = 1) Iqbal town (n = 1) Madina town (n = 3) Total (n = 11)Target met frequency

Percent compliance

Target met frequency

Percent compliance

Target met frequency

Percent compliance

Target met frequency

Percent compliance

Target met frequency

Percent compliance

pH 6 100% 1 100% 1 100% 3 100% 11 100% Total dissolved solids 6 100% 1 100% 1 100% 3 100% 11 100% Electrical conductivity 5 83.3% 0 0% 1 100% 2 66.7% 8 72.7% Turbidity 6 100% 1 100% 1 100% 3 100% 11 100% Total coliform count 1 16.7% 1 100% 0 0% 0 0% 2 18.2%Cadmium (Cd) 6 100% 1 100% 1 100% 3 100% 11 100% Chromium (Cr) 2 33.3% 0 0% 1 100% 2 66.7% 5 45.4%Copper (Cu) 6 100% 1 100% 1 100% 3 100% 11 100% Iron (Fe) 0 0% 0 0% 0 0% 0 0% 0 0%Manganese (Mn) 6 100% 1 100% 1 100% 3 100% 11 100% Nickel (Ni) 2 33.3% 0 0% 1 100% 1 33.3% 4 36.4% Lead (Pb) 0 0% 0 0% 0 0% 0 0% 0 0%Zinc (Zn) 6 100% 1 100% 1 100% 3 100% 11 100%

a Number of water purification plants inspected.

Page 20 of 30

Table 4: Chronic daily intake (CDI) indices for heavy metals via drinking waterHeavy metals Statistics Jinnah Town Layellpur Town Iqbal Town Madina Town

na = 6 n = 1 n = 1 n = 3Cadmium (Cd)b Range BLd BL BL BL

Mean BL BL BL BLStd dc BL BL BL BL

Chromium (Cr) Range -2.80E-4-2.5E-3 8.00E-4-1.90E-3 8.00E-4-1.40E-3 0.00-2.20E-3Mean 1.40E-3 1.50E-3 1.10E-3 1.05E-3Std d 7.00E-4 6.00E-4 3.00E-4 8.00E-4

Copper (Cu) Range 1.40E-3-1.39E-2 4.20E-3-1.33E-2 2.80E-3-1.61E-2 2.20E-3-1.36E-2Mean 9.60E-3 7.50E-3 7.30E-3 8.50E-3Std d 4.10E-3 5.10E-3 7.60E-3 3.70E-3

Iron (Fe) Range 8.30E-3-4.56E-2 3.19E-2-3.78E-2 2.44E-2-3.33E-2 2.22E-2-4.47E-2Mean 3.12E-2 3.43E-2 2.93E-2 3.11E-2Std d 8.00E-3 3.10E-3 4.50E-3 7.40E-3

Manganese (Mn) Range 1.40E-3-3.30E-3 1.90E-3-4.40E-3 1.40E-3-1.90E-3 1.40E-3-3.30E-3Mean 2.30E-3 2.90E-3 1.70E-3 1.90E-3Std d 6.00E-4 1.40E-3 3.00E-4 6.00E-4

Nickel (Ni) Range -3.00E-4-2.20E-3

5.60E-4-1.67E-3 -3.00E-4-1.11E-3 0.00-2.78E-3

Mean 8.30E-4 1.02E-3 5.60E-4 1.23E-3Std d 7.70E-4 5.80E-4 7.30E-4 9.50E-4

Lead (Pb) Range 2.78E-4-3.89E-3 1.67E-3-2.22E-3 1.39E-3-2.22E-3 8.33E-4-3.61E-3Mean 1.99E-3 2.04E-3 1.85E-3 1.85E-3Std d 8.48E-4 3.21E-4 4.24E-4 9.21E-4

Zinc (Zn) Range 4.40E-3-1.36E-2 4.40E-3-7.80E-3 5.30E-3-1.14E-2 4.70E-3-9.40E-3Mean 7.75E-3 6.30E-3 9.00E-3 6.90E-3Std d 2.50E-3 1.70E-3 3.30E-3 1.50E-3

a Number of water samples.b Metals unit was mg/L-day or ppm.c Standard deviation.d Below limits.

Page 21 of 30

Table 5: Hazard quotient (HQ) indices for heavy metals via drinking waterHeavy metals Statistic

sJinnah Town Layellpur Town Iqbal Town Madina Townna = 6 n = 1 n = 1 n = 3

Cadmium (Cd)b Range BLd BL BL BLMean BL BL BL BLStd dc BL BL BL BL

Chromium (Cr) Range -1.90E-4-1.67E-3 5.60E-4-1.30E-3 5.60E-4-9.26E-4 0.00-1.48E-3Mean 9.50E-4 9.90E-4 7.40E-4 7.00E-4Std d 4.30E-4 3.90E-4 1.90E-4 5.10E-4

Copper (Cu) Range 3.75E-2-3.75E-1 1.13E-1-3.60E-1 7.51E-2-4.35E-1 6.01E-2-3.68E-1Mean 2.58E-1 2.03E-1 1.98E-1 2.28E-1Std d 1.12E-1 1.37E-1 2.06E-1 1.00E-1

Iron (Fe) Range - - - -Mean - - - -Std d - - - -

Manganese (Mn)

Range 9.90E-3-2.38E-2 1.39E-2-3.17E-2 9.90E-3-1.39E-2 9.90E-3-2.38E-2Mean 1.65E-2 2.05E-2 1.19E-2 1.37E-2Std d 4.51E-3 9.79E-3 1.98E-3 4.14E-3

Nickel (Ni) Range -1.39E-2-1.11E-1 2.78E-2-8.33E-2 -1.39E-2-5.56E-2 0.00-1.39E-1Mean 4.17E-2 5.09E-2 2.78E-2 6.17E-2Std d 3.84E-2 2.89E-2 3.67E-2 4.76E-2

Lead (Pb) Range 7.72E-3-1.08E-1 4.63E-2-6.17E-2 3.86E-2-6.17E-2 2.31E-2-1.0E-1Mean 5.53E-2 5.66E-2 5.14E-2 5.14E-2Std d 2.34E-2 8.91E-3 1.18E-2 2.56E-2

Zinc (Zn) Range 1.48E-2-4.54E-2 1.48E-2-2.59E-2 1.76E-2-3.80E-2 1.57E-2-3.15E-2Mean 2.58E-2 2.09E-2 2.99E-2 2.29E-2Std d 8.49E-3 5.66E-3 1.08E-2 5.02E-3

a Number of water samples.b Metals unit was mg/L-day or ppm.c Standard deviation.d Below limits.

Page 22 of 30

Table 6a: Risk priority matrix of water purification plants located in study area (modified from Tadesse et al., 2010)Total coliform count per 100 mL

Jinnah Town (na = 6) Layellpur Town (n = 1) Iqbal Town (n = 1) Madina Town (n = 3) Total (n = 11)SIRSb SIRS SIRS SIRS SIRS0-2 3-5 6-8 9-10 0-2 3-5 6-8 9-10 0-2 3-5 6-8 9-10 0-2 3-5 6-8 9-10 0-2 3-5 6-8 9-10

<1 1 - - - - 1 - - - - - - - - - - 1 1 - -1-10 - - - - - - - - - - - - - 1 - - 1 - -11-100 - 3 2 - - - - - - 1 - - - 2 - - - 6 2 ->100 - - - - - - - - - - - - - - - - - - - -

a Number of water purification plants inspected.b Sanitary inspection risk score.

Legend for risk priority categories: LOW RISKINTERMEDIATE RISKHIGH RISKVERY HIGH RISK

Table 6b: Overall risk priority classification of water purification plants located in study area (modified from Tadesse et al., 2010)Risk category Jinnah town (na = 6) Layellpur town (n = 1) Iqbal town (n = 1) Madina town (n = 3) Total (n = 11)

Frequency Proportion Frequency Proportion Frequency Proportion Frequency Proportion Frequency ProportionLow risk 1 17% 0 0% 0 0% 0 0% 1 9%Intermediate risk 0 0% 1 100% 0 0% 1 33% 2 18%High risk 5 83% 0 0% 1 100% 2 67% 8 73%Very high risk 0 0% 0 0% 0 0% 0 0% 0 0%

a Number of water samples.

Page 23 of 30

Page 24 of 30

Table 7a: One way ANOVA comparison for selected heavy metals pollution for different sites in the study areaHeavy metals Source dfa Sum of

squaresMean square

Fb Significance

Cadmium (Cd) Between groups 10 0 0 Mc MWithin groups 22 0 0Total 32 0

Chromium (Cr) Between groups 10 0.00279 2.79E-04 0.44 0.9076

Within groups 22 0.0138 6.27E-04Total 32 0.01659

Copper (Cu) Between groups 10 0.23679 0.02368 1.08 0.4183

Within groups 22 0.48307 0.02196Total 32 0.71985

Iron (Fe) Between groups 10 0.44392 0.04439 0.85 0.5906

Within groups 22 1.15147 0.05234Total 32 1.59539

Manganese (Mn)

Between groups 10 0.00661 6.61E-04 0.98 0.4893

Within groups 22 0.01487 6.76E-04Total 32 0.02147

Nickel (Ni) Between groups 10 0.01536 0.00154 3.02 0.0147*

Within groups 22 0.0112 0.00051Total 32 0.02656

Lead (Pb) Between groups 10 0.00693 6.93E-04 0.82 0.6161

Within groups 22 0.01867 8.49E-04Total 32 0.0256

Zinc (Zn) Between groups 10 0.00693 6.93E-04 2.95 0.0165*

Within groups 22 0.01867 8.49E-04Total 32 0.0256

The mean difference is significant at a level of 0.05a Degree of freedom.b Factor.c Missing case; sum of squares is too small.* Values are significant at the 0.05 level.

Table 7b: One way ANOVA for comparison of heavy metals pollution in the study areaSource of variation dfa Sum of squares Mean square Fb SignificanceBetween groups 7 32.5067 4.64381 373 0.0000*Within groups 256 3.1897 0.01246Total 263 35.6964The mean difference is significant at a level of 0.05.

a Degree of freedom.b Factor.* Value is highly significant.

Page 25 of 30

Table 8: Correlation matrix of selected parameters in water samples collected from study area (na = 11) pH TDSc ECd Turbidity Coliform Cd Cr Cu Fe Mn Ni Pb ZnpH 1.000TDS -.405** 1.000EC -.483** .746** 1.000Turbidity -.335 .211 .054 1.000Coliform .222 -.242 -.147 .260 1.000Cd -b - - - - -Cr -.244 .043 .199 -.278 -.320 - 1.000Cu -.077 .006 -.185 -.067 -.107 - .267 1.000Fe .024 .221 -.011 -.123 -.131 - .367* .224 1.000Mn -.013 .116 .032 -.375* -.276 - .349* .175 .393* 1.000Ni .156 -.215 -.346* -.220 -.190 - -.120 .097 .171 .155 1.000Pb .309 .147 -.010 -.032 .225 - -.315 -.021 .288 .162 -.038 1.000Zn .486** -.068 -.258 .109 .228 - -.279 -.303 .347* -.142 -.059 .475** 1.000

a Number of water samples.b Cannot be computed because at least one of the variables is constant.c Total dissolved solids.d Electrical conductivity.* Correlation is significant at the 0.05 level (2-tailed)** Correlation is significant at the 0.01 level (2-tailed)

Page 26 of 30

Table 9: Factor loading for selected heavy metals (na = 11)Heavy metals Factor 1 Factor 2 Factor

3Cr .780* -.092 -.441Cu .616* -.023 .158Fe .491 .732* -.092Mn .648* .361 .056Ni .194 .143 .904*Pb -.251 .776* .009Zn -.471 .724* -.175Eigen value 1.971 1.822 1.079Loading% 28.163 26.032 15.416Cumulative% 28.163 54.195 69.611

a Number of water samples.* Values of dominant heavy metals in each factor.

Page 27 of 30

Figure 1: Location of study site (Map data ©2015 Google)

Page 28 of 30

Figure 2: Bar chart comparison of selected heavy metals with their sources

Page 29 of 30

Jinnah town Layellpur town

Iqbal town Madina town0

0.2

0.4

0.6

0.8

1

CdCo

nc. (

mg/

L)

Jinnah town Layellpur town

Iqbal town Madina town0

0.01

0.02

0.03

0.04

0.05

0.06

Cr

Conc

. (m

g/L)

Jinnah town Layellpur town

Iqbal town Madina town0.95

1

1.05

1.1

1.15

1.2

1.25

Fe

Conc

. (m

g/L)

Jinnah town Layellpur town

Iqbal town Madina town0

0.050.1

0.150.2

0.250.3

0.350.4

Cu

Conc

. (m

g/L)

Jinnah town Layellpur town

Iqbal town Madina town0

0.01

0.02

0.03

0.04

0.05

Ni

Conc

. (m

g/L)

Jinnah town Layellpur town

Iqbal town Madina town0

0.02

0.04

0.06

0.08

0.1

0.12

Mn

Conc

. (m

g/L)

Jinnah town Layellpur town

Iqbal town Madina town0.064

0.066

0.068

0.07

0.072

0.074

Pb

Conc

. (m

g/L)

Jinnah town Layellpur town

Iqbal town Madina town0

0.050.1

0.150.2

0.250.3

0.35

Zn

Conc

. (m

g/L)

Linkage distance (Pearson r)

C A S E 0 5 10 15 20 25Label +---------+---------+---------+---------+---------+

Pb -+-------------------------------------+Zn -+ +---------+Cd ---------------------------------------+ |Fe -------------+-+ |Mn -------------+ +---------+ |Cr ---------------+ +-----------+ |Cu -------------------------+ +-----------+Ni -------------------------------------+

Figure 3: Dendogram of selected heavy metals using complete linkage method

Page 30 of 30