environmental geochemistry of attock and haripur basins, pakistan

ENVIRONMENTAL GEOCHEMISTRY OF
ATTOCK AND HARIPUR BASINS, PAKISTAN
BY
SHAZIA JABEEN
NATIONAL CENTRE OF EXCELLENCE IN GEOLOGY
UNIVERSITY OF PESHAWAR
PAKISTAN
2013

ENVIRONMENTAL GEOCHEMISTRY OF
ATTOCK AND HARIPUR BASINS, PAKISTAN
A MANUSCRIPT PRESENTED TO THE NATIONAL CENTRE OF
EXCELLENCE IN GEOLOGY, UNIVERSITY OF PESHAWAR IN
THE PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR
THE DEGREE OF
DOCTOR OF PHILOSOPHY
IN
ENVIRONMENTAL GEOSCIENCES
BY
SHAZIA JABEEN
NATIONAL CENTRE OF EXCELLENCE IN GEOLOGY
UNIVERSITY OF PESHAWAR
PAKISTAN
2013

IN THE NAME OF ALLAH, MOST COMPASSIONATE, EVER MERCIFUL

“In the name of Allah the most merciful and beneficent”
All prayers for Almighty Allah, the most merciful and beneficent, without Whose
consent and consecration nothing would ever be imaginable. I am absolutely beholden
by my Lord’s generosity in this effort. Praises be to Holy Prophet for He is a beacon as
I pace on in my life and work.
ACKNOWLEDGEMENTS
First of all I want to acknowledge my supervisor Dr. Mohammad Tahir Shah,
Professor, National Centre of Excellence in Geology, University of Peshawar, Pakistan
without whom I may have not been able to compile this research thesis than I am
indebted to co-supervisor Dr. Sardar Khan, Associate Professor, Department of
Environmental Sciences, University of Peshawar, Pakistan for his kind support during
the entire period of my PhD. I like to gratitude my foreign supervisor Dr. Andrew
Meharg, Professor, Department of Soil and Environmental Sciences, Institute of
Biological Sciences, University of Aberdeen, United Kingdom for his help in
completing ICPMS work for my thesis. I am thankful to external evaluators and
internal viva examiners for their kind suggestions to improve the quality of research
presented in this thesis. Thanks are also due to Professor Dr. M. Asif Khan, Director,
National Centre of Excellence in Geology, University of Peshawar, Peshawar, Pakistan
for facilitating the research work during entire period of my PhD program.
My gratitude goes to Dr. Tazeem Khan, Dr. Rubina Bilques, Dr. Samina Sadique, Dr.
Fazal-i-Rabi, Mrs Seemi and Mrs Farhi Sahar, whose moral support always boosted my
energies. Special thanks are to Mr. Muhammad Tariq (Lab technician) and Mr. Bilal
(Lab Attendant) for their cooperation during entire laboratory work. I am highly

obliged to my teachers and colleagues of all university especially who are working in
National Centre of Excellence in Geology, University of Peshawar, Pakistan who
appreciated the compilation of this Thesis.
I am thankful to all people of Attock and Haripur Basins for helping me during field
survey, especially local community of remote villages. My sincere thanks are to all
staff, scientists and professors of University of Aberdeen, United Kingdom, especially
Prof. Dr. Adam Price, Prof. Dr. Angel, and Mrs. Claire Deacon for their cooperation,
technical assistant and provision of laboratory facilities. I am also thankful to my
brother Assistant Professor Dr. Iftikhar Ahmed, Chairman, Department of Mathematics,
University of Gujrat, Pakistan for his encouragement to do such type of unique research
work. My sincere thanks are for all my precious friends and colleagues (Safia
Tabassum, Khalid Latif, Wajid Ali, Muhammad Ali, Azra Yaseem, Reema Fida,
Humaira Fida, Humaira Gul, Shahia Khattak, Anne Marie, Zainab, Faiz, Dr. Lorna, Dr.
Nimbe Ewald, Tanveer, and Gillian Kerr) for their forbearance, helpful and enjoyable
company.
Nevertheless, it’s the inspiration that I derived from the unconditional love, care, and
prayers of my parents, in laws, husband Dr. Muhammad Qasim Hayat, Assistant
Professor, Atta-ur-Rehman School of Applied Bio-Sciences (ASAB), NUST,
Islamabad, Pakistan, brothers, sisters, nephews, nieces and my children (Sabaina and
Mahdi Hayat) that have propelled me as far as I have triumphed.
SHAZIA JABEEN

D E D I C A T I O N
I DEDICATED MY THESIS TO
MY PARENTS, HUSBAND
AND CHILDREN

Table of Contents
Chapters Title Page
List of Tables iv
List of Figures vi
List of Appendices viii
List of abbreviations ix
Preface x
Abstract xii
Chapter 1 Introduction 1-15
1.1 General statement 1
1.2 Problem statement 4
1.3 Aims and objectives 5
1.4 Study area 6
1.4.1 Attock Basin 6
Drainage 8
Population and domestic water supply 8
1.4.2 Haripur Basin 8
Drainage 9
Population and domestic water supply 9
1.5 Geology of the area 9
1.5.1 Punjal- Khairabad block 10
Proterozoic formations 10
Paleozoic and Mesozoic formations 10
1.5.2 Nathia Gali-Hissartang block 10
Proterozoic formations 12
Cambrian formations 12
Mesozoic formations 12
Tertiary formations 12
1.5.3 Kala Chitta- Margalla hill block 13
Plaeocene formations 13
Cenozoic formations 13
Mesozoic formations 14
1.6 Anthropogenic activities and sources of pollution 14
Chapter 2 Material and method 16-36
2.1 Field investigation 16
2.1.1 Water sampling 16
2.1.2 Soil sampling 16
2.1.3 Plant sampling 19
2.2 Analytical Procedures 19
2.2.1 Water analysis 19
Determination of physiochemical parameters 19
Temperature 19
pH 20
Electrical conductivity 20
Total dissolve solids 20
Total hardness 20
i

Determination of anions 21
Nitrate 21
Sulphate 21
Chloride 21
Carbonate and bicarbonate 21
Determination of light elements in water 22
Calcium and Magnesium 22
Sodium and Potassium 22
Determination of heavy metals in water 24
Copper 24
Iron 24
Lead 24
Zinc 26
Nickel 26
Chromium 26
Cobalt 27
Mercury and Arsenic 27
2.2.2 Soil and plant analysis 27
Preparation of soil samples 27
Pulverizing of soil samples 27
Preparation of solution of soils for major cations 28
Preparation of solution of soils for heavy and trace elements 28
Preparation of plant samples 29
Pulverizing of plant samples 29
Preparation of solution for plant samples 29
2.2.3 Determination of physical parameters in soils 29
pH 29
Electrical conductivity 30
2.2.4 Determination of major elements in soils and plant samples 30
Calcium and Magnesium 30
Sodium and Potassium 30
2.2.5 Determination of heavy and trace elements 31
Copper 31
Iron 31
Manganese 31
Lead 33
Zinc 33
Nickel 34
Chromium 34
Cobalt 34
2.2.6 ICPMS 35
Preparation of plant samples for ICPMS 35
Preparation of soil samples for ICPMS 36
Chapter 3 Literature review 37-44
Chapter 4 Water chemistry 45-88
4.1 Introduction 45
4.2 Materials and methods 47
4.2.1 Sampling and analysis 47
ii

4.2.2 Statistical analysis 47
4.2.3 Health risk assessment 50
4.3 Results 51
4.3.1 Physico-chemical variables of water 51
4.3.2 Hydrochemical facies 54
4.3.3 Light and heavy metals in water samples 55
4.3.4 Groundwater and surface water comparison 63
4.3.5 Statistical analysis 65
4.3.5.1 Inter- relationships among metals 65
4.3.5.2 Principal component analysis 72
4.3.6 Health risk assessment 76
4.4 Discussion 82
Chapter 5 Soil chemistry 89-119
5.1 Introduction 89
5.2 Materials and methods 91
5.2.1 Statistical analysis 91
5.2.2 Index of geoaccumulation 91
5.3 Results 93
5.3.1 Inter-elemental relationship 98
5.3.2 Principal component analysis 102
5.4 Discussion 106
Chapter 6 Plant chemistry 120-146
Section I Heavy metal concentration in vegetables and cereal 120
6.1 Introduction 120
6.2 Materials and methods 122
6.2.1 Transfer factor 122
6.2.2 Metal pollution index (MPI) 122
6.2.3 Health risk index (HRI) 124
6.3 Result and discussion 124
6.3.1 Plant transfer factor from soil to plant 128
6.3.2 Metal pollution index 129
6.3.3 Estimated daily intake for HMs 131
6.3.4 Health risk index of HMs 134
Section II Heavy metal concentration in medicinal herbs 136
6.1 Introduction 136
6.2 Materials and methods 137
6.3 Results 137
6.4 Discussion 143
Chapter 7 Conclusions and Recommendations 147-150
References 151
Appendices 180
iii

List of Tables
Tables Title Page
Table 2.1 Analytical conditions for light elements determination in water samples on
air acetylene flame mood
23
Table 2.2 Analytical conditions for heavy metals determination in water samples by
graphite furnace
25
Table 2.3 Analytical conditions for major, heavy and trace elements determination in
soil samples
32
Table. 4.1a Description of Physico-chemical parameters of water samples of Attock and
Haripur basins, Pakistan
52
Table 4.1b Description of selected elements in surface and groundwater samples Attock
and Haripur basins, Pakistan
59
Table 4.2 Drinking water quality guidelines by National and International Agencies. 60
Table 4.3a Pearson’s correlation matrix indicating the association within surface water
samples of Attock Basin
66
Table 4.3b Pearson’s correlation matrix indicating the association within groundwater
samples of Attock Basin
67
Table 4.4a Pearson’s correlation matrix indicating the association within surface water
samples of Haripur Basin
70
Table 4.4b Pearson’s correlation matrix indicating the association within groundwater
samples of Haripur Basin
71
Table 4.5a Factor analysis of selected elements in surface water of Attock Basin 74
Table 4.5b Factor analysis of selected elements in groundwater of Attock Basin 75
Table 4.6a Factor analysis of selected elements in surface water of Haripur Basin 77
Table 4.6b Factor analysis of selected elements in groundwater of Haripur Basin 78
Table 4.7 Chronic daily intake (CDI) of heavy metal via the consumption of surface
and groundwater in Attock and Haripur basins
80
Table 4.8 Hazard quotient (HQ) of heavy metals via the consumption of surface and
groundwater in Attock and Haripur basins
81
Table 5.1 Statistical parameters for major cations distribution in soils of Attock and
Haripur basins
94
Table 5.2 Correlation coefficient matrix of selected metals in the soil of Attock Basin 99
Table 5.3 Correlation coefficient matrix of selected metals in the soil of Haripur Basin 100
Table 5.4 Factor analysis of selected elements in soil samples of Attock Basin 103
Table 5.5 Factor analysis of selected elements in soil samples of Haripur Basin 105
Table 5.6 Mean concentrations of metals of different soils of the world in comparison
to present study
110
Table 6.1 Vegetable and cereal crops collected from the study area 123
iv

Table 6.2 Heavy metal concentrations in soil, edible parts of vegetables, cereal and
transfer factor
125
Table 6.3 Estimated daily intake (EDI) of HMs via consumption of different vegetables
and cereal
132
Table 6.4 Health risk index of HMs via consumption of different vegetables and cereal 135
Table 6.5a Common medicinal herbs used in folk remedies by the inhabitants of Attock
Basin, Pakistan
138
Table 6.5b Common medicinal herbs used in folk remedies by the inhabitants of Haripur
Basin, Pakistan
140
Table 6.6a Heavy metals concentrations in medical plant collected from the Attock
Basin
141
Table 6.6b Heavy metals concentrations in medical plant collected from the Haripur
Basin
142
v

List of Figures
Figures Title Page
Fig. 1.1. Location map of the study area 7
Fig. 1.2. Geological map of study area (Pogue et al., 1999) 11
Fig. 2.1. Location map of water samples collected from the study area 17
Fig. 2.2. Location map of water samples collected from the study area 18
Fig. 4.1. Location map of water samples collected from the study area 48
Fig.4.2a. Classification of hydrochemical facies using the Piper plot 56
Fig.4.2b. Piper diagram water samples of Attock basin 57
Fig.4.2c. Piper diagram water samples of Haripur basin 58
Fig. 4.3a Comparison of surface and groundwater quality of Attock Basin 64
Fig. 4.3b Comparison of surface and groundwater quality of Attock Basin 64
Fig. 4.4a. Dendrogram showing association of metals in surface water samples collected
from Attock Basin
Fig. 4.4b. Dendrogram showing association of metals in groundwater samples collected from
Attock Basin
Fig. 4.5a. Dendrogram showing association of metals in surface water samples collected
from Haripur Basin
Fig. 4.5b. Dendrogram showing association of metals in groundwater samples collected from
Haripur Basin
Fig. 5.1. Location map of soil samples collected from the study area 92
Fig. 5.2. Box and Whisker plots of (a)major cations and (b) selected HMs in soil
samples of Attock Basin
Fig. 5.3. Box and Whisker plots of (a)major cations and (b) selected HMs in soil
samples of Haripur Basin
Fig. 5.4a. Cluster analysis showing association of metals soil samples of Attock Basin 101
Fig. 5.4b. Cluster analysis showing association of metals soil samples of Haripur Basin 101
Fig. 5.5a Spatial distribution map of Ca concentration in the soil samples of the study area 107
Fig. 5.5b Spatial distribution map of Mg concentration in the soil samples of the study area 107
Fig. 5.5c Spatial distribution map of K concentration in the soil samples of the study area 108
Fig. 5.5d Spatial distribution map of Na concentration in the soil samples of the study area 108
vi
68
68
73
73
96
97

Fig. 5.5e Spatial distribution map of Fe concentration in the soil samples of the study area 111
Fig. 5.5f Spatial distribution map of Mn concentration in the soil samples of the study area 111
Fig. 5.5g Spatial distribution map of Cd concentration in the soil samples of the study area 113
Fig. 5.5h Spatial distribution map of Cr concentration in the soil samples of the study area 113
Fig. 5.5i Spatial distribution map of Co concentration in the soil samples of the study area 114
Fig. 5.5j Spatial distribution map of Cu concentration in the soil samples of the study area 114
Fig. 5.5k Spatial distribution map of Zn concentration in the soil samples of the study area 116
Fig. 5.5l Spatial distribution map of Pb concentration in the soil samples of the study area 116
Fig. 5.5m Spatial distribution map of As concentration in the soil samples of the study area 117
Fig. 5.5n Spatial distribution map of Ni concentration in the soil samples of the study area 117
Fig. 5.6a. Geoaccumulation index for selected metals in soil samples of Attock basin 118
Fig. 5.6b. Geoaccumulation index for selected metals in soil samples of Haripur basin 118
Fig. 6.1 Heavy metal concentration in different vegetables and cereal crop samples 127
Fig. 6.2 Metal pollution index of different vegetables and cereal 130
vii

List of Appendices
Appendices Title Page
Appendix Ia. Longitude, latitude and altitude of 140 sampling sites located in Attock
and Haripur basins
Appendix Ib. Longitude, latitude and altitude of 110 sites of soil sampling located in
Attock and Haripur basins
Appendix II Concentration of major cations in groundwater samples of Haripur and
Attock basins
Appendix.III. Concentration of major cations in soil samples of Haripur and Attock
basins
180
185
189
197
viii

LIST OF ABBREVIATION
As Arsenic HQ Hazard quotient
BOD Biological Oxygen
Demand
Igeo Geoaccumulation Index
Ca Calcium ICP-MS Inductively Coupled
Plasma Mass Spectrometry
Cd Cadmium JECFA Joint Expert Committee on
Food Additives
CDI Chronic Daily Intake K Potassium
CEPA Chinese Environmental
Protection Administration
Mg Magnesium
Cl Chloride Mn Manganese
Co Cobalt Na Sodium
COD Chemical Oxygen Demand Ni Nickel
Cr Chromium NO3 Nitrate
Cu Copper Pb Lead
EC Electrical Conductivity PCA Principal Component
Analysis
EPA Environmental Protection PMTDI Provisional Maximum
Agency
Tolerable Daily Intake
FAO Food and Agriculture
Organization of United
Nations
RAC Risk Assessment Code
FC Fecal Coliform S.D Standard Deviation
Fe Iron SO4 Sulfate
GIS Geographical Information
System
SS Suspended Solid
HCA Hierarchical cluster
analysis
TDS Total Dissolve Solid
HCO3 Bicarbonate TOC Total Organic Carbon
Hg Mercury USEPA United State
Environmental Protection
Agency
HIE Hattar Industrial Estate WIC Wah Industrial Complex
HMs Heavy Metals WHO World Health Organization
HPI Heavy Metal Pollution
Index
Zn Zinc
ix

PREFACE
The main objectives of present thesis was to study the impacts of anthropogenic
activities on surface and ground water quality, soil and plants of Attock and Haripur basins
and to achieve these objectives, the thesis research work has been divided into seven
chapters; each chapter is focused on specific objectives in details.
First Chapter describes the general introduction and background information that reviews
the role of anthropogenic factors deteriorating the water and soil qualities and affecting the
flora. This chapter also describes the environmental problems in study area and presents
research objectives. It also provides description of the study area in relation to topography,
climate, geology, drainage pattern, land use, human population and other anthropogenic
activities.
Second Chapter describes the sampling strategy for collection, transportation, preservation
and analysis of water, soil and plant samples.
Third Chapter highlights the researches carried out throughout the world. These studies
describe the quality of surface and groundwater in different countries. This chapter also
covers the research carried out on quality of soil and transfer of different metals from soil to
plant.
Fourth Chapter highlights the water quality of surface and groundwater quality of Attock
and Haripur Basins, identification of important variables responsible for variations and their
source of origin. Comparison of water quality with national and international standard has
also been discussed. This chapter also describes the health risk to local community via the
consumption of the water. Two papers have been compiled from the data of this chapter and
are submitted to the international journal for publication. One paper is entitled “Health risk
x

assessment for exposure to heavy metals and source apportionment using multivariate
analysis in Haripur Basin, Pakistan” in Environmental Earth Sciences (under review) and
the second “Health risk assessment and multivariate statistical analysis of heavy metals
pollution in industrial area and its comparison with relatively less polluted area: A case
study from the Attock Basin” in Food and Chemical Toxicology (under review).
Fifth Chapter describes major and trace element accumulation in soils of Attock and
Haripur basins. It also describes the spatial distribution of metals in study area. The results of
heavy metals accumulation in soils are compared with other such kind of research work.
Sixth Chapter describes the accumulation of major and trace elements in vegetables and
medicinal plants and translocation of these metals from soil to plant and variation among the
different plant species of the study area. The data of this chapter has been compiled in three
research publications. These are entitled (1) Determination of major and trace elements in ten
important folk therapeutic plants of Haripur basin, Pakistan. 2010. Journal of Medicinal
Plants Research, 4(7), 559-566, (2) Health risk assessment of heavy metals via consumption
of medicinal herbs, A case study of Attock Basin, Pakistan, Pakistan Journal of Botany
(Accepted), and (3) Potentially toxic elements (PTEs) in the vegetable diet of the
industrialized Haripur Basin in Food and Chemical Toxicology (under review).
Seventh Chapter concludes the findings of the research and provides guidelines for
restoration and management of Attock and Haripur Basins. Finally, this chapter also includes
the recommendations for the improvement of environmental conditions of both the basins.
xi

ABSTRACT
The purpose of this work was to investigate the environmental geochemistry of
Attock and Haripur basins of Pakistan; using water, soil and plants as indicators. The
study included determination of seven physiochemical parameters (pH, TDS, EC, NO3 - ,
SO4 2- , Cl - and HCO3 - ) along with the monitoring of 15 major and trace elements (Na,
K, Ca, Mg, Cd, Cr, Cu, Pb, Fe, Ni, Zn, Co, Mn, As and Hg) concentrations and these
were analyzed through atomic-absorption spectrometer and inductively coupled plasma
mass spectrometry (ICP-MS). Data presentation and interpretation were done by
employing a range of statistical tools like Piper diagram, chronic daily intake, hazard
quotient and also by applying multivariate analysis (Principal component analysis,
Correlation, Cluster analysis). The GIS based spatial distribution of samples and
parameters were analyzed using ArcGIS 9.3.
The physico-chemical parameters of water were compared with those of WHO
(2008) and USEPA standards. Piper diagram showed that 80% and 90% water samples
of Attock and Haripur basins respectively fell in the field of Ca-Mg type on the basis of
cations and HCO3 - type on anion basis. Chronic daily intake (CDI) and hazard quotient
(HQ) were also calculated. HQ was

anthropogenic intrusions of HMs in the soils. Geoaccumulation indices values of As,
Na, Ca, Pb and Cd indicated moderate to heavy contamination. Rest of the elements
(Co, Cr, Cu, Fe, K, Mg, Mn and Zn) revealed practically no contamination in the
studied soils. The spatial distribution of HMs of soil showed high concentration near
the industrial areas while major cations concentrations were high near the agricultural
areas.
Vegetables, cereal and their respective soil samples were analyzed for As, Cd,
Cu, Ni, Pb, Mn, Cr and Zn by ICP-MS. All toxic element concentrations in the edible
parts of leafy vegetables were higher than non leafy vegetables and, also, higher than
the FAO/WHO recommended limits. The risk assessment of HMs through consumption
of vegetables suggested that Health risk index (HRI) values for adults and children
were higher than the safe limit (>1) with exception of Cr (

1.1. General Statement
CHAPTER 1
INTRODUCTION
Water is the main source for all the physiological changes throughout the world
(Boyd, 2000). According to Miller (2002), 97.4% of the total water reserves of the world
is present in ocean while the remaining 2.6% is freshwater resources. Among the total
fresh water resources 68.7%, 30.1%, 0.3% and 0.9% are present in glaciers and icecaps,
ground water, surface water and in other forms, respectively (Gleick, 1996). It is single
most important agent sculpturing the earth’s surface. Life cannot be sustained more than
few days without water, even inadequate supply of water change the pattern of
distribution of organisms as well as human being. The global use of water varies among
different sectors, for example, agriculture uses 70%, industry 20% and domestic about
10%. Agricultural sector is largest consumer of the freshwater resources throughout the
world. About 32% of Asian population depends on groundwater sources for drinking
purposes (Fukushi et al., 2010).
Water quality is considered the main factor controlling health and the state of
disease in both human beings and animals. Surface water quality in a region is largely
determined both by natural processes (weathering and soil erosion) and by anthropogenic
inputs (municipal and industrial wastewater discharge). Approximately 25 million
persons die every year due to water pollution and it has become a major problem in many
countries (Pimpunchat et al., 2008).
Increasing industrialization and urbanization leads to ever increasing pollution of
streams and rivers in developing countries (Jan et al., 2010). The discharge of effluents
1

and associated toxic compounds enter the surface water and subsurface aquifers resulting
in pollution of irrigation and drinking water (Sial et al., 2006; Manzor et al., 2006;
Rehman et al., 2008). The movement of trace metals and metalloids between the soil,
plants, water and even atmosphere is part of a complex and intricately interrelated
biogeochemical cycling processes in nature, and is affected by several factors that are
both natural and anthropogenic. Anthropogenic influences as well as natural processes are
responsible for deterioration of surface and groundwater, and impair their use for
drinking, industrial, agricultural, recreation or other purposes (Carpenter, et al., 1998;
Fergusson, 1990). Metals are non-biodegradable and accumulative in nature.
Earth crust has mainly composed of alkali and alkaline earth metals, and also has
trace amount of heavy metals (HMs). Some essential HMs, in trace amount, are necessary
for biological and physiological development in living organisms (Wepener et al., 2001),
whereas, non-essential metals have no known role in metabolic functions of the
organisms and are toxic even in trace amount. Essential heavy metals are required in trace
quantities by organisms and if their concentration exceeds the threshold level become
toxic (Wright and Welbourn, 2002). Toxic effects of heavy metal vary according to their
position in food chain. At higher trophic levels, the effects of heavy metals become more
conspicuous due to biomagnification (Devlin, 2006).
A human health concern is usually associated with excessive exposures to metals
that cause toxic effects to biological organisms. World Health Organization (WHO)
estimates that every day on average 3700 children die due to water borne diseases as they
don’t have access to safe drinking water (WHO, 2004). Trace metals are most important
because many of these metals are essential nutrients when in lower concentrations;
however, they become toxic if they are present above the permissible limits (Goldhaber,
2

2003). Continuous exposure to these metals can result in bioaccumulation (Nguyen et al.,
2009) and cause many diseases.
Soil is the non-renewable natural resource and is, therefore, considered as the
foundation of human being's survival and development. It is the most fundamental part of
environment as it acts as a natural buffer between different spheres by controlling the
movement of elements. It is thus extremely important to protect this resource and ensure
its sustainability. Soil quality has been deteriorated by increasing reliance on
agrochemicals coupled with rapid industrialization in developing countries (Iqbal and
Shah, 2011). Heavy metals can be mobilized by changes of environmental conditions land
use, agricultural input, and climatic change.
The toxic metals can be taken up directly by humans and animals through the
inhalation of dusty soil or they may enter the food chain as a result of their uptake by
edible plants and leach down to groundwater and contaminate drinking water resources,
and may cause, in both cases, hazards to the health of human beings and animals. This led
to increasing public concern over the adverse human and ecological health effects of the
increasing accumulation of heavy metal contaminants in the agricultural soils (Wong et
al., 2002; Nicholson et al., 2003).
Intake of heavy metals via the soil-crop system has been considered as the
predominant pathway of human exposure to environmental heavy metals in agricultural
area. According to numerous studies, the pollution sources of heavy metals in
environment are mainly derived from anthropogenic sources (Al-Zubi, 2007; Dahal et al.,
2008). In the last few years, the effects of urbanization and industrialization on
accumulation of heavy metals in soils and their distribution have been extensively
studied. Soil pollution is an undesirable change in the physical, chemical and biological
3

characteristics, which reduces the amount of land for cultivation and habitation. Human
health is closely related to the quality of soil and especially to its level of pollution
(Romic and Romic, 2003). Soil acts as a sink and also as a source of pollution with the
capacity to transfer pollutants to groundwater and food chain, and then to the human
and/or animals. The basic chemical properties of soil depend on the types of weathered
rocks of the concerned areas. Food chain translocation of heavy metals is one of the
consequences of soil contaminated with heavy metals, and excessive intake of metals
through consumption of contaminated vegetables and other plants is associated with
human health risks (Khan et al., 2010).
1.2. Problem Statement
Pakistan has diverse climatic settings and has tremendous amount of freshwater
resources (Khan, 1991). Rivers, streams and groundwater, are the major sources for
irrigation which irrigate over 36 million hectares of land in Pakistan (Alam and Naqvi,
2003). It is estimated that Pakistan has 7.8 million hectors of freshwater, including that of
3.1 million hectares of rivers and streams (Naik, 1985). Pakistan is trying to develop both
the industrial and agricultural sectors to fulfill the demands for local population. Several
environmental problems related to water, air and soil resources have been created due to
the unsystematic industrialization and urbanization. These are caused by the continuous
discharge of untreated industrial effluents and municipal waste into streams and rivers.
Pakistan is facing degradation in the quality of groundwater and surface water due
to industrial, municipal and agricultural sources (UNIDO, 2000). Water quality of Attock
and Haripur basins is also deteriorated due to establishment of two major industrial
estates; Hattar industrial estate and Wah Industrial Complex. The effluents of these two
estates are discharge in local rivers and streams. The streams are the recharge sources of
4

groundwater of the area; therefore, the groundwater quality along with surface water is
degraded day by day.
Irrigation with contaminated water is one of the main causes for vegetable and soil
degradation (Al-Zubi, 2007). Ground and surface water of the area get contaminated due
to rapid urbanization and industrialization. The use of contaminated irrigated water may
result in increased accumulation of HMs in the soils and vegetables (Khan et al., 2008).
The residents of the area are mostly using the ground and stream water for irrigation
purposes and vegetable crops are mainly grown for home consumption and sale to
residential areas of urban and suburban region. There is no empirical data available for
heavy metal contamination of soil and irrigation water and its transfer to vegetable crops
in study area. Also the assessment of heavy metals effects on local community through
consumption of locally growing vegetables and cereals is unknown.
1.3. Aims and Objectives
This research work, in regard to pedo, hydro and biogeochemical investigation of
both Attock and Haripur basins. It is a pioneer report on the subject in the study area. This
study enables us to investigate the trace and heavy metal contamination caused by both
the geogenic and anthropogenic sources. However, the specific objectives of the study
are:
To identify and characterize the waters (surface and subsurface), soils and plants of the
two basins on the basis of their physico-chemical characteristics.
To identify the anomalous concentrations of various trace, heavy and toxic metals in
waters, soils and plants and their relation to possible health hazards of the area.
To characterize hyper-accumulative plant species taxonomically.
5

To determine the sources of pollution, if any, and to suggest the possible remedial
measures for future planning and development of the area.
To use the Geographic Information System (GIS) for data interpretation and to prepare
geochemical maps for the delineation of anomalous zones in various media of the basins.
1.4. Study area
Present environmental geochemical study has been carried out in Attock and
Haripur Basins of Pakistan. Details of both the basins are given below.
1.4.1 Attock Basin
Attock Basin has been known as Campbellpore Basin since 1970 after the name
Campbellpore city, the capital city of the Basin. Now as the name of Campbellpore city
has been changed as Attock, therefore, the name Attock Basin has been used throughout
this thesis. The Attock Basin lies south of Peshawar Basin and is dissected by Attock
Cherat ranges. It is bordered in the north by Indus River, toward south by Kala Chitta
range and in east by Haro River a tributary of the Indus River (Fig.1.1). The basin is
approximately 40 Km broad and 64 Km in length. Southwestward- directed fluvial and
alluvial sedimentation in the Attock basin began at least 1.8 Ma (Burbank, 1982),
possibly in response to the uplift of Kawa Ghar hills, and continued until about 0.6 Ma
(Burbank and Tahirkheli, 1985; Pivnik and Johnson, 1995).
Annual average rainfall is 694 mm. On an average the rainfall is scanty, uncertain
and unevenly distributed and mostly received in monsoon season. It is characterized by
semi-arid climate and the maximum temperature exceeds 45 o C in summer while falls
below 20 o C in winter (Census, 1998).
6

Fig. 1.1. Location map of study area
7

a. Drainage
It is mainly drained by Haro River, with its tributaries such as Nandna, Dhamruh
and Banudra streams. Haro River rises near Donga Gali in Abbottabad enters Rawalpindi
near village Bhallar-top. It cuts across a small portion of Rawalpindi tehsil and then
enters Attock tehsil. Total drainage area of Haro River is 3059 km 2 . It varies in elevation
from about 240 to 690 m above mean sea level (Khan et al., 2002). Vegetation is sparse,
except in certain higher areas where it is under thick forest. This river enters into plains at
Sanjawal. Attock Basin generally has very little and uncertain rainfall varying from year
to year. River Indus passes through Attock Basin without irrigating the adjoining areas of
the basin.
b. Population and domestic water supply
According to census report 1998, the total population of Attock Basin is 0.15
million, of which 21% is urban population while 79% is rural population. This population
obtained the drinking water from various sources which includes 43.31% tape water,
7.82% hand pumps, 21.92% motor pumps, 22.97% dug wells and 3.99% others sources
(District census, 1998).
1.4.2. Haripur Basin
Haripur Basin is a vast alluvial plain lying at the north-eastern side of Attock
Basin (Fig. 1.1). It is located between latitude 34´08´´ N and 33´15´´ N and longitude
72´45´´E and 73´15´´E. Haripur Basin is approximately 53 km long, 32 km wide and
covers 644 Km 2 . It is characterized by semi-arid climate and has extreme temperature in
both summer and winter. Basin topography ranges from 375 meters to 970 meters above
8

the sea level. The surface of the basin is fairly plain with an average gradient of 20 meter
per km; however, along the boundary of the plain the gradient is steeper (Jones, 1992).
a. Drainage
The Haripur Basin is mainly drained by Dor river, along with Haro river and two
streams named as Jabbi kas and Soka Nala. The Dor river is originated from hills 20km
northwest of Havelian which primarily drains the northern part of the basin. Soka nallah
drains the northern region of basin and falls into Tarbella Lake. Jabbi Kas stream drains
the central part of the basin and falls into Haro river which drains the southern part of the
basin.
b. Population and domestic water supply
According to population and census report (1998), estimated population density in
the basin is 0.69 million. Among these 88% are living in rural areas while 12% are living
in urban areas. According to an estimate, 67.76% of population of Haripur Basin has tap
water facility while 2.61% use water from hand pumps, 3.48% motor pumps, 17.67 dug
wells and 8.48% others sources (District census, 1998).
1.5. Geology of the Area
The surrounding areas of Attock and Haripur basins can be divided into three
tectonic blocks (Fig.1.2). The southern block is referred to as the Kala Chitta- Margala
hill block. The central and northern blocks are known as the Nathia Gali Hissarthang
block and the Punjal- Khairabad block respectively (Pogue et al., 1999) (Fig. 1.2).
9

1.5.1. Punjal- Khairabad block
Punjal- Khairabad block is composed of Proterozoic, Paleozoic and Mesozoic
formations. These are briefly described below.
a. Proterozoic formations
The oldest exposed rocks of Proterozoic age in this block are known as Gandaf
Formation located, 3 km north of the Tarbella dam. These are also exposed in the
Gandghar range where these have transitional contact with the overlying Manki
Formation. These rocks are mainly carbonaceous and calcareous phyllite and schist and
carbonaceous marble. Manki Formation consists of argillite, slate, phyllite and
argillaceous meta-siltstone. It is overlain by Shahkot Formation (limestone), Utch Khattak
Formation (slate and argillite), and Shekhai Formation (dolomite and arenaceous
limestone and marble) (Hussain, 1984; Yeats and Hussain, 1987). The Tanawal
Formation consists of feldspathic sandstone, siltstone and shale. It is exposed near
Tarbella dam.
b. Paleozoic and Mesozoic formations
The Paleozoic strata are exposed in the northwestern margin of the Attock Basin.
Ambar Formation of early Cambrian age is exposed in this section (Pogue et al., 1999). It
overlies the Tanawal Formation and lithologically similar to the Sibran Formation of the
Abbottabad group.
1.5.2. Nathia Gali- Hissartang Block
Nathia Gali- Hissartang block is composed of Proterozoic, Cambrian, Mesozoic
and Tertiary age. These are briefly discussed below.
10

Fig. 1.2. Geological map of study area (Adopted from Pogue et al., 1999)
11

a. Proterozoic formations
The oldest rocks of the Proterozoic age exposed in this block belong to the Hazara
Formation. Shale and sandstone are the dominated lithologies of this formation. The
Dakhner Formation of Attock Cherat range is lithologically identical to the southern
Hazara Formation (Yeast and Hussain, 1987). The exposed thicknesses of both
formations are more than 1000m.
b. Cambrian formations
Near Abbotttabad, rocks are subdivided into three formations such as Sibran,
Kakul and Tanawal formations. The Kakul and Sibran formations are part of Abbottabad
group. Kakul Formation consists of Tanakki conglomerates which are derived primarily
from the overlying Hazara Formation (Latif, 1974; Pogue et al., 1999). Tanawal
Formation consists of a lower Galdanian member composed of siltstone, mudstone,
glauconitic and phosphatic shale and siltstone.
c. Mesozoic formations
Mesozoic Datta Formation present at northeast of Abbottabad, consists of shale
and sandstone. The overlying Shinwari Formation consists of shale interbedded with
limestone. Middle Jurassic Samana Suk Formation consists of limestone (Calkin et al.,
1975).
d) Tertiary formations
Paleocene rocks unconformably overlie the Jurrasic Samana Suk Formation near
Hassan Abdal. Shale of the Patala Formation is the youngest bedrock in this area (Latif,
1970).
12

1.5.3. Kala Chitta- Margalla hill block
Kala Chitta- Margalla hill block is composed of Paleocene, Cambrian, Cenozoic
and Mesozoic age. These are briefly discussed below.
a). Plaeocene formations
The Hangu Formation dominantly white quartzitic sandstone. In Kala chitta range,
it overlies disconformably over the Kawagarh Formation. Oldest exposed rocks in this
block are limestone and marl of lower Triassic Mianwali Formation. Jabbi and Kingriali
formations overlie the Mianwali Formation. They are composed of middle to upper
Triassic limestone and dolomite. The Jurassic Samana Suk formation is present in east of
Kala Chitta range. The Rocks of the Margalla hill range in this block age from Jurassic to
Paleocene and are of sedimentary origin. The various lithological units are described as
under:
b). Cenozoic formations
Hangu Formation mainly consists of grey to reddish brown, weathers dark rusty
brown, fine-to coarse-grained, pisolitic and ferruginous. In certain places this Formation
has intercalations of calcareous sandstone and argillaceous limestone. The Hangu
Formation is Early Paleocene in age. Lockhart Formation confirmable overlies the Hangu
Formation. It consists of predominantly marine limestone and subordinate intercalations
of marl and shale. Limestone is pale-grey to dark-grey, medium-grained, and thick-
bedded. It is at places nodular, hard, bituminous, and fossiliferous. Marl is grayish-black
and fossiliferous. The shale is olive, gray to greenish-gray and has weakly developed
cleavage.
13

c). Mesozoic formations
Chichali Formation comprises of mainly sandstone and shale. Sandstone is
greyish-green to dark-yellowish green, glauconitic, and massive hard. Shale is greenish
black, thin bedded and fissile. It has grey silty glauconite shale in the lower part. It is of
Late Jurassic age. Lumshiwal Formation is generally grey, thick-bedded to massive-
bedded feldspathic and ferrogenous sandstone. However, it contains silty or sandy
glauconitic shale in the basal part. This Formation grades into marine sequence of
sandstone, siltstone and shelly limestone. Samana Suk Formation is composed of thin-to
medium-bedded limestone but at places it is shelly or dolomitic limestone with
interbedded marl and shale. The limestone and dolomite belong to marine environment
and deposited on a continental shelf. The limestone is brownish-grey to yellowish grey. It
is oolitic biomicritic, and intrasparitic. Its contact with overlying Lumshiwal Formation is
unconformable; however, the base is not exposed.
1.6. Anthropogenic activities and sources of pollution
The study area is densely populated and house a significant number of industrial
units in urban areas, whereas, rural areas are intensively used for agricultural purposes
(Fig. 1.1). Major industrial activities are concentrated in Hattar Industrial Estate (HIE)
and Wah Industries Complex (WIC). The Hattar Industrial Estate consists of
approximately 117 industries and is extended on 700 acres (Sial et al., 2006). The major
industries consist of ghee industry, chemical (sulfuric acid, synthetic fiber) industry,
textile industry and pharmaceuticals industry. Most of the industries discharge their
effluents without any treatment into drains that directly or indirectly fall into Chahari Kas
stream (Fig. 1.1). Wah Industrial Complex consists of large number of industrial units
which are producing brass, copper, acids, and different kinds of weapons. The effluents of
14

WIC are discharged in Dhamrah Kas and Kala Kas streams (Fig. 1.1). There are lots of
other small industries in area, like marble, glass and textile industries etc. (Khan and
Malik, 1993; 1995).
15

2.1. Field investigations
2.1.1. Water sampling
CHAPTER 2
MATERIALS AND METHODS
Water samples were collected from groundwater (both dug wells and tube wells)
and surface water (rivers and their tributaries and streams) sources throughout the study
area. Among these, 61 groundwater and 9 surface water samples were collected from
Haripur Basin and 50 groundwater samples and 11 surface water samples were collected
from Attock Basin (Fig. 2.1).
To avoid any chance of contamination, the cleaned newly purchased polythene
sampling bottles were treated with 5% HNO3 and then rinsed with double dionized water.
The temperature, pH and electrical conductivity (EC) of each water sample were
measured on the spot by using thermometer and Consort Electrochemical Analyzer,
respectively. Water samples were collected from each site in two clean polythene bottles.
One was used for analysis of anions and physiochemical parameters, while another bottle
was acidified with few drops of 0.5% HNO3 for analysis of various light, heavy and trace
elements. These water samples were properly coded and transferred to the Geochemistry
Laboratory of National Centre of Excellence in Geology, University of Peshawar,
Peshawar, Pakistan.
2.1.2. Soil sampling
About one kilogram topsoil sample was collected up to a depth of about 0-20 cm,
by auger from each representative sample site (Fig. 2.2). The color and texture of these
samples were noted at the site. These soils samples were properly labeled, stored in Kraft
16

Fig. 2.1. Location map of water sampling points in study area.
17

Fig. 2.2. Location map of soil sampling points in study area.
18

papers and transferred to the Geochemistry Laboratory for further processing and
analysis.
2.1.3. Plant sampling
Different types of plants species in the study area were uprooted and cut by using
stainless steel scissors/cutter. These were indentified and characterized with the help of
taxonomist at the site. The plant samples were properly packed and transported to the
Geochemistry laboratory for further processing and analysis.
2.2. Analytical Procedure
The non acidified water samples were used for the determination of physio-
chemical parameters within the 48 hours of sampling. Nitrate (NO3 - ), sulphates (SO4 2- )
and chloride (Cl - ) in the water samples were determined by HACH DR-2800 photometer.
The acid-treated water samples were analyzed for light (i.e. Na, K, Ca, Mg) and heavy
(i.e. Hg, Fe, Mn, Pb, Zn, Ni, Cr, Co, Cd, As) elements using Perkin Elmer 700 Flame
atomic absorption spectrometer (FAAS) equipped with graphite furnace (GF) and
Hydride generation system (HGS).
2.2.1. Water analysis
I. Determination of physio-chemical parameters
a. Temperature
One of the important physical aspects of water quality is its temperature.
Temperature of both surface and groundwater was determined in the field by inserting
thermometer directly into samples at the sampling point, having a quick and precision
response possessing 0.1 o C divisions.
19

. pH
pH of water samples was determined at sampling site by using field pH meter and
confirmed again in laboratory by using Consort Electrochemical Analyzer. The normal
range for pH in surface water systems is 6.5 to 8.5 and for groundwater systems 6 to 8.5.
The pH of pure water (H2O) is generally 7 at 25 o C.
c. Electrical conductivity (EC)
Electrical conductivity is the common indication of water quality and is consider
as important parameter of irrigation and industrial purposes. EC was measured in
microsiemens/cm (μS/cm) by using Consort Electrochemical Analyzer.
d. Total dissolve solids (TDS)
Total dissolve solids comprise inorganic salts (principally calcium, magnesium,
potassium, sodium, bicarbonates, chlorides and sulfates) and small amounts of organic
matter that are dissolved in water. Groundwater with a TDS value less than 300 mg/L can
be considered as excellent for drinking purpose (WHO, 2008). TDS of water samples
were measured in mg/L by using Consort Electrochemical analyzer.
e. Total Hardness
Total hardness is expressed as mg/L of CaCO3. Water hardness was calculated as
amount of dissolved calcium and magnesium in water (APHA, 1992) by using the
equation:
Hardness mg/L = (Ca × 2.497) + (Mg × 4.118)
20

II. Determination of anions
a. Nitrate
Nitrate is the oxidized form of nitrogen present in water as end product of the
aerobic decomposition of nitrogenous materials. The nitrate of the water samples was
determined by using HACH DR-2800 photometer.
b. Sulphate
photometer.
c. Chloride
The sulphate of the water samples were determined by using HACH DR-2800
Chloride ions are major anions in water and produce salty taste. Silver nitrate
titration method with potassium chromate (K2CrO4) as indicator is used for analysis (Garg
et al., 2000).
Cl - (mg/L) = (volume of AgNO3 x N x 35.5/ volume of sample) x 100
Where N stands for normality of H2SO4
d. Carbonate and Bicarbonate
Carbonate and bicarbonate ions in water samples have been determined by acid
titration. A known volume of water was pipetted into the flask. A drop of phenolpthalein
indicator (1% in 5% alcohol) was added and titrated with 0.01N H2SO4 till the color
disappeared. The reading was noted as Y. To the same flask few drops of methyl orange
were added as indicator and titrated till the appearance of first orange color. The reading
was noted as Z. The CO3 - and HCO3 - were calculated as
21

Milliequivalent per liter of CO3 - = 2Y× 0.01 × 1000/ml of water
Milliequivalent per liter of HCO3 - = (Z-2Y) × 0.01 × 1000/ml of water
III. Determination of light elements in water
a. Calcium (Ca) and Magnesium (Mg)
For the determination of Ca and Mg, 1000 mg/L standard stock solution was
prepared by dissolving 2.47g of CaCO3 and 4.95g of MgCO3 in 50ml of dionized water.
10 ml of conc. HCl was added and the solution was made up to the volume in 1000ml
volumetric flask with deionized water. Working standards of 2.5, 5 and 10 mg/L were
prepared from 1000 mg/L standard stock solution by adding LaO3. Each water sample
was also added the same proportion of LaO3 as was used in the working standard. The
atomic absorption was standardized by the standard instrumental conditions as given in
Table 2.1. After standardizing the instrument, the concentrations of Ca and Mg were
determined in mg/L by aspirating the water samples through nebulizer into the Air-
acetylene flame.
b. Sodium (Na) and Potassium (K)
For the determination of Na and K, 1000 mg/L standard stock solution was
prepared by dissolving 2.542g of NaCl and 1.91g of KCl in dionized water and the
volume was made up to 1000ml in volumetric flask. Working standard solutions of 2.5, 5
and 10 mg/L were prepared from 1000 mg/L standard stock solution. After standardizing
the atomic absorption by the working standards under the standard instrumental
conditions as given in Table 2.1, the concentrations of Na and K were determined in
mg/L in water samples.
22

Table 2.1. Analytical conditions for light elements determination in water on air acetylene flame mood.
Parameters Ca Mg Na K Mn
Mode Absorption Absorption Emission Emission Emission
Wavelength 422nm 285.2nm 589nm 766.5nm 279.5nm
Slit width 0.4nm 0.4nm 0.2nm 0.4nm 0.4nm
Air flow 51/min 51/min 51/min 51/min 51/min
Fuel flow 51/min Best flame 11/min 11/min Best flame
Burner height 10mm 10mm 20mm 20mm 20mm
Detection limit 1.5 0.15 0.3 3 1.5
23

2.2.1.4. Determination of heavy metals
a. Copper (Cu)
For determination of Cu, 1000 mg/L standard stock solution was prepared by
dissolving 1g of copper metal in 30 ml of (1:1) HNO3. This solution was diluted to
1000ml by double deionized water. From the stock solution, working standards of 25, 50
and 100 μg/L were prepared. The graphite furnace atomic absorption was standardized
by the working standards under the standard instrument conditions as given in Table 2.2.
After calibrating the instrument, the concentration of copper in μg/L was determined in
each water sample using auto-sampler.
b. Iron (Fe)
Standard stock solution of 1000 mg/L was prepared by dissolving 1g pure iron
metal in minimum quantity of HCl in 1000 ml volumetric flask and was made up to the
mark with deionized water. Working standards of 25, 50 and 100 μg/L were prepared
from the stock solution. The graphite furnace was standardized by the working standards
under the standard instrumental conditions as given in Table 2.2. After standardizing the
instrument, the concentration of iron in μg/L was determined in each water sample using
auto-sampler.
c. Lead (Pb)
For the determination of lead in water samples, 1000 mg/L of Pb standard stock
solution was prepared by dissolving 1.598 g of lead nitrate (Pb(NO3)2) in 200 ml of
deionized water in volumetric flask. Then added 10 ml of conc. HNO3 and diluted the
resulting solution to 1000 ml with deionized water in volumetric flask. 50, 100 and 200
μg/L working standards were prepared from the standard stock solution.
24

Table 2.2. Analytical conditions for heavy metal determination in water samples by graphite furnace.
Parameter Cu Fe Pb Zn Ni Cr Co
Mode Absorption Absorption Absorption Absorption Absorption Absorption Absorption
Wavelength 325.8nm 248.3nm 283.3nm 213.9nm 232.0nm 357.9nm 240.7nm
Slit width 0.7nm 0.2nm 0.7nm 0.7nm 0.2nm 0.7nm 0.2nm
Tube/site Pyro/Platform Pyro/Platform Pyro/Platform Pyro/Platform Pyro/Platform Pyro/Platform Pyro/Platform
Matrix modifier Nil 0.05mg (NO3)2 0.05mg H4H2PO4 0.05mg H4H2PO4 0.05mg (NO3) 2 0.05mg (NO3) 2 0.05mg (NO3) 2
Pretreated T 0 C 1200 1400 1200 1200 1400 1600 1400
Atomization T 0 C 2300 2400 2300 2300 2500 2500 2500
Detection limit 0.014 5 0.05 0.02 0.07 0.004 0.15
25

The graphite furnace was set under analytical conditions for Lead (Pb) as given in
Table 2.2. After proper standardizing the instrument, the concentration of lead in μg/L
was determined by graphite furnace using auto-sampler.
d. Zinc (Zn)
For determination of Zn in water samples, 1000 mg/L of Zn standard stock
solution was prepared by dissolving 100 mg of zinc metal in 20 ml of (1:1) HCl and
diluted the resulting solution to 1000 ml with deionized water in volumetric flask. The
standard solutions of 25, 50 and 100 μg/L were prepared from the standard stock solution.
The graphite furnace was standardized by the working standards under the standard
instrumental conditions as given in Table 2.2. After standardizing the instrument, the
concentration of Zn in μg/L was determined by graphite furnace using auto-sampler.
e. Nickel (Ni)
1000 mg/L of Nickel stock solution was prepared by dissolving 1 gram of Ni
metal in a minimum volume of (1:1) HNO3 and diluted to 1 litre with deionized water.
Working standards of 25, 50 and 100 μg/L were prepared from the standard stock
solution. The graphite furnace was standardized by the working standards under the
standard instrumental conditions as given in Table 2.2. After standardizing the
instrument by using working standards, the concentration of Ni in μg/L was determined
by graphite furnace using auto-sampler.
f. Chromium (Cr)
For determination of Chromium, 1000 mg/L standard stock solution was
prepared by dissolving 3.735 g of K2CrO4 in deionized water and diluting to one litre.
Working standards of 25, 50, and 100 μg/L were prepared from the standard stock
26

solution. Analytical conditions for Cr on graphite furnace were set as given in Table 2.2.
After standardizing the instrument by the working standards, the concentration of Cr in
μg/L was determined by graphite furnace using auto-sampler.
g. Cobalt (Co)
For determination of Cobalt, 1000mg/L standard stock solution was prepared by
dissolving 1g of cobalt metal in 30 ml of (1:1) HCl and was diluted to one liter with
deionized water. Working standards of 25, 50, and 100 μg/L were prepared from standard
stock solution. Analytical conditions for Co on graphite furnace were set as given in
Table 2.2. After standardizing the instrument by the working standards, the concentration
of Co in μg/L was determined by graphite furnace using auto sampler.
h. Mercury (Hg) and Arsenic (As)
Mercury (Hg) and Arsenic (As) in water samples were determined by atomic
absorption using hydride generation system (HGS) under the standardized instrument
conditions. In case of arsenic the water samples were pre-reduced by adding 1 ml
Potassium Iodide solution (KI solution) per 10 ml of the water sample in 5 mol/l HCl and
kept for 30 min to complete the reaction before running through HGS.
2.2.2. Soil and plant analysis
I. Preparation of soil samples
a. Pulverizing of soil samples
Soil samples were air-dried and organic matters were removed. These were then
sieved through a 2-mm sieve. Each sample was homogeneized and then representative
portion was selected by quartering and coning. This portion was then pulverized in a
27

tungsten carbide ball mill to 200 mesh size. The powered samples were stored in air tight
bottles and were kept in oven at 110 0 C for two hours to remove moisture. The samples
were cooled by placing in desiccator.
b. Preparation of solution for major elements
0.5g of each dried pulverized soil sample was taken in Teflon beaker and 10 ml of
hydrofluoric acid (HF) and 4 ml of perchloric acid (HClO4) was added and placed on hot
plate at low heat. After one hour 2 ml perchloric acid was added again and the sample
was evaporated till the dry paste was obtained. 10 ml of deionized water and 4 ml of
perchloric acid were added and heated for 10 minutes (Jeffery and Hutchison, 1986).
Sample was removed from hot plate and diluted up to 250 ml in volumetric flask. This
solution was kept for the determination of the Ca, Mg, Fe, Mn, Na and K by using atomic
absorption spectrometer.
c. Preparation of solution for heavy and trace elements
I gram of each dried pulverized soil sample was taken in Teflon beaker and 15 ml
Aqua regia (1HNO3:3HCl) was added. The sample was heated on hot plate till the
complete evaporation. 20 ml of 2 N hydrochloric acid (HCl) was added and heated for a
while, then the solution was diluted to 30 ml with deionized water and filtered (Jeffery
and Hutchison, 1986). This filtrate was kept for the determination of Cu, Pb, Zn, Ni, Cr,
Co, and Cd by using flame atomic absorption spectrometer.
II. Preparation of plant samples
a. Pulverizing of plant samples
28

The plant samples were washed with deionized water to remove dust and then
oven dried for 48 hours at 60 0 C in oven. The dried samples were cut in small pieces and
pulverized in grinder.
b. Preparation of solution for plant samples
2g of dried plant powdered sample was taken in a beaker and kept for 24 hours
after adding 10 ml of nitric acid HNO3. It was then heated carefully till the production of
HNO3 fumes ceased. 4ml of perchloric acid (HClO4) was added and heated till a small
volume left. After cooling, 10ml of Aqua-regia was added and heated again till a small
volume left. The beaker content was then filtered and made the volume to 50 ml with
deionized water in a 50ml volumetric flask (Perkin- Elmer, 1982). This solution was kept
for determination of both trace and major elements by using atomic absorption
spectrometer.
2.2.3. Determination of physical parameters in soil
a. pH
pH in the soil samples was determined by using the method of Page et al., (1982).
About 50 gram of air dry soil was taken in a glass beaker and 100 ml of distilled water
was added. The content was mixed thoroughly by shaker and allowed to stand for one
hour. The pH of saturated soil paste was recorded by using Consort Electrochemical
Analyzer which was calibrated with buffers solution pH 4, 7 and 9.
b. Electrical conductivity (EC)
Electrical conductivity of soil paste was recorded by using Consort
Electrochemical Analyzer conductivity meter after standardization with 0.01 N KCl
solution (Page el al., 1982).
29

2.2.4. Determination of major elements in soil and plant samples
Perkin Elmer atomic absorption spectrometer was used for determination of major
elements (i.e. Ca, Mg, Na and K) in both soil and plant samples.
a. Calcium (Ca) and Magnesium (Mg)
For the determination of Ca and Mg, 1000 mg/L standard stock solution was
prepared by dissolving 2.47g of CaCO3 and 4.95g of MgCO3 in 50ml of dionized water,
10 ml of conc. HCl was added and after this the solution was made up to volume in
1000ml volumetric flask with deionized water. Working standard solutions 2.5, 5 and 10
mg/L were prepared from the 1000 mg/L standard stock solution. The LaO3 solution was
added to standards and samples in same proportion. The atomic absorption was
standardized with analytical conditions as given in Table 2.3. After standardizing the
instrument by working standards, the concentrations of Ca and Mg in mg/Kg were
determined in both soil and plant samples through air acetylene flame mode by atomic
absorption spectrometer.
b. Sodium (Na) and Potassium (K)
For determination of Na and K, 1000 mg/L standard stock solution was prepared
by dissolving 2.542g of NaCl and 1.91g of KCl in dionized water and the volume made
up to 1000ml in volumetric flask. Working standards of 2.5, 5 and 10 mg/L were prepared
from 1000 mg/L standard stock solution. The atomic absorption was standardized by the
analytical conditions as presented in Table 2.3. After standardizing the instrument by
working standards, the concentrations of Na and K in mg/Kg were determined in both soil
and plants samples by atomic absorption spectrometer in air acetylene flame mode.
30

2.2.5. Determination of heavy and trace elements
a. Copper (Cu)
For the determination of Cu, 1000ml standard stock solution was prepared by
dissolving 1g of copper metal in 30 ml of (1:1) HNO3. This solution was diluted to
1000ml by double deionized water. From the stock solution, working standards of 2.5, 5
and 10 mg/L were prepared. Analytical conditions for Copper (Cu) were set as given in
Table 2.3. After standardizing the instrument by working standards, the concentration of
Cu was determined in mg/Kg in both soil and plant samples by atomic absorption
spectrometer in air acetylene flame mode.
b. Iron (Fe)
Standard stock solution of 1000 mg/L was prepared by dissolving 3.51g of Mohr’s
salt [Fe(NH4)2(SO4)2.H2O] in deionized water in 1000 ml volumetric flask. Working
standards of 2.5, 5 and 10 mg/L were prepared from stock solution. Analytical conditions
for Fe were set as provided in Table 2.3. After standardizing the instrument by working
standards, the concentration of Fe in mg/Kg was determined in both soil and plant
samples by atomic absorption spectrometer in air acetylene flame mode.
c. Manganese (Mn)
Standard stock solution of 1000 mg/L was prepared by dissolving 4.058g
MnSO4.4H2O in 20 ml of IN H2SO4 and diluted the resulting solution to 1000 ml with
deionized water in volumetric flask. The working standards of 2.5, 5 and 10 mg/L were
31

Table 2.3. Analytical conditions for major, heavy and trace elements determination in soil and plant samples on air acetylene flame mood.
Element Wavelength Slit width Air flow Fuel flow Lamp current Energy
(nm) (mm) (L/min) (L/min) (mA)
Ca 422.7 0.7 17 2 10 63
Mg 285.2 0.7 17 2 6 64
Na 589 0.2 17 2 8 79
K 766.5 0.7 17 2 12 92
Cu 324.8 0.7 17 2 15 68
Fe 248.3 0.2 17 2.3 25 25
Mn 279.5 0.2 17 2 30 38
Pb 283.3 0.7 17 2 10 46
Zn 213.9 0.7 17 2 15 45
Ni 232 0.2 17 2 25 46
Cd 228 0.7 17 2 6 66
Cr 357.9 0.7 17 2.5 25 75
Co 240.7 0.2 17 2 30 50
32

prepared from stock solution. Analytical conditions for Mn were set as provided in Table
2.3. After standardizing the instrument by working standards, the concentrations of Mn in
mg/Kg was determined in both soil and plant samples by atomic absorption spectrometer
in air acetylene flame mode.
d. Lead (Pb)
For the determination of lead, 1000 mg/L of Pb standard stock solution
was prepared by dissolving 1.598g of lead nitrate (Pb(NO3)2) in 200 ml of dionized water
in volumetric flask. Then added 10 ml of conc. HNO3 and diluted the resulting solution to
1000 ml with deionized water in volumetric flask. 2.5, 5 and 10 mg/L working standards
were prepared from standard stock solution. Analytical conditions for Pb were set as
given in Table 2.3. After standardizing the instrument by working standards, the
concentrations of Pb in mg/Kg were determined in both soil and plant samples by atomic
absorption spectrometer in air acetylene flame mode.
e. Zinc (Zn)
For determination of Zn in water samples, 1000 ml of Zn standard stock solution
was prepared by dissolving 100 mg of zinc metal in 20 ml of (1:1) HCl and diluted the
resulting solution to 1000 ml with deionized water in volumetric flask. The working
standards of 2.5, 5 and 10 mg/L were prepared from standard stock solution. Analytical
conditions for Zn were set as presented in Table 2.3. After standardizing the instrument
by working standards, the concentrations of Zn in mg/Kg were determined in both soil
and plant samples by atomic absorption spectrometer in air acetylene flame mode.
33

f. Nickel (Ni)
1000 mg/L standard stock solution of Ni was prepared by dissolving 1 gram of Ni
metal in a minimum volume of (1:1) HNO3 and diluted to 1 liter with deionized water.
Working standards of 2.5, 5 and 10 mg/L were prepared from the standard stock solution.
Analytical conditions for Ni were set as given in Table 2.3. After standardizing the
instrument by using working standards, the concentrations of Ni in mg/Kg were
determined in both soil and plant samples using atomic absorption spectrometer in air
acetylene flame mode.
g. Chromium (Cr)
For the determination of Cr, 1000 mg/L standard stock solution was prepared by
dissolving 3.735 g of K2CrO4 in deionized water and diluting to one liter. Working
standards of 2.5, 5 and 10 mg/L were prepared from standard stock solution. Analytical
conditions for Cr were set as presented in Table 2.3. After standardizing the instrument by
working standards, the concentrations of Cr was in mg/Kg were determined in both soil
and plant samples by atomic absorption spectrometer in air acetylene flame mode.
h. Cobalt (Co)
For determination of Co, 1000 mg/L standard stock solution was prepared by
dissolving 1g of cobalt metal in 30 ml of (1:1) HCl and was diluted to one liter with
deionized water. Working standards of 2.5, 5 and 10 mg/L were prepared from standard
stock solution. Analytical conditions for Cobalt (Co) were set as given in Table 2.3. After
standardizing the instrument by working standards, the concentration of Co was in mg/Kg
was determined in both soil and plant samples by atomic absorption spectrometer in air
acetylene flame mode.
34

2.2.6. ICPMS
Plant samples, used as vegetable and cereal, and their related soil samples were
selected for experimental work at the Department of Biological and Environmental
Sciences, University of Aberdeen, Aberdeen, United Kingdom under the International
Research Support Initiative Program (IRSIP). Before analyzing the samples through
ICPMS 7500 (Agilent Technologies, Tokyo, Japan) the following digestion methods were
adopted for the preparation of plant and soil solution extracts.
a. Preparation of plant samples for ICP-MS
For plant digestion, 0.2 g of plant shoot and root samples were weighed into 50 ml
polypropylene digest tubes and 2 ml of HNO3 was added and left to stand overnight. Then
2 ml of hydrogen peroxide was added and the samples were digested using a microwave
oven (CEM Mars 5, CEM Corp., Matthews, NC). The temperature was raised to 55 0 C
held for 10 min, then to 75 0 C held for 10 min, and finally to 95 0 C for 30 min, and then
allowed to cool to room temperature (Marwa et al., 2012). Aristar grade reagents were
used throughout the analysis. Nitric acid and hydrogen peroxide were obtained from
VWR International and 1000 mg/L standards of the elements measured was obtained
from Merck.
CTA-OTL-1- Oriental tobacco leaves CRM was used to validate the analyses.
Quality controls of CRMs, spikes and blanks were run with each plant digest batch of 30
samples, which were analyzed in according to a randomized order. The concentrations of
trace elements in solution were determined by ICP-MS 7500 (Agilent Technologies,
Tokyo, Japan). Standards were run after every set of 30 samples, 10% of samples were
digested and analyzed in duplicate.
35

. Preparation of soil samples for ICP-MS
For soil digestion, 0.1 g soil samples were weighed into quartz glass tubes and 2.5
ml of nitric acid was added and left to stand overnight. 2.5 ml of hydrogen peroxide was
added to it and was digested on the block digester at 100 0 C for 1 h, then at 120 0 C for 1 h
and finally at 140 0 C until the sample was fully digested (Adomako et al., 2009).
NCS ZC 73007 soil CRM was used to validate the analyses. Quality controls of
CRMs, spikes and blanks were run with each soil digest batch of 30 samples, which were
analyzed in according to a randomized order. The concentrations of trace elements in
solution were determined by ICP-MS 7500 (Agilent Technologies). Standards were run
after every set of 30 samples, 10% of samples were digested and analyzed in duplicate.
36

CHAPTER 3
LITERATURE REVIEW
The rapid industrialization, development and urbanization have directly affected the
environment. The degradation and contamination of the ecosystem has, today become a key
threat for all life on earth. It is not only the fault of industrialization only but also the
mismanagement and lack of the planning, especially in Pakistan, which has lead humanity to
the point where the environment that once sustain life is now indication of decay, disease and
death.
Globally the lithosphere and hydrosphere has been contaminated with heavy metals
through various human activities which have become a major human health hazard. In
Pakistan, heavy metal contaminated soils and surface and ground water is increasingly due to
rapid industrialization and increase used of pesticides and fertilizers in agricultural activities.
Drinking water is derived either from surface or groundwater. But the groundwater
has more importance as 65% of Europe while 49% of USA population is using groundwater
for drinking purpose. However, water is rarely found uncontaminated. The intensive
agricultural activities also contribute to the addition of contaminant trace elements in soils
and groundwater due to the use of fertilizers and pesticides (Huang et al., 2006). Lot of
researches have been carried out throughout the world to characterize of the water and soil
quality. Salient findings of such research studies are reviewed here.
Afzal et al. (2000) studied water quality parameters of Hudiara drain. This
investigation revealed that all parameters e.g. Chemical oxygen demand (COD), Biological
oxygen demand (BOD), Total organic carbon (TOC), pH, Suspended solids (SS), Fecal
coliform (FC) and trace metals are present in higher concentration. The concentrations varied
due to small village drains and industrial effluents. Concentration of NO3-N, Se and Fe were
37

found to be more than WHO guidelines in 30% samples. Major pollutants were SS, COD and
FC. They suggested that the drainage network can be converted to sediment and storage
reservoir. The runoff water can be used for irrigation after disinfection.
Mastoi et al. (2008) investigated water quality of Manchar lake located in Sindh
(Pakistan). Physico-chemical parameters, cations, anions and seven trace metals i.e. Cu, Ni,
Zn, Co, Fe, Pb and Cd were analyzed in water samples of Nara valley drain and Manchar
lake. The pH, Pb, and Cd were found higher than the WHO guidelines for drinking water
quality. The water quality of lake is degraded day by day due to anthropogenic activities.
Arain et al. (2009) determined arsenic levels in sediment, soil, lake water,
groundwater, grain crops, vegetables and fish from selected areas of Sindh, Pakistan. The
results showed that the contamination by arsenic exceeded WHO guidelines. The
concentration of As in lake sediment and agricultural soil samples ranged between 11.3-55.8
and 8.7-46.2 mg/Kg, respectively. It was observed that the leafy vegetables (spinach,
coriander and peppermint) contain higher As levels (0.90-1.20 mg/Kg) as compared to
ground vegetables (0.048- 0.25) and grain crops (0.248-0.367 mg/Kg) on dried weight basis.
The estimated daily intake of total As in the diet was 9.7–12.2 µg/Kg body weight/day.
Krishna et al. (2009) was applied multivariate statistical approach for assessment of
heavy metals in industrial area of Patancheru, Medak district, India. 53 sampling points from
ground and surface water were investigated for 13 parameters including trace elements.
Different statistical techniques like R-mode, Factor analysis (FA) and PCA were used for
source identification. In groundwater, 2 factors explaining 85% variance and four factors
explaining 75% of total variance in surface water was found. Sr, Ba, Co, Ni, and Cr were
associated with anthropogenic and geogenic sources while Fe, Mn, As, Pb, Zn, B and Co
were originated from anthropogenic activities.
38

Mora et al. (2009) surveyed the trace metal concentration in rural population of
Venezuela. They found that all the metals were found within the Venezuelan and
international guidelines of quality criteria for drinking water except the calcium and
magnesium concentration.
Barati et al. (2010) investigated 8 trace elements in drinking water sources in villages
of Kurdistan Province, Iran. The concentration of As, Cd and Se exceeded WHO guideline in
28 drinking water sources. The main disorder and their prevalence were found as 86.1%
Mee`s line, 77.2% Keratosis and 67.8%, pigment disorder. This study also showed
relationship between, arsenic concentration, disorder and living duration in the village of
Kurdistan Province.
Bhuiyan et al. (2010) have evaluated sources and intensity of pollution in drinking
and irrigation water system of north western region of Bangladesh using statistical techniques
like Principal component analysis (PCA) and Cluster analysis (CA). The physicochemical
parameters and heavy metal concentrations exceeded the permissible limits of international
and Bangladesh standards. Heavy metal pollution index (HPI) and degree of contamination
though correlated but exhibit different results. The results showed that about 50% of the
mine drainage, irrigation and groundwater were contaminated in a range of moderate to high
contamination. Pollution by coal mining was considered the major environmental and health
issue in the area.
Facchinelli et al. (2001) reported the soil contamination on a regional scale in
Piemonte (NW Italy). Multivariate statistic approaches (PCA and CA) were adopted for data
treatment, allowing the identification of three main factors controlling the heavy metal
variability in cultivated soils. They used geostatistics to construct regional distribution maps,
to be compared with the geographical, geologic and land use regional database by using GIS
39

software. This approach, evidencing spatial relationships, proved very useful to the
confirmation and refinement of geochemical interpretations of the statistical output. Cr, Co
and Ni were associated with and controlled by parent rocks, whereas Cu together with Zn,
and Pb alone were controlled by anthropogenic activities.
Li et al. (2001) reported that due to rapid urbanization and scarcity of land, most of
the urban parks and recreational areas in Hong Kong were built close to major roads or
industrial areas, where they were subject to many potential pollution sources. The results of
the total concentrations of heavy metals indicated that urban soils in Hong Kong were having
elevated concentrations of Cd, Cu, Pb and Zn. High Pb contamination was found due to the
traffic emissions and industrial activities, while high Cd contamination was found due to
phosphate fertilizers. The chemical partitioning results showed that Pb and Zn were mainly in
the carbonate and Fe-Mn oxide phases, while Cu was largely associated with the organic and
sulphide fractions.
Input of heavy metals in agricultural soils of England and Wales was investigated by
Nicholson et al. (2003). The major sources causing pollution were livestock manure,
atmospheric deposition, inorganic fertilizers and industrial waste water. 25- 85% input was
centralized by atmospheric deposition. Livestock and sewage sludge contributed 37-40% and
8-17%, respectively to total Cu and Zn input in soil. This work contributed to developing the
strategy to reduce heavy metals input to the agricultural soils.
Micó et al. (2006) reported that for soil protection, the characterization of the content
and source of heavy metals in soils are necessary to establish quality standards on a regional
level that allow the detection of sampling sites affected by pollution. The surface horizons of
54 agricultural soils under vegetable crops in the Alicante province (Spain), were sampled to
determine the contents of Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn. Multivariate analysis (PCA
40

and CA) was performed to identify a common source for heavy metals. Moreover, soil
properties were determined in order to characterize agricultural soils and to analyze
relationships between heavy metal contents and soil properties. The content of Co, Cr, Fe,
Mn, Ni and Zn were associated with parent rocks and corresponded to the first principal
component called the lithogenic component. A significant correlation was found between
lithogenic metals and some soil properties such as soil organic matter, clay content, and
carbonates, indicating an important interaction among them. On the other hand, elements
such as Cd, Cu and Pb were related to anthropogenic activities and comprised the second (Cu
and Pb) and third principal components (Cd), designated the anthropogenic components.
Generally, Cd, Cu and Pb showed a lower correlation with soil properties due to the fact that
they remain in available forms in these agricultural soils.
Al-Zubi (2007) investigated the importance of irrigation water for soil of Jordon
valley. He assessed the effect of different kinds of irrigation on soil and plant (i.e. one
irrigated with Yarmouk river and other with wastewater from King Talal dam). The result
showed that there was no considerable adverse effect of irrigation water on agricultural
practices.
Sharma et al. (2007) have investigated the effect of waste water irrigation on the soil
and vegetables of Varanasi, India. They reported that leafy vegetables have higher capacity to
accumulate the heavy metals as compared to non leafy vegetables. The study concluded that
the use of wastewater for irrigation has increased the contamination of Cd, Pb, and Ni in
edible portion of vegetables causing potential health risk.
Yang et al. (2007) have investigated the heavy metal concentrations in soil and
vegetables of Chongqing, China. The results showed that soils investigated in this study
were heavily contaminated with cadmium and lead, which exceeded the national (China) and
41

local (Chongqing) background values. None of the heavy metals were found in high
concentration in vegetables with exception of lead concentration of vegetables in the district
of Dadakou.
Arora et al. (2008) investigated heavy metal concentrations in vegetables which were
irrigated by different kinds of water sources. Concentration of heavy metals varies with the
different species of vegetable. Vegetable irrigated with the wastewater showed the highest
concentration of heavy metals. However, the concentrations of heavy metals were found
below the maximum tolerable limit established by FAO/WHO. However, they suggested the
regularly monitoring of the levels of heavy metals in vegetables to avoid the excessive
increase of these metals in food chain.
Li et al. (2009) reported in the heavy metals sources in the coastal soils of Shanghai,
China. They used multivariate statistical methods (PCA, CA, and correlation analysis). Cu,
Ni, Pb, and Cd had anthropogenic sources (e.g., overuse of chemical fertilizers and
pesticides, industrial and municipal discharges, animal wastes, sewage irrigation, etc.). Zn
and Cr were associated with parent materials and, therefore, had natural sources (e.g., the
weathering process of parent materials and subsequent pedogenesis due to the alluvial
deposits). The effect of heavy metals in the soils was greatly affected by soil formation,
atmospheric deposition, and human activities.
Khan et al. (2010) reported high concentrations of heavy metals in soils and
vegetables of the northern areas of Pakistan. These metals were contributed from parent rocks
and the extent of enrichment was in the order of Cd>Pb>Zn>Cu>Ni. The leafy vegetables
were highly enriched with heavy metals because of their greater capability to accumulate
heavy metals from soil but also there were potential health risks for the local residents that
regularly consume heavy metals enriched vegetables. The mean concentrations of heavy
42

metals in various vegetable species collected from the study area were also compared with
the standards set by China, India and FAO/WHO for vegetables and fruits.
Rodrigues et al. (2010) determined water soluble content of arsenic, mercury and
some other toxic elements in sediment and soils of Portugal. Hg concentration was found in
the range of 0.15-3180 mg/Kg and As in the range of 11-6365 mg/Kg. Water soluble fraction
for both arsenic (

fractionation. The health risk to human beings was assessed by determining health risk index
(HRI) and hazard index (HI). Cu, Cr and Ni contamination was found to be of hazardous
level near the plant area. RAC analysis of soil showed a risk of highest level for Ni and a
medium risk for Cu and Cr. In case of rice, Ni was found a major contaminant which was
followed by Cu and Cr. The overall results concluded that Cu and Ni were the key
contaminants which contribute potential health risk for local population.
Shah et al. (2011) estimated trace metals in water and soil samples from a remote
Himalayan region using AAS. The soil samples were analyzed for soluble and acid
extractable fraction of trace metals. In water samples, the dominating contributors were Ca,
Na, Mg and K, and same contributors were also found in water extract of soil samples. In
acid extract of soil samples, the dominating contributors were found as Ca, K, Fe, Mg, Mn
and Na. In water samples, decreasing concentration order was found as
Ca>Na>Mg>K>Pb>Co>Cu>Zn> Mn>Cr>Fe>Cd>Li, however, in acid extract of the soil
samples, following order was noted Ca>K>Fe>Mg> Mn>Na>Pb>Zn>Cr>Li>Cu>Co>Cd.
They also support the fact that the multivariate cluster analysis help in source apportionment
for contamination in soil and water.
Tume et al. (2011) reported the effect of parent material of soil property in central
Catalonia, Spain. They have investigated seven trace and five major metals in surface soil.
Soil formed from lutite had higher concentration of heavy metals as compared to soil formed
from sandstone.
44

4.1. Introduction
CHAPTER 4
WATER CHEMISTRY
The quality of groundwater depends on of all the processes and reactions that
act on the water from the moment it condensed in the atmosphere to the time it is
discharged by a well or spring. Groundwater quality varies from place to place and
with the depth of the water table. Water quality is considered the main factor in
controlling health and the state of disease in both human and animal. Surface water
quality in a region is largely determined both by natural processes (weathering and
soil erosion) and by anthropogenic inputs (municipal and industrial wastewater
discharge) (Singh et al., 2004). The anthropogenic discharges constitute a constant
polluting source, whereas surface runoff is a seasonal phenomenon, largely affected
by climate within the basin (Vega et al., 1996; Singh et al., 2004). The toxic metals in
these effluents are accumulated in the biota, depending on the bioaccumulation factors
of the individual metals, thus constituting a potential source of direct intake to man.
Approximately 25 million persons die every year due to water pollution and it has
become a major problem in many countries (Pimpunchat et al., 2008).
Increasing industrialization and urbanization leads to ever increasing pollution
of rivers in developing countries (Jan et al., 2010). The discharge of effluents and
associated toxic compounds enter the surface water and subsurface aquifers resulting
in pollution of irrigation and drinking water (Manzor et al., 2006; Sial et al., 2006;
Rehman et al., 2008).
45

The scarcity of some basic cations as calcium (Ca) and magnesium (Mg) in
drinking water has been associated with cardiovascular and cerebrovascular diseases
(Yang et al., 1998; Yang et al., 2006). On the other hand, it is well known that high
concentrations trace metals in food and drinking water can provoke serious health
hazards in humans. For example, elevated Cu and Mn in drinking water can cause the
brain disorders Alzheimer’s and Manganism, respectively (Dieter et al., 2005). Lead
(Pb) is linked to damage of brain, kidneys, nervous system and blood cells (Gump et
al., 2008; Jusko et al., 2008; Kim et al., 2011). High intake of Co through
consumption of contaminated food and water, can cause abnormalities in the thyroid
artery, polycythemia and over-production of red blood cells (RBCs) and high intake
of Cd is associated with kidney damage, skeletal damage and itai-itai (ouch-ouch)
disease (Nordberg et al., 2002; Robert and Mari, 2003). Numerous human’s
epidemiological studies have documented the carcinogenic effects including skin
lesions, skin cancer and lung cancer of As entering through drinking water and
inhalation exposure (Arain et al., 2009; Fatmi et al., 2009).
The rivers and streams of Attock and Haripur basins, Pakistan receive untreated
industrial and municipal discharge from different industrial units and urban
settlements. These contaminants are putting pressure on ecological life of these rivers
and streams which are at risk and have been considered as major threat to aquatic
ecosystem, which are ultimately turning into municipal drains (Qadir et al., 2008).
High load of pollutants into the surface and groundwater of the study area are severely
altering the water quality which resulted in degradation of its natural ecosystem. No
previous data and scientific work are available on potential impacts of these polluted
streams on the groundwater and inhabitants of surrounding area. There is a dire need
for comprehensive assessment of variation trends in the quality of both surface water
46

and groundwater of both basins and to address the consequences of present and future
threats of contamination. It is also important that spatio-temporal monitoring of water
quality should be done for future water resource management. A monitoring program
was felt necessary to provide a representative and reliable spatial and temporal dataset
of water quality for future management of drinking water supplied to community.
The main objectives of this research work are
To analyze heavy metals (HMs) concentrations in the surface water and
groundwater of Attock and Haripur basins
To assess the potential health risk via the ingestion of contaminated water
To use the statistical analysis such as principal component analysis (PCA) and
cluster analysis (CA) to find out the similarity and dissimilarities among the
different monitoring stations and to identify possible pollution sources
4.2. Materials and Methods
4.2.1. Sampling and analysis
Water samples were collected from the surface water and groundwater sources
of Attock and Haripur basins (Apendix. Ia). Figure 4.1 shows the location of the
sampling points from the study area. Details of water sampling and chemical analysis
of physiochemical parameters of water quality are given in Chapter 2.
4.2.2. Statistical analysis
Basic statistical analyses were performed using SPSS 17 software and for
graphical representation of water quality data Microsoft Excel 2007 and Sigmaplot
47

Fig. 4.1. Location map of the study area showing the water sampling points
48

were used. Three multivariate techniques such as correlation matrix, hierarchical
cluster analysis (HCA), and principal component analysis (PCA) based on Factor
analysis was used for the water quality assessment and interpretation of the results
(Kazi et al., 2009; Jan et al., 2010; Muhammad et al., 2011). These multivariate
statistical techniques have been widely used in various studies to determine point
sources of elements in water samples and interpretation of chemical/physical
characteristics of water quality parameters (Shrestha and Kazama, 2007; Krishna et
al., 2009; Noori et al., 2010) in comparison to uni-variant techniques that were
applied to process the analytical data in terms of its distribution and correlation
between pairs of metals.
The water quality data set of the surface water and groundwater was subjected
to HCA to identify clusters of the water quality parameters based on their similarity.
Euclidean distances were chosen as a measure of linkage that uses analysis of
variance to evaluate the distances between clusters, attempting to minimize the sum
squares of any two clusters that can be formed at each step (Kent and Coker, 1992).
Pearson correlation was also used to confirm the results of HCA and to find
association between different metals.
The PCA was used to extract a lower dimensional linear structure from the
water quality data set of two spatial groups viz; surface water and groundwater
separately. The main purpose of this analysis was to reduce the contribution of less
significant variables of the water quality parameters, which was achieved by rotating
the axis defined by PCA to produce new groups of variables (varimax factors). PCA
technique starts with the covariance matrix describing the dispersion of the original
variables and extracting the eigen values and eigenvectors (Singh et al., 2005).
49

4.2.3. Health risk assessment
The method developed by US-EPA for the potential non-cancer risk for
individual HM was used in this study and was expressed as hazard quotient (HQ)
HQ= CDI/RfDo
Where, chronic daily intake (CDI) was exposure expressed as concentration of
HM per unit body weight per unit time, mean over a long period of time and RfDo
was the oral reference dose (g L −1 day −1 ). Units of CDI and RfDo were same (US
EPA, 2005).
For calculation of the chronic daily intake (CDI) following formula had been
adopted from Chrostowski (1994) such as:
CDI = (CF × IR × EF× ED) / (BW × AT)
Where CF, IR, EF, ED, BW, AT represent the mean concentration of HM in
water samples (µg/L) (CF), ingestion rate of water 2 L/day (IR), exposure frequency
(365 days/year) (EF), exposure duration 65 years equivalent to the average lifetime
(ED) (Census, 1998), average body weight 72 kg (BW) and the averaging exposure
time for non-carcinogenic effects (23725, ED×365 days/year), respectively. The
greater, the value of HQ above unity the greater the level of concern as a rule. RfDo
values were based on 3×10 −4 , 1.5, 3.6×10 −2 , 4×10 −2 , 2×10 −2 , 3×10 −1 and 1×10 −3
mg/kg/day for As, Cr, Pb, Cu, Ni, Zn and Cd, respectively (US EPA 2000; 2005).
50

4.3. Results
4.3.1. Physico-chemical variables of water
Physico-chemical characteristics of water samples collected from different
sites located in Attock and Haripur basins are given in Table 4.1a and 4.1b, while the
concentrations of physico-chemical parameters in individual sample are given in
Appendix IIa. The international and national permissible limits of individual
parameters are presented in Table 4.2. The temperature of ground and surface water
samples of Attock Basin varied between 18 to 26 o C and 19 to 23 o C, respectively.
Variations in water temperature of Haripur Basin were found between 14 to 26 o C and
11 to 28 o C for groundwater and surface water, respectively. pH of water samples of
Attock Basin ranged from 7.0 to 8.4 (mean= 7.7), and 7.5 to 8.5 (mean= 8.1) for
groundwater and surface water, respectively. pH of water samples of Haripur basin
varied between 6.6 to 9.0 (mean= 7.4) and 5.4 to 9.2 (mean= 7.9) for groundwater and
surface water, respectively. Maximum pH (pH= 9.2) was observed in Dhotal Kas
stream near the marble industry, while lowest pH (pH= 5.36) was found in the
Chahari Kas stream receiving effluents from Hattar industrial estate (Fig. 4.1). All the
groundwater samples showed neutral and alkaline values which can be attributed to
presence of limestone rocks in the surrounding areas and calcareous nature of soil
(Hylland et al., 1988; Khan and Malik, 1993). According to WHO, pH less than 6.5 or
greater than 9.2 would markedlyimpair the potability of drinking water. Usually pH
has no direct impact on human health; however, low value of pH can increase the
reactivity of water (WHO, 2008).
51

Table. 4.1a. Description of Physico-chemical parameters of water samples of Attock and Haripur Basins, Pakistan
Element Attock Basin Haripur Basin
Groundwater Surface water Groundwater Surface water
Range Mean± S.D *
Range Mean± S.D Range Mean± S.D Range Mean± S.D
Temperature 18- 26 21± 1.92 19- 23 21± 1.35 16-26 22± 3.63 11-28 18±5.96
pH 7.0- 8.4 7.7± 0.33 7.5- 8.5 8.1± 0.31 6.6-9.0 7.4± 0.45 5.4-9.2 7.9±1.15
EC (μs/cm) 246-1692 580± 297 297- 584 395± 78 210- 2310 596± 366 180-1182 426±339
TDS (mg/L) 131- 908 309± 160 159- 309 210± 41 104- 1250 320± 201 116-956 322±293
Cl -1 (mg/L) 2.5- 129.8 40.5± 33.2 4.9- 95.2 39.2 ± 34.3 2.7- 145.5 19.5± 24.5 2.5- 304.1 46.2±97.6
NO3 -1 (mg/L) 1.5-112.5 28.5± 28.7 3.0- 8.5 5.8 ± 1.8 1.0- 32.4 6.8± 5.2 0.9- 3.3 1.7±1.4
SO4 -2 (mg/L) 5.0-226.0 62.7± 58.3 33.0- 103 66.1± 18.7 1.0-224.0 39.5± 47.5 9.0-101.0 32.2± 31.4
HCO3 -1 (mg/L) 260- 838 453± 121 276 - 427 344± 47.2 166-740 351± 111.6 101- 468 267± 122
Total hardness (mg/L) 144-673 337± 152 166- 484 258± 84 112-648 302± 106 93- 531 230± 121
S.D= * Standard deviation
52

EC is related to the conduction of electricity through the water and is related to
the saturation of water with respect to the dissolved solids. Average values of EC of
groundwater and surface water of Attock Basin were 580 and 395 μs/cm, respectively
while the average concentrations of ground and surface water of the Haripur Basin
were 596 and 426 μs/cm, respectively. The maximum permissible concentration of
EC for drinking water is 1400 μs/cm (WHO, 2008). In both basins the mean EC
values were lower than the permissible limit.
The level of TDS in the water samples of Attock Basin ranged between131 to
908 mg/L (mean= 309 mg/L) and 159 to 309 mg/L (mean= 210 mg/L), ground and
surface water, respectively. TDS of the water samples of Haripur Basin ranged from
104 to 1250 mg/L (mean= 320 mg/L), and 116 to 956 mg/L (mean= 322 mg/L),
ground and surface water, respectively. The results showed that groundwater had
higher TDS value as compared to the surface water. All the water samples had
average values less than permissible limit (1000 mg/L) of TDS for drinking purposes
(WHO, 2008).
The high concentrations of chloride (Cl - ) can give a salty taste to drinking
water and increase the rate of corrosion in water pipes. According to WHO, the taste
thresholds for Cl - are in the range of 200–300 mg/L. The Cl - concentration greater
than 600 mg/L would distinctly impair the potability of water and is, therefore,
considered as the maximum permissible concentration for drinking water (WHO,
2008). The Cl - of Attock Basin ranged from 2.5-129.8 mg/L (mean= 40.5 mg/L), 4.9-
95.2 mg/L (mean= 39.2 mg/L) for ground and surface water, respectively while in
Haripur Basin the Cl - concentrations ranged from 2.7-145.5 mg/L (mean= 19.5 mg/L),
and 2.5-304.1 mg/L (mean= 46.2 mg/L) for ground and surface water, respectively.
53

Nitrate (NO3 - ) concentration of water samples of Attock Basin varied between
1.5-112.5 mg/L (mean= 28.5 mg/L) and 3.0-8.5 mg/L (mean= 5.8 mg/L) in ground
and surface water, respectively while in Haripur Basin the mean concentration of
NO3 - varied between 1.0-32.4 mg/L (mean= 6.8 mg/L) and 0.9-3.3mg/L (mean= 1.7
mg/L) in ground and surface water, respectively. The surface water samples had lower
NO3 - concentration as compared to the WHO guidelines (50 mg/L) while the 60% of
groundwater samples of Attock Basin had concentration higher than permissible limit.
The results indicated that the high concentration of NO3 - was found in wells located in
agricultural lands/area. The sulphate (SO4 -2 ) concentration of ground and surface
water samples of the Attock Basin were in the range of 5.0-226.0 mg/L (mean= 62.7
mg/L) and 33.0-103.2 mg/L (mean= 66.1 mg/L), while in Haripur Basin, the SO4 -2
concentrations ranged from 1.0-224.0 mg/L (mean= 39.5 mg/L) and 9.0-101.0
(mean= 32.2 mg/L) in ground and surface water samples, respectively.
Average concentrations of bicarbonate (HCO3 - ) in ground and surface water
samples were 453 and 344 mg/L, respectively in Attock Basin while 351 and 267
mg/L respectively, in Haripur Basin. The groundwater generally had higher
concentration of bicarbonates than the surface water in both the basins. Total hardness
of ground and surface water samples of Attock Basin ranged from 144 to 673 mg/L
and 166 to 484 mg/L, respectively while in Haripur Basin it ranged between 112 to
648 mg/L and 93 to 531 mg/L, respectively.
4.3.2. Hydrochemical facies
The Piper–Hill diagram (Fig. 4.2a) is generally used to infer
hydrogeochemical facies (Piper, 1953). These plots include two triangles, one for
plotting cations and the other for plotting anions. The cation and anion fields are
54

combined to show a single point in a diamond-shaped field, from which inference is
drawn on the basis of hydrogeochemical facies concept (Ahmad and Qadir, 2011).
These trilinear diagrams are useful in bringing out chemical relationships among
cations and anions. Chemical data of representative surface and groundwater samples
from Attock and Haripur basins were graphically presented in Fig 4.2b and 4.2c,
respectively by plotting these on a Piper diagram. To define the composition class,
subdivisions of the tri-linear diagram classified by Kehew (2001) had been used (Fig
4.2a). These plots showed that 80% water samples of Attock Basin and 90% water
samples of Haripur Basin fall in the field of Ca-Mg type suggesting that Ca and Mg
cations are dominants. For anion concentration, HCO3-type of water predominated in
Attock and Haripur basins with 90% and 95% samples, respectively. There is no
significant change in the hydro-chemical facies noticed between the two basins, which
indicated that most of the major ions are natural in origin.
4.3.3. Light and heavy metals in water samples
Mean values and ranges of 15 elements including Na, K, Ca, Mg, As, Hg, Fe,
Mn, Cu, Pb, Zn, Ni, Cr, Co and Cd in water samples are given in Table 4.1b. The
average concentrations of light elements such as Na, K, Mg, and Ca in water samples
were higher than those of heavy metals. The average concentration of Na in ground
and surface water Attock Basin were found 56.7 and 28.1 mg/L respectively while in
Haripur Basin it was found as 60.3 and 36.8 mg/L in ground and surface water,
respectively. Groundwater samples had higher concentrations of Na as compared to
surface water samples, whereas, surface water samples of Haripur Basin had higher
concentration as compared to Attock Basin. Like Na, K exhibited similar spatial
pattern. Surface water showed lesser concentration of K in comparison with
groundwater (Table 4.1b).
55

Fig. 4.2a. Classification of hydrochemical facies using the Piper plot (Adopted from Kehew, 2001)
56

Fig. 4.2b. Piper diagram of water samples Attock Basin
57

Fig. 4.2c. Piper diagram of water samples Haripur Basin
58

Table 4.1b. Description of selected elements in surface and ground water samples of Attock and Haripur basin, Pakistan
Element
Attock Basin Haripur Basin
Groundwater Surface water Groundwater Surface water
Range Mean± S.D a Range Mean± S.D Range Mean± S.D Range Mean± S.D
Na 4.0- 311.1 56.7± 65.3 3.9-60.8 28.1± 19.6 5.2-406.1 60.3± 54.7 3.0-117.2 36.8± 40.6
K 0.2- 28.1 4.6± 6.4 1.3- 12.7 4.2± 3.4

Table 4.2. Drinking water quality guidelines by National and International Agencies.
Parameters WHO Pak- EPA US- EPA
Chloride (mg/L) 250 ≤250 250
Nitrate (mg/L) 50 50 10
pH 6.5-9.2 6.5-8.5 6.5-8.5
Sulfate (mg/L) - - 250
Total dissolve solids (mg/L) 600-1000 ≤1000 500
Arsenic (µg/L) 10 50 10
Cadmium (µg/L) 3 10 5
Chromium (µg/L) 50 50 100
Copper (µg/L) 2000 2000 1000
Iron (µg/L) 300 300
Lead (µg/L) 10 50 -
Manganese (µg/L) 500 ≤500
Mercury (µg/L) 6 1 -
Nickel (µg/L) 70
Zinc (µg/L) 3000 - 5000
60

The mean concentration of Ca in ground and surface water samples of Attock
Basin were 29.4 and 74.7 mg/L, respectively while highest concentration was found
in groundwater samples of Taxilla. It is due to presence of limestone in area. The
concentration of Ca is also higher those reported by Khan (1997). In Haripur Basin
the average concentrations of Ca in ground and surface water samples were 79.4 and
68.7 mg/L, respectively. Mg concentrations of groundwater samples ranged between
9.3-88.2 mg/L and 8.20-109.1 mg/L while surface water samples it ranged from 13.4-
27.1 mg/L and 4.0-33.0 mg/L in Attock and Haripur basins, respectively.
In groundwater samples, As concentrations ranged from

it ranged between 13.9-166.2 μg/L and 1.6-34.3 μg/L in ground and surface water
respectively. Cu concentrations were in all the water samples, as compared to
permissible limit (2000 μg/L) set by WHO (Table 4.2). Pb concentrations in ground
and surface water of Attock Basin varied from 0.4 to 135.1 µg/L (mean= 23.3 µg/L)
and 4.6 to 71.7 µg/L (mean= 16.5 µg/L), respectively. Pb concentrations in ground
and surface water of Haripur Basin ranged between 4.36-147.7 µg/L (mean= 37.5
µg/L) and 9.2-112.4 µg/L (mean=39.3 µg/L). In the study area, 90% of the surface
water and 50% of groundwater samples of Haripur and Attock basins showed higher
level of Pb as compared to the Pb permissible limit (10 μg/L )set by WHO which can
be correlated to industrial effluent or by the erosion of sulphide veins in surrounding
rocks (Tahirkheli, 1982, Javied et al., 2009). Zn concentrations in the ground and
surface water of Attock Basin ranged from 59 to 1591 µg/L (mean= 500 µg/L), and
19 to 1658 µg/L (mean= 395 µg/L), respectively, while in Haripur Basin it ranged
from 8.0 to 1486 µg/L (mean= 224 µg/L) and 8.3 to 122.8 µg/L (mean= 64.4 µg/L) in
ground and surface water samples respectively. All water samples had lower
concentrations than the WHO recommended guidelines (Table 4.2). Ni concentrations
ranged from 3.2 to 43.1 µg/L (mean= 8.2 µg/L) and 1.5 to 10.9 µg/L (mean= 4.7
µg/L) in ground and surface water of Attock Basin and

(mean= 24.73 µg/L) and 0.82 to 49.1 µg/L (mean= 9.8 µg/L), respectively in ground
and surface water of Haripur Basin. All the water samples had Cr concentrations
within the permissible limit (Table 4.2) Co concentrations in ground and surface
water of Attock Basin varied from Co>Ni>Cd>As>Cr>Hg and in Haripur Basin the order was
noticed as Zn>Fe>Pb>Mn>Cu>Cr>Ni>Cd>Co>As>Hg. The order of distribution of
selected elements in surface water was found as Fe>Mn>Zn>Pb>Ni>Co>Cu>Cr>
As>Cd>Hg and Zn>Fe>Mn>Cu>Pb>Co>Ni>Cr> Cd>As>Hg in Attock and Haripur
basins, respectively.
4.3.4. Groundwater and surface water comparison
The comparison of the geochemical data in Figure 4.3a and b clearly showed
that surface water was less contaminated as compared to groundwater in the Attock
Basin, while the surface water in Haripur Basin was more contaminated as for as the
heavy metals as concerned. The reason is that the streams following in the Attock
Basin are not receiving much of the industrial and sewage effluent as the Haripur
Basin. Groundwater contamination in Attock Basin can be attributed to leaching of
63

Concentration
Concentration
1000
100
10
1
0.1
Na K Ca Mg As Hg Fe Mn Cu Pb Zn Ni Cr Co Cd
Fig. 4.3a. Comparison of surface and groundwater quality of Attock Basin
1000.0
100.0
10.0
1.0
0.1
Na K Ca Mg As Hg Fe Mn Cu Pb Zn Ni Cr Co Cd
Groundwater
Fig. 4.3b. Comparison of surface and groundwater quality of Haripur Basin
Groundwater
Surface water
Surface water
64

metals from agricultural land and other geogenic sources. In comparison to Attock
Basin, in the Haripur Basin majority of the streams are located near to the Hattar
industrial estate which contributes effluents to main streams such as Chahari Kas and
Dhotal Kas (Sial et al., 2006).
4.3.5. Statistical Analysis
4.3.5.1. Inter- relationships among metals
The metal correlations were determined for both surface and groundwater of
Attock and Haripur basins by calculating Pearson correlation matrix (Table 4.3a and b
and Table 4.4a and b). The inter- elemental relationship showed that the metal pairs of
Na-Mg, K-Mn, Ca-Mg, Hg-Cd, Mn-Cr, Cu-Zn, Pb-Ni and Pb-Cd were correlated
significantly at p

Table 4.3a. Pearson’s correlation matrix indicating the association within surface water samples of Attock Basin
Na 1
Na K Ca Mg As Hg Fe Mn Cu Pb Zn Ni Cr Co Cd
K .290 1
Ca -.105 -.255 1
Mg .626 .101 .541 1
As .251 .878 -.168 .241 1
Hg .076 -.073 .078 -.003 -.314 1
Fe -.103 .081 -.237 -.326 -.294 .180 1
Mn -.136 .718 -.220 -.322 .581 -.324 .301 1
Cu -.453 -.143 .012 -.221 -.047 -.256 -.294 .056 1
Pb -.521 -.268 -.116 -.461 -.097 -.006 -.093 .157 .390 1
Zn -.434 .073 -.086 -.268 -.075 -.293 .348 .432 .609 .068 1
Ni -.271 .133 -.207 -.470 .053 .473 .180 .242 .066 .689 -.187 1
Cr -.446 .168 -.057 -.465 -.094 -.027 .566 .680 .185 .208 .768 .147 1
Co -.417 -.291 -.057 -.416 -.102 .087 -.240 .036 .343 .956 -.160 .745 .006 1
Cd -.261 -.175 -.043 -.301 -.157 .651 -.187 -.169 .185 .674 -.303 .810 -.092 .778 1
Bold r>0.500 values are significant at the 0.05 level.
Bold and underline r>0.500 values are significant at the 0.01 level.
66

Table 4.3b. Pearson’s correlation matrix indicating the association within groundwater samples of Attock Basin
Na 1
Na K Ca Mg As Hg Fe Mn Cu Pb Zn Ni Cr Co Cd
K .516 1
Ca .173 .011 1
Mg .647 .624 .240 1
As .096 .252 -.220 .207 1
Hg -.121 -.135 -.003 .235 -.272 1
Fe .073 -.234 .489 -.225 -.262 .111 1
Mn .619 .216 .108 .328 -.016 -.155 -.064 1
Cu .022 .040 .265 .205 -.171 .321 .465 -.039 1
Pb -.115 -.034 .073 .027 -.187 .249 .166 .009 .392 1
Zn -.204 -.134 .214 -.102 -.290 .131 -.055 -.112 .097 .427 1
Ni -.071 -.122 .234 -.026 -.222 .212 .434 -.020 .425 .856 .358 1
Cr -.144 -.154 .342 -.098 -.125 -.151 -.189 -.129 -.065 -.026 .288 -.097 1
Co .267 .224 .068 .391 .216 -.112 -.094 .186 .068 .186 -.087 .237 -.088 1
Cd -.168 .054 -.088 -.014 .233 -.180 -.022 .080 .098 .525 -.030 .420 -.032 .283 1
Bold r>0.350 values are significant at the 0.05 level.
Bold and underline r>0.350 values are significant at the 0.01 level.
67

Fig. 4.4a. Dendrogram showing association of metals in surface water samples
collected from Attock Basin
Fig. 4.4b. Dendrogram showing association of metals groundwater samples collected
from Attock Basin
68

Pb was positively correlated with Ni (r= 0.859) and Cd (r= 0.525). It was also
supported by Cluster analysis where the Na, Mg, K and Mn were grouped together
(Fig. 4.4b), while Hg, As, Cr and Co showed no correlation with any metal and were
considered as outlier in cluster analysis.
The surface water correlation of the Haripur Basin is presented in Table 4.4a.
In case of surface water samples of Haripur Basin the significant positive inter-
elemental correlation of Na with K (r = 0.599), Mn (r = 0.554) and Cr (r = 0.670)
were noticed. K exhibited positive correlations with Ca (r = 0.540), Mn (r = 0.691)
and Cr (r = 0.538). Ca showed positive correlation with Mg (r = 0.824), Mn (r= 0.526)
and Co (r =0.642) and negative correlation with Cu (r = -0.612) and Ni (r= -0.552).
Strong positive correlation was found between Mg and Co (r= 0.728), while As
showed strong positive correlation with Fe (r= 0.832) and Pb (r= 0.718). Fe was found
positively correlated with Cu (r= 0.586) and Pb (r= 0.681) while Mn showed positive
correlation with Cr (r = 0.926). Cu was positively correlated with Pb (r= 0.901), Ni
(r= 0.902) and Cd (r=0.670) and Pb was strongly correlated with Ni (r= 0.835). Ni is
positively correlated with Cd (r= 0.830). However, Hg was not correlated with any of
these metals (Fig. 4.5a).
Correlation analysis of groundwater of Haripur Basin was presented in Table
4.4b. In groundwater Na exhibited strong positive correlation with Mg (r = 0.664) and
Ni (r= 0.361). Mg was positively correlated with Cr (r= 0.483). Arsenic was strongly
correlated with Fe (r = 0.554), Mn (r = 0.620), Cu (r= 0.370) and Zn (r= 0.351). Fe
exhibited positive correlation with Mn (r = 0.551) and Pb (r = 0.453). Mn showed
strong correlation with Cu(r=0.369) and Pb (r =0.480). A significant correlation of Cu
was observed with Pb (r= 0.557), Zn (r= 0.482), Ni (r= 0.356), Co (r= 0.491) and Cd
69

Table 4.4a. Pearson’s correlation matrix indicating the association within surface water samples of Haripur Basin
Na 1
Na K Ca Mg As Hg Fe Mn Cu Pb Zn Ni Cr Co Cd
K .599 1
Ca .434 .540 1
Mg .496 .469 .824 1
As -.202 .046 -.175 -.261 1
Hg -.322 -.167 -.266 -.437 -.035 1
Fe -.310 -.070 -.453 -.610 .832 .458 1
Mn .554 .691 .526 .162 .344 .023 .304 1
Cu .214 .107 -.612 -.349 .499 .048 .586 .055 1
Pb .309 .129 -.380 -.259 .718 -.056 .681 .324 .901 1
Zn -.036 -.152 -.340 -.434 .421 .096 .494 .134 .398 .496 1
Ni .356 -.050 -.552 -.206 .333 -.152 .322 -.085 .902 .835 .243 1
Cr .670 .538 .393 .047 .213 -.110 .191 .926 .098 .362 .222 .052 1
Co .039 .165 .642 .728 .101 .066 -.125 .080 -.311 -.162 -.269 -.266 -.181 1
Cd .491 -.002 -.381 .095 -.181 -.150 -.146 -.296 .670 .477 .076 .830 -.141 -.141 1
Bold r> 0.500 are significant at the 0.05 level.
Bold and underline r> 0.500 are significant at the 0.01 level.
70

Table. 4.4b. Pearson’s correlation matrix indicating the association within groundwater samples of Haripur Basin
Na 1
Na K Ca Mg As Hg Fe Mn Cu Pb Zn Ni Cr Co Cd
K .195 1
Ca .102 .299 1
Mg .664 .178 .145 1
As .033 -.099 .054 -.045 1
Hg .102 -.048 -.181 .071 .228
Fe -.016 -.017 .281 -.032 .554 -.024 1
Mn .112 -.072 .059 .098 .620 .241 .551 1
Cu .188 -.015 -.138 .038 .370 .278 .164 .369 1
Pb -.024 .108 .117 .028 .315 .102 .453 .480 .557 1
Zn .244 -.004 -.104 .083 .351 .244 .007 .225 .482 .003 1
Ni .361 .030 .193 .287 .128 -.122 .167 .170 .356 .281 -.005 1
Cr .210 .144 -.036 .483 .035 -.037 .145 .064 -.040 .180 -.082 .163 1
Co -.002 -.090 -.196 -.094 .034 .125 .140 .281 .491 .369 -.020 .034 -.138 1
Cd .003 .028 -.061 .041 -.023 .076 .110 .270 .520 .526 .038 .114 .003 .757 1
Bold r> 0.330 are significant at the 0.05 level.
Bold and underline r> 0.330 are significant at the 0.01 level.
71

(r= 0.520). Pb showed the positive relationship with Cd (r=0.526) and Co with Cd (r=
0.757). Ca, K and Hg were not correlated with any other metal (Fig. 4.5b).
The results of correlation analysis were further confirmed by cluster analysis
(Fig. 4.5a and b). The surface water of Haripur Basins showed two distinct clusters.
Cluster-1 consisted of Mn, Cr, Na, K, Ca, Mg, and Co, whereas, Cluster-2 contained
As, Fe, Cu, Ni, Pb, Cd and Zn. Hg was identified as outlier. Three clusters were
formed in groundwater samples. Cluster-1 consisted of Na, Mg, Cr and Ni. Cluster-2
was made up of As, Mn and Fe whereas, Cluster-3 comprised of Co, Cd, Pb, Cu and
Zn in groundwater.
4.3.5.2. Principal component analysis
Principal component analysis (PCA) was used to investigate the extent of
metal pollution and source identification (Vega et al., 1996; Helena et al., 2000;
Shrestha and Kazama, 2007). The data was analyzed through factor analysis in Table
4.5a and b and 4.6a and b for Attock and Haripur basins respectively. These tables
represent the factor loadings, together with cumulative percentage and percentages of
variance explained by each factor. Five and six factors with eigenvalues >1 were
extracted for the data sets of surface water and groundwater of Attock Basin
respectively, while five factors for surface water and four factors for groundwater
samples of Haripur Basin were extracted.
PCA results of the surface water samples of Attock Basin are presented in
Table 4.5a. PC1, PC2, PC3, PC4 and PC5 account for 28.766%, 22.447%, 16.072%,
12.935% and 7.713% of the total variance, respectively. PC1 had high loading of Pb,
Ni, Co and Cd. PC2 had the high loading of Mn, Zn and Cr, PC3 had high loading of
K and As, PC4 had high loading of Cu while PC5 showed high loading of Ca. For
72

Fig. 4.5a. Dendrogram showing association of metals in surface water samples
collected from Haripur Basin
Fig. 4.5b. Dendrogram showing association of metals in groundwater samples
collected from Haripur Basin
73

Table 4.5a. Factor analysis of selected elements in surface water of Attock Basin
Element Factor 1 Factor 2 Factor 3 Factor 4 Factor 5
(PC1) (PC2) (PC3) (PC4) (PC5)
Na -.687 -.208 .400 -.144 -.099
K -.244 .563 .743 .019 .172
Ca -.195 -.301 -.319 .212 .774
Mg -.727 -.320 .073 .221 .425
As -.254 .376 .763 .411 .079
Hg .219 -.463 .169 -.633 .377
Fe .117 .460 -.157 -.774 .001
Mn .189 .836 .411 .049 .154
Cu .441 .184 -.323 .616 .064
Pb .886 -.111 .098 .259 -.030
Zn .210 .752 -.481 .116 .157
Ni .779 -.132 .506 -.221 .121
Cr .394 .749 -.225 -.256 .300
Co .850 -.313 .193 .274 -.037
Cd .739 -.511 .312 -.074 .171
Eigen 4.315 3.367 2.411 1.940 1.157
% of Variance 28.766 22.447 16.072 12.935 7.713
Cumulative % 28.766 51.213 67.285 80.220 87.932
74

Table 4.5b. Factor analysis of selected elements in groundwater of Attock Basin
Element Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6
(PC1) (PC2) (PC3) (PC4) (PC5) (PC6)
Na -.550 .565 .411 -.025 -.222 -.136
K -.607 .504 -.077 .041 .297 .202
Ca .187 .316 .500 .466 -.181 .381
Mg -.460 .678 .270 .079 .367 .003
As -.572 .116 -.526 -.042 .177 .370
Hg .384 .134 .336 -.328 .629 -.201
Fe .471 .185 .261 -.473 -.441 .322
Mn -.374 .436 .212 .066 -.431 -.493
Cu .465 .476 .214 -.264 .130 .385
Pb .645 .568 -.323 .103 .104 -.191
Zn .510 .064 .074 .541 .248 -.245
Ni .695 .590 -.190 -.008 -.104 -.041
Cr .134 -.217 .139 .780 -.013 .250
Co -.198 .563 -.286 .131 -.107 .022
Cd .183 .380 -.734 .089 -.180 .001
Eigen 3.221 2.799 1.831 1.570 1.257 1.039
% of Variance 21.474 18.662 12.209 10.464 8.377 6.925
Cumulative % 21.474 40.137 52.345 62.810 71.186 78.111
75

groundwater data set, PC1, PC2, PC3, PC4, PC5 and PC6 represented 21.474%,
18.662%, 12.209%, 10.464%, 8.377% and 6.925% total variance respectively (Table
4.5b). PC1 was heavily loaded with Pb and Ni. PC2 was loaded with Na, K, Mg, Pb
and Co which could represent an anthropogenic source for possible contamination.
PC3 was loaded with Ca only. PC4 was loaded by Zn and Cr. This loading could be
due to the effluent discharges from industry. PC5 was loaded by Hg only while PC6
showed no major contributor. It has, therefore, been noted that the PC1 in surface and
groundwater may be characterized as anthropogenic sources.
PCA results of the surface water samples of Haripur Basin are presented in
Table 4.6a. PC1, PC2, PC3, PC4 and PC5 accounted for 34.183%, 24.375%,
16.502%, 9.885% and 6.885% of the total variance respectively. PC1 was mostly
contributed by As, Fe, Cu, Pb, Zn and Ni, while PC2 was contributed by Na, K, Ca,
Mn and Cr. PC3 showed high loading of Ni and Cd while PC4 showed high loading
of Co. PC5 showed high loading of Hg. PCA results of the groundwater samples of
Haripur Basin are presented in Table 4.6b. PC1, PC2, PC3, PC4, PC5 and PC6
represented 22.255%, 15.407%, 10.438%, 9.235%, 7.161% and 6.761% of total
variance, respectively. PC1 contributed by Mn, Cu, Pb, Co and Cd. PC2 was
contributed by Na and Mg. PC3 was contributed by As and Fe while PC4 was
contributed by Ca. PC5 was contributed Zn while PC6 was attributed by Hg.
4.3.6. Health risk assessment
Results of chronic daily intake (CDI) and hazard quotient (HQ) for HMs via
the consumption of surface and groundwater are presented in Table. 4.7 and 4.8,
76

Table 4.6a. Factor analysis of selected elements in surface water of Haripur Basin
Element Factor 1 Factor 2 Factor 3 Factor 4 Factor 5
(PC1) (PC2) (PC3) (PC4) (PC5)
Na -.088 .812 .463 -.265 .095
K -.234 .728 -.022 -.023 .321
Ca -.806 .541 -.102 .168 -.074
Mg -.688 .430 .388 .403 -.057
As .578 .293 -.456 .493 -.297
Hg .176 -.253 -.441 .032 .803
Fe .808 .148 -.480 .184 .121
Mn -.047 .873 -.450 -.146 .080
Cu .894 .149 .268 .211 .141
Pb .843 .485 .070 .191 -.075
Zn .596 .095 -.278 -.086 -.273
Ni .789 .217 .539 .061 .009
Cr .045 .834 -.295 -.416 -.062
Co -.482 .184 -.006 .809 .139
Cd .444 .114 .856 -.001 .187
Eigen 5.127 3.656 2.475 1.480 1.033
% of Variance 34.183 24.375 16.502 9.885 6.885
Cumulative % 34.183 58.558 75.060 84.929 91.814
77

Table 4.6b. Factor analysis of selected elements in groundwater of Haripur Basin
Element Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6
(PC1) (PC2) (PC3) (PC4) (PC5) (PC6)
Na .398 .760 -.059 -.108 .180 .087
K .101 .418 -.138 .327 -.502 .434
Ca .142 .290 .365 .611 -.187 .283
Mg .319 .797 -.187 -.095 .250 -.001
As .465 -.135 .580 -.381 -.019 .087
Hg .317 .023 -.119 -.583 .000 .587
Fe .553 -.167 .560 .151 -.076 -.172
Mn .724 -.154 .272 -.213 -.014 .071
Cu .607 -.225 .039 .177 .360 .093
Pb .711 -.245 -.072 .220 -.190 -.053
Zn -.146 -.050 .126 .409 .719 .270
Ni .505 .342 .011 .184 .018 -.330
Cr .287 .542 -.050 -.140 -.034 -.397
Co .574 -.372 -.504 .051 .031 -.009
Cd .583 -.327 -.598 .172 -.016 .007
Eigen 3.338 2.311 1.566 1.385 1.074 1.014
% of Variance 22.255 15.407 10.438 9.235 7.161 6.761
Cumulative % 22.255 37.662 48.100 57.335 64.496 71.256
78

espectively. The results suggested that in Attock Basin, the CDI values due to the
consumption of groundwater ranged as 0.00-0.31, 0.03-5.64, 0.01-4.04, 0.00- 3.75,
1.65- 44.18, 0.00- 1.20, 0.01-0.48 and 0.00-1.16 μg/day for As, Mn, Cu, Pb, Zn, Ni,
Cr and Cd, respectively (Table 4.7). Similarly, the people in Attock Basin had CDI
values via the consumption of surface water ranged from 0.00 to 0.14, 0.03 to 3.75,
0.00 to 2.42, 0.13 to 1.99, 0.54 to 46.81, 0.00 to 0.30, 0.01 to 0.36, and 0.00 to 0.42
μg/day for As, Mn, Cu, Pb, Zn, Ni, Cr and Cd, respectively (Table 4.7). The CDIs for
heavy metals due to the intake of ground and surface water were found in the order of
Zn> Cu> Mn> Pb> Ni> Cd > Cr> As and Zn >Mn >Pb >Cu >Cr > Ni >Cd >As,
respectively.
The CDI values due to the consumption of ground and surface water by the
community of Haripur Basin are presented Table 4.7. These values ranged as 0.00-
0.104, 0.03- 2.86, 0.03- 6.36, 0.00- 4.10, 0.22- 37.61, 0.00- 1.31, 0.00- 5.39 and 0.00-
1.74 μg/day for As, Mn, Cu, Pb, Zn, Ni, Cr and Cd, respectively (Table 4.7).
Similarly, CDI values due to the consumption of surface water ranged from 0.00 to
0.15, 0.08 to 14.67, 0.00 to 0.95, 0.26 to 3.12, 0.23 to 3.41, 0.00 to 3.12, 0.02 to 1.36,
and 0.02 to 0.39 μg/day for As, Mn, Cu, Pb, Zn, Ni, Cr and Cd, respectively (Table
4.7). The trends of CDIs for heavy metals due to the intake of ground and surface
water were found in the order of Zn> Pb> Mn> Cu> Cr> Ni> Cd> As and Mn >Zn >
Pb > Ni > Cu >Cr > Cd >As, respectively.
Table 4.8 summarizes the HQ indices of HMs through consumption of ground
and surface water in the study area. In Attock Basin, the mean HQ index values for
As, Mn, Cu, Pb, Zn, Ni, Cr and Cd for groundwater were 4.27E-03, 8.20E-04, 1.11E-
02, 7.66E-03, 4.17E-02, 6.53E-04, 6.55E-05 and 7.93E-02, while in Haripur Basin,
mean HQ index values were 9.33E-04, 1.07E-03, 8.85E-03, 1.24E-02, 1.72E-02,
79

Table 4.7. Chronic daily intake (CDI) of heavy metals via the consumption of surface and groundwater in Attock and Haripur basins
Element
Attock Basin Haripur Basin
Groundwater Surface water Groundwater Surface water
Average± S.D Range Average± S.D Range Average± S.D Range Average± S.D Range
As 0.05± 0.09 0.00- 0.31 0.02± 0.04 0.00- 0.14 0.012±0.022 0.00- 0.104 0.02± 0.05 0.00- 0.15
Mn 0.59± 0.96 0.03- 5.64 1.10± 1.14 0.03- 3.75 0.76± 0.75 0.03- 2.86 4.37 ± 4.75 0.08- 14.67
Cu 0.81± 1.08 0.01- 4.04 0.40± 0.75 0.00- 2.42 0.65± 1.02 0.03- 6.36 0.31± 0.36 0.00- 0.95
Pb 0.59± 0.84 0.00- 3.75 0.46± 0.53 0.13- 1.99 0.96± 0.83 0.00- 4.10 1.09± 1.01 0.26- 3.12
Zn 13.90± 12.0 1.65- 44.18 10.99± 16.80 0.54- 46.81 5.75± 7.81 0.22- 37.61 1.79± 1.05 0.23- 3.41
Ni 0.16± 0.30 0.00- 1.20 0.10± 0.10 00- 0.30 0.11± 0.20 0.00- 1.32 0.75± 1.07 0.00- 3.12
Cr 0.10± 0.12 0.01- 0.48 0.10± 0.10 0.01- 0.36 0.59± 1.14 0.00- 5.39 0.27± 0.44 0.02- 1.36
Cd 0.13± 0.28 0.00- 1.16 0.08± 0.15 0.00- 0.42 0.10± 0.22 0.00- 1.74 0.06± 0.12 0.02- 0.39
80

Element
Table 4.8. Hazard quotient (HQ) of heavy metals via the consumption of surface and
groundwater in Attock and Haripur basins
Attock Basin
Groundwater Surface water
Average± S.D Range Average± S.D Range
As 4.27E-03± 7.43E-03 0.00- 2.53E-02 1.31E-03± 3.30E-03 0.00- 1.11E-02
Mn 8.20E-04± 1.35E-03 3.89E-05- 7.89E-03 1.53E-03± 1.60E-03 3.89E-05- 5.25E-03
Cu 1.11E-02± 147E-02 0.00- 5.53E-02 5.51E-03± 1.03E-02 0.00- 3.31E-02
Pb 7.66E-03± 109E-02 0.00- 4.86E-02 5.95E-03± 6.93E-03 1.67E-03- 2.58E-02
Zn 4.17E-02± 3.60E-02 4.95E-03- 1.33E-01 3.30E-02± 5.04E-02 1.63E-02- 1.40E-01
Ni 6.53E-04± 1.21E-03 0.00- 4.78E-03 3.81E-04± 4.08E-04 0.00- 1.21E-03
Cr 6.55E-05±8.04E-05 5.26E-06- 3.18E-04 6.95E-05± 6.87E-05 6.81E-06- 2.43E-04
Cd 7.93E-02± 1.77E-01 0.00- 7.27E-01 4.79E-02± 9.61E-02 0.00- 2.65E-01
Haripur Basin
Grounwater Surface water
Average± S.D Range Average± S.D Range
As 9.33E-04± 1.81E-03 0.00- 8.39E-03 1.86E-03± 4.05E-03 0.00- 1.23E-02
Mn 1.07E-03± 1.06E-03 3.89E-05- 4.01E-03 4.81E-02± 1.26E-01 1.17E-04- 3.85E-01
Cu 8.85E-03± 1.40E-01 4.46E-04- 8.71E-02 7.11E-03± 1.03E-02 0.00- 3.12E-02
Pb 1.24E-02± 1.07E-02 0.00- 5.32E-02 2.15E-02 ±2.50E-02 3.34E-03- 7.82E-02
Zn 1.72E-02 ±2.34E-02 6.65E-04- 1.13E-01 2.32E-02± 5.40E-02 6.90E-04-1.67E-01
Ni 4.29E-04± 8.16E-04 0.00- 5.27E-036 3.00E-03±4.27E-03 0.00- 1.25E-02
Cr 3.90E-04±7.57E-04 0.00- 3.59E-03 1.83E-04±2.96E-04 1.52E-05- 9.09E-04
Cd 6.08E-02± 1.36E-01 0.00- 1.09 3.99E-02±7.55E-02 1.06E-02- 2.41E-01
81

4.29E-04, 3.90E-04 and 6.08E-02, respectively (Table 4.8). Mean HQ index values
for As, Mn, Cu, Pb, Zn, Ni, Cr and Cd for surface water were 1.31E-03, 1.53E-03,
5.51E-03, 5.95E-03, 3.30E-02, 3.81E-04, 6.95E-05 and 4.79E-02 for Attock Basin
while for Haripur Basin these values were found as 1.86E-03, 4.81E-02, 7.11E-03,
2.15E-02, 2.32E-02, 3.00E-03, 1.83E-04 and 3.99E-02.
Though the exposure to the HMs of the population of both basins was
different but HQs of HMs were lower than 1. This means that the daily intake of
individual metal through the consumption of groundwater would be unlikely to cause
adverse health effects for inhabitants of Attock and Haripur basins. The HQ indices of
Cd, Cu, Mn, Ni, Pb, As and Zn metals were in general, lower than those reported by
other researchers in groundwater (Lim et al., 2008; Kavcar et al., 2009; Chai et al.,
2010).
4.4. Discussion
The spatial variations of HMs are highly influenced by natural and
anthropogenic activities (Mora et al., 2009; Bhuiyan et al., 2010) Anthropogenic
activities (i.e. industrial and agricultural) in the surroundings of any river and stream
highly contaminate not only surface water as well the groundwater quality of the
surrounding area. This process of contamination becomes severe in densely populated
and industrialized areas (Rehman et al., 2008; Ullah et al., 2009). Attock and Haripur
basins are facing severe contamination due to anthropogenic activities taking place in
surrounding areas of various streams and rivers. The water quality in these basins was
relatively better in the upstream of the industrial areas because these areas were least
affected by the point sources. Most of the point sources are concentrated in
82

southeastern side of the study area that drains effluents in streams and raw sewage
throughout the year.
The results showed that pH values of all the groundwater samples were
alkaline in nature due to presence of the carbonate rocks (such as limestone and
dolomite) in the study area (Khan and Malik, 1993). The surface water samples were
also alkaline in nature except the one collected from the Chahari Kas stream which
had the acidic pH (pH= 5.36). All the studied water samples had the pH within the
permissible range of WHO (WHO, 2008). The electrical conductivity (EC) of water
samples was higher than reported EC of groundwater by Phuong et al., (2011).
Similarly, average concentration of TDS of surface water was found below the
permissible level (500 mg/L) described by USEPA (1998) and WHO (2008).
However, the water samples collected from Chahari Kas stream had higher TDS value
(629 mg/L) as compared to the permissible limit. The 10% groundwater samples of
the Attock Basin had the TDS concentration higher than the permissible limit. These
results are in accordance with those as mentioned in the reported by PCRWR (2010)
on rural area of Attock Basin. However, TDS values of both the basins were found
lower than those reported by Alhumoud et al. (2010) in groundwater and Afzal et al.
(2000) in surface water. High values of TDS in some of the groundwater ad surface
water samples could due to the higher concentration of soluble salts contributed by
the natural and anthropogenic sources.
In the study area, all the groundwater and 95% surface water samples of both
the basins had lower Cl - concentrations than that of prescribed limit (250 mg/L) for
drinking water. The highest concentration (304.1 mg/L) of total chloride was found in
Chahari Kas water samples. Among the anions, the average concentrations of the
NO3 - in surface water of both the basins were found below the permissible limit (50
83

mg/L) set by WHO (2008). However, the NO3 - concentrations in the studied water
samples were found higher than those reported by Chapman (1996) for natural stream
water. The NO3 - concentrations in 10% groundwater samples of Attock Basin were
found higher than the permissible limit (50 mg/L) set by WHO (2008) which could be
attributed to the agricultural activities such as excessive use of fertilizers in these
areas. Mondal et al. (2008) and Hu et al. (2005) also reported similar reason of high
level of NO3 - in groundwater especially in shallow groundwater. All the water
samples of both the basins showed lower sulphate values compared with the standard
values (250 mg/L) prescribed by US-EPA. The concentrations of HCO3 - reported in
the present study were found higher than those reported by Afzal, et al., (2000) in
surface water of Hudiara drain and Alhumoud (2010) in groundwater of Kuwait. This
high concentration could be due to the percolation of the studied water through the
carbonate rocks of the area.
Among light elements, Na and K concentrations in surface and groundwater
samples were found greater than those reported by Phuong et al., (2011) and Batarseh
(2006) while Ca and Mg concentrations were found lower those reported by the Phuong
et al., (2011) in drinking water samples. Ca and Mg are the major determining factors for
total hardness in water; however, other factors also contribute an increase in total
hardness. According to Wright and Welbourn (2002), four classes of water can be
recognized on the basis of hardness. These are soft water (0-75 mg/L), moderately hard
(75-150 mg/L), hard (150-300 mg/L) and very hard (above 300 mg/L) water. On this
basis, the surface water of Haripur Basin can be categorized as hard water, whereas,
surface water of Attock Basin can be characterized as very hard water. The results
indicated that maximum total hardness was recorded in Chahari Kas stream of Haripur
Basin which could be due to the dissolution of calcium salts in the streams water from the
84

marble industries in the Hattar industrial estate of the study area. Lowest values of total
hardness were recorded in the water samples collected from Indus River, and streams
located away from the industrial area.
Arsenic concentrations in all water samples were found within the
recommended level (10 μg/L) for drinking water set by the WHO with exception of
one groundwater sample (11.2 μg/L) collected from Ghazi that are located near Indus
River. As concentrations in the studied water samples were found lower than those
reported in Sindh, Pakistan by Arain et al. (2009) and Bhuiyan et al. (2010) in north-
western Bangladesh. Hg concentrations in most of the groundwater falls below the
detection limit and were therefore, found within the permissible limit (6 µg/L) of
drinking water by WHO (2008). Average concentration of Fe and Mn in surface water
was found higher than those reported by Li and Zhang (2010) and Krishna et al.
(2009). The average concentration of Mn in groundwater was found lower than
reported by Jan et al. (2010) and Krishna et al. (2009).
Copper concentrations in all the studied water samples was found lower than
permissible limits set by U.S.EPA (1000 µg/L) (US-EPA, 2002) and WHO (2000
µg/L) (WHO, 2008). About 80% of the groundwater samples of the Haripur Basin
and 60% of the Attock Basin have the higher Pb concentration than the WHO
recommended limit (10 µg/L). While in surface water 95% of the samples had the
higher Pb concentration than those reported for freshwater (10 µg/L) (Chapman,
1996). It is noticed that the Pb concentration increased from upstream towards
downstream sites. There could two main reasons for the high concentration of Pb in
the studied water samples (1) presence of sulfide bearing veins in the surrounding
area rock (Tahirkheli, 1982) and (2) industrial activities within the study area (i.e.
manufacturing processes such as paints and pigments, incineration of municipal solid
85

wastes and hazardous wastes) (FDA, 1993). Concentration of Pb in water samples of
the present study was found higher than those reported by Haq et al. (2005), Arain et
al. (2009) in different areas of Pakistan and Bhuiyan et al. (2010) in Bangladesh.
Zinc concentrations in all the surface and groundwater samples of the study
area was found within the permissible limit of WHO (3000 µg/L) (WHO, 2008) and
USEPA (5000 µg/L) (US-EPA, 2002). However, it was found higher than the Zn
concentration reported by Ilyas and Sarwar (2003) and Krishna et al. (2010). Highest
level of Ni concentration was found in sample collected from Dhotal Kas stream
which decreases with increasing distance from industrial area. This is in accordance
with the observation reported by Wright and Welbourn (2002). This higher Ni
concentration in surface water could be caused by the industrial effluent and
municipal waste (Ntengwe and Maseka, 2006). Concentrations of Ni recorded from
all sampling sites were found within the safe limits (65 µg/L) as described by
Chapman (1996) for freshwater as well as by WHO (2008) for drinking water.
No greater variation in Cr concentration was found in surface and groundwater
samples of Attock Basin. However, notable variation of Cr concentrations in the
groundwater of Haripur Basin was noticed. This variation was due to two main factors
(i) distance from the effluent receiving streams and (ii) depth of aquifer (as shallow
aquifer was more contaminated then the deep aquifer). All the surface water samples
had concentration less the WHO guidelines while 16% of groundwater samples had
concentration greater than the WHO (2008) recommended limit (50 µg/L) for
drinking water. Maximum concentration of Cr was recorded from those sites, which
were close to the Hattar industrial area. Relatively higher concentration of Cr (194
µg/L) was observed in groundwater close to the industrial area. However, high
concentration (49.1 µg/L) was observed in the sample collected from Chahari Kas
86

stream. Cr concentration in surface water was found higher than the average
concentration (0.022mg/L) for freshwater suggested by Wright and Welbourn, (2002)
and also as reported by Krishna et al. (2009) and Muhammad et al. (2011).
The distribution of Co concentration was higher than as reported by Krishna et
al., (2009) and Muhammad et al., (2011). Average Cd concentration in both the
surface and groundwater samples was higher than the WHO (2008) recommended
guidelines for drinking water. Cd concentrations were also higher than those reported
by Afzal et al., (2000), Ilyas and Sarwar (2003), and Arain et al., (2009) in different
areas of Pakistan. This could also be attributed to the sulphide bearing veins in
surrounding rocks.
Correlation matrix (CM), principle component analysis (PCA) and cluster
analysis have been used to evaluate the intensity and sources of pollution in surface
and groundwater. PCA revealed that the effluent received by the streams from the
industries were the major sources of contamination in corresponding groundwater. By
comparing the groundwater of Attock Basin with those of Haripur Basin, it is evident
that the effluent receiving streams may cause the potential health risk to inhabitants of
the study area.
Ingestion of water containing the significant amount of the metals could
results in adverse health effects and it is, therefore, considered as most important
route for exposure to trace metals. A provisional maximum tolerable daily intake
(PMTDI) of 0.5 mg/d/kg of body weight was established for Cu by Joint FAO/WHO
Expert Committee on Food Additives (JECFA) (WHO, 1982). The daily intake of Cu
in drinking water was much higher than that in reported by Tarit et al., (2003). JECFA
recommended a daily dietary requirement of Zn as 0.3 mg/kg of body weight and
87

PMTDI of 1.0 mg/kg of body weight (WHO, 1982). In this study, the daily intake of
Zn was found lower than both these guidelines. The main source of As intake for the
general population is the drinking water. On the basis of the PMTDI of inorganic As
of 2 µg/kg of body weight set by the Joint FAO/WHO (WHO, 1982). In our study, the
average daily intake of As was found lower than PMTDI. The daily intake values of
Mn, Cr, Ni, and Zn were higher than as reported by Kavcar et al., (2009). The HQ
indices of Cd, Cu, Mn, Ni, Pb, As and Zn metals were less than 1 and also lower than
as reported by other researchers (Lim et al., 2008; Kavcar et al., 2009; Chai et al.,
2010). It is, therefore, concluded that inhabitants of both the basins will not confront
with a significant potential health risk due to consumption of water.
88

5.1. Introduction
CHAPTER 5
SOIL CHEMISTRY
Soil is non-consolidated upper part of the earth’s crust that serves as a natural
medium for growth of plants (Gardiner and Miller, 2008). It is dynamic and unique
gift of nature that acquires the properties in accordance with forces acting upon it and
within itself. It is complete physical and biological system providing support,
nutrients, water and oxygen to plants. It sustains the growth of many plants and
animals. Human has been using the soil for food production since 11,000 years BP
(Lenne and Wood, 2011). In addition to the natural weathering-pedological
(geogenic) inputs under terrestrial settings, anthropogenic activities, such as the
mining and smelting industries, sewage sludge application and the use of mineral
fertilizers are said to be significantly responsible for elevated trace metals
concentrations in soils (Singh et al., 2004; Mapanda et al., 2005; Huang et al., 2006).
The contamination of agricultural soils with toxic metals is among the current
environmental issues as contaminated soils can enhance the release and uptake of
toxic metals by plants which threats to human health through the trophic transfer into
the food chain (Cui et al., 2005; Zhang et al., 2007). Pollutant activities can have
implications for the quality of agricultural soils, including phytotoxicity at high
concentrations and the transfer of heavy metals to the human diet from crop uptake or
soil ingestion by grazing livestock (Nicholson et al., 2003). In the past three decades,
the use of agrochemicals in this region has increased in an effort to enhance
production and improve soil fertility. Most of these fertilizers and pesticides contain
heavy metals such as Cd, Hg, Pb, and Zn (Kabata-Pendias and Pendias, 2001; Tariq et
89

al., 2007). The continuous and over application of these agrochemicals may enrich the
agricultural soil with heavy metals.
Soil pollution has become an important environmental issue due to rapid
industrialization, urbanization and excessive uses of chemical in agricultural sectors
over the last few decades. Numerous studies have indicated a significant increase of
heavy metal concentrations in agricultural soils (Wong et al., 2002, Nicholson et al.,
2003; Koleli, 2004; Mico et al., 2006; Yu, et al., 2008). In the Pakistan, researchers
have done a lot of work on the heavy metal contamination of industrial and urban soil,
(Tariq et al., 2006; Khan et al., 2010; Malik et al., 2010; Tariq et al., 2010; Ali and
Malik, 2011; Shah et al., 2011). However, not much work has been done on heavy
metal contamination, source identification and their spatial distribution in agricultural
soils of Pakistan. Similarly, none of research has reported heavy metal soil pollution
in Attock and Haripur basins. Thus, the assessment and monitoring of heavy metal
concentration and subsequent soil pollution remain unknown. The results of this study
provide geochemical baseline concentrations in soil of Attock and Haripur basins and
spatial variation along with possible identified sources of heavy metal pollution in soil
which may help in future environmental monitoring, remediation and planning
processes. The spatial maps validated for pollution sources identified using GIS is
used to assess the quality of soil in the study area (Imperato et al., 2003, Mahmut et
al., 2005, Malik et al., 2010) which may enable the decision makers and planners to
use different techniques to decontaminate the polluted soil (Xie et al., 2011). Spatial
distribution maps of metal concentration are helping to present the relationship
between human activities and heavy metals accumulation (Romic and Romic, 2003).
In this regard, spatial relationship of heavy metals using GIS is helpful in the
90

identification of hotspots which are the main concern for further remediation
programmes.
5.2. Materials and methods
The detail of the geochemical experimental work carried out on the soils of
Attock and Haripur basins in the Geochemistry laboratory of the NCE in Geology,
University of Peshawar, is given in the Chapter 2. Distributions of the sampling points
in both basins are given in Figure 5.1 (Apendix. Ib).
5.2.1. Statistical analysis
Analytical results were compiled to form a multielemental database using
EXCEL and SPSS prior to multivariate analysis. Descriptive statistics such as
minimum, maximum, mean and standard deviation were carried out and presented in
Table 5.1. Inter-elemental correlation was determined by using the Pearson
correlation matrix and cluster analysis. Principal component analysis (PCA) based on
factor analysis was applied for source identification of metals input in soils of the
study area. Factor loadings with a varimax rotation were also used. ArcGIS 9.2
software has been used for generation of the Geo-spatial maps of major (Ca, Mg, Na,
K, Fe, Mn) and heavy elements (Cd, Cr, Co, Cu, Zn, Pb, As and Ni,) in soils of both
basins. It will provide unbiased estimates and distribution of selected elements in soil
samples.2
5.2.2 Index of geoaccumulation (Igeo)
The geoaccumulation index allows evaluation of contamination by comparing
preindustrial and recent metal concentrations (Muller, 1969).
91

Fig. 5.1. Location map of the soil samples collected from the study area.
92

et al. (2004),
The geoaccumulation index is calculated from the equation modified by Loska
Igeo = log2 (Cn/1.5Bn)
where Cn is the measured concentration of the element in the examined soil
and Bn is the geochemical background value in the Earth's crust (Bowen, 1979). The
constant 1.5 allows us to analyze the natural fluctuations in the content of a given
substance in the environment and very small anthropogenic influences.
Muller (1969) divided the geoaccumulation index into seven classes, such as:
(Igeo≤0) practically uncontaminated; (0

Table 5.1. Statistical description of selected parameters in soils of Attock and Haripur basins.
Elements Attock Basin (n=50) Haripur Basin (n=60)
Range Mean± S.D Range Mean± S.D
pH 7.10-8.25 7.76± 0.24 6.70- 7.99 7.56± 0.31
EC 283- 520 423±105 220-455 246± 98
Ca 8698-199850 71381±46849 630-178439 69673±46513
Mg 11426-27803 20240±3821 6848-43911 19640±6308
Na 10058-117602 33243±32261 5957- 101014 20367±15412
K 8194-37852 18170±7534 10273-29989 19842±3351
Fe 14836-50694 40037±6964 25955-53697 40111±5401
Mn 589-1031 853±97 519-1110 798±109
Cd 0.39-1.71 0.81±0.33 0.06-1.32 0.75±0.31
Cr 30.15-89.07 50.65±13.34 18.57-76.35 42.80±9.72
Co 9.51-19.56 15.64±2.47 10.02-22.11 15.57±2.90
Cu 9.30-28.44 15.92±4.43 8.10-39.33 16.06±4.91
Zn 20.46-50.55 34.83±6.55 12.99-162.00 41.73±24.70
Pb 8.46-21.05 14.40±3.10 3.72-36.42 13.29±5.55
As 2.92- 7.61 4.73±1.71 5.84-17.24 8.79±1.98
Ni 18.96-44.22 36.04±5.08 18.09-50.52 34.03±6.34
Unit EC (Electrical conductivity) is (µS/cm)
Major cations, heavy and trace element are (mg/Kg)
n= number of samples
94

significantly higher in Attock Basin (423.0 µS/cm) as compared to the Haripur Basin
(249.6 µS/cm).
The major cations and heavy metals statistical analysis are given in Table 5.1,
graphically presented in Figure 5.2a-b and 5.3a-b and detail is given in Appendix III.
In Attock Basin, considerably elevated mean levels of major elements were shown by
Ca (71381 mg/Kg), Mg (20240 mg/Kg), Na (33243 mg/Kg), K (18170 mg/Kg), Fe
(40037 mg/Kg), and Mn (589 mg/Kg) (Table 5.1; Appendix III) . The average
concentrations of heavy metals were recorded as 0.81 mg/Kg, 50.65 mg/Kg, 15.64
mg/Kg, 15.92mg/Kg, 34.83 mg/Kg, 14.40 mg/Kg, 4.73 mg/Kg, and 36.04 mg/Kg, for
Cd, Cr, Co, Cu, Zn, Pb, As and Ni, respectively, in soil samples of Attock Basin
(Table 5.1; Appendix III). The decreasing order of major cations was found as
Ca>Fe>Na>Mg>K>Mn whereas, in heavy metals the decreasing order was found as
Cr>Ni>Zn>Cu >Co>Pb>As>Cd in the soil samples of Attock Basin.
The major elemental data showed that Ca (69673 mg/Kg), Mg (19640
mg/Kg), Na (20367 mg/Kg), K (19842 mg/Kg), Fe (40111 mg/Kg) and Mn
(798mg/Kg) were among the dominant elements in the soil samples of Haripur Basin.
Cations in the decreasing order found as Ca>Fe>Na>K>Mg>Mn. The average
concentration of heavy metals in soil samples were found as Cd (0.75 mg/Kg), Cr
(42.80 mg/Kg), Co (15.57 mg/Kg), Cu (16.06 mg/Kg), Zn (41.73 mg/Kg), Pb (13.29
mg/Kg), As (8.79 mg/Kg) and Ni (34.03 mg/Kg). The heavy metals were found in
increasing order such as Cr>Zn>Ni>Cu>Cr>Pb>As>Cd.
95

Concentration (mg/Kg)
Concentration (mg/Kg)
1e+6
1e+5
1e+4
1e+3
1e+2
100
80
60
40
20
0
K Na Ca Mg Fe Mn
Cu Zn Co Ni Pb Cd Cr As
Fig. 5.2. Box and Whisker plot of (a) major cations (b) selected HMs in soil samples
of Attock Basin
b
a
96

Concentration (mg/Kg)
Concentrations (mg/Kg)
1e+6
1e+5
1e+4
1e+3
1e+2
80
60
40
20
0
K Na Ca Mg Fe Mn
Cu Zn Co Ni Pb Cd Cr As
Fig. 5.3. Box and Whisker plots of (a) major cations (b) selected HMs in soil samples
of Haripur Basin
b
a
97

5.3.1. Inter- elemental relationship
The elemental correlations observed in the soils of Attock Basin soil samples
are given in Table 5.2. Among major elements, significant positive correlation of K
was found with Na (r =0.913), Mg (r = 0.524), Fe (r= 0.399) and Mn (r = 0.356). Na
exhibited positive correlations with Mg (r = 0.526), Fe (r = 0.377) and Mn (r = 0.342).
Mg had positive correlation with Fe (r = 0.456), Zn (r= 0.353) and Mn (r=0.575). Fe
exhibited strong positive correlation with Mn (r = 0.677). Among heavy and trace
metals, Cu was found to be positively correlated with Zn (r =0.746), Ni (r= 0.471) and
Pb (r = 0.397). Zn showed positive correlation with Ni (r = 0.553) and Pb (r = 0.486),
whereas, Ni showed positive correlation with Pb (r= 0.453). Metals such as As, Cd,
Co, Ca and Cr were not positively correlated with any other metal (Table 5.2).
The results of correlation analysis of the soil samples of Attock Basin were
further confirmed by Hierarchical cluster analysis (HCA) (Fig. 5.4a). Three clusters of
selected metals were formed. Cluster-1 consisted of Na, K, Mg, Fe and Mn. Cluster-2
was made up of Co, Cr and Cd, whereas, Cluster-3 comprised of Cu, Zn, Ni and Pb.
Ca and As was identified as outlier (Fig. 5.4a).
The Pearson correlation of metals in soil samples of Haripur Basin is
presented in Table 5.3. K exhibited strong positive correlation with Na (r = 0.534), Fe
(r = 0.322), Cu (r = 0.348), and Ni (r = 0.397). Na was strongly correlated with Cu (r
= 0.417). Ca exhibited significant positive correlation with Mg (r = 0.722) and
negative correlation with Zn (r = -0.445) and Co (r = -0.504). Fe exhibited significant
positive correlation with Mn (r= 0.669). Cu showed positive correlation with the Co
(r= 0.459), Ni (r= 0.355) and Cr (r= 0.356). Co showed positive correlation with Ni
(r= 0.406) while Ni exhibited positive correlation with Cd (r= 0.340) and Cr
98

Table 5.2. Correlation coefficient matrix of selected metals in the soil of Attock Basin
K 1
Na .913 1
K Na Ca Mg Fe Cu Zn Co Ni Pb Cd Cr Mn As
Ca -.260 -.239 1
Mg .524 .526 .045 1
Fe .399 .377 -.177 .456 1
Cu .186 .320 .032 .261 .016 1
Zn .107 .141 -.023 .353 .036 .746 1
Co .245 .239 -.583 .061 .227 .161 .271 1
Ni -.204 -.171 .032 -.164 -.082 .471 .553 .432 1
Pb .172 .206 .298 .083 .000 .397 .486 -.091 .453 1
Cd .034 .070 -.075 .106 .085 -.213 -.156 .284 .015 -.155 1
Cr .067 .157 -.310 -.141 .154 .061 -.050 .316 .152 .038 .171 1
Mn .356 .342 .014 .575 .677 .114 .204 .452 .030 .081 .245 .154 1
As -.147 -.140 .186 -.104 -.031 -.132 -.191 -.250 -.101 .005 -.343 -.133 -.177 1
Bold r-Values >0.330 are significant at p < 0.05.
Bold and underline r-Values >0.330 are significant at p < 0.01.
99

Table 5.3. Correlation coefficient matrix of selected metals in the soil of Haripur Basin
K 1
Na .534 1
K Na Ca Mg Fe Cu Zn Co Ni Pb Cd Cr Mn As
Ca -.084 .205 1
Mg -.067 .131 .772
Fe .322 .231 .128 .141 1
Cu .348 .417 -.259 -.193 .163 1
Zn .028 -.092 -.445 -.431 -.044 .263 1
Co .201 -.067 -.504 -.319 .017 .459 .262 1
Ni .397 .263 -.017 .149 .063 .355 -.180 .406 1
Pb .098 .135 -.129 -.200 .051 .311 .142 .294 .319
Cd .162 -.009 .259 .243 -.047 -.097 -.146 .004 .340 -.061 1
Cr .156 .141 -.109 -.001 .172 .356 .131 .198 .515 .246 .107 1
Mn .232 .167 .257 .281 .669 .144 -.314 .174 .233 .195 .027 .130 1
As -.110 -.143 .043 .184 .007 -.151 .094 -.165 .038 -.174 -.051 .146 -.033 1
Bold r-Values >0.300 are significant at p < 0.05.
Bold and underline r-Values >0.300 are significant at p < 0.01.
100

Fig. 5.4a. Cluster analysis of selected metals in soil samples of Attock Basin
Fig. 5.4b. Cluster analysis of selected metals in soil samples of Haripur Basin
101

(r= 0.515). However, As, Zn and Pb showed no positive correlation with any other
metals.
The results of correlation analysis of the soil samples of Haripur Basin were
further supported by HCA (Fig. 5.4b). Three clusters of metal were obtained by
cluster analysis. Cluster-1 consisted of Ca, Mg, Cd while Ni, Cr, Cu, Co and Pb were
grouped together in Cluster-2. Cluster-3 was made up of Fe, Mn, K and Na. However,
As and Zn in Haripur Basin recognized as outlier.
5.3.2. Principal component analysis
The main function of PCA is to reduce the dimensionality of the data set, since
no more than the first three principal components can explain the major part of the
variation of the data. It also facilitates in assigning source identity to each one of the
Principal components (Miller and Miller, 2000). It is being widely applied in soil
pollution (Mico et al., 2006; Zhang, 2006, Li et al., 2009; Saby et al., 2009). The
eigen values representing factors, the factor loading are generally classified as
“strong”, “moderate”, and “week” corresponding to absolute loading values of >0.75,
0.75-0.50 and

Table 5.4. Factor analysis of selected elements in soil samples of Attock basin
Element Factor 1 Factor 2 Factor 3 Factor 4 Factor 5
K
Na
Ca
Mg
Fe
Cu
Zn
Co
Ni
Pb
Cd
Cr
Mn
As
(PC1) (PC2) (PC3) (PC4) (PC5)
.737 -.290 .306 -.368 -.162
.763 -.224 .283 -.382 -.172
-.307 .325 .555 .525 -.050
.671 -.129 .475 .236 -.090
.601 -.352 .134 .242 .462
.498 .678 .067 -.172 -.081
.517 .728 -.008 .028 -.064
.568 -.042 -.672 -.027 .152
.201 .742 -.453 .145 .150
.287 .649 .239 .013 .017
.181 -.349 -.397 .504 -.386
.249 -.104 -.524 -.169 .254
.705 -.206 .043 .511 .285
-.336 .025 .367 -.191 .668
Eigen 3.649 2.519 2.013 1.304 1.078
% of Variance 26.411 17.990 14.377 9.316 7.697
Cumulative % 26.411 44.401 58.777 68.093 75.790
103

PC2 explained 17.99% of the variance of total results. This includes Cu, Zn,
Ni and Pb can be considered as a geogenic and anthropogenic component due to the
presence of high levels in soils (Mico et al., 2006; Li et al, 2009). The high Cu values
can be contributed from Cu-based agrochemicals related to specific agronomic
practices, whereas water and irrigation time can also be the source for the high Pb
values found in some soils (Rajaganapathy et al., 2011). In the study area, it was
noticed that the soil samples collected from near the road and the areas influenced by
waster contained high amount of Pb. PC3 and PC4 explained 14.37% and 9.31% of
the total variance, respectively. PC3 showed the high loading of the Ca while PC4
showed the high loading of the Ca, Mn and partially by Cd. PC5 contributed 7.67% of
the total cumulative variance with high loading of As.
PCA results for the soil samples of Haripur Basin are represented in Table.
5.5. Five principal components (PCs) were obtained with eigen values greater than 1,
which are explaining more than 72.4% variance of the data. PC1 explained 22.46% of
variance and exhibited elevated loadings of K, Cu, Co, Ni, Pb, and Cr which also
constituted a strong cluster (Fig. 5.4b), mostly coming from both natural and
anthropogenic sources. PC2 explained 20.05% of total variance and indicated
significant loadings of Ca, Mg, Fe and Mn along with a strong relation as shown by
cluster analysis (Fig. 5.4b). These metals could be contributed by the lithogenic
source. PC3 explained 10.38% of total variance and revealed higher contributions of
Ni and Cd, indicating anthropogenic interference in the soil samples. PC4 contributed
9.05% of total variance and showed high loading of As while PC5 showed the high
loading of none of element. By comparing the PCA with the CA of the soil samples of
both Attock and Haripur basins it was noticed that the CA was in total agreement with
the PCA results.
104

Table 5.5. Factor analysis of selected elements in soil samples of Haripur basin
Element Factor 1 Factor 2 Factor 3 Factor 4 Factor 5
(PC1) (PC2) (PC3) (PC4) (PC5)
K .599 .284 -.136 -.305 .301
Na .427 .425 -.246 -.425 .480
Ca -.408 .775 .029 -.083 .040
Mg -.317 .777 .173 .098 .048
Fe .326 .466 -.549 .391 -.024
Cu .765 -.054 -.082 -.083 .186
Zn .265 -.618 -.045 .180 .343
Co .668 -.297 .137 .080 -.381
Ni .631 .356 .543 -.002 -.074
Pb .537 -.058 .028 .020 -.316
Cd .020 .363 .599 -.250 -.130
Cr .545 .130 .396 .372 .202
Mn .329 .608 -.367 .353 -.383
As -.187 .050 .263 .673 .478
Eigen
3.145 2.8082 1.454 1.267 1.161
% of Variance
Cumulative %
22.466 20.058 10.389 9.053 8.291
22.466 45.524 52.912 61.965 70.256
105

5.4. Discussion
Soil pH of both basins are basic (pH>7) in nature which showed that soils are
insensitive to heavy metals accumulation (Wu et al., 2009) and are moderately
alkaline corresponding to high percentage of carbonate parent material (Pogue et al.,
1992; Khan and Malik, 1995). Lower EC value in the soil of Haripur Basin relative to
that of Attock Basin may be associated with the climatic variations as Haripur Basin
receive more precipitation, while Attock Basin is mostly remained dry or arid (Leong,
1992). Consequently, the soluble ions may be leached out in Haripur Basin.
The concentration of Ca in the earth’s crust is about 3.6%, where its
concentration in soils is about 1.37% (Lindsay, 1979). Cacite is the main source of Ca
in the soils of semiarid and arid regions like most of Pakistan (Rashid and Memon,
2005). It is essential element for plants and animal health and growth but its amount is
rarely deficient in soils. The average concentration of Ca in the soils of Attock and
Haripur basins were found as 7.13% and 6.96%, respectively. The concentration of
Mg in earth crust is 2.1% and average content of normal soil is 0.5% (Bohn et al.,
2001). In comparison, the soils of Attock (2.02%) and Haripur (1.96%) basins have
similar average concentration of Mg as that of earth crust, while it exceeded the
normal soil. The spatial distributions of Ca and Mg are given in Figure 5.5a and 5.5b
respectively. The concentration of Ca, Mg, K and Na in soils were found higher than
the reported concentration of these elements in the soils in other areas of Pakistan
(Malik et al., 2010; Iqbal and Shah, 2011; Muhammad et al., 2011, Shah et al., 2011).
The spatial distributions of Na and K are given in Figure 5.5c and 5.5d, respectively.
106

Fig. 5.5a. Spatial distribution of Ca concentrations in the soil samples of the study
areas
Fig. 5.5b. Spatial distribution of Mg concentrations in the soil samples of the study
areas
107

Fig. 5.5c. Spatial distribution of K concentration in the soils samples of the study
areas
Fig. 5.5d. Spatial distribution of Na concentrations in the soil samples of the study
areas
108

The decreasing order of cation concentrations in the soil of Attock Basin was
found as Ca> Na> Mg> K which is in compliance with Shah et al. (2011) where in
soils of Haripur Basin the decreasing order of cations was found as Ca>Na>K>Mg.
The concentrations of Fe in both of basins were found higher than the reported
by other researchers (Ali and Malik, 2011, Tume et al., 2011) while lower than
reported by Iqbal and Shah (2011). The concentration of Mn was found higher than
the reported by Sharma et al. (2007) for the soils of suburban areas of Varanasi, India
while lower than the Muhammad et al. (2011) for the soils of Kohistan region of
Pakistan. The spatial distributions of Fe and Mn are given in Figure 5.5e and 5.5f,
respectively.
A comparison of result of the major, heavy and trace element concentrations
in the soils of the present with those reported by other researchers is presented in
Table 5.6. Cd concentrations in the 90% of the soil samples of both basins were
found below 1.0 mg/Kg (Fig. 5.5g). This is in agreement with the observations of
Kabata-Pendias who reported that Cd concentrations for most of the surface soils did
not exceed 1.0 to 1.1 mg/Kg worldwide. A survey of Cd concentration in surface soils
from many parts of the world reported average concentration between 0.07 and 1.1
mg/Kg (Kabata-Pendias and Pendias, 2001). In studied soils of Attock and Haripur
basins the Cd concentrations were found within this range. The average concentration
of Cd in the studied soils was found higher than those reported by other researchers
elsewhere in the world (Wong et al., 2002; Hani and Pazira, 2011) while it was found
lower than that reported by Malik et al. (2010) in soils collected from different areas
of Pakistan.
109

Table. 5.6. Mean concentrations of selected elements of different soils of the world in comparison to present study
Na K Ca Mg As Fe Mn Zn Co Ni Pb Cd Cr Cu Reference(s)
33243 18170 71381 20240 4.73 40037 853 34.83 15.64 36.04 14.40 0.81 50.6 15.9 This study (Attock Basin)
20367 19842 69673 19640 8.79 40111 798 41.73 15.57 34.03 13.29 0.75 42.8 16.1 This study (Haripur Basin)
- - - - 13.9 6110 400 50.7 22.91 11.20 0.34 36.9 21.3 Roychowdhury et al., 2002
- - - - - - - 84.7 9.11 21.2 40.0 0.58 71.4 33.0 Wong et al., 2002
- - - - - - - - - - 47.0 1.89 27.4 - Lucho-Constantino et al.,2005
- - - - - 13608 295 52.8 7.1 20.9 22.8 0.34 26.5 22.5 Mico et al., 2007
- - - - - 156 43.2 - 13.37 15.57 2.80 30.6 20.3 Sharma et al., 2007
- - - - - - - 112.9 - - 46.7 0.14 58.6 14.3 Zhao et al., 2007
4110 17967 - 3.49 649 - - 1403 - 36.65 1175 5.3 33.9 1100 Qishlaqi et al., 2009
- - - - 8.0 - 547 69.8 11.2 24.2 24.0 - 59.4 21.9 Wu et al., 2009
297 4645 36412 16014 - 40694 - 1658 16.27 90.81 209.2 3.37 - 17.39 Ali and Malik, 2011
999 737 27531 2769 - 12784 393 23.83 10.34 - 2.5 1.56 21.0 10.2 Iqbal and Shah, 2011
4645 12146 9792 7153 - 25080 2437 361 117 99 117 2.0 146 193 Muhammad et al., 2011
92.3 1489 3520 906 - 1241 343 35.5 3.49 - 47.0 1.90 32.6 18.1 Shah et al., 2011
- - - - - 21,754 463 72.2 - 23.6 19.7 0.32 25.0 20.3 Tume et al., 2011
110

Fig. 5.5e. Spatial distribution of Fe concentrations in the soil samples of the study
area
Fig. 5.5f. Spatial distribution of Mn concentrations in the soils sample of the study
area
111

Generally, in most of the soils, Cr ranged from 10 to 50 mg/Kg depending on
the parental material (Adriano, 2001). The mean Cr concentrations of soil samples of
Attock Basin (50.65 mg/Kg) and Haripur Basin (42.80 mg/Kg) fall within this range.
However, the Cr concentrations in the studied soil samples were found greater than
those reported by Sharma et al. (2007), Iqbal and Shah, (2011) and Shah et al. (2011)
from elsewhere in the world. But its concentration was found lower then that reported
by Muhammad et al. (2011) for the soil of Kohistan region. The average
concentrations of Co in the soils throughout the world is 8 mg/Kg (Bowen, 1979) and
average concentration Co in soils of both the basins were found higher than this. The
spatial distributions of Cr and Co are presented in Figure 5.5h and 5.5i, respectively.
Comparing the Copper concentrations in the soils of Attock (15.92 mg/Kg)
and Haripur (16.06 mg/Kg) basins with soils of the other places in the world, it was
noticed that the studied soils have high Cu concentration then those reported in the
soils of Wuxi, China by Zhao et al. (2007) and Iqbal and Shah (2011) for the soils of
Islamabad region, Pakistan. However, it was found lower than those reported for
China soil (CEPA, 1995) and European Union soils (European Union, 2000)
Distribution pattern of Cu (Figure 5.5j) showed that high Cu concentrations were
found toward the north-east of the study area. Thus, it is likely that the high Cu
concentrations in the agricultural soils have been contributed by geogenic and
agricultural activities rather than from the industrial activities.
Zinc concentrations in soil samples in Attock and Haripur basins ranged from
20.4 to 50.6 mg/Kg (mean=34.8) and 12.9 to 162.1 mg/Kg (mean= 41.7), respectively
and found lower than the Chinese standards (250 mg/Kg) (CEPA, 1995) but higher
than those reported by other researchers for Pakistani soils (Iqbal and Shah, 2011;
Shah et al., 2011). Spatial distribution of Zn contents is shown in Figure 5.5k.
112

Fig. 5.5g. Spatial distribution of Cd concentrations in the soil samples of the study
area
Fig. 5.5h. Spatial distribution of Cr concentrations in the soil samples of the study
area
113

Fig. 5.5i. Spatial distribution of Co concentrations in the soil samples of the study
area
Fig. 5.5j. Spatial distribution of Cu concentrations in the soil samples of the study
area
114

Mean Pb concentrations of Attock and Haripur basins were 14.40 and 13.29
mg/Kg, respectively. The distribution pattern of Pb in the soils of the study area
suggested that the concentration of Pb was increasing toward industrial area (Fig.
5.5l). The Pb concentrations in the studied soils were found less than those reported
by other researchers in the soils elsewhere in the world (Sharma et al., 2007; Yang et
al., 2007). However, the Pb concentration in the studied soils is not in agreement with
the observation of Kabata-Pendias and Dudka (1991), as the Pb concentrations in the
agricultural soils of rural areas of Attock Basin showed high concentrations as
compared to those of the industrialized area of Haripur Basin. This could be due to the
irrigation with Pb contaminated-water as has already been mentioned in Chapter-4.
Total As concentrations in the studied soil ranged from 2.9 to 7.6 mg/Kg
(mean= 4.73) and 5.8 to 17.2 mg/Kg (mean= 7.99) in Attock and Haripur basins
respectively, was found higher than those reported in the vegetative soils by other
researchers elsewhere in the world (Roychowdhury et al., 2002; Huang et al., 2006;
Liu et al., 2006; Dahal et al., 2008). However, it was found lower than those reported
in the paddy soils by CEPA (1995). The Ni concentrations in the studied soils were
found lower than the toxic limit (100 mg/Kg) as suggested by Alloway (1995). It was
also found lower than those reported in the Pakistani soils by Malik et al. (2010). The
spatial distributions of As and Ni are shown in Figure 5.5m and 5.5n.
The contamination levels of selected metals were also assessed by using
geoaccumulation index (Igeo). It is the quantitative measure of the pollution index in
the soils. The contamination level was assessed by comparing the current and
preindustrial concentrations of the metals in soils. Fig. 5.6a and 5.6b demonstrated the
minimum, maximum and mean Igeo values of selected metals in the soil samples of
115

Fig. 5.5k. Spatial distribution of Zn concentrations in the soil samples of the study
area
Fig. 5.5l. Spatial distribution of Pb concentrations in the soil samples of the study area
116

Fig. 5.5m . Spatial distribution of As concentrations in the soils samples of the study
area
Fig. 5.5n. Spatial distribution of Ni concentrations in the soils samples of the study
area
117

Geoaccumulation Index (I geo)
4.00
2.00
0.00
-2.00
-4.00
Fig 5.6a. Geoaccumulation index for selected metals in soil samples of Attock basin
Geoaccumulation Index (I geo)
As K Na Ca Mg Fe Cu Zn Co NI Pb Cd Cr Mn
4.00
2.00
0.00
-2.00
-4.00
-6.00
-8.00
Elements
As K Na Ca Mg Fe Cu Zn Co NI Pb Cd Cr Mn
Elements
Fig 5.6b. Geoaccumulation index for selected metals in soil samples of Haripur basin
Max
Min
Average
Max
Min
Average
118

Attock and Haripur basins, respectively. Among the metals, the mean Igeo values of
As, Na, Ca, Pb and Cd indicated moderate to heavy contamination. Rest of elements
(Co, Cr, Cu, Fe, K, Mg, Mn and Zn) revealed practically no contamination in the
studied soils. The average Igeo values for Cd showed that the soil was moderately to
heavily contaminated in both the Attock and Haripur basins, while rest of the metals
showed almost similar behaviours in both the basins.
The spatial distribution map (Fig. 5.5 a-n) of all elements gathered from the study
area showed similar geographical trends, especially for As, Pb, Ni, Cr, Zn and Co,
with high concentration near the industrial area. As we move away from the polluted
areas, their concentrations were found relatively low. The inter-elemental correlation
among the As, Pb, Ni, Cr, Zn and Co were highly significant, and imply that they had
the same pollution sources. These correlations between elements are exactly in
accordance with the similarities in their distribution pattern.
119

CHAPTER 6
PLANT CHEMISTRY
This chapter has been divided into two sections. The first section discusses the
experimental work conducted on the vegetable and cereal crop samples in the
Department of Biological Sciences, University of Aberdeen, United Kingdom. While
the second section deals with the experimental work conducted on the medicinal
plants in the Geochemistry Laboratory of the National Centre of Excellence in
Geology, University of Peshawar, Pakistan.
SECTION I Heavy metal concentration in vegetable and cereal
6.1. Introduction
Vegetables and cereals have been estimated to account for up to 70% of the
dietary intake of Heavy metals (HMs) (Wagner, 1993; Nabulo et al., 2010).
Contamination of vegetables and cereals cannot be underestimated as these foodstuffs
are the main components of human diet. Vegetables are known for the supply of
vitamins, minerals, and fibers, and also have beneficial antioxidative effects.
However, consumption of vegetables elevated with heavy metals may cause a risk to
the human health. Heavy metal contamination of the food items is one of the most
important aspects of food safety (Wang et al., 2005; Radwan and Salama, 2006;
Sharma et al., 2009; Khan et al., 2010).
Heavy metals are among the major contaminants of food supply and may be
considered the most important problem to the environment (Zaidi et al., 2005). Such
problem is getting more serious all over the world, especially in developing countries
due to relatively unregulated industries, resulting in environmental contamination.
120

Heavy metals are non-biodegradable and persistent, continual release into soil is ever
mounting problem (Sathawara et al., 2004).
Food and water are the main sources through which human beings are exposed
to various toxic metals. Heavy metals are easily accumulated in vegetable as
compared to grain (Mapanda et al., 2005). High accumulation of heavy metals in
edible and non-edible parts cause clinical problem for animals and humans. Chronic
arsenic intake can cause serious health problems including cancers, melanosis,
hyperkeratosis (hardened skin), peripheral vascular disease (Blackfoot disease),
gangrene, diabetes mellitus, hypertension, and ischaemic heart disease (Srivastava et
al., 2001; Rahman, 2002; Fatmi et al., 2009) while high lead intake can cause
permanent neurological, developmental, and behavioral disorders, particularly in
children (Laidlaw et al., 2005). High concentration of heavy metals (Cr, Cu and Cd)
can cause lung cancer, upset stomachs and ulcers, respiratory problems, weakened
immune systems, kidney and liver damage, and alteration of genetic material
(Shanker and Venkateswarlu, 2011).
Monitoring and assessment of heavy metals concentration in agricultural soils
and vegetables has been carried out in some developed (Jorhem and Sundstroem,
1993; Milacic and Kralj, 2003) and underdeveloped countries (Parveen et al., 2003;
Mapanda et al., 2005; Radwan and Salama, 2006; Khan et al., 2010; Singh et al.,
2010; Yang et al., 2011). However, there are no such kinds of data available on
Attock and Haripur basins, Pakistan, for heavy metal contamination of soil and its
transfer to vegetable crops.
Eight heavy metals (As, Mn, Cr, Ni, Cu, Zn, Cd and Pb) concentrations in some
key leafy vegetables (spinach, fenugreek and mustard), non-leafy vegetable (garlic,
121

onion, radish, spinach and pea) and one main grain cereal wheat grown locally in both
the basins were investigated. The contribution of the heavy metal contamination
through dietary intake of the vegetables tested is also assessed based on the health risk
index and pollution load index of the vegetables.
6.2. Materials and methods
Table 6.1 presented the scientific name of vegetables and cereal crop (Wheat)
along with their abbreviation, common name and family name. The detail of the
experimental work carried out on the plant and soil samples of study area in
Laboratory of Department of Biological and Environmental Sciences, University of
Aberdeen have been given in the Chapter 2.
6.2.1. Transfer factor
The transfer factor (TF) was generally defined as the ratio of metal
concentration in the plants to the total metal concentration in soil (Zheng et al., 2007).
The TF of As, Cr, Co, Ni, Cu, Zn, Cd, Pb and Mn from soil to plant were calculated
as follows
TF = Metal concentration in plant samples/ Metal concentration in
corresponding soil sample
6.2.2. Metal pollution index (MPI)
The Metal pollution index (MPI) was calculated to examine the overall heavy
metal concentration in all the vegetables and cereal by using following formula (Singh
et al., 2010).
MPI (mg/Kg) = (Cf1× Cf1×. . . . × Cfn) 1/n
Where Cfn = concentration of metal n in the sample
122

Table 6.1. Vegetable and cereal crops collected from the study area
Botanical name Abbreviation Common name Family Edible part
Allium cepa L. (8) n A. cepa Onion Liliaceae Bulb/ stem
Allium sativum L. (9) A. sativum Garlic Alliaceae Bulb
Brassica campestris L. (11) B. campestris Mustard Brassicaceae Leaves
Brassica rapa L. (9) B. rapa Turnip Brassicaceae Root
Pisum sativum L. (10) P. sativum Pea Papilionaceae Fruit
Raphanus sativus L.(7) R. sativus Radish Brassicaceae Root
Spinacia oleracea L.(12) S. oleracea Spinach Chenopodiaceae Leaves
Trigonella foenum-graecum L. (9) T. foenum-graecum Fenugreek Papilionaceae Leaves
Triticum aestivum L. (12) T. aestivum Wheat Poaceae Grain
n number of plant samples
123

6.2.3. Health risk index (HRI)
The health risk, through the consumption of vegetables and cereal, to the local
inhabitants were calculated as a ratio of estimated exposure of test plant and oral
reference dose.
HRI = EDI/ RfD
Where EDI is the estimated daily intake and RfD is reference dose. Reference
doses were 4×10 -2 , 0.3, 1×10 -3 , 0.004, 0.02, 1.5, 0.3×10 -3 mg/Kg/day for Cu, Zn, Cd,
Pb, Ni, Cr, As (USEPA, 1996; 2002). HRI more than 1 is not considered safe for
human health. The estimated daily intake (EDI) of HMs was calculated by following
equation:
Estimated daily intake of element (EDI) = (M × K × I)/ W
Where M is the HMs concentration in plants (mg/Kg), K is conversion factor,
I is the daily average consumption of vegetables and W is the average body weight of
local population. The conversion factor used to convert green vegetable weight to dry
weight was 0.85. The average adult and child body weights were considered being 65
and 30 Kg, respectively, while the average daily intake for adult and children were
0.453 and 0.232 Kg/ person/day.
6.3. Result and discussion
In Pakistan, the cereals remain the main staple food and providing 62% of total
energy. Zaman (2011) had reported that there is an increasing trend of vegetables use
in food since 1979 to 2005 from 11.5% to 14.7%. Table 6.2 summarizes the mean
concentration of HMs in plant and soil and their TF. Figure 6.1 shows Cr, Cd, Cu, Zn,
124

Table 6.2. Heavy metals concentration in soil, edible part of vegetables and cereal and transfer factor (TF)
Plants Cr Cd Cu Zn
Soil Plant TF Soil Plant TF Soil Plant TF Soil Plant TF
Fenugreek 136.78 7.30 0.05 0.15 0.14 0.93 58.59 14.03 0.24 132.21 58.17 0.44
Garlic 136.78 1.71 0.01 0.15 0.11 0.73 58.59 6.41 0.11 132.21 47.65 0.36
Mustard 62.59 2.24 0.04 0.17 0.40 11.59 37.94 6.64 0.21 75.65 53.63 0.75
Onion 65.74 1.68 0.03 0.21 0.04 0.18 35.65 5.48 0.19 79.26 15.13 0.24
Radish 56.95 1.46 0.02 0.08 0.56 48.53 22.02 6.98 0.33 63.15 56.94 0.89
Spinach 37.62 3.83 0.11 0.14 0.28 2.31 41.17 13.85 0.44 56.49 51.15 0.95
Sweet pea 76.11 0.73 0.01 0.19 0.02 0.10 31.65 8.73 0.32 74.34 30.70 0.44
Turnip 77.44 1.07 0.02 0.11 0.24 9.93 32.92 7.10 0.27 81.49 39.95 0.61
Wheat 48.24 1.77 0.04 0.15 0.10 1.15 29.60 7.70 0.28 70.22 34.16 0.53
Reference 39.82 1.37 0.18 1.04 27.24 13.78 74.08 34.68
%recovery 59.43 52.78 73.67 92.46 85.11 97.74 74.08 69.51
Table 6.2. (continued) Heavy metals concentration in soil, edible part of vegetable and cereal and transfer factor (TF)
Plants Ni As Pb Mn
Soil Plant TF Soil Plant TF Soil Plant TF Soil Plant TF
Fenugreek 85.56 3.32 0.04 17.24 1.39 0.08 43.06 4.14 0.10 1399.12 129.15 0.09
Garlic 85.56 1.46 0.02 17.24 0.29 0.02 43.06 2.60 0.06 1399.12 62.20 0.04
Mustard 46.14 1.71 0.04 8.63 0.37 0.05 20.01 1.71 0.09 698.14 79.84 0.15
Onion 54.51 1.97 0.04 9.88 0.36 0.04 19.85 0.67 0.05 865.94 58.68 0.09
Radish 39.08 1.57 0.04 7.34 0.30 0.04 13.78 0.50 0.04 585.57 61.44 0.11
Spinach 32.46 3.06 0.11 5.54 0.66 0.15 14.86 4.52 0.29 393.14 145.63 0.48
Sweet pea 48.29 0.91 0.02 9.47 0.12 0.01 20.54 0.59 0.03 746.96 30.41 0.04
Turnip 52.37 1.10 0.03 10.24 0.25 0.03 22.42 0.61 0.04 792.47 56.35 0.09
Wheat 41.10 1.34 0.03 7.77 0.29 0.04 20.55 1.75 0.10 681.12 103.06 0.17
Reference 22.16 6.18 11.57 0.55 47.03 3.07 422.57 398
%recovery 80.88 97.71 64.29 102.28 77.09 62.46 95.82 96.60
125

Ni, As, Pb and Mn concentrations in species of vegetables and cereal. Difference in
metal concentrations among the vegetables implied that different species of
vegetables had different abilities and capacities to take up and accumulate the metals.
The mean Zn concentration in leafy vegetables was higher than those in non-leafy
vegetables, or that they have enhanced abilities to trap soil dust which was not
removed by subsequent washing. Of the leafy vegetables, the Zn concentration in
fenugreek was the highest (58.17 mg/Kg). The highest Zn level in the vegetables was
above the Chinese Food Hygiene Standard (20 mg/Kg). Among the non-leafy
vegetables, radish had the highest Zn concentration 56.9 mg/Kg, and pea had the
lowest Zn concentration of 30.7 mg/Kg. Zn concentration in all vegetables was higher
than the Zn concentration reported in Indian vegetables (Sharma et al., 2009).
The highest Cu concentration was in fenugreek (14.0 mg/Kg). All vegetables
with exception of fenugreek and spinach, were below the Chinese Food Hygiene
Standard of 10 mg/Kg and also less than Cu concentration reported in Chinese
vegetables (Yang et al., 2007) and Indian vegetables (Sharma et al., 2009) and higher
than the Cu concentration reported in Egyptian vegetables (Radwan and Salama,
2006). Lead level in vegetables varied from 0.5 to 4.14 mg/Kg. For all samples Pb
concentration was above the Chinese Food Hygiene Standard of 0.2 mg/Kg. Pb
concentration in all vegetables was less than Pb concentration reported by the other
researchers in vegetables (Fytianos et al., 2001; Sharma et al., 2009). Cd
concentration was higher than values reported by other researchers (Liu et al.,2006;
Fytianos et al., 2001; Nabulo et al., 2010), but significantly lower than that found in
Indian vegetables (Gupta et al., 2008; Sharma et al., 2009). Cd concentration in
126

1.8
1.6
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
10
8
6
4
2
0
8
6
4
2
0
25
20
15
10
5
0
Fenugreek
root
stem
seed
Garlic
Mustard
Onion
Chinese standard 1 FAO/WHO standards 2
Pea
Radish
Spinach
Turnip
Wheat
Fig. 6.1. Heavy metal concentration in different vegetable and cereal crop samples
1 Hao et al., 2009; 2 Khan et al., 2010
As
Cr
Ni
Cu
70
60
50
40
30
20
10
0
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
5
4
3
2
1
0
200
150
100
50
0
Fenugreek
Garlic
Mustard
Onion
Pea
Radish
Spinach
Turnip
Wheat
Zn
127
Cd
Pb
Mn

mustard (0.4 mg/Kg) and radish (0.56 mg/Kg) was also higher than the FAO/WHO
limit (0.3 mg/Kg).
It was cleared from the results that, leafy vegetables (such as fenugreek, leaf
mustard, and spinach) contained more As in their edible parts than non-leafy
vegetables (such as radish, garlic, onion, pea and turnip). These results were in
agreement with Huang et al., (2006), that the As concentrations in the edible parts of
non-leafy vegetables were lower than those for the leafy vegetables. Arsenic
concentration is higher than the As concentration reported in vegetables by other
researcher (Smith et al., 2006; Dahal et al., 2008).
Cr concentrations in all vegetables with exception of fenugreek (7.30mg/Kg),
were below the safety limit of contaminants in foods recommended by FAO/WHO
(5mg/Kg) while higher than Cr concentrations in vegetables and cereal reported in
other parts of the world (Fytianos et al., 2001; Liu et al., 2006; Singh and Garg, 2006;
Yang et al., 2007; Nabulo et al., 2010). Mn and Ni concentration in vegetable samples
ranged from 30.41 to 145.63mg/Kg and 0.91 to 3.32mg/Kg respectively and lower
than the concentration reported by Yang et al. (2007) and Gupta et al., (2008) in
vegetables. Mn concentration in the studied vegetables and cereal were three folds
higher than the Mn concentration reported by the Singh and Garg (2006) in Indian
vegetables and cereal.
6.3.1. Plant Transfer Factor from soil to plants
The plant transfer factor (TF) is usually used to evaluate the transfer ability of
a metal from soil to plant in a given soil–plant system and it is a ratio of the metal
concentration in the vegetables (fresh weight except for wheat) to the metal
concentration in the soil (dry weight) (Cui et al., 2004). The most important path of
128

human exposure to HMs is via the consumption of foodstuffs. The risk of human
exposure to the soil HMs through this path depends on the ability of crops to take up
HMs from soil and transfer it to edible parts and the daily consummation of the crop
products. Table 6.2 shows the TF values of Cr, Cd, Cu, Zn, Ni, As, Pb and Mn for
soil-to-edible parts of cereal and vegetables. The order of TF of heavy metals from
soil to cereal was Cd>Zn> Cu>Mn>Pb>Ni>As=Cr. The TFs of Cd, Zn, Cu, Mn, Pb,
Ni, As and Cr in cereal were 1.1, 0.53, 0.28, 0.17, 0.10, 0.03, 0.04 and 0.04,
respectively. Zn, Cu and Cd were more easily transferred to cereal than other metals.
The trend of TFs for heavy metals in total in leafy vegetable samples was in the order:
Cd>Zn>Cu>Mn>Pb>As>Cr>Ni. The highest TFs of Cd, Zn, Cu, Mn, Pb, As, Cr and
Ni in leafy vegetables were 11.59, 0.95, 0.44, 0.48, 0.29, 0.15, 0.11 and 0.11
respectively. This TF order of heavy metals in vegetables agreed with the results of
some of the previous researches (Khan et al., 2008; Zhuang et al., 2009; Cao et al.,
2010). Cd has the highest TF value in vegetables which is in agreement with the
findings of Fytianos et al. (2001), Singh et al., (2010) and Chary et al., (2008). The
transfer factor for non-leafy vegetable was in order of
Cd>Zn>Cu>Mn>Pb>Ni>As>Cr. The highest TF values in non-leafy vegetables for
Cd, Zn, Cu, Mn, Pb, Ni, As, Cr were 48.58, 0.89, 0.33, 0.11, 0.06, 0.04, 0.04 and 0.03
respectively. The higher uptake of the heavy metals in leafy vegetables may be due to
higher transpiration rate to maintain the growth and moisture content of these plants
(Tani and Barrington, 2005; Chary et al. 2008).
6.3.2. Metal pollution index
Metal pollution index (MPI) is the reliable and precise method for metal
pollution monitoring in edible plants of different edible plants. It is presented in
129

wheat
turnip
sweat pea
spinach
raddish
Onion
mustard
garlic
Fenugreek
0 1 2 3 4 5 6 7
Metal Pollution Index
Fig.6.2. Metal pollution index of different vegetables and cereal
130

Figure 6.2 for different plants. As MPI. The MPI of different plants in reducing order
was found as fenugreek> spinach> mustard> reddish> wheat> turnip> garlic>onion>
pea. The MPI of leafy vegetables was higher than non-leafy vegetables as they tend to
accumulate more metals then the others which is in agreement with the findings of
Singh et al. (2010). High MPI of leafy vegetables suggests that these vegetables may
cause more health risk in human due to higher accumulation of HMs in their edible
parts.
6.3.3. Estimated daily intake (EDI) for HMs
Although there are many pathways of human exposure to HMs, but in study
area cereal and vegetables have been identified as one of the major pathways. The
health risk of any pollutant is estimated by level of exposure, by detecting the routes
of exposure to target organism. The EDI values of HMs from vegetables for different
age groups in study are listed in Table 6.3. The EDI of HMs were compared with the
provisional tolerable daily intakes (PTDIs) suggested by the Joint FAO/WHO Expert
Committee on Food Additives JECFA or reference dose (RfD) to assess the potential
health risks. As a result, children had the highest EDI of each element than adults. The
Provisional Daily Intake (PTDI) for Pb, Cd, Cu, and Zn were 214 μg, 60 μg, 3 mg and
60 mg, respectively, for an average adult (60 Kg body weight) (FAO/WHO, 1999).
The mean EDI of Cd by vegetable consumption in study area was 1.38 and
1.18 μg/Kg/day for children and adults, respectively. In comparison, the EDI of Cd
from vegetables was higher than those reported in Santiago, Chile (Munoz et al.,
2005) but lower than those reported in Rio de Janerio (Santos et al., 2004) and Samta
of Bangladesh (Alam et al., 2003). The mean EDI of Zn was found 259.0 and 287.4
μg/Kg/day for adult and child, respectively. The mean EDI of Cu was 51.5 and 57.2
131

Table 6.3. Estimated daily intake (EDI) of HMs via consumption of different
vegetables and cereal
Plants As Cr Ni Cu Zn Cd Pb Mn
Fenugreek Adult 8.25 a 43.2 19.7 83.1 344.6 0.83 24.5 765.1
Child 9.16 47.9 21.8 92.2 382.4 0.92 27.2 848.9
Garlic Adult 1.70 10.2 8.6 37.9 282.3 0.64 15.4 368.5
Child 1.88 11.3 9.6 42.1 313.2 0.72 17.1 408.8
Mustard Adult 2.22 13.3 10.1 39.3 317.7 2.35 10.1 472.9
Child 2.46 14.7 11.2 43.6 352.5 2.61 11.2 524.8
Onion Adult 2.13 9.9 11.6 32.4 89.6 0.21 3.9 347.6
Child 2.36 11.1 12.9 35.9 99.8 0.23 4.4 385.7
Radish Adult 1.77 8.6 9.3 41.3 337.3 3.32 2.9 363.9
Child 1.96 9.6 10.3 45.9 374.3 3.68 3.3 403.8
Spinach Adult 3.93 22.7 18.1 82.0 303.0 1.68 26.8 862.7
Child 4.36 25.2 20.1 91.0 336.2 1.86 29.7 957.3
Pea Adult 0.74 4.3 5.4 51.7 181.8 0.11 3.5 180.2
Child 0.82 4.8 5.9 57.4 201.9 0.13 3.9 199.9
Turnip Adult 1.50 6.3 6.5 42.1 236.6 1.40 3.6 333.8
Child 1.66 7.0 7.3 46.7 262.6 1.55 4.0 370.4
Wheat Adult 2.00 12.4 9.3 53.7 238.1 0.06 1.0 718.3
RfD b
Child 2.22 13.7 10.3 59.6 264.2 0.74 13.5 797.0
0.3 1500 20 40 300 1 4 140
a Estimated daily intake (µg /Kg/day)
b Reference dose (µg/Kg/day)
132

μg/ Kg/day for adult and child, respectively. In comparison with other countries, the
estimated dietary intake of Cu and Zn by vegetables in study area was above than
those reported by the other researches (Zheng et al., 2007; Song et al., 2009; Sharma
et al., 2008). EDI for Cd and Cu was less than the PTDI values but high in case of Zn.
The mean EDI of Ni by consumption of vegetables was ranged from 5.4 to
19.7 μg/Kg/day and 5.9 to 21.8 μg/Kg/day, for adults and children respectively. It was
lower than EDI reported in literature (89 μg/g/day) (Santos et al., 2004) but higher
than reported by other researchers (Zheng et al., 2007; Song et al., 2009). Daily intake
values were also lower than the RfD of 20 μg/Kg. Estimated daily intake values for
Mn was ranged from 180 to 862 μg/Kg/day (mean= 490) and 199 to 957 μg/Kg/day
(Mean= 544) lower than the reported EDI 2.2 to 4.5 mg/day (Santos et al., 2004;
Yang et al., 2007).
The EDI for Cr was 14.6 and 16.1 μg/Kg for adults and children respectively.
It was lower than the RfD of 1500 μg/Kg body weight. The estimated value falls in
the low-range of the values reported in literature (62 to 320 μg/Kg/day) (Wang et al.,
2005; Zheng et al., 2007; Song et al., 2009). The mean EDI of Pb was 10.2 and 12.7
μg/Kg/day for adults and children respectively. The estimated values was lower than
those reported by Zheng et al. (2007) in China, Mapanda et al. (2007) in Zimbabwe
and Khan et al. (2010) in Pakistan.
The results showed that the estimated total As daily intake by vegetable
consumption was 2.69, and 2.99 μg/Kg/day for adults and children, respectively. The
As intake was higher than 0.038 μg/Kg for adults in Santiago, Chile (Munoz et al.,
2005), 0.463 μg/ Kg for adults in Bangladesh (Alam et al., 2003) and 0.08 for adults
and 0.102 μg/Kg for children in Beijing (Song et al., 2009) but less than 31.04 μg/Kg
133

for adult in Spain (Matos-Reyes et al., 2010). The Joint FAO/WHO Expert
Committee on Food Additives established 2 μg/Kg as a provisional maximum
tolerable daily intake for ingested arsenic (World Health Organisation, 1981). It is
known that inorganic arsenic is much more toxic than organic arsenic and 96% of the
total arsenic in vegetables is inorganic arsenic (Smith et al., 2006). According to
WHO, intake of 1.0 µg of inorganic As per day may give rise to skin lesions within a
few years (FAO/WHO, 1999).
6.3.4. Health risk index of HMs
Health risk index was calculated as ratio of estimated EDI and reference dose
(RfD). An index more than 1 is considered not safe for human health. The HRIs of
HMs in vegetables for the inhabitants in study area are listed in Table 6.4. Among
those 8 elements, the HRI of As was the highest, and was higher by 2- 14 folds than
that of the other elements. The results showed that HRI for As and Mn were >1 for all
the vegetables (both leafy and non-leafy) while in case of Zn, Cu, Pb, Cd, and Ni, it is
>1 only in leafy vegetables. HRI for Cr was lower than 1 for all the vegetables. This is
an agreement with Wang et al. (2005) who also suggested that HRI of Cr in the
consumption of vegetables is minimal, comparing with others HMs. The health risk
index of leafy vegetables was higher than the non-leafy vegetables. This suggests that
the inhabitants of the study area including adults and children are experiencing the
potential health risk via the consumption of vegetables.
134

Table 6.4. Health risk index of HMs via consumption of different vegetables and cereal
Plants As Cr Ni Cu Zn Cd Pb Mn
Fenugreek Adult
Child
Garlic Adult
Child
Mustard Adult
Child
Onion Adult
Child
Radish Adult
Child
Spinach Adult
Child
Pea Adult
Child
Turnip Adult
Child
Wheat Adult
Child
27.5 2.88E-02 0.98 2.08 1.15 0.83 6.13 5.46
30.5 3.20E-02 1.09 2.31 1.27 0.92 6.80 6.06
5.7 6.77E-03 0.43 0.95 0.94 0.64 3.85 2.63
6.3 7.51E-03 0.48 1.05 1.04 0.72 4.27 2.92
7.4 8.86E-03 0.51 0.98 1.06 2.35 2.53 3.38
8.2 9.83E-03 0.56 1.09 1.18 2.61 2.80 3.75
7.1 6.65E-03 0.58 0.81 0.30 0.21 0.99 2.48
7.9 7.38E-03 0.65 0.90 0.33 0.23 1.09 2.76
5.9 5.75E-03 0.47 1.03 1.12 3.32 0.75 2.60
6.5 6.38E-03 0.52 1.15 1.25 3.68 0.83 2.88
13.1 1.51E-02 0.91 2.05 1.01 1.68 6.70 6.16
14.5 1.68E-02 1.00 2.28 1.12 1.86 7.43 6.84
2.5 2.87E-03 0.27 1.29 0.61 0.11 0.87 1.29
2.7 3.18E-03 0.30 1.43 0.67 0.13 0.96 1.43
5.0 4.23E-03 0.33 1.05 0.79 1.40 0.91 2.38
5.5 4.69E-03 0.36 1.17 0.88 1.55 1.01 2.65
6.7 8.24E-03 0.47 1.34 0.79 0.06 0.26 5.13
27.5 2.88E-02 0.98 2.08 1.15 0.83 6.13 5.46
135

SECTION II Heavy metals contamination in medicinal herbs
6.1. Introduction
Therapeutic plants have always been valued as a mode of treatment of variety
of ailments in folk cultures and have played a very important role in discovering the
modern day medicines with novel chemical constituents (Chan, 2003; Haider et al.,
2004; Devi et al., 2008). It is known fact that generally medicinal plants have higher
elemental content then other plants (Rajurkar and Pardeshi, 1997). Therefore, it is the
major interest to establish the levels of HMs in common therapeutic plants because at
elevated levels, these metals can also be dangerous and toxic (Schumacher et al.,
1991; Ajasa et al., 2004).
In recent years, several authors reported many studies on the importance of
elemental constituents of the herbal drug plants which enhanced the awareness about
trace elements in these plants (Kanias and Loukis, 1987 in Greece; Wong et al., 1993
in China; Ajasa et al., 2004 in Nigeria; Basgel and Erdemoglu, 2006 in Turkey;
Sheded et al., 2006 in Egypt; Koe and Sari, 2009 and Sharma et al., 2009 in India).
Most of these studies concluded that essential metals can also produce toxic effects
when the metal intake is in high concentrations, whereas non-essential metals are
toxic even in very low concentrations for human health.
Phytotherapy is a common practice in Pakistan (Hayat et al., 2008).
Inhabitants of rural areas are intensely dependent on medicinal flora of their
surroundings (Ikram and Hussain, 1978). The present study was conducted in Attock
and Haripur basins that are relatively rich in medicinal plants. A number of
ethnobotanical studies have documented various healing plants with folk recipes in
the Attock and Haripur basins (Shinwari and Khan, 2000; Ahmed et al., 2003; Ashfaq
136

et al., 2004; Marwat et al., 2004; Ahmed et al., 2006; Qureshi et al., 2007; Qureshi
and Ghufran 2007; Hayat et al., 2008; Hussain et al., 2008; Mahmood et al., 2008;
Ahmed et al., 2008; Abbasi et al., 2009; Ahmed et al., 2009). But to date no study has
been conducted in this region to estimate the medicinal plants quality with respect to
HMs. This study aims to determine the heavy metals (Cu, Zn, Ni, Pb, Cr, Co, Cd and
Mn) levels in most popular medicinal plants of the study area in a comparison with
available international standards. Also, potential health risks associated with toxic
metals were discussed.
6.2. Materials and methods
Most popular medicinal plants were collected throughout the Attock and
Haripur basins. Details of these plants are given in Table 6.5a and 6.5b. The
identification and nomenclature of these plants was based on The Flora of Pakistan
(Nasir and Ali, 1978).
The detail of the experimental work carried out on the medicinal plant samples
of Attock and Haripur basins in Geochemistry Laboratory of NCE in Geology,
University of Peshawar, has been given in the Chapter 2.
6.3. Results
Heavy metal concentrations in studied medicinal plants of Attock and Haripur
basins are presented in Table 6.6a and Table 6.6b, respectively. Results of heavy
metal concentrations in the medicinal plants in the Attock Basin revealed that the
highest mean levels of Zn (50.21 mg/Kg) was found in C. melo, Co (7.06 mg/Kg) in
C. sativa and Cu (19.19 mg/Kg) was found in B. compestrris. However, C. sativa
samples showed the highest mean levels of Ni (15.85 mg/Kg) and Cr (29.45 mg/Kg).
The highest mean levels of Pb
137

Table 6.5a. Common medicinal herbs used in folk remedies by the inhabitants of Attock Basin, Pakistan
Plant species Family Vernacular
name
Achyranthes aspera L. Amaranthaceae Puth Kanda
Part used Disease cure Reference (s)
Whole plant
Kidney stone, cough asthma,
stomachache,
dropsy, piles, skin eruption
Ahmed et al., 2006;
Qureshi et al., 2007;
Qureshi and Ghufran, 2007;
Hayat et al., 2008;
Ahmed et al., 2009
Brassica campestris L. Brassicaceae Sarso Whole plant Skin infection Ahmad et al., 2008;
Hayat et al., 2008
Cannabis sativa L. Cannabaceae Bhang Whole Body inflammation,
Ahmed et al., 2006;
Plant intoxication, sedative,
Qureshi et al., 2007;
narcotic intoxicant,
Qureshi and Ghufran, 2007;
antispasmodic, diarrhea
Hayat et al., 2008;
Ahmed et al., 2008
Chenopodium album L. Chenopodiaceae Batwa Vegetative Jaundice Qureshi et al., 2007;
parts
Hayat et al., 2008
Citrus grandis L. Rutaceae Malta Whole plant Hepatic disorder, jaundice,
Shinwari & Khan, 2000;
urinary diseases, malaria &
rheumatism
Hayat et al., 2008
Convolvulus arvensis L. Convolvulaceae Vahri Whole plant Skin wounds, constipation
Qureshi et al., 2007;
and abdominal sore
Ahmad et al., 2008
Calotropis procera R. Asclepiadaceae Ak Root and Diabetics, cholera, gastritis
Ashfaq et al., 2004;
leaves and malaria
Qureshi et al., 2007
Cucumis melo Cucurbitaceae Chibber Fruit Digestive and stomach
Ashfaq et al., 2004;
problem.
Hayat et al., 2008
Desmostachyia bipinnata L. Poaceae Dub grass Roots Broken bone, asthma,
Ashfaq et al., 2004;
jaundic
Ahmad et al., 2008;
Hayat et al., 2008
Justicia adhatoda L. Acanthaceae Bhekkar Whole plant Toothache, abdominal pain, Shinwari and Khan, 2000;
rheumatism, skin, cough,
Hayat et al., 2008;
asthma
Ahmed et al., 2005;
Ahmed et al., 2007;
138

Ahmed et al., 2009
Malva parviflora L. Malvaceae Sunchal Whole plant Cold, cough and constipation Ashfaq et al., 2004;
Hayat et al., 2008
Peganum harmala L. Zygophyllaceae Hermal Whole plant Insecticide and as brain tonic Ashfaq et al., 2004;
Mahmood et al., 2008
Spinacia oleracea L. Chenopodiaceae Palak Aerial parts Anemia, bone tonic. Ahmed et al., 2003;
Hayat et al., 2008
Trigonella foenum-graecum L. Methray Aerial parts Diabetes Ahmed et al., 2008
Withania somnifera L. Solanaceae Axan Leaves and
roots
Blood purification, analgesic,
joint pain, Anticancer
Ashfaq et al., 2004;
Qureshi and Ghufran, 2007;
Qureshi et al., 2007
139

Table 6.5b. Common medicinal herbs used in folk remedies by the inhabitants of Haripur Basin, Pakistan
Plant species Family Local name Part use Disease cure Reference(s)
Achyranthes aspera L. Amaranthaceae Puthkanda Whole plant Cough, asthma, kidney stone, anti
Abbasi, 1999;
inflammatory,
Marwat et al., 2004;
diuretic
Hussain et al., 2008
Alternanthera pungens Amaranthacea Kabli Whole plant Itching Marwat et al., 2004
Brassica campestris L. Brassicaceae Sarsoon Whole plant Leucorrhoea, menstrual disorder, body
weakness,
internal pain, skin diseases
Abbasi, 1999
Cannabis sativa L. Cannabaceae Bhang Leaves Body inflammation, boils, sedative, relaxant Abbasi, 1999;
Marwat et al., 2004;
Hussain et al., 2008
Convolvulus arvensis L. Convolvulaceae Liali Whole plant Painful joints, skin disorder, constipation Abbasi, 1999;
Marwat et al., 2004;
Hussain et al., 2008
Hordeum vulgare L. Poaceae Jou Seeds Jaundice, hepatitis Abbasi et al., 2009
Justicia adhatoda L. Acanthaceae Bhekkar Whole plant Cough, asthma, bronchitis, stomach
Abbasi, 1999;
inflammation,
dysentery, diarrhea, phelgum, jaundice,
diabetes,
mouth gum, toothache, tuberculosis
Abbasi et al., 2009
Parthenium hysterophorus
L.
Asteraceae Gandi booti Whole plant Anti-hysteric, dysentery, anti-amoebic Marwat et al., 2004
Ricinus communis L. Euphorbiaceae Arand Whole plant Constipation, stomach disorder, swelling, Abbasi, 1999;
Chambal,
Matin et al., 2001;
against scorpion sting
Hussain et al., 2008
Withania somnifera (L.)
Dunal
Solanaceae Asghand Whole plant Aphrodisiac, diuretic, bronchitis, ulcer Hussain et al., 2008
140

Table 6.6a. Heavy metals concentrations in medical plants collected from the Attock Basin
Plant Zn Cu Cr Ni Co Cd Pb Mn
A. aspera 19.91±4.61 7.56±1.22 2.48±0.90 4.90±0.92 4.23±0.42 0.69±0.41 8.28±1.66 102.56±6.70
B. campestris 18.65±0.18 15.54±3.14 12.44±1.13 5.93±1.03 4.83±0.71 2.01±0.97 11.54±2.11 65.25±4.44
C. sativa 29.25±4.81 8.96±0.98 29.45±2.93 15.85±4.57 4.73±1.58 1.65±0.64 10.51±2.46 51.19±6.54
C. album 13.79±0.19 13.36±3.38 5.04±1.26 3.81±0.21 7.06±0.58 1.65±0.57 5.43±0.04 65.64±5.54
C. grandis 14.85±2.30 15.50±2.13 12.05±1.67 4.58±0.99 4.93±0.32 2.20±0.33 20.03±0.89 41.45±2.89
C. arvensis 16.58±2.67 8.93±0.78 1.28±0.08 2.79±0.98 4.36±0.98 1.24±0.54 3.46±0.87 67.35±11.98
C. procera 13.45±1.89 3.63±0.13 0.68±0.04 5.15±0.83 3.93±0.67 0.68±0.12 14.88±2.21 42.12±3.78
C. melo 50.21±3.28 11.76±1.56 18.78±0.68 9.95±2.76 6.68±1.41 2.61± 0.21 14.56±0.94 47.33±3.57
D. bipinnata 16.93±3.56 4.85±0.34 9.36±1.14 8.43±2.57 1.81±0.82 0.36±0.14 6.08±1.02 41.36±4.67
J. adhatoda 19.10±0.18 7.73±0.78 7.28±1.13 4.75±0.78 3.00±1.23 2.13±0.89 1.90±0.09 7.70±1.23
M. parviflora 21.41±3.03 13.57±1.01 13.63±2.02 3.34±1.49 4.16±1.46 1.65±0.59 4.31±1.89 14.27±1.43
P. harmala 18.68±3.34 12.26±2.63 8.48±2.99 1.60±0.40 0.96±0.03 1.24±0.74 4.14±1.12 35.41±2.76
S. oleracea 38.88±4.87 14.04±2.11 11.80±2.99 2.25±0.05 5.35±0.52 2.18±0.54 4.70±0.79 163.98±10.98
T. foenum-graecum 16.16±2.34 14.93±3.01 5.79±2.56 1.76±1.96 2.68±0.57 1.63±0.07 4.96±1.57 16.73±0.53
W. sominifera 21.33±3.63 8.54±0.98 8.24±2.89 5.67±2.62 3.69±0.61 1.34±0.64 7.83±3.29 33.14±5.87
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Table 6.6b. Heavy metals concentrations in medical plants collected from the Haripur Basin
Plant Zn Cu Cr Ni Co Cd Pb Mn
A. aspera 20.91±4.61 7.06±1.15 1.48±0.90 5.90±0.92 5.23±0.42 0.59±0.41 9.28±1.66 105.56±6.70
A. pungens 37.86±2.76 9.11±3.09 17.74±1.56 7.97±1.67 3.41±0.60 1.45±0.80 9.89±2.95 40.50±5.48
B. campestris 37.56±2.34 10.78±3.49 8.19±1.08 6.64±1.98 7.55±3.57 1.20±0.28 8.78±2.33 87.01±6.32
C. sativa 29.45±4.81 9.60±3.59 29.49±2.93 15.80±4.57 4.79±1.58 1.66±0.64 10.57±2.46 54.19±21.54
C. arvensis 17.38±2.67 8.93±1.21 1.20±0.08 2.60±0.98 4.33±0.98 1.23±0.54 3.15±0.87 77.35±11.98
H. vulgare 65.85±1.06 19.19±0.69 6.21±1.45 14.96±1.68 11.26±0.30 1.16±0.19 10.34±1.75 37.00±10.91
J. adhatoda 31.64±7.84 8.38±3.58 5.30±2.50 4.09±1.47 6.50±1.50 0.99±0.29 5.12±2.05 32.64±18.33
P. hysterophorus 28.92±9.18 12.98±4.17 6.07±2.12 6.54±2.41 4.93±1.65 1.19±0.50 8.24±3.12 35.36±5.50
R. communis 31.55±4.20 15.62±2.24 14.26±1.28 8.10±2.92 4.70±0.95 1.58±0.07 10.63±2.44 64.60±4.28
W. somnifera 22.33±3.63 8.33±1.93 8.34±2.89 5.66±2.62 3.59±0.61 1.33±0.64 7.93±3.29 34.14±5.87
142

(20.03 mg/Kg), Cd (2.61 mg/Kg) and Mn (102.56 mg/Kg) were found in C. gradis, C.
melo, A. aspera samples respectively.
Results of heavy metal concentrations in medicinal plant of Haripur Basin are
presented in Table 6.6b. The range of Mn varied with values between 32.64 mg/Kg (J.
adhatoda) and 105.56 mg/Kg (A. aspera). The content of Zn ranged between 17.38
mg/Kg (C. arvensis) and 65.85 mg/Kg (H. vulgare). The lowest (7.06 mg/Kg) content
of Cu was in A. aspera and maximum concentration (19.19 mg/Kg) was found in H.
vulgare. The range of Cr varied between 1.2 mg/Kg (C. arvensis) and 29.49 mg/Kg
(C. sativa). C. arvensis accumulated lowest (2.6 mg/Kg) Ni and C. sativa
accumulated maximum (15.8 mg/Kg) Ni. H. vulgare had highest (11.26 mg/Kg) Co
concentration, while A. pungens recorded the minimum (3.41 mg/Kg) accumulation
of Co. Cd concentration ranged between 0.59 mg/Kg in A. aspera and 1.66 mg/Kg in
C. sativa. Among the investigated medicinal plants R. communis exhibited highest
(10.63 mg/Kg) Pb concentration and C. arvensis possess minimum (3.15 mg/Kg)
concentration of Pb.
6.4. Discussion
The maximum tolerable zinc level has been set as 500 mg/Kg for cattle and
300 mg/Kg for sheep (National Research Council, 1984). The permissible limit set by
FAO/WHO (1984) in edible plants was 27.4 mg/Kg. By comparing the metals
concentrations in the studied medicinal plants with those proposed by FAO/WHO
(1984), it is found that all studied plants of Attock Basin except C. sativa, C. melo and
S. oleracea were found within this range and in case of Haripur Basin only A. aspera,
C. arvensis and W. somnifera are within this limit. However, for medicinal plants the
WHO (2005) limits have not yet been established for Zn. According to Bowen (1966)
143

and Allaway (1968), the range of Zn in agricultural products should be between 15 to
200 mg/Kg.
The permissible limit of Cu set by FAO/WHO (1984) in edible plants was
3.00 mg/Kg. After comparing, the metals concentrations in the studied medicinal
plants with those proposed by FAO/WHO (1984), it was found that all the medicinal
plants of both basins accumulated Cu above this limit. Cu concentrations in medicinal
plants of Attock Basin were found lower than the Cu concentrations in medicinal
plants set by China (20 mg/Kg) and Singapore (150 mg/Kg) (WHO, 2005) while in
case of the medicinal plants of Haripur Basin, Cu concentrations were found above
the limit set by China and below the limit set by Singapore. Cu concentrations in
studied plants of Attock Basin were found lower than that reported by Reddy and
Reddy (1997) in medicinally important leafy material of India (17.6 mg/Kg to 57.3
mg/Kg), where as the studied plants of Haripur Basin were found within this range.
Chronic exposure to Cr may result in liver, kidney and lung damage (Zayed
and Terry, 2003). After comparing, Cr concentration in the studied medicinal plants
with those proposed by FAO/WHO (1984) in edible plants (0.02 mg/Kg), it was
found that all studied plants of both the basins accumulated higher then this limit. The
high concentration of Cr is due to presence of high Cr in both surface and
groundwater of study area as discussed in Chapter 4. The permissible limit for Ni set
by FAO/WHO (1984) in edible plants is 1.63 mg/Kg. After comparison, metal
concentration in the studied medicinal plants with those proposed by FAO/WHO
(1984), it was found that all plants accumulated Ni above this limit. There are no
established criteria for Co in medicinal plants. However, the medicinal plants of both
the basins had Co concentrations higher than those reported by Basgel and Erdemoglu
(2006) in herbs of Turkey.
144

The permissible limit of Cd set by FAO/WHO (1984) in edible plants is 0.21
mg/Kg and for medicinal plants it is set as 0.3 mg/Kg. Similarly, permissible limit in
medicinal plants for Cd set by Canada is 0.3 mg/Kg in medicinal plant material
(WHO, 2005). By comparing, the Cd concentrations in the studied medicinal plants
with those proposed by FAO/WHO (1984) and WHO (2005), it was found that all
studied plants accumulated Cd above this limit. This may cause both acute and
chronic poisoning, adverse effect on kidney, liver, vascular and immune system of the
local community of the study area (Heyes, 1997).
The permissible limit of Pb concentration in edible plants is 0.43 mg/Kg and
in medicinal plants it is 10 mg/Kg (FAO/WHO, 1984; WHO, 2005). Similarly,
permissible limits of Pb in medicinal plants set by Canada, is 10 mg/Kg in medicinal
plants (WHO, 2005). Comparing the Pb concentrations in the studied medicinal plants
with the proposed limits, it was found that the medicinal plants such as B. campestris,
C. sativa, C. procera and C. melo of the Attock Basin and R. communis, H. vulgare
and C. sativa of the Haripur Basin accumulated Pb above these limits. It could be due
to the presence of high Pb in both water and soils of the study area as discussed in
Chapter 4 and Chapter 5, respectively.
If the results obtained during this study were compared with the data of Kim et
al. (1994), who examined the heavy metals contents in 291 samples of medicinal
plants, grown on unpolluted area, it was noticed that the studied data did not agree
with what the Kim et al. (1994) have reported. They have reported Cd, Cu, Pb, Zn, Cr,
and Ni contents in the plants as 0.386, 6.636, 0.817, 27.776, 1.448 and 0.729 mg/Kg
respectively. Most of the studied plant samples contain heavy metal contents above
these concentrations (Table 6.6a and 6.6b). High level of HMs in the medicinal plants
145

could be due to the industrial and agricultural activities in the study area as mentioned
in Chapter 4 and 5.
146

CHAPTER 7
CONCLUSIONS AND RECOMMENDATIONS
Water quality of Attock and Haripur basins was highly impaired due to unwise and
wide spread human activities in the area. It is cleared from the results of this study that the
area near to the industrial zone was highly contaminated by heavy metals while
concentrations of heavy metals decreased as we moved away from the industrial area. The
water quality investigations of the Attock and Haripur basins showed that the water quality of
Attock Basin was comparatively less degraded as compared to Haripur Basin. Therefore,
spatial variations were observed in water quality parameters. Multivariate techniques
discriminated the most influencing factors and identified their possible sources. Main factors
that bring changes in chemical composition of water are either related to anthropogenic and/or
natural factors. Point sources such as industrial, municipal sewage and non-point sources
(atmospheric deposition, urban and agricultural runoff) were identified the most important
factors. Non carcinogen risk assessment for ten HMs were found

heavy metals in the surface soils of the Attock and Haripur basins. These included parent
rock materials, agricultural activities, and industrial activities. Significant degree of metal
pollution existed in areas near to Hattar industrial estate, which were significantly
contaminated with metals like Cu, Co, Ni, Pb, and Cr. High amount of these metals in surface
soils may give rise to various health hazards. The results showed that the soils of Haripur
Basin were more contaminated with HMs then that of the Attock Basin while the major
cations concentrations were found higher in Attock Basin as compared to the Haripur Basin.
It was caused mainly due to difference of agricultural and industrial activities in two basins
which was also supported by the GIS maps. These spatial maps could be useful for
preliminary monitoring and information related with spatial variability and distribution
patterns, anthropogenic versus natural origin of potentially harmful elements in surface soils
which may be critical to assess human impact. Furthermore, identification of the origin and
potential sources of heavy metals in soil could be essential in order to assess the
environmental risk caused by heavy metals in the study area. It was cleared from spatial
distribution of HMs in soil that soil near the industrial areas had high level of toxic elements
as compared to that of distant areas.
The investigation of the concentrations of HMs in vegetables and cereal of study were
found in the decreasing order of Mn>Zn>Cu>Cr>Pb>Ni>As>Cd. Dietary intake of food
result in long term low level body accumulation of heavy metals and detrimental impact
becomes apparent only after several years of exposure. The health risk index of all heavy
metals were found >1 with exception of Cr which was

the excess accumulation of heavy metals in their bodies. The situation may pose serious
threat to human health and highlight the need to device and implement appropriate means of
monitoring and regulating industrial effluents, providing the appropriate advice and support
for the safe and productive use of surface and groundwater for irrigation.
It was also concluded from the present study that the medicinal plants were subjected
to trace element contamination. Therefore, it should be the need of the time to educate the
people not to collect the medicinal plants from non-cultivated and other sources, which are
prone to heavy metal contamination. Assessment and constant evaluation of heavy metals in
medicinal plants are crucial for quality assurance and safer use of herbal medicine.
For the improvement of conditions in quality of water, soil and plants of study area
the following recommendations are proposed:
• Concerned authorities should install the effluent treatment plants in the industrial area.
• There should be appropriate regulations for the production through industries.
• National environmental quality standard should be implemented in disposal of
effluents generated as a result of anthropogenic activities in the study area.
• Fostering a positive change in attitude of residents and policy makers towards use of
local knowledge in waste management and planning, through a mapping of the
diversity of actors, and the involvement of neighborhood level resources, and
indigenous institutions in the planning process.
• Taxes and fines should be charged from industrialist and inhabitant on the basis of
polluter pay principle.
149

• Soils of study area have low organic matter and high pH. Irrigation with high pH
effluent water may result in high organic matter and pH. Therefore, pH of the
irrigation should be reduced before irrigation.
• Proper landfill should be constructed for the disposal of industrial and municipal
waste.
• There should be a regular assessment of metal contents in different vegetable, cereal
and medicinal plants of the study area to educate the people about the consequences
of consumption of contaminated plant species.
• Vegetables and cereal should be irrigated with the non-contaminated water.
• Leafy vegetables should be washed carefully before use so that there should not be
any trace of soil and atmospheric dust on them.
150

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179

Appendix Ia. Longitude, latitude and altitude of 140 sampling sites located in Attock and Haripur
basins
Sample# Temperature Location Latitude Longitude Source
Surface water samples
Sw1 24 o C Jari Kas 33 o 54 / 14 // N 72 o 46 / 35 // E Stream
Sw 2 25 o C Jabbi Kas 33 o 54 / 45 // N 72 o 46 / 06 // E Stream
Sw 33 17 o C Tarbella lake 34 o 02 / 39 // N 72 o 54 / 45 // E River
Sw 53 18 o C Doar river 34 o 01 / 04 // N 72 o 57 / 11 // E River
Sw 54 18 o C Soka Kas 33 o 59 / 20 // N 72 o 54 / 44 // E Stream
Sw 58 15 o C Miani Kas 33 o 58 / 43 // N 73 o 04 / 20 // E Stream
Sw 59 11 o C Miani Kas 33 o 57 / 51 // N 73 o 04 / 24 // E Stream
Sw 71 28 o C Dhotal Kas 33 o 54 / 56 // N 72 o 51 / 32 // E Stream
Sw 77 15 o C Dhotal Kas 33 o 55 / 37 // N 72 o 48 / 30 // E Stream
Sw 78 22 o C Indus river 33 o 53 / 96 // N 72 o 15 / 05 // E River
Sw 91 22 o C Bauti Kas 33 o 49 / 70 // N 72 o 44 / 83 // E Stream
Sw 95 23 o C Dhamrah Kas 33 o 48 / 67 // N 72 o 42 / 42 // E Stream
Sw 98 22 o C Banudra Kas 33 o 38 / 91 // N 72 o 41 / 20 // E Stream
Sw 100 22 o C Nandana Kas 33 o 38 / 05 // N 72 o 33 / 35 // E Stream
Sw 103 23 o C Nandana Kas 33 o 43 / 29 // N 72 o 20 / 99 // E Stream
Sw 108 21 o C Haro river 33 o 44 / 81 // N 72 o 15 / 61 // E River
Sw 117 21 o C Haro river 33 o 45 / 63 // N 72 o 26 / 23 // E River
Sw 119 19 o C Ganeeri Kas 33 o 43 / 88 // N 72 o 32 / 62 // E Stream
Sw 126 20 o C Kala Kas 33 o 43 / 75 // N 72 o 46 / 01 // E Stream
Sw 130 23 o C Haro river 33 o 49 / 44 // N 72 o 38 / 42 // E River
Groundwater samples
Gw1 22 o C JariKas 33 o 54 / 14 // N 72 o 46 / 35 // E Dugwell
Gw2 22 o C Jahar 33 o 54 / 44 // N 72 o 46 / 20 // E HandPump
Gw3 23 o C Motia 33 o 54 / 21 // N 72 o 47 / 16 // E Borewell
Gw4 23 o C Dingi 33 o 54 / 13 // N 72 o 48 / 10 // E Borewell
Gw5 23 o C Motia 33 o 54 / 06 // N 72 o 47 / 57 // E Dugwell
Gw6 23 o C Dingi 33 o 54 / 35 // N 72 o 47 / 52 // E Borewell
180

Gw7 22 o C Dingi 33 o 54 / 38 // N 72 o 48 / 08 // E Tubewell
Gw8 22 o C Dingi 33 o 54 / 46 // N 72 o 48 / 30 // E Tubewell
Gw9 23 o C Dehdar 33 o 55 / 57 // N 72 o 48 / 20 // E Dugwell
Gw10 22 o C Dehdar 33 o 55 / 56 // N 72 o 48 / 37 // E Borewell
Gw11 24 o C Chamba Pind 33 o 56 / 59 // N 72 o 46 / 51 // E Borewell
Gw12 23 o C Chamba Hicthe 33 o 57 / 42 // N 72 o 46 / 16 // E Tubewell
Gw13 23 o C Mohri Pir Bakhsh 33 o 56 / 23 // N 72 o 48 / 03 // E Dugwell
Gw14 23 o C Sarai Gadahia 33 o 56 / 35 // N 72 o 49 / 01 // E Tubewell
Gw15 23 o C Kot Najibullah 33 o 56 / 06 // N 72 o 56 / 56 // E Borewell
Gw16 23 o C Jhang Kora 33 o 56 / 51 // N 72 o 48 / 54 // E Borewell
Gw17 23 o C Mori Malia 33 o 57 / 02 // N 72 o 48 / 14 // E Borewell
Gw18 21 o C Faridabad 33 o 57 / 16 // N 72 o 48 / 38 // E Dugwell
Gw19 23 o C Ladha 33 o 57 / 32 // N 72 o 48 / 03 // E Dugwell
Gw20 23 o C Qayyumabad 33 o 57 / 09 // N 72 o 48 / 59 // E Dugwell
Gw21 26 o C Pind Khan Khel 33 o 57 / 41 // N 72 o 49 / 11 // E Dugwell
Gw22 23 o C Bakka 33 o 58 / 21 // N 72 o 48 / 50 // E Dugwell
Gw23 24 o C Pandori 33 o 58 / 30 // N 72 o 48 / 16 // E Dugwell
Gw24 23 o C Panian 33 o 58 / 32 // N 72 o 51 / 00 // E Dugwell
Gw25 23 o C Bhera 33 o 59 / 52 // N 72 o 50 / 52 // E Dugwell
Gw28 23 o C Pindori 34 o 00 / 27 // N 72 o 50 / 46 // E Dugwell
Gw29 22 o C Sirikot 34 o 02 / 26 // N 72 o 46 / 16 // E Dugwell
Gw30 24 o C Siri 34 o 01 / 25 // N 72 o 49 / 48 // E Tubewell
Gw31 22 o C Padhana 34 o 02 / 09 // N 72 o 55 / 00 // E Tubewell
Gw32 22 o C
Afghan refugee
camp 34 o 02 / 23 // N 72 o 54 / 42 // E HandPump
Gw34 21 o C Khalabut township 34 o 01 / 23 // N 72 o 55 / 01 // E Tubewell
Gw35 22 o C Skundarpur 34 o 00 / 29 // N 72 o 56 / 19 // E Tubewell
Gw36 22 o C Dheri 34 o 00 / 50 // N 72 o 56 / 54 // E Tubewell
Gw37 23 o C Parala 34 o 01 / 07 // N 72 o 57 / 36 // E Dugwell
Gw38 22 o C Kamara 33 o 56 / 00 // N 72 o 52 / 07 // E Dugwell
Gw39 22 o C Gangia 33 o 55 / 53 // N 72 o 52 / 41 // E Dugwell
181

Gw40 23 o C Siria 33 o 56 / 09 // N 72 o 53 / 11 // E Dugwell
Gw41 22 o C Kangara colony 33 o 57 / 28 // N 72 o 52 / 46 // E Tubewell
Gw42 23 o C Bhand 33 o 58 / 10 // N 72 o 53 / 13 // E Dugwell
Gw44 18 o C Derwaza 34 o 05 / 26 // N 72 o 56 / 51 // E Spring
Gw45 22 o C
34 o 04 / 02 // N 72 o 56 / 52 // E Tubewell
Gw46 21 o C Aleoli 34 o 04 / 40 // N 72 o 58 / 23 // E Tubewell
Gw47 18 o C Banda bakhtawar 34 o 05 / 44 // N 72 o 59 / 45 / E Spring
Gw49 18 o C 34 o 05 / 00 // N 73 o 02 / 27 // E Dugwell
Gw50 26 o C Sirinemat khan 34 o 05 / 11 // N 73 o 01 / 58 // E Tubewell
Gw51 20 o C Pind hashim khan 34 o 03 / 14 // N 73 o 00 / 09 // E Tubewell
Gw52 22 o C Sarai sallah 33 o 59 / 09 // N 72 o 59 / 16 // E Tubewell
Gw55 22 o C Bakhra mori 33 o 59 / 52 // N 73 o 04 / 25 // E Tubewell
Gw56 16 o C Basti sheer khan 33 o 59 / 12 // N 73 o 04 / 27 // E Dugwell
Gw57 11 o C 33 o 59 / 02 // N 73 o 03 / 25 // E Tubewell
Gw58 20 o C Baldare 34 o 00 / 29 // N 73 o 05 / 05 // E Tubewell
Gw60 22 o C 33 o 56 / 38 // N 73 o 02 / 34 // E Borewell
Gw61 21 o C Rehana village 33 o 56 / 24 // N 73 o 01 / 41 // E Tubewell
Gw62 20 o C Mona village 33 o 59 / 01 // N 72 o 57 / 33 // E Tubewell
Gw63 22 o C Khal bala 32 o 56 / 19 // N 72 o 58 / 08 // E Tubewell
Gw64 14 o C Mirpur 33 o 56 / 51 // N 72 o 56 / 17 // E Tubewell
Gw65 22 o C Chichian 33 o 56 / 35 // N 72 o 54 / 26 // E Dugwell
Gw66 22 o C Pind munim khan 33 o 52 / 30 // N 72 o 54 / 51 // E Dugwell
Gw67 14 o C Surag gali 33 o 50 / 34 // N 72 o 54 / 51 // E Tubewell
Gw68 23 o C Hattar village 33 o 51 / 40 // N 72 o 51 / 21 // E Tubewell
Gw69 12 o C 33 o 52 / 54 // N 72 o 50 / 50 // E Tubewell
Gw70 16 o C Hattar state phase 1 33 o 53 / 50 // N 72 o 52 / 11 // E Tubewell
Gw72 17 o C Haripur 33 o 59 / 57 // N 72 o 56 / 10 // E Tubewell
Gw73 20 o C Jial road 33 o 59 / 12 // N 72 o 55 / 41 // E Tubewell
Gw74 16 o C Pathan colony 33 o 59 / 07 // N 72 o 54 / 52 // E Tubewell
Gw75 18 o C Farooq abad 33 o 58 / 16 // N 72 o 55 / 10 // E Tubewell
Gw76 21 o C Telephone colony 33 o 58 / 18 // N 72 o 55 / 30 // E Tubewell
182

Gw79 20 o C Mansor camp 33 o 54 / 23 // N 72 o 18 / 55 // E Borewell
Gw80 18 o C Khawakhel 33 o 55 / 17 // N 72 o 19 / 41 // E Tubewell
Gw81 20 o C Mallah 33 o 53 / 63 // N 72 o 21 / 62 // E Borewell
Gw82 20 o C Gondal 33 o 53 / 34 // N 72 o 20 / 75 // E HandPump
Gw83 21 o C Sirka 33 o 55 / 37 // N 72 o 23 / 55 // E HandPump
Gw84 21 o C Pandia 33 o 56 / 73 // N 72 o 24 / 73 // E Borewell
Gw85 22 o C Daman 33 o 56 / 58 // N 72 o 25 / 20 // E Dugwell
Gw86 22 o C Lakori 33 o 57 / 42 // N 72 o 28 / 18 // E HandPump
Gw87 20 o C Khurkhasti 33 o 56 / 77 // N 72 o 31 / 63 // E HandPump
Gw88 23 o C Ghazi 34 o 00 / 32 // N 72 o 38 / 27 // E Borewell
Gw89 25 o C 33 o 53 / 79 // N 72 o 33 / 14 // E Dugwell
Gw90 22 o C Wah cantt 33 o 49 / 38 // N 72 o 44 / 28 // E Borewell
Gw92 23 o C Shahia 33 o 52 / 31 // N 72 o 45 / 56 // E Borewell
Gw93 23 o C Pindmehri 33 o 52 / 52 // N 72 o 47 / 45 // E Borewell
Gw94 21 o C Hasan abdal 33 o 49 / 25 // N 72 o 41 / 43 // E Tubewell
Gw99 24 o C Bahtar 33 o 40 / 74 // N 72 o 38 / 59 // E Borewell
Gw96 25 o C Bahtar 33 o 44 / 40 // N 72 o 42 / 11 // E Borewell
Gw97 25 o C Jhang 33 o 40 / 23 // N 72 o 41 / 58 // E Borewell
Gw101 26 o C Jab Kasran 33 o 39 / 26 // N 72 o 31 / 51 // E HandPump
Gw102 24 o C Akhori 33 o 41 / 49 // N 72 o 26 / 94 // E Borewell
Gw104 22 o C Mallah 33 o 43 / 73 // N 72 o 19 / 54 // E Dugwell
Gw105 23 o C 33 o 43 / 38 // N 72 o 21 / 19 // E Dugwell
Gw106 23 o C Attock city bazaar 33 o 46 / 34 // N 72 o 21 / 52 // E Tubewell
Gw107 25 o C 33 o 43 / 70 // N 72 o 14 / 66 // E HandPump
Gw109 21 o C Dekhnar 33 o 50 / 39 // N 72 o 14 / 54 // E Dugwell
Gw110 21 o C Haji shah 33 o 53 / 37 // N 72 o 19 / 44 // E Borewell
Gw111 21 o C Shamsaabad 33 o 54 / 22 // N 72 o 25 / 30 // E Borewell
Gw112 21 o C Hazro city 33 o 54 / 64 // N 72 o 29 / 18 // E HandPump
Gw113 21 o C Qutab bandi 33 o 56 / 33 // N 72 o 37 / 49 // E Spring
Gw114 23 o C Kamra colony 33 o 52 / 00 // N 72 o 25 / 86 // E Tubewell
Gw115 21 o C Faqeer Abad 33 o 49 / 63 // N 72 o 30 / 21 // E Borewell
183

Gw116 18 o C Bora Sajawal 33 o 46 / 29 // N 72 o 25 / 83 // E Tubwell
Gw118 25 o C Durdad Khan 33 o 44 / 60 // N 72 o 31 / 16 // E Borewell
Gw120 20 o C Brahma 33 o 44 / 79 // N 72 o 42 / 40 // E Borewell
Gw121 21 o C Margalla Chowk 33 o 42 / 28 // N 72 o 49 / 47 // E Tubewell
Gw122 22 o C Taxilla 33 o 44 / 81 // N 72 o 49 / 07 // E Tubewell
Gw123 21 o C Usman Khattar 33 o 48 / 37 // N 72 o 49 / 25 // E Tubewell
Gw124 23 o C Taxilla 33 o 44 / 69 // N 72 o 46 / 23 // E Tubewell
Gw125 22 o C Thatta Khalil 33 o 41 / 70 // N 72 o 45 / 72 // E Borewell
Gw127 22 o C 33 o 43 / 85 // N 72 o 46 / 06 // E Dugwell
Gw128 19 o C Wah cantt 33 o 45 / 86 // N 72 o 46 / 05 // E Tubewell
Gw129 19 o C Nawab abad 33 o 44 / 42 // N 72 o 46 / 71 // E BoreWell
Gw131 21 o C Burhan 33 o 49 / 28 // N 72 o 37 / 51 // E Borewell
184

Appendix Ib. Longitude, latitude and altitude of 110 sites for soil samplings located in Attock
and Haripur basins
Sample Locality name Latitude Longitude
S1 Jari Kas 33 o 54 / 14 // N 72 o 46 / 30 // E
S2 Jahar 33 o 54 / 46 // N 72 o 46 / 19 // E
S3 Jahar 33 o 54 / 45 // N 72 o 46 / 19 // E
S4 Jabbi 33 o 54 / 46 // N 72 o 46 / 06 // E
S5 Jabbi 33 o 54 / 47 // N 72 o 46 / 06 // E
S6 Dingi 33 o 54 / 50 // N 72 o 48 / 10 // E
S7 Motia 33 o 54 / 07 // N 72 o 47 / 59 // E
S8 Dingi 33 o 54 / 88 // N 72 o 48 / 08 // E
S9 Dingi 33 o 54 / 46 // N 72 o 48 / 30 // E
S10 Dingi 33 o 54 / 44 // N 72 o 48 / 28 // E
S11 Dehdar 33 o 55 / 57 // N 72 o 48 / 34 // E
S12 Dehdar 33 o 55 / 57 // N 72 o 48 / 27 // E
S13 Dehdar 33 o 55 / 57 // N 72 o 48 / 20 // E
S14 Pehdea 33 o 55 / 59 // N 72 o 48 / 31 // E
S15 Chamba pind 33 o 56 / 59 // N 72 o 46 / 52 // E
S16 Chamba pind 33 o 56 / 54 // N 72 o 46 / 53 // E
S17 Chamra hicthe 33 o 57 / 44 // N 72 o 46 / 17 // E
S18 Mohri pir bakhsh 33 o 56 / 21 // N 72 o 48 / 02 // E
S19 Sarai gadahia 33 o 56 / 25 // N 72 o 48 / 58 // E
S20 Kot najibullah 33 o 55 / 54 // N 72 o 51 / 07 // E
S21 Jhang kora 33 o 56 / 49 // N 72 o 48 / 55 // E
S22 Mori malia 33 o 57 / 02 // N 72 o 48 / 13 // E
S23 Faridabad 33 o 57 / 16 // N 72 o 48 / 38 // E
S24 Ladha 33 o 57 / 84 // N 72 o 47 / 57 // E
S25 Ladha 33 o 57 / 84 // N 72 o 47 / 57 // E
S26 Qayyumabad 33 o 57 / 09 // N 72 o 49 / 02 // E
S27 Bakka 33 o 57 / 19 // N 72 o 49 / 01 // E
S28 Pandori 33 o 58 / 29 // N 74 o 81 / 69 // E
185

S29 Penian 33 o 58 / 35 // N 72 o 51 / 19 // E
S30 Bhera 33 o 59 / 52 // N 72 o 50 / 52 // E
S31 Pindori // N E
S32 Siri kot 34 o 02 / 27 // N 72 o 46 / 17 // E
S33 Seri 34 o 01 / 25 // N 72 o 49 / 48 // E
S34 Afghan refugee camp 34 o 02 / 21 // N 72 o 54 / 41 // E
S35 Padhana 34 o 02 / 37 // N 72 o 54 / 46 // E
S36 Skindarpur 34 o 00 / 29 // N 72 o 56 / 19 // E
S37 Dheri 34 o 00 / 50 // N 72 o 56 / 54 // E
S38 Parala 34 o 01 / 02 // N 72 o 57 / 28 // E
S39 Kamara 33 o 56 / 01 // N 72 o 52 / 07 // E
S40 Gangia 33 o 55 / 50 // N 72 o 52 / 39 // E
S41 Siria 33 o 56 / 09 // N 72 o 53 / 09 // E
S42 Kangara colony 33 o 57 / 20 // N 72 o 52 / 40 // E
S43 Abdullah pur 33 o 58 / 42 // N 72 o 53 / 10 // E
S44 Darvaza 34 o 05 / 26 // N 72 o 56 / 51 // E
S45 34 o 04 / 02 // N 72 o 56 / 52 // E
S46 Aleoli 34 o 04 / 40 // N 72 o 58 / 23 // E
S47 Teer 34 o 05 / 44 // N 72 o 59 / 45 / E
S48 Sarai 34 o 05 / 00 // N 73 o 02 / 27 // E
S49 Sarai Namat khan 34 o 05 / 11 // N 73 o 01 / 58 // E
S50 Pind Hashim khan 34 o 03 / 14 // N 73 o 00 / 09 // E
S51 Pind hashim khan 34 o 03 / 26 // N 73 o 00 / 51 // E
S52 Lartopa 34 o 02 / 41 // N 72 o 59 / 20 // E
S53 34 o 01 / 01 // N 72 o 57 / 27 // E
S54 Sarai Sallah 33 o 59 / 08 // N 72 o 58 / 45 // E
S55 Sarai Sallah 33 o 59 / 16 // N 72 o 57 / 42 // E
S56 Haripur 33 o 59 / 22 // N 72 o 54 / 49 // E
S57 Haripur 33 o 59 / 21 // N 72 o 53 / 49 // E
S58 Baldher 34 o 00 / 29 // N 73 o 05 / 05 // E
S59 Bakhara More 33 o 69 / 22 // N 72 o 54 / 29 // E
186

S60 Bakhara 33 o 00 / 29 // N 73 o 03 / 34 // E
S61 Bhajawa village 33 o 01 / 29 // N 73 o 02 / 34 // E
S62 Rehana village 33 o 58 / 07 // N 73 o 00 / 16 // E
S63 33 o 58 / 21 // N 72 o 57 / 31 // E
S64 Mirpur 33 o 57 / 15 // N 72 o 55 / 14 // E
S65 Along khanpur road 33 o 56 / 22 // N 72 o 54 / 34 // E
S66 Pind kamal khan 33 o 54 / 21 // N 72 o 51 / 14 // E
S67 Pind munir khan 33 o 52 / 30 // N 72 o 54 / 51 // E
S68 Suraj gali 33 o 50 / 34 // N 72 o 54 / 51 // E
S69 Hattar village 33 o 51 / 31 // N 72 o 51 / 14 // E
S70 33 o 52 / 30 // N 72 o 50 / 57 // E
S71 33 o 54 / 42 // N 72 o 49 / 18 // E
S72 Dhinda 34 o 00 / 41 // N 72 o 56 / 01 // E
S73 Jial road 33 o 58 / 44 // N 72 o 55 / 16 // E
S74 Indus river 33 o 53 / 92 // N 72 o 15 / 54 // E
S75 Mansor camp 33 o 54 / 23 // N 72 o 18 / 55 // E
S76 Khawakhel 33 o 55 / 17 // N 72 o 19 / 41 // E
S77 Mallah 33 o 53 / 99 // N 72 o 21 / 29 // E
S78 Gondal 33 o 53 / 34 // N 72 o 20 / 75 // E
S79 Sirka 33 o 55 / 37 // N 72 o 23 / 55 // E
S80 Pandia 33 o 56 / 58 // N 72 o 24 / 20 // E
S81 Daman 33 o 57 / 37 // N 72 o 26 / 99 // E
S82 Lakori 33 o 57 / 46 // N 72 o 28 / 37 // E
S83 Khurkhasti 33 o 56 / 91 // N 72 o 32 / 21 // E
S84 Ghazi 34 o 00 / 23 // N 72 o 38 / 16 // E
S85 Wah cantt 33 o 49 / 39 // N 72 o 44 / 29 // E
S86 Shahia 33 o 52 / 31 // N 72 o 45 / 56 // E
S87 Pindmehri 33 o 52 / 52 // N 72 o 47 / 45 // E
S88 Wah garden 33 o 48 / 07 // N 72 o 42 / 12 // E
S89 Bahtar 33 o 44 / 40 // N 72 o 42 / 11 // E
S90 Jhang 33 o 39 / 82 // N 72 o 41 / 33 // E
187

S91 Bahtar 33 o 40 / 70 // N 72 o 38 / 35 // E
S92 Jab Kasran 33 o 39 / 39 // N 72 o 31 / 29 // E
S93 Akhori 33 o 41 / 66 // N 72 o 26 / 28 // E
S94 Mallah 33 o 43 / 73 // N 72 o 19 / 54 // E
S95 Attock city bazaar 33 o 46 / 34 // N 72 o 21 / 52 // E
S96 33 o 43 / 74 // N 72 o 14 / 64 // E
S97 Dekhnar 33 o 49 / 86 // N 72 o 16 / 35 // E
S98 Haji shah 33 o 53 / 00 // N 72 o 19 / 82 // E
S99 Shamsaabad 33 o 54 / 22 // N 72 o 25 / 30 // E
S100 Hazro city 33 o 54 / 76 // N 72 o 29 / 93 // E
S101 Qutab bandi 33 o 56 / 33 // N 72 o 37 / 49 // E
S102 Hatian 33 o 51 / 10 // N 72 o 28 / 56 // E
S103 Faqeer abad 33 o 49 / 53 // N 72 o 29 / 78 // E
S104 Bora sajawal 33 o 46 / 29 // N 72 o 25 / 83 // E
S105 Durdad khan 33 o 44 / 44 // N 72 o 31 / 84 // E
S105 Brahma 33 o 44 / 79 // N 72 o 42 / 40 // E
S105 Margalla chowk 33 o 44 / 80 // N 72 o 49 / 04 // E
S106 Taxilla 33 o 44 / 50 // N 72 o 50 / 76 // E
S107 Usman khattar 33 o 48 / 38 // N 72 o 49 / 21 // E
S108 Thatta khalil 33 o 41 / 75 // N 72 o 45 / 73 // E
S109 Jalala abad 33 o 43 / 85 // N 72 o 46 / 06 // E
S110 Burhan 33 o 49 / 28 // N 72 o 37 / 51 // E
188

Appendix. II. Concentration of major cations in groundwater samples of Haripur and
Attock basins
Sample Na K Ca Mg Fe Mn
Haripur Basin
Gw1 69.0 2.2 113.8 32.9 950 103.0
Gw2 204.4 2.7 64.5 47.6 199 103.0
Gw3 49.3 1.7 46.3 32.6 128 58.0
Gw4 37.1 1.7 113.9 22.0 114 70.0
Gw5 26.1 1.7 107.5 13.3 686 89.0
Gw6 29.5 1.8 111.2 25.3 606 87.0
Gw7 19.9 1.4 77.5 11.4 90 70.0
Gw8 25.3 1.5 38.4 15.1 33 61.0
Gw9 35.4 4.3 109.7 19.2 225 99.0
Gw10 48.6 2.2 105.6 28.4 68 53.0
Gw11 31.5 2.2 89.3 37.9 98 32.0
Gw12 12.2 1.2 82.2 34.7 72 26.0
Gw13 116.2 2.9 91.3 93.8 86 12.0
Gw14 34.7 1.3 65.1 13.0 96 18.0
Gw15 118.6 3.9 63.1 37.0 96 20.0
Gw16 59.0 1.8 44.5 26.4 72 99.0
Gw17 162.4 4.4 111.9 63.9 88 20.0
Gw18 405.9 5.0 110.9 90.4 144 39.0
Gw19 113.5 5.0 99.8 57.1 116 42.0
Gw20 61.9 3.6 73.0 36.6 86 49.0
Gw21 48.4 3.8 69.5 38.2 177 81.0
Gw22 55.6 3.4 44.1 32.4 215 18.0
Gw23 22.3 5.1 74.8 45.0 59 15.0
Gw24 152.5 7.8 72.7 109.0 34 6.0
Gw25 83.2 2.9 51.0 34.2 78 2.0
Gw28 26.7 2.7 60.0 32.8 28 27.0
Gw29 24.0 0.5 91.9 11.6 33 7.0
Gw30 8.4 4.6 62.6 14.4 84 12.0
Gw31 8.4 1.5 80.0 12.3 158 34.0
Gw32 9.6 1.5 90.5 13.8 42 7.0
Gw34 10.6 1.7 62.4 16.0 103 14.0
Gw35 8.1 1.4 67.6 13.1 79 10.0
Gw36 61.1 1.6 62.0 12.6 60 13.0
Gw37 18.5 1.3 65.7 9.5 115 5.0
Gw38 8.5 4.9 83.2 27.5 76 22.0
189

Gw39 18.0 2.0 99.3 15.5 135 4.0
Gw40 60.9 3.4 113.4 34.4 99 9.0
Gw41 12.2 1.8 66.9 14.3 165 33.0
Gw42 84.4 28.4 141.3 14.0 150 11.0
Gw43 30.9 1.7 49.3 16.6 109 18.0
Gw44 5.1 0.7 43.1 28.7 84 41.0
Gw45 13.5 1.9 59.8 15.2 100 18.0
Gw46 10.3 6.5 76.1 8.3 117 6.0
Gw47 12.0 10.0 84.9 8.9 80 4.0
Gw49 13.7 1.3 69.0 13.2 70 16.0
Gw50 10.0 1.9 65.1 13.9 86 7.0
Gw51 18.6 0.9 54.0 10.8 164 45.0
Gw52 9.4 1.3 76.0 13.5 81 6.0
Gw55 11.0 1.0 87.6 13.0 133 18.0
Gw56 13.1 1.2 97.1 17.6 152 19.0
Gw57 23.1 1.2 65.2 16.0 98 4.0
Gw58 11.4 1.0 89.9 13.5 111 13.0
Gw60 24.2 0.7 156.6 24.5 129 9.0
Gw61 15.6 0.8 83.8 8.2 127 25.0
Gw62 10.4 1.6 74.8 15.7 141 2.0
Gw63 16.6 1.3 77.7 12.8 115 59.0
Gw64 22.7 2.4 81.8 15.1 98 14.0
Gw65 14.5 2.4 77.8 10.0 150 13.0
Gw66 18.8 1.5 93.1 14.0 182 3.0
Gw67 14.0 1.8 83.9 22.0 141 6.0
Gw68 11.5 1.2 98.7 18.1 138 29.0
Gw69 4.4 1.8 33.9 13.3 207 17.0
Gw70 19.2 1.3 35.2 14.6 138 23.0
Gw72 10.6 1.7 91.6 20.0 19 13.0
Gw73 10.3 1.6 84.0 15.1 56 11.0
Gw74 19.8 1.6 84.0 18.2 50 3.0
Gw75 27.4 1.7 87.3 29.1 13 2.0
Gw76 11.9 1.4 63.0 13.3 48 16.0
Attock Basin
Gw79 56.6 27.2 70.6 33.8 14 51.0
Gw80 26.1 6.7 45.8 23.1 207 17.0
Gw81 122.5 11.9 97.1 74.4 5 9.0
Gw82 311.0 10.1 122.6 80.5 52 203.0
Gw83 81.6 10.0 51.6 71.4 36 11.0
Gw84 223.5 28.0 100.8 88.5 60 9.0
190

Gw85 24.6 3.1 48.9 32.5 15 5.0
Gw86 57.4 2.5 60.7 31.6 172 6.0
Gw87 54.0 5.9 124.2 88.3 58 10.0
Gw88 77.6 3.4 53.6 18.3 20 27.0
Gw89 18.9 1.9 83.3 8.7 107 11.0
Gw94 22.0 1.4 56.0 13.6 53 25.0
Gw97 14.7 0.6 87.5 24.2 314 1.0
Gw101 26.7 1.1 38.3 17.7 208 53.0
Gw102 11.5 1.4 79.6 9.2 37 4.0
Gw104 65.3 1.4 40.1 10.7 493 13.0
Gw105 70.8 1.0 150.4 18.6 803 4.0
Gw106 30.6 2.5 47.4 23.7 22 27.0
Gw107 181.5 1.9 76.6 22.7 418 19.0
Gw109 15.5 1.6 107.9 9.7 17 1.0
Gw110 65.5 1.8 149.5 17.4 395 24.0
Gw111 107.2 6.5 38.3 21.3 164 22.0
Gw112 95.5 5.1 79.6 53.8 101 15.0
Gw113 29.8 0.2 55.0 21.1 4 26.0
Gw114 14.0 2.1 41.1 11.3 6 4.0
Gw115 34.5 4.3 150.4 27.7 22 14.0
Gw116 33.1 2.0 47.4 17.1 54 6.0
Gw118 37.2 2.8 38.5 19.0 16 6.0
Gw121 13.2 1.3 123.8 23.8 91 20.0
Gw122 67.3 1.8 153.0 28.8 29 7.0
Gw123 30.0 0.8 65.9 11.6 45 3.0
Gw124 32.5 1.3 144.9 25.7 10 10.0
Gw125 6.8 0.8 109.5 26.5 273 42.0
Gw128 5.3 1.6 145.3 29.7 45 12.0
191

Appendix.II. Concentration of trace elements in groundwater samples of Haripur and
Attock basins
Sample As Hg Cu Pb Zn Ni Cr Co Cd
Haripur Basin
Gw1 1.4 0.0 55.2 123.1 107.0 16.6 41.7 3.5 8.6
Gw2 3.4 0.7 166.9 51.3 486.0 9.1 5.6 2.4 9.1
Gw3 1.7 0.7 50.6 59.7 127.0 1.4 33.7 2.6 1.4
Gw4 0.4 0.3 17.2 72.0 83.0 8.9 6.0 1.5 2.4
Gw5 3.7 0.5 21.1 76.9 92.0 5.4 16.9 4.0 2.9
Gw6 1.9 0.1 22.8 85.2 8.0 9.9 137.6 1.4 2.8
Gw7 1.6 0.3 38.6 147.7 76.0 4.4 26.7 2.1 4.4
Gw8 1.0 0.3 5.9 23.3 53.1 BD 20.7 0.5 2.8
Gw9 1.1 0.2 7.3 28.8 72.6 0.7 5.5 0.1 1.4
Gw10 0.2 0.1 9.2 22.8 127.0 BD 34.7 BD 3.5
Gw11 BD 0.2 42.8 83.0 277.0 9.0 16.0 0.5 7.0
Gw12 BD 0.7 0.9 14.6 102.1 1.3 BD BD 1.3
Gw13 BD 0.1 1.2 16.8 55.0 BD 9.4 BD 0.8
Gw14 1.2 0.2 30.8 33.4 73.0 BD 2.5 BD 1.6
Gw15 BD 0.3 61.7 63.9 278.0 3.5 56.8 BD 1.5
Gw16 0.2 0.2 2.2 23.6 611.0 BD BD 2.6 1.8
Gw17 0.2 0.1 33.8 53.7 101.0 47.4 90.3 BD 1.9
Gw18 BD 0.2 1.6 4.4 41.7 21.4 28.1 2.0 BD
Gw19 0.4 0.0 1.3 20.7 87.0 1.1 157.2 0.3 1.4
Gw20 BD 0.3 18.2 41.1 50.0 BD 25.3 1.2 4.5
Gw21 0.1 0.3 90.0 110.9 140.0 4.7 26.3 25.1 62.5
Gw22 BD 0.1 12.5 41.6 87.0 BD 171.3 1.3 2.0
Gw23 BD 0.2 12.4 48.6 73.0 7.0 42.2 0.8 1.9
Gw24 BD 0.5 0.6 BD 102.0 BD 138.9 BD 5.8
Gw25 BD 0.1 7.6 42.0 509.0 BD 194.1 BD 1.9
Gw28 0.9 0.1 65.9 25.4 81.0 33.5 55.4 0.8 2.8
Gw29 0.1 BD 21.2 30.0 54.0 BD BD 0.5 1.0
Gw30 BD 0.2 10.8 27.2 273.8 BD 1.0 1.3 0.5
Gw31 BD 0.4 50.3 71.0 73.0 9.4 BD 0.4 15.1
Gw32 BD 0.6 8.6 18.9 90.0 1.8 BD BD 1.3
Gw34 BD 0.2 13.9 41.4 82.0 3.2 BD BD 7.8
Gw35 BD 0.4 16.9 33.1 284.0 2.5 BD BD 10.8
Gw36 1.4 0.1 7.0 15.2 216.0 1.4 BD BD 0.7
Gw37 BD 0.2 1.4 36.4 75.1 2.8 3.1 0.1 0.9
Gw38 BD 0.5 BD 8.9 27.4 5.9 67.8 BD 0.6
192

Gw39 0.1 0.1 BD 18.1 65.8 0.6 4.3 BD 0.3
Gw40 BD 0.1 10.5 60.6 67.0 2.7 14.1 BD 2.5
Gw41 0.1 0.2 112.9 95.4 218.0 13.0 9.1 18.7 16.4
Gw42 BD 0.2 21.4 73.5 268.0 2.9 11.1 BD 2.5
Gw43 BD 0.3 6.5 30.5 1354.0 1.5 7.6 BD 1.9
Gw44 0.3 0.0 9.3 44.1 119.0 3.0 3.0 BD 1.4
Gw45 BD BD 5.1 14.2 103.8 0.5 0.6 BD 0.5
Gw46 BD 0.1 8.9 22.0 101.0 4.3 2.9 BD 10.5
Gw47 0.1 BD BD 8.8 49.0 BD 1.8 BD 0.8
Gw49 BD 0.1 6.2 19.4 163.0 1.8 1.2 BD 0.7
Gw50 BD 0.5 50.4 20.7 108.0 0.2 1.5 BD 0.7
Gw51 0.7 0.3 23.5 23.5 71.0 1.4 1.0 15.3 0.6
Gw52 BD 0.0 59.7 75.1 83.6 9.6 2.1 BD 17.3
Gw55 0.4 0.6 9.6 20.9 56.4 0.3 1.7 BD 1.2
Gw56 BD BD BD 15.9 12.6 1.9 2.2 BD 1.3
Gw57 BD 0.1 6.9 21.7 417.0 BD 0.7 BD 0.9
Gw58 0.3 0.0 3.2 10.1 131.0 0.1 1.3 BD 0.5
Gw60 BD BD BD 10.9 805.0 2.6 0.7 BD 0.5
Gw61 BD BD 54.0 85.4 163.3 10.1 1.4 BD 14.1
Gw62 BD BD 5.9 11.9 38.6 0.4 2.2 5.7 1.1
Gw63 0.3 BD 8.9 20.3 324.0 BD 1.2 BD 1.4
Gw64 0.3 BD 4.4 10.0 109.0 BD 2.8 BD 0.5
Gw65 1.6 BD 7.4 27.1 67.0 1.0 2.6 BD 0.9
Gw66 1.0 BD 2.5 15.5 219.0 3.5 2.0 BD 1.1
Gw67 0.1 BD 0.7 24.5 1299.0 0.1 4.3 BD 1.0
Gw68 0.2 BD 0.1 6.1 23.4 BD 1.1 BD 1.4
Gw69 BD BD BD 18.1 36.1 2.8 1.3 BD 2.0
Gw70 BD BD 18.0 10.9 436.0 BD 7.8 BD 0.7
Gw72 0.1 BD 26.5 20.0 382.0 3.0 2.7 BD 1.1
Gw73 0.0 BD 24.9 15.3 111.2 0.9 2.0 2.9 0.5
Gw74 BD 0.4 22.3 14.9 135.0 0.8 6.8 BD 0.8
Gw75 BD BD 41.1 28.5 146.0 2.8 11.2 BD 0.8
Gw76 BD BD 11.6 27.2 37.8 0.8 2.7 BD 0.7
Attock Basin
Gw79 10.720 BD 7.5 14.9 585.0 0.6 1.2 BD 13.8
Gw80 5.490 BD 35.0 10.7 113.0 0.6 2.9 BD 0.7
Gw81 8.068 BD 1.2 3.6 348.0 5.8 2.1 67.5 4.8
Gw82 BD BD BD BD 277.0 1.8 0.3 15.4 0.8
Gw83 3.937 BD 0.6 4.8 340.0 BD 1.3 6.0 0.4
Gw84 4.414 BD 73.6 36.9 224.0 3.0 2.4 7.1 2.8
193

Gw85 7.800 BD 12.7 16.9 190.0 1.0 2.6 2.5 40.9
Gw86 BD 0.976 34.0 112.4 1399.0 35.0 1.3 0.3 1.5
Gw87 0.235 1.452 101.3 24.8 236.0 7.6 1.4 3.2 0.1
Gw88 11.260 BD 7.4 6.4 180.0 BD 4.4 0.7 0.3
Gw89 6.367 BD 14.6 12.7 151.0 0.9 2.8 0.4 0.7
Gw94 BD 0.208 3.2 7.8 347.0 BD 4.1 BD 0.3
Gw97 BD 0.757 29.1 11.6 165.0 0.2 3.2 BD 0.1
Gw101 BD 0.182 129.2 49.2 258.0 5.5 2.0 23.9 14.8
Gw102 BD 0.255 43.7 15.5 386.0 10.0 1.5 1.1 2.2
Gw104 BD 0.356 0.2 5.6 213.0 3.3 0.8 1.9 0.2
Gw105 BD 0.141 145.5 31.2 902.0 32.0 0.7 BD 0.2
Gw106 BD 0.398 20.9 36.4 1203.0 3.7 0.5 BD 1.6
Gw107 BD 0.142 23.6 13.2 167.0 0.7 0.5 BD 0.1
Gw109 BD BD BD 4.2 190.0 1.4 0.4 BD 0.6
Gw110 0.030 0.019 BD 3.6 266.0 4.5 0.3 BD 0.2
Gw111 2.098 BD 4.4 25.9 179.0 18.1 0.8 22.0 12.3
Gw112 1.638 0.055 37.7 16.4 572.0 2.0 0.5 0.6 0.2
Gw113 BD 0.054 2.9 BD 170.0 0.1 0.3 BD 1.2
Gw114 0.524 0.055 5.0 BD 153.2 0.1 0.3 BD 0.7
Gw115 BD 0.006 52.0 69.4 1207.0 18.7 7.0 17.5 9.1
Gw116 BD 0.324 12.1 13.7 1590.5 BD 4.2 BD BD
Gw118 0.120 BD BD 17.2 1023.0 BD 12.6 BD BD
Gw121 0.715 BD 31.4 8.2 919.0 BD 17.2 BD BD
Gw122 0.004 0.060 15.6 6.8 757.5 BD 17.0 BD BD
Gw123 BD BD BD 0.4 223.0 BD 6.1 BD 2.6
Gw124 0.621 0.031 BD 2.8 1225.5 BD 5.2 BD BD
Gw125 BD 0.024 42.2 135.1 795.5 43.1 6.8 21.1 41.9
Gw128 0.415 0.007 104.0 5.6 59.4 BD 5.8 BD BD
194

Appendix.II. Concentration of major cations in surface water samples of Haripur and
Attock basins
Sample Na K Ca Mg Fe Mn
Haripur Basin
Sw1 117.4 6.6 139.4 18.9 343.0 528.0
Sw 2 47.5 4.7 158.0 33.2 100.0 189.0
Sw 33 3.3 3.2 35.4 3.9 1102.0 171.0
Sw 53 8.8 1.5 60.2 14.1 608.0 50.0
Sw 54 22.1 7.2 73.0 15.9 217.0 131.0
Sw 58 13.2 0.8 50.4 9.6 102.0 3.0
Sw 59 11.9 1.5 55.3 9.8 111.0 7.0
Sw 71 90.9 3.6 19.0 15.5 543.0 33.0
Sw 77 16.5 3.6 29.8 4.6 1659.0 303.0
Attock Basin
Sw 78 46.9 12.8 60.5 20.9 10.0 97.0
Sw 91 4.0 1.0 71.2 13.4 30.0 40.0
Sw 95 5.5 1.8 99.9 15.0 17.0 20.0
Sw 98 34.1 5.6 70.2 17.2 232.0 12.0
Sw 100 47.9 1.8 149.5 27.1 92.0 1.0
Sw 103 45.6 2.7 55.0 18.1 179.0 2.0
Sw 108 20.2 3.3 70.2 16.3 362.0 19.0
Sw 117 15.6 2.9 48.9 16.6 317.0 37.0
Sw 119 60.9 3.3 38.5 17.1 142.0 32.0
Sw 126 17.6 7.6 76.8 13.5 466.0 135.0
Sw 130 11.2 3.6 81.3 17.3 85.0 39.0
195

Appendix.II. Concentration of trace elements in surface water samples of Haripur and
Attock basins
Sample# As Hg Cu Pb Zn Ni Cr Co Cd As
Haripur Basin
Sw1 BD BD BD 42.2 66.8 12.2 49.1 BD 0.7 BD
Sw 2 1.3 BD 1.6 23.7 35.0 BD 2.9 51.9 1.0 1.3
Sw 33 0.7 0.6 13.9 34.7 74.2 12.6 5.4 10.2 0.6 0.7
Sw 53 BD 0.0 6.7 16.6 63.7 3.4 2.9 BD 0.9 BD
Sw 54 BD BD 10.2 9.3 24.4 3.1 1.1 BD 0.7 BD
Sw 58 BD BD BD 12.3 8.3 27.5 0.8 BD 1.1 BD
Sw 59 BD BD 3.2 16.0 122.8 3.5 0.8 BD 1.0 BD
Sw 71 BD BD 34.3 87.2 73.0 112.4 4.7 BD 13.9 BD
Sw 77 5.5 BD 30.2 112.4 112.0 68.3 21.0 0.7 0.7 5.5
Attock Basin
Sw 78 4.954 BD 5.9 7.8 51.7 3.6 1.2 BD 0.3 4.954
Sw 91 0.236 0.342 43.9 71.8 83.4 10.9 3.3 27.5 15.3 0.236
Sw 95 BD 0.205 BD 4.6 39.6 BD 3.1 BD 0.4 BD
Sw 98 BD 1.302 2.5 8.1 22.6 7.7 3.3 1.9 12.4 BD
Sw 100 BD 0.379 BD 6.9 19.5 0.1 1.4 BD 0.7 BD
Sw 103 BD 0.347 8.3 9.3 154.1 3.9 1.1 1.6 0.6 BD
Sw 108 BD 0.173 2.4 10.3 28.3 4.1 0.4 1.1 0.6 BD
Sw 117 0.189 0.252 1.7 23.0 1009.0 1.1 7.0 BD BD 0.189
Sw 119 BD 0.128 BD 5.8 41.4 BD 1.8 BD BD BD
Sw 126 0.699 0.258 7.7 20.9 1219.0 6.3 13.1 2.5 BD 0.699
Sw 130 0.341 BD 87.0 13.3 1685.0 BD 5.8 0.2 0.1 0.341
196

Appendix.III. Concentration of major cations in soil samples of Haripur and Attock
basins
Sample K Na Ca Mg Fe Mn
Haripur Basin
S1 17006 30932 164780 24833 43615 848
S2 19958 15981 86380 24729 42364 737
S3 22383 17061 112613 21636 43436 829
S4 14822 21263 76405 17841 42793 683
S5 15740 16554 65503 17511 36251 538
S6 18527 28232 76335 20316 42006 688
S7 12035 19980 95953 17201 39575 584
S8 18150 15643 29943 18789 36608 703
S9 20244 19963 131653 22110 44008 724
S10 19175 17499 24518 15118 36322 620
S12 23769 16892 156433 29019 41542 829
S13 26977 25768 101343 26957 45581 822
S14 26088 31911 133210 28174 46296 941
S15 22850 15323 58048 32608 43222 831
S16 17879 28232 182700 37393 32497 655
S17 10273 15188 152058 43911 40112 797
S18 21298 18293 150728 25493 36572 820
S19 19777 19389 103390 24008 36143 702
S20 21750 32957 70945 23987 39683 833
S21 22247 22731 151340 25286 40862 828
S22 20530 23541 144060 34980 33140 759
S23 24296 17196 82968 22729 39540 789
S24 18271 21431 153528 22089 42972 702
S25 16780 26528 203350 27638 38717 1055
S26 19551 25566 96565 19738 34141 711
S27 18000 28890 85925 18006 34249 859
S28 18045 20453 68775 21821 34749 798
S29 19792 19457 112000 23533 44437 928
S30 20997 29194 19040 17469 41542 897
S31 19687 13854 12215 13406 45045 745
S32 22052 26477 11655 11612 39289 881
S33 20380 14698 25043 17346 53697 1028
S34 26314 27101 24553 17841 48370 715
S35 20078 16386 44748 19099 42864 773
S36 22142 14192 61635 21821 47834 839
197

Attock Basin
S37 18738 13281 44345 15902 36251 711
S38 21660 18731 63840 17799 45689 884
S39 20108 25296 84035 23492 40684 829
S40 19958 18731 78978 22749 39540 833
S41 18497 14918 84613 25802 41291 816
S42 16825 13635 79573 20625 42900 904
S43 18979 19609 63035 17531 39146 784
S44 13903 9450 630 6848 27849 690
S45 19657 10581 2118 9467 36930 520
S46 22684 10125 4515 10766 34821 647
S47 14144 5957 1593 8209 28993 542
S48 17714 10209 2293 9549 33891 596
S49 18150 13365 60393 20006 45188 853
S50 17352 8792 8768 12231 34463 601
S51 18211 16656 44170 16438 37788 706
S52 18873 20621 67130 18583 41542 838
S53 21088 21870 65153 17676 36358 795
S54 15213 12977 14630 12334 25955 617
S55 19114 10952 49123 17057 32890 749
S56 16704 14496 81078 18934 36644 740
S57 19581 13061 34370 20192 46439 911
S58 18196 12184 22488 13901 36036 789
S59 23829 8589 13248 15036 36143 771
S61 22353 11694 17693 16438 39611 844
S62 23226 14749 25025 14912 40755 779
S63 17307 16622 67883 19491 38825 836
S64 19581 17837 102743 22894 44402 895
S65 16524 15660 44433 17490 35929 744
S66 20048 12386 81533 18294 45331 981
S67 14490 14141 96443 15386 44652 715
S68 18180 16116 72625 16851 36358 736
S69 19762 16470 165043 20027 47083 931
S70 22729 18090 77893 20893 43758 923
S71 20862 14934 43838 17284 38932 825
S72 29989 94085 55440 19037 46332 881
S73 27188 101014 107853 20151 45867 822
S74 35005 107966 47810 23306 46868 1031.51
S75 35201 112539 62755 26524 43973 901.76
S76 37852 117602 46533 27803 48227 967.60
198

S77 32625 101250 52255 23513 44866 844.96
S78 22142 106954 51240 21388 45188 838.50
S79 35668 114159 53305 25389 43401 954.05
S80 18632 23625 58258 23471 47941 941.78
S81 16599 21938 48265 24420 44974 919.84
S82 18361 27692 47408 23698 39611 901.76
S83 16192 18428 40775 22729 37359 810.10
S84 18949 16453 32218 19264 51230 1110.26
S85 16885 17803 30240 16191 36215 733.29
S86 14897 12353 186550 25761 37180 824.30
S87 15725 14124 8698 13386 34713 716.51
S88 15650 16149 126840 20171 38574 791.38
S89 17397 18731 36855 18253 37716 790.74
S90 16252 11441 75828 19841 48441 1020.54
S91 16644 13736 84875 19326 38431 855.93
S92 15921 15863 136815 22791 44866 942.43
S93 13677 14985 69703 15778 46404 852.06
S94 17051 17415 51695 23533 48763 861.10
S95 13948 12167 66710 18294 14836 770.08
S96 12171 12066 171990 17841 31210 897.89
S97 13873 25988 53865 19161 43937 1003.11
S98 8194 18698 46708 21120 37037 819.79
S99 12472 17078 22960 19264 30066 717.80
S100 17789 18816 40058 20687 44044 946.30
S101 12683 15272 77630 18707 36000 761.04
S102 14520 32383 37223 15902 39754 871.43
S103 15740 16959 33600 17078 50694 950.82
S104 23016 25464 29733 11426 32139 589.34
S105 15981 18849 48283 18253 40290 889.50
S106 11101 13939 80150 16686 34177 757.17
S107 12020 10058 80150 22708 40934 808.17
S108 11945 13213 199850 14004 32247 739.74
S109 16554 15424 153528 20955 39754 907.57
S110 13737 25650 110600 19284 40505 793.97
199

Appendix. III. Concentration of heavy metals in soil samples of Haripur and Attock
basins
Sample As Cu Zn Co Ni Pb Cd Cr
Haripur Basin
S1 9.3 8.10 24.03 11.31 18.09 6.04 0.09 18.57
S2 5.7 17.16 45.36 17.31 31.83 6.09 1.44 40.14
S3 9.9 15.09 65.91 14.94 27.30 5.13 1.02 38.70
S4 8.5 13.41 44.88 14.76 31.74 4.35 1.26 33.93
S5 7.9 12.51 62.85 14.46 28.44 5.82 1.11 48.24
S6 7.1 14.94 48.69 17.28 38.97 8.37 0.90 39.42
S7 6.6 12.84 37.89 12.57 28.80 7.17 0.57 41.94
S8 5.7 11.67 31.17 13.32 28.02 6.36 1.14 44.52
S9 5.6 18.45 56.97 15.54 37.68 6.06 1.29 43.02
S10 7.4 14.04 55.35 17.22 36.99 10.32 1.29 45.18
S12 9.0 13.05 29.25 13.17 35.10 10.20 0.93 50.40
S13 9.4 14.52 29.52 18.09 32.34 11.10 1.02 41.94
S14 5.7 13.20 31.83 13.98 35.64 5.16 0.99 40.41
S15 6.7 12.93 19.11 14.49 41.73 8.79 0.72 54.57
S16 6.4 10.02 14.37 11.10 35.22 5.55 1.32 36.96
S17 7.3 13.98 12.99 12.27 29.61 10.23 0.63 36.30
S18 6.4 12.48 17.79 12.15 36.90 15.87 0.99 38.55
S19 9.9 11.67 17.55 12.33 32.04 18.36 0.99 37.71
S20 7.4 15.45 27.54 16.38 36.12 18.78 0.84 44.55
S21 10.3 11.40 22.92 15.72 31.26 5.13 1.23 38.31
S22 9.2 16.41 54.30 13.50 41.01 6.69 0.93 44.25
S23 8.9 12.18 21.57 16.38 40.50 8.85 1.20 47.46
S24 9.4 13.05 14.40 11.13 38.10 11.61 0.99 40.41
S25 11.2 12.60 17.76 9.93 28.86 10.02 0.99 35.67
S26 7.9 13.71 21.39 11.61 34.08 13.11 0.81 38.34
S27 7.3 15.27 20.43 14.52 34.92 11.88 1.02 40.89
S28 6.4 14.25 16.65 13.14 39.60 9.15 0.81 41.76
S29 10.1 17.01 18.24 13.92 42.42 9.54 0.87 58.44
S30 6.6 17.31 27.93 15.03 39.87 15.24 0.63 43.17
S31 8.1 12.06 32.28 10.02 31.95 5.49 0.81 42.72
S32 8.5 16.86 56.40 16.92 27.69 14.70 0.42 31.32
S33 8.1 19.44 54.42 18.12 35.28 10.92 0.78 52.65
S34 6.4 15.15 37.95 14.79 37.83 3.72 0.66 38.07
S35 9.2 15.27 36.27 15.18 31.68 3.96 1.05 38.31
S36 10.1 26.76 62.52 17.85 41.64 14.04 0.93 42.78
200

S37 6.0 16.74 39.09 16.50 33.42 14.10 0.78 42.99
S38 14.9 19.08 41.61 16.08 35.10 28.08 0.99 55.98
S39 9.3 15.66 40.77 16.59 39.18 11.34 0.12 46.02
S40 7.9 14.07 39.42 13.68 31.05 16.29 1.14 39.81
S41 11.6 13.50 39.12 15.93 25.98 15.93 0.06 35.88
S42 9.3 14.25 38.46 15.51 30.33 14.22 0.48 34.44
S43 5.6 13.83 34.35 14.22 34.80 12.30 BD 37.41
S44 6.0 9.36 18.57 10.38 18.93 10.02 BD 24.24
S45 8.6 14.40 148.62 11.58 23.16 13.23 0.06 48.09
S46 7.5 12.03 53.34 12.21 25.92 14.01 0.33 27.54
S47 6.6 12.33 45.42 10.50 20.13 15.81 BD 64.68
S48 8.1 14.91 37.26 15.00 23.49 12.21 0.27 47.73
S49 7.9 18.33 45.03 16.26 34.47 18.48 0.42 53.64
S50 9.0 13.89 130.74 13.05 29.01 17.04 0.12 40.65
S51 10.0 20.97 192.72 24.00 31.92 13.17 1.02 52.62
S52 8.1 12.24 32.46 16.62 33.06 10.17 0.81 46.80
S53 11.5 18.27 58.80 16.71 30.78 14.37 1.32 36.09
S54 10.3 13.08 39.60 20.16 35.43 13.41 0.48 35.37
S55 11.2 20.91 42.18 16.89 40.50 11.49 0.75 76.35
S56 5.7 22.92 60.90 17.76 35.28 18.33 0.36 47.04
S57 11.6 20.64 45.84 19.11 41.25 13.71 0.42 64.71
S58 6.7 26.52 56.28 17.67 30.57 15.30 0.72 21.90
S59 6.4 28.53 36.66 22.11 33.45 8.61 0.48 35.52
S61 7.8 20.91 64.65 21.93 44.85 15.78 1.05 51.51
S62 9.3 16.05 47.82 21.30 39.66 14.25 0.78 34.02
S63 7.1 12.78 32.13 16.53 35.04 13.14 1.05 42.99
S64 11.5 14.70 37.53 16.44 34.47 15.21 0.69 41.67
S65 6.2 13.44 36.12 17.58 38.88 17.64 0.93 48.03
S66 5.4 15.03 42.96 18.30 33.42 15.42 0.51 37.20
S67 6.5 14.52 36.30 14.85 31.05 17.97 0.54 37.47
S68 5.6 15.42 34.62 16.62 35.13 14.88 0.66 38.52
S69 5.7 14.07 35.52 10.62 29.13 19.38 0.81 42.09
S70 7.2 16.77 44.52 19.56 50.52 36.42 0.99 48.51
S71 5.7 15.84 39.96 19.95 42.93 12.54 0.84 42.36
S72 8.2 21.87 43.74 18.33 43.80 21.15 0.69 46.98
S73 5.3 39.33 52.92 15.36 41.70 19.65 0.51 60.39
Attock Basin
S74 5.9 17.91 41.91 19.56 41.67 17.91 0.90 53.01
S75 5.4 23.52 46.11 17.52 39.06 17.55 0.42 73.77
S76 3.3 18.30 34.98 17.61 34.08 17.01 1.23 39.24
201

S77 7.2 9.51 20.46 9.51 -1.47 9.87 0.48 43.71
S78 2.8 27.48 44.25 17.85 42.09 17.22 0.78 60.57
S79 4.7 18.60 35.70 17.82 38.76 16.11 1.17 48.03
S80 3.2 14.67 40.92 16.38 44.22 19.38 0.48 68.76
S81 5.9 11.10 33.12 17.79 27.78 12.72 1.17 30.15
S82 5.4 11.91 29.82 16.02 28.20 12.03 0.45 52.26
S83 3.3 15.87 41.34 15.54 29.70 13.26 1.32 49.68
S84 7.2 17.10 50.37 17.91 25.77 13.35 0.24 45.66
S85 2.8 12.42 30.39 15.63 34.20 9.78 0.39 31.11
S86 4.7 14.34 30.69 12.30 32.64 13.11 0.96 39.12
S87 3.2 15.54 34.08 17.28 41.07 12.36 0.54 46.92
S88 5.9 12.87 36.42 12.42 32.61 16.74 0.57 32.19
S89 5.4 20.40 36.72 15.57 38.34 15.93 0.39 46.20
S90 3.3 17.31 38.49 16.95 38.49 14.97 0.90 48.33
S91 7.2 18.12 36.99 14.97 33.84 11.22 0.84 43.47
S92 2.8 14.04 33.93 15.06 35.52 12.09 1.20 41.52
S93 4.7 12.30 29.70 16.41 35.52 11.16 0.84 53.34
S94 3.2 15.90 30.75 15.60 37.23 8.46 0.84 45.06
S95 5.9 19.26 39.36 17.58 40.68 15.03 1.05 52.95
S96 5.4 18.03 30.78 14.07 33.99 15.60 0.51 43.47
S97 3.3 10.74 25.89 17.07 32.01 12.39 1.41 69.06
S98 7.2 15.87 33.54 13.77 31.23 12.63 0.69 69.66
S99 2.8 16.98 38.76 17.34 36.63 9.96 0.42 36.06
S100 4.7 20.82 50.55 17.97 36.63 16.65 0.84 54.81
S101 3.2 13.44 33.99 13.95 38.55 16.20 1.38 34.02
S102 5.9 9.93 24.12 19.02 35.28 8.85 1.71 89.07
S103 5.4 13.14 27.15 18.90 35.79 14.64 0.63 66.51
S104 3.3 9.30 22.95 13.83 32.19 14.94 0.90 71.31
S105 7.2 15.18 34.62 18.36 42.81 15.39 0.69 49.68
S106 2.8 15.06 35.82 14.91 40.89 16.65 0.75 47.04
S107 4.7 15.87 40.35 11.64 41.19 18.99 0.72 49.86
S108 3.2 12.39 29.10 10.83 36.06 21.06 0.60 39.75
S109 3.4 16.59 40.86 14.10 38.76 13.89 0.54 47.91
S110 4.2 28.44 39.30 11.94 40.95 16.68 0.63 56.01
202