Environmental Geochemistry of Attock and Haripur Basins, Pakistan

Home , Kala Chitta Range, Mohammad Tahir Shah, Teer (Pind Hasham Khan)

ENVIRONMENTAL GEOCHEMISTRY OF ATTOCK AND HARIPUR BASINS, PAKISTAN

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

ENVIRONMENTAL GEOSCIENCES

SHAZIA JABEEN

NATIONAL CENTRE OF EXCELLENCE IN GEOLOGY UNIVERSITY OF PESHAWAR PAKISTAN 2013

IN THE NAME OF ALLAH, MOST COMPASSIONATE, EVER MERCIFUL ACKNOWLEDGEMENTS

“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.

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

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

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

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List of Tables

Tables Title Page Table 2.1 Analytical conditions for light elements determination in water samples on 23 air acetylene flame mood Table 2.2 Analytical conditions for heavy metals determination in water samples by 25 graphite furnace Table 2.3 Analytical conditions for major, heavy and trace elements determination in 32 soil samples Table. 4.1a Description of Physico-chemical parameters of water samples of Attock and 52 Haripur basins, Pakistan Table 4.1b Description of selected elements in surface and groundwater samples Attock 59 and Haripur basins, Pakistan 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 66 samples of Attock Basin Table 4.3b Pearson’s correlation matrix indicating the association within groundwater 67 samples of Attock Basin Table 4.4a Pearson’s correlation matrix indicating the association within surface water 70 samples of Haripur Basin Table 4.4b Pearson’s correlation matrix indicating the association within groundwater 71 samples of Haripur Basin 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 80 and groundwater in Attock and Haripur basins Table 4.8 Hazard quotient (HQ) of heavy metals via the consumption of surface and 81 groundwater in Attock and Haripur basins Table 5.1 Statistical parameters for major cations distribution in soils of Attock and 94 Haripur basins 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 110 to present study Table 6.1 Vegetable and cereal crops collected from the study area 123

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

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 68 from Attock Basin Fig. 4.4b. Dendrogram showing association of metals in groundwater samples collected from 68 Attock Basin Fig. 4.5a. Dendrogram showing association of metals in surface water samples collected 73 from Haripur Basin Fig. 4.5b. Dendrogram showing association of metals in groundwater samples collected from 73 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 96 samples of Attock Basin Fig. 5.3. Box and Whisker plots of (a)major cations and (b) selected HMs in soil 97 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

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

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List of Appendices

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

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LIST OF ABBREVIATION

As Arsenic HQ Hazard quotient

BOD Biological Oxygen Igeo Geoaccumulation Index Demand 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 Mg Magnesium Protection Administration 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 RAC Risk Assessment Code Organization of United Nations FC Fecal Coliform S.D Standard Deviation

Fe Iron SO4 Sulfate GIS Geographical Information SS Suspended Solid System HCA Hierarchical cluster TDS Total Dissolve Solid analysis 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 Zn Zinc Index

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.

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 ,

2- - - SO4 , 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 <1 for all the heavy metals (HMs) suggesting no risk to health. Application of different multivariate techniques for the interpretation of the metal data obtained during the monitoring program revealed that geogenic and anthropogenic activities were major sources of water contamination in the study area.

Fourteen elements (Na, K, Ca, Mg, Cd, Cr, Cu, Pb, Fe, Ni, Zn, Co, Mn and As) were analyzed in soil samples and were compared with that of the normal agricultural soils. Most of the metals showed random distribution with diverse correlations in both basins. Principal component analysis and cluster analysis revealed significant

xii 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); therefore, the health risks of all elements through the consumption of vegetables were of great concern in the study area. Nine HMs (Zn, Cu, Cr, Ni, Co, Cd, Pb, Mn and Fe) were analyzed in medicinal plants. Their HMs concentrations were high according to the international safety standards for the consumption of human beings. High level of HMs in the medicinal plants could be due to the industrial and agricultural activities in the study area. It is concluded that water and soil quality of the Attock and Haripur basins are facing severe degradation due to unwise industrial activities in the study area. This study will, therefore, provide basis for the future management of other polluted streams and soils of the regions. The quality of ground and irrigation water can be improved by implementing national quality standards and installing proper treatment plants in the industries.

Key words: Haripur Basin, Attock Basin, Groundwater, Soil, Vegetable, Medicinal plant

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CHAPTER 1

INTRODUCTION

1.1. General Statement

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).

Health and state of disease of human beings and animals is mainly controlled by water quality. Water quality in a region is largely depending on both by geogenic processes (weathering of rocks and soil erosion) and by anthropogenic activities

(agricultural and industrial activities). 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 groundwater aquifers resulting in contamination 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 activities 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,

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). Changes in environmental conditions like land use, agricultural input, and climatic change may result in mobilization of heavy metals.

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 leachig to groundwater which result in contamination of drinking water resources, and may cause risk to the health of human beings and animals. This led to increasing public concern on the adverse effects on human and ecological health due to the increasing accumulation of heavy metal contaminants in the agricultural soils (Wong et al., 2002; Nicholson et al., 2003).

Intake of toxic metals through the soil-crop system has been determined as the major pathway to exposure of human to environmental toxic metals in agricultural area.

According to various studies, in environment these metals are mainly derived from anthropogenic activities (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 characteristics, which reduces the amount of land

3 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

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.

 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 45oC in summer while falls

below 20oC in winter (Census, 1998).

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 km2. 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 Km2. 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).

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.

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 is made of shale interbedded by limestone. Middle Jurassic Samana Suk Formation composed of limestone (Calkin et al.,

1975). d) Tertiary formations

Paleocene rocks unconformably overlie the Jurrasic Samana Suk Formation near

Hassan Abdal. The youngest bedrock in this area is shale of the Patala Formation (Latif,

1970).

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 area 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 in this block are sedimentary in origin and their age range from Jurassic to Paleocene. 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

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).

CHAPTER 2

MATERIALS AND METHODS

2.1. Field investigations

2.1.1. Water sampling

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

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

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-

- 2- chemical parameters within the 48 hours of sampling. Nitrate (NO3 ), sulphates (SO4 ) 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 0.1oC divisions.

19 b. 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.

o The pH of pure water (H2O) is generally 7 at 25 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)

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

The sulphate of the water samples were determined by using HACH DR-2800 photometer. c. Chloride

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

- 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.

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

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.

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 T0C 1200 1400 1200 1200 1400 1600 1400

Atomization T0C 2300 2400 2300 2300 2500 2500 2500

Detection limit 0.014 5 0.05 0.02 0.07 0.004 0.15

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 0C 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

The plant samples were washed with deionized water to remove dust and then oven dried for 48 hours at 60 0C 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).

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.

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

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.

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 0C held for 10 min, then to 75 0C held for 10 min, and finally to 95 0C for 30 min, and then allowed to cool to room temperature (Marwa et al., 2012). The 1000 mg/L standards of the elements measured was obtained from Merck, while HNO3 and H2O2 were obtained from VWR International.

CTA-OTL-1- Oriental tobacco leaves CRM was used for the validation the analyses. The CRMs, spikes and blanks were run with each batch of 30 plant 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).

35 b. Preparation of soil samples for ICP-MS

For the preparation of the soil digest, 0.1 g soil samples were weighed into quartz glass tubes and left to stand overnight after the addition of 2.5 ml of HNO3. 2.5 ml of

0 H2O2 was added to it and was digested on the block digester at 100 C for 1 h, then at 120

0C for 1 h and finally at 140 0C until the sample was fully digested (Adomako et al.,

2009).

NCS ZC 73007 soil CRM was used to confirm the analyses. After each soil digest batch of 30 samples, the CRMs, spikes and blanks were run, which were arranged in according to a randomized order. The concentrations of heavy metals in soil digest were determined by ICP-MS 7500 (Agilent Technologies).

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

(HMs) 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 may result in the addition of heavy metals 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.

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 HMs 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 it is necessary to characterize the content and source of HMs in soils to establish the quality standards on the regional level. It allowed the detection of sampling sites that were affected by pollution. The surface soil of 54 agricultural sites having 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 and CA) was

40 used to identify a common source for HMs. Moreover, soil properties have been determined to characterize agricultural soils and to analyze relationships between concentration of HMs and soil properties. The metals like Co, Cr, Fe, Mn, Ni and Zn were linked with parent rocks and corresponded to the first principal component called the lithogenic component. The lithogenic metals were also correlated with soil properties such as soil clay content, organic matter, and carbonates. Also the elements such as Cd, Cu and Pb were associated with anthropogenic activities and comprised the second (Cu and Pb) and third principal components (Cd), designated the anthropogenic components. Generally, Cd, Cu and Pb remained unavailable forms in agricultural soils that’s why they showed less correlation with soil properties.

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 local (Chongqing) background values. None of the heavy metals were found in high

41 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 (<4.6%) and mercury (<1.2%) was considerably low. Sediments from 15-25 cm depth contained the highest level of water soluble toxic elements, especially in areas which were occupied with plants (Halimione portulacoides), and in mining soil samples. The percentage of Zn, Cu, Co and Cd was highest in relation to total metal contents. Significant changes in sediment matrix were caused due to the presence of plant, which resulted in the mobility of various toxic elements.

Ali and Malik (2011) reported that the soil quality of rapidly growing city of

Islamabad, Pakistan. They analyzed the seven physico-chemical parameters and 11 metals in surface soils. Statistical analysis was used to identify the sources of contamination. Geo- accumulation index and metal pollution index were used for estimation 0f pollution. Soil parent material is responsible for concentration of major elements (Ca, Mg, Na, K) in surface soils, while high concentration of other toxic metals were mainly associated with anthropogenic activities. Geostatistical methods were used to identify hotspot areas of heavy metals contamination in built-up areas influenced primarily by disposal of waste and vehicular emissions.

Liu et al. (2011) investigated the heavy metal pollution around an electroplating plant.

The risk assessment was done in water, paddy soil and rice. Atomic absorption spectrophotometer was used to determine the concentration of heavy metals. The risk assessment parameters were done by evaluation of risk assessment code (RAC) and

43 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.

CHAPTER 4

WATER CHEMISTRY

4.1. Introduction

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).

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

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

48 were used. Three multivariate methods such as correlation matrix, hierarchical cluster analysis (HCA), and principal component analysis (PCA) were 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).

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

−1 −1 was the oral reference dose (g L day ). 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. Greater the HQ value than unity, the more 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).

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 26oC and 19 to 23oC, respectively.

Variations in water temperature of Haripur Basin were found between 14 to 26oC and

11 to 28 oC 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).

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

-1 NO3 (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

-2 SO4 (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

-1 HCO3 (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

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.

- 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

-2 agricultural lands/area. The sulphate (SO4 ) 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

-2 mg/L) and 33.0-103.2 mg/L (mean= 66.1 mg/L), while in Haripur Basin, the SO4 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).

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

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

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

Table 4.1b. Description of selected elements in surface and ground water samples of Attock and Haripur basin, Pakistan Attock Basin Haripur Basin Groundwater Surface water Groundwater Surface water Element Range Mean± S.Da 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 <0.15b-28.2 2.7± 3.5 1.0- 7.00 3.88± 2.1 Ca 38.2-152.9 29.4± 22.6 38.4- 149.5 74.7± 29.8 34.1- 157.2 79.4± 23.9 19.1-158.2 68.7± 48.3 Mg 9.3- 88.2 29.4± 22.6 13.4- 27.1 17.5± 3.8 8.20- 109.1 24.9± 19.7 4.0- 33.0 14.1± 8.71 As <0.15- 11.2 2.03± 3.1 0.2- 4.9 1.3± 1.4 <0.15-3.7 0.39±0.75 0.6- 5.4 2.48±2.60 Hg <0.15- 1.45 0.28± 0.38 0.13-1.30 0.38± 0.36 <0.15-0.67 0.22± 0.19 <0.15- 0.56 0.29± 0.37 Fe 4.1- 803 125± 171 10.2-466 175± 152 13.1- 950 133± 144 100- 4659 1087±1641 Mn 1- 203 21.1± 32.0 1-135 39.4±41.1 2-103 28.5± 28.2 3.1- 528.2 157.2± 170.9 Cu 0.2- 145.5 35.4± 40.1 1.7- 87.2 19.9± 27.1 13.9- 166.2 22.1± 29.1 1.6- 34.3 14.3± 12.9 Pb 0.4- 135.1 23.3± 30.9 4.6- 71.7 16.5±19.3 4.36-147.7 37.5± 28.2 9.2- 112.4 39.3± 36.4 Zn 59- 1591 500± 432 19-1658 395±604 8.0-1486 224± 270 8.3- 122.8 64.4± 37.9 Ni 3.2- 43.1 8.2± 11.4 1.5- 10.9 4.7± 3.5 <0.15- 47.4 5.3± 8.06 3.1-112.4 30.3± 39.6 Cr 0.69- 17.2 3.13± 4.24 0.37-13.1 3.82± 3.71 <0.15-194.10 24.73± 44.67 0.82-49.1 9.8± 15.99 Co <0.15- 23.9 4.75± 7.70 0.2- 27.5 5.8± 10.6 <0.15-25.5 2.21± 5.06 0.67-51.8 20.9± 27.21 Cd <0.15- 41.9 5.48± 9.77 0.09-15.25 3.71± 5.52 <0.15-17.54 3.90± 8.25 0.61-13.84 2.29± 4.35 aStandard deviation b<0.15= below detection

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

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 <0.15 to 11.2, and

<0.15 to 3.7 μg/L, while in surface water it ranged from 0.2 to 4.9, and 0.6 to 5.4 μg/L in Attock and Haripur basins, respectively. Similarly, the Hg concentrations in groundwater samples ranged from <0.15 to 1.45, and <0.15 to 0.67 μg/L, while in surface water it ranged from 0.13 to 1.30 and <0.15 to 0.56 μg/L in Attock and

Haripur basins, respectively (Table 4.1b). Fe concentrations were found in the range of 4.1-803.2, and 13.2-950.1 μg/L in groundwater and 10.2 to 466.1, and 100.1 to

4659.4 μg/L in surface water of Attock and Haripur basins, respectively (Table 4.1b).

The highest Fe concentration (950.1 μg/L) was observed in dug-well sample from

Chahari Kas stream area. Similarly, Mn concentrations in groundwater ranged from 1 to 203, and 2 to 103 μg/L, while in surface water samples it ranged from 1 to 135, and

3 to 528 μg/L of the Attock and Haripur basins, respectively (Table 4.1b). However, the Mn concentrations in both surface water and groundwater samples were within the permissible limits (528 μg/L) set by WHO and USEPA (Table 4.2) except one surface water sample, collected from Chahari Kas stream which had 528 μg/L of Mn.

Average concentrations of Cu in ground and surface water in Attock Basin varied between 0.2-145.5 μg/L and 1.6-87.2 μg/L, respectively while in Haripur Basin

61 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 <0.15 to 47.4 µg/L (mean= 5.3

µg/L) and 3.1 to 112.4 µg/L (mean=30.3 µg/L), respectively in ground and surface water of Haripur Basin. The highest Ni concentration (112.4 µg/L) was found in

Dhotal Kas upstream sample near the discharge of industrial effluent and followed by downstream sample of Dhotal Kas (68.4 µg/L). The surface water samples of Attock

Basin showed less Ni concentrations than those of Haripur Basin. Cr concentrations ranged between 0.69 to 17.2 µg/L (mean= 3.13 µg/L) and 0.37 to 13.1 µg/L (mean=

3.82 µg/L) in ground and surface water of Attock Basin and <0.15 to 194.1 µg/L

(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 <0.15 to 25.9 µg/L (mean= 4.75 µg/L), respectively. While in Haripur Basin, the Co concentration ranged between <0.15 to

25.5 µg/L (mean= 2.21 µg/L) and 0.67 to 51.8 µg/L (mean= 20.9 µg/L) ground and surface water samples, respectively. Like Cr, in all samples, the Co concentrations were lower than the permissible limits (Table 4.2). Cd concentrations ranged between

<0.15 to 41.9 µg/L (mean= 5.48 µg/L) and <0.15 to 15.2 µg/L (mean= 3.7 µg/L) in ground and surface water of Attock Basin, respectively, while in Haripur Basin it ranged between <0.15 to 17.5 µg/L (mean= 2.77 µg/L) and 0.6 to 13.8 µg/L (mean=

2.2 µg/L) in ground and surface water, respectively. The order of distribution of heavy metals in groundwater samples in Attock Basin was found as

Zn>Fe>Cu>Pb>Mn> 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

1000

100

Groundwater 10

Surface water Concentration

1 Na K Ca Mg As Hg Fe Mn Cu Pb Zn Ni Cr Co Cd

0.1

Fig. 4.3a. Comparison of surface and groundwater quality of Attock Basin

1000.0

100.0

Groundwater 10.0

Surface water Concentration

1.0 Na K Ca Mg As Hg Fe Mn Cu Pb Zn Ni Cr Co Cd

0.1

Fig. 4.3b. Comparison of surface and groundwater quality of Haripur Basin

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<0.05 with correlation (r) values being 0.626, 0.718, 0.541, 0.651,

0.680, 0.609, 0.689 and 0.674, respectively, in the surface water samples of Attock

Basin (Table. 4.3a). Significantly correlated pairs at p<0.01 were found as K-As, As-

Mn, Pb-Co, Zn-Cr, Ni-Co, Ni-Cd and Co-Cd with r values of 0.878, 0.581, 0.956,

0.768, 0.745, 0.810 and 0.778, respectively. Four clusters were noticed while ploting data in Figure 4.4a. Clusters-1 grouped Pb, Co, Ni, Cd and Hg, Cluster-2 had K, As and Mn, Cluster-3 grouped Zn, Cr and Cu and Cluster-4 grouped light elements Na,

Mg and Ca together. Fe showed no relationship with any metal and was considered as outlier.

In the groundwater samples of Attock Basin, correlation at <0.05 in Table 4.3b were found between Mg and Co (r= 0.391), Fe and Ni (r= 0.434), Cu and Pb (r=

0.392), Cu and Ni (r= 0.425), Pb and Zn (r= 0.427), Zn and Ni (r=0.358) and Ni and

Cd (r= 0.420). Positively correlated pairs at <0.01 were Na- K (r= 0.516), Na-Mg (r=

0.647), Na-Mn (r= 0.619), K-Mg (r= 0.624), Ca-Fe (r= 0.489), and Fe-Cu (r= 0.465).

Table 4.3a. Pearson’s correlation matrix indicating the association within surface water samples of Attock Basin Na K Ca Mg As Hg Fe Mn Cu Pb Zn Ni Cr Co Cd Na 1 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.

Table 4.3b. Pearson’s correlation matrix indicating the association within groundwater samples of Attock Basin Na K Ca Mg As Hg Fe Mn Cu Pb Zn Ni Cr Co Cd Na 1 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.

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

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 was positively correlated 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

Table 4.4a. Pearson’s correlation matrix indicating the association within surface water samples of Haripur Basin Na K Ca Mg As Hg Fe Mn Cu Pb Zn Ni Cr Co Cd Na 1 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.

Table. 4.4b. Pearson’s correlation matrix indicating the association within groundwater samples of Haripur Basin Na K Ca Mg As Hg Fe Mn Cu Pb Zn Ni Cr Co Cd Na 1 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.

(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

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

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

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,

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

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 respectively. 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,

Table 4.7. Chronic daily intake (CDI) of heavy metals via the consumption of surface and groundwater in Attock and Haripur basins Attock Basin Haripur Basin

Groundwater Surface water Groundwater Surface water

Element 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

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

Element 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

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 there are no adverse health effects on the inhabitants of Attock and Haripur basins through the ingestion of drinking water. 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 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

- 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 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 northwestern 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 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 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

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

87 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.

CHAPTER 5

SOIL CHEMISTRY

5.1. Introduction

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 may affected the quality of agricultural soils, such as phytotoxicity due to high concentrations of heavy metals (HMs). These metals transfer to the human beings by the intake of contamination crop and 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 HMs contamination of the 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 source identification of HMs contamination and their spatial distribution in agricultural soils of Pakistan. Similarly, none of research has reported soil pollution with HMs in

Attock and Haripur basins. Therefore, the assessment and monitoring of HMs concentration and consequent soil pollution remain unidentified. The results of this study provide geochemical baseline for metal concentrations in soil of Attock and

Haripur basins and spatial variation along with potential identified sources of HMs pollution in soil which might be helpful in future soil monitoring, remediation and planning processes. The spatial maps validated for pollution sources known using GIS is used for assessment of the quality of soil in the study area (Imperato et al., 2003,

Mahmut et al., 2005, Malik et al., 2010) which may facilitate the decision makers and planners to use various techniques to decontaminate the contaminated soil (Xie et al.,

2011). Spatial distribution maps of HMs concentration are helping to present the association between anthropogenic activities and HMs accumulation (Romic and

Romic, 2003). In this regard, spatial relationship of HMs using GIS is helpful in the

90 identification of hotspots which are the key concern for future 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).

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

The geoaccumulation index is calculated from the equation modified by Loska et al. (2004),

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

5.3. Results

The surface soils were collected from two to three random places with quadrat size of 100 m2 at a depth of 22cm from each grid, and a total of 110 surface soil samples were collected from Attock and Haripur basins (Fig. 5.1). The geographical coordinates of each quadrat was recorded with a Garmin GPS. The statistical summary of the distribution parameters for major, heavy and trace elements in soil samples of Attock and Haripur basins is given in Table 5.1, while, their quartile distribution is represented as Box and Whisker plot in Figure 5.2a and b. The soils were found slightly basic in nature having mean pH values ranged from 7.76 and 7.56 in Attock and Haripur basins, respectively. Electrical conductivity (EC) values were

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 considerably 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, the soil samples showed elevated mean levels of major elements as

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.

1e+6 a

1e+5

1e+4

Concentration (mg/Kg) Concentration 1e+3

1e+2 K Na Ca Mg Fe Mn

100 b 80

Concentration (mg/Kg)

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

1e+6 a

1e+5

1e+4

Concentration (mg/Kg) Concentration 1e+3

1e+2 K Na Ca Mg Fe Mn

80 b

Concentrations (mg/Kg)

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

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 was positively correlated 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

Table 5.2. Correlation coefficient matrix of selected metals in the soil of Attock Basin K Na Ca Mg Fe Cu Zn Co Ni Pb Cd Cr Mn As K 1 Na .913 1 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.

Table 5.3. Correlation coefficient matrix of selected metals in the soil of Haripur Basin K Na Ca Mg Fe Cu Zn Co Ni Pb Cd Cr Mn As K 1 Na .534 1 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.

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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 <0.4 and the proportion of total variance explained by the factors for the raw data (Zhao and Cui., 2009).

The results of PCA for metal contents of the soil samples of Attock and

Haripur basins are presented in Table 5.4 and 5.5, respectively. Soil samples of

Attock Basin were grouped into five-components that accounts for 75.79% of all the data variation. PC1 represented 26.41% of the total variance and is the most important component. This distribution was control by K, Na, Mg, Fe, Mn and, partially by Zn and Co in the first principal component (Table 5.4) which could be due to non-point source such as agricultural activities.

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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

(PC1) (PC2) (PC3) (PC4) (PC5)

K .737 -.290 .306 -.368 -.162 Na .763 -.224 .283 -.382 -.172 Ca -.307 .325 .555 .525 -.050 Mg .671 -.129 .475 .236 -.090 Fe .601 -.352 .134 .242 .462 Cu .498 .678 .067 -.172 -.081 Zn .517 .728 -.008 .028 -.064 Co .568 -.042 -.672 -.027 .152 Ni .201 .742 -.453 .145 .150 Pb .287 .649 .239 .013 .017 Cd .181 -.349 -.397 .504 -.386 Cr .249 -.104 -.524 -.169 .254 Mn .705 -.206 .043 .511 .285 As -.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

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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 due to high utilization of Cu-based agrochemicals, whereas water and irrigation time may result in 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 having eigen values more than 1.

These components explaining more than 72.4% total variance of the data. PC1 explained 22.46% of variance and showed high loadings of K, Cu, Co, Ni, Pb, and Cr which also represented a strong cluster (Fig. 5.4b). These metals are mostly coming from both natural and anthropogenic sources. PC2 explained 20.05% of total variance and showed the high 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 shown higher contributions of Ni and Cd, representing 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 results were in total agreement with the PCA results.

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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 22.466 20.058 10.389 9.053 8.291

Cumulative % 22.466 45.524 52.912 61.965 70.256

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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 soils of Haripur Basin as compared to the soils of the Attock Basin may be associated with climatic variations as Haripur Basin receives more precipitation which may result in the leaching of the soluble ions. On the other hand, Attock Basin is mostly remained dry or arid (Leong,

1992).

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.

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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

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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.

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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

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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

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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.

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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

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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

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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 geoaccumulation index (Igeo) has been used for the assessment of the contamination levels of selected metals. It is the quantitative evaluation of the pollution index in the soils. The index is calculated 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

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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

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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

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4.00 Max

Min

) 2.00 Average geo

0.00

-2.00 Geoaccumulation Index(I Geoaccumulation

-4.00 As K Na Ca Mg Fe Cu Zn Co NI Pb Cd Cr Mn Elements

Fig 5.6a. Geoaccumulation index for selected metals in soil samples of Attock basin

4.00 Max Min

2.00

) Average geo 0.00

-2.00

-4.00 GeoaccumulationIndex(I -6.00

-8.00 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

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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) showed practically no contamination in the studied soils. The average Igeo values for Cd revealed 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.

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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 are the main components of human diet. Vegetables are known for the supply of minerals, fibers and vitamins. They also have antioxidative effects. However, consumption of vegetables elevated with heavy metals may cause a risk to the human health. HMs contamination of the edible plant is one of the most essential 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.

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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 reported 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, Zn, Ni, Pb, Cd and Cu) 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 health risk index and pollution load index also calculated to assess role heavy metal through intake 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).

1/n MPI (mg/Kg) = (Cf1× Cf1×. . . . × Cfn)

Where Cfn = concentration of metal n in the sample

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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

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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 daily intake of studied plant and 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 greater 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,

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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

root 1 2 stem Chinese standard FAO/WHO standards seed 1.8 70 As Zn 1.6 60 1.4 50 1.2

1.0 40

0.8 30 0.6 20 0.4 10 0.2

0.0 0 10 0.7 Cr Cd 0.6 8 0.5

6 0.4

0.3 4

0.2 2 0.1

0 0.0 8 5 Ni Pb

4 6

3 4 2

2 1

0 0 25 200 Cu Mn

20 150

15 100 10

50 5

0 0

Pea

Garlic

Onion Garlic

Onion

Turnip

Wheat

Radish

Spinach

Mustard

Fenugreek

Fig. 6.1. Heavy metal concentration in different vegetable and cereal crop samples 1Hao et al., 2009; 2Khan et al., 2010

127 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 HMs in leafy vegetables might be result of higher transpiration rate of these plants to sustain the growth and moisture content

(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 8.25a 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 Child 2.22 13.7 10.3 59.6 264.2 0.74 13.5 797.0 b RfD 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

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

Medicinal plants have always been important for the treatment of variety of ailments in folk cultures and have played a vital role in discovering novel chemical constituents used in the modern day medicines (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 significance of elemental constituents of the herbal plants which enhanced the awareness about toxic 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 Part used Disease cure Reference (s) name Achyranthes aspera L. Amaranthaceae Puth Kanda Kidney stone, cough asthma, Ahmed et al., 2006; Whole plant stomachache, Qureshi et al., 2007; dropsy, piles, skin eruption 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 & Hayat et al., 2008 rheumatism 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 Blood purification, analgesic, Ashfaq et al., 2004; roots joint pain, Anticancer 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 Abbasi, 1999 weakness, internal pain, skin diseases 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, Abbasi et al., 2009 dysentery, diarrhea, phelgum, jaundice, diabetes, mouth gum, toothache, tuberculosis Parthenium hysterophorus Asteraceae Gandi booti Whole plant Anti-hysteric, dysentery, anti-amoebic Marwat et al., 2004 L. 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.) Solanaceae Asghand Whole plant Aphrodisiac, diuretic, bronchitis, ulcer Hussain et al., 2008 Dunal

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

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(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, according to the WHO

(2005) no limit has been established for Zn in medicinal plants. According to Bowen

143

(1966) 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 established by FAO/WHO (1984), it was noticed 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 established 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 established 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 established 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 <1 which means that these

HMs did not pose health related risks in the inhabitant of the area. The statistical techniques used in present study pointed out the factors responsible for degradation of water quality. These results will help the environmental managers to develop restoration activities with minimum operational cost and expenditures.

The results offered interesting information on relationship between studied metals and soil properties of the study area, and their sources of origin either geogenic or anthropogenic.

Among the studied elements Ca, Mg, Fe, Mn, Na, and K were mainly related with parent rock material and agricultural activities. On the basis of the multivariate analysis (CA, HCA and PCA) different pollution sources were identified, which shaped the pollution patterns of

147

HMs in the surface soils of the Attock and Haripur basins. These sources included parent rock materials, agricultural and industrial activities in area. Considerable high metal pollution existed in areas near to Hattar industrial estate, which were highly contaminated with HMs like Cu, Co, Ni, Pb, and Cr. High quantity of these HMs in surface soils may result in various health risks. 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 maps could be helpful for preliminary monitoring and gathering the information related to the distribution patterns and anthropogenic versus geogenic origin of potentially toxic metals in surface soils which may be crucial for assessment of human impact.

Furthermore, the source identification of these heavy metals in soil could be necessary for the assessment of environmental risk caused by HMs 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 <1 for both adults and children. HRIs of leafy vegetables were higher than the non-leafy vegetable. Also HRIs for children was higher than the adults. Therefore, It is strongly recommended that people of study area should not eat large quantities of leafy vegetables (spinach, mustard and fenugreek), so as to avoid the excess accumulation of heavy metals in their bodies. The situation may pose serious

148 threat to human health and highlight the need to device and apply suitable means of monitoring and regulating industrial effluents. It also provides the right advice 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.

• 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.

149

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

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

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

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

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

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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 33o 54/ 14// N 72o 46/ 30// E S2 Jahar 33o 54/ 46// N 72o 46/ 19// E S3 Jahar 33o 54/ 45// N 72o 46/ 19// E S4 Jabbi 33o 54/ 46// N 72o 46/ 06// E S5 Jabbi 33o 54/ 47// N 72o 46/ 06// E S6 Dingi 33o 54/ 50// N 72o 48/ 10// E S7 Motia 33o 54/ 07// N 72o 47/ 59// E S8 Dingi 33o 54/ 88// N 72o 48/ 08// E S9 Dingi 33o 54/ 46// N 72o 48/ 30// E S10 Dingi 33o 54/ 44// N 72o 48/ 28// E S11 Dehdar 33o 55/ 57// N 72o 48/ 34// E S12 Dehdar 33o 55/ 57// N 72o 48/ 27// E S13 Dehdar 33o 55/ 57// N 72o 48/ 20// E S14 Pehdea 33o 55/ 59// N 72o 48/ 31// E S15 Chamba pind 33o 56/ 59// N 72o 46/ 52// E S16 Chamba pind 33o 56/ 54// N 72o 46/ 53// E S17 Chamra hicthe 33o 57/ 44// N 72o 46/ 17// E S18 Mohri pir bakhsh 33o 56/ 21// N 72o 48/ 02// E S19 Sarai gadahia 33o 56/ 25// N 72o 48/ 58// E S20 Kot najibullah 33o 55/ 54// N 72o 51/ 07// E S21 Jhang kora 33o 56/ 49// N 72o 48/ 55// E S22 Mori malia 33o 57/ 02// N 72o 48/ 13// E S23 Faridabad 33o 57/ 16// N 72o 48/ 38// E S24 Ladha 33o 57/ 84// N 72o 47/ 57// E S25 Ladha 33o 57/ 84// N 72o 47/ 57// E S26 Qayyumabad 33o 57/ 09// N 72o 49/ 02// E S27 Bakka 33o 57/ 19// N 72o 49/ 01// E S28 Pandori 33o 58/ 29// N 74o 81/ 69// E

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

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

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

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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

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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

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 Attock Basin 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