ASSESSMENT OF HEAVY METAL POLLUTION IN SOILS AND WATER OF
SAMBURU COUNTY, KENYA
Salano, Erick Miheso (B. Ed Science)
I56/CE/11204/2007
A Thesis Submitted in Partial Fulfillment of the Requirements for the Award of the Degree
of Master of Science in Applied Analytical Chemistry in the School of Pure and Applied
Sciences of Kenyatta University
July, 2013
ii
DECLARATION
I declare that this thesis is my original work and has not been presented to any other
University for the award of a degree
………………………………
Salano, Erick Miheso
This thesis has been submitted with our approval as University supervisors
………………………
Prof. Hudson Nyambaka
………………………
Date
Chemistry Department
Kenyatta University
……………………………..
Dr. Ruth Wanjau
Chemistry Department
Kenyatta University
………………………….
Date
iii
DEDICATION
This work is dedicated to my late mother Sera Musimbi who taught me the value of education.
iv
ACKNOWLEDGEMENTS
I express my sincere gratitude to all the staff members of the Chemistry Department of Kenyatta
University for their guidance and their positive criticism that directed this work. Special thanks
to my supervisors, Prof. Hudson Nyambaka and Dr. Ruth Wanjau of the Chemistry Department
for being there for me any time I needed their direction. I also wish to express my gratitude to the
Department of Chemistry (JKUAT) for allowing me to use their atomic absorption spectroscopy
machine for analysis of the samples, Kenyatta University through the Chemistry Department for
giving me the opportunity to study at Kenyatta University.
Special appreciation goes to my wife Lenah Khalili for her encouragement and moral support
during the entire course, our daughter Albright Musimbi for her patience during the research
period. Special thanks to Mr. David Burns for having taught me the computer skills that enabled
me to type and format this work.
v
TABLE OF CONTENTS
TITLE PAGE……………………………………………………………………………………I
DECLARATION.......................................................................................................................... II
DEDICATION............................................................................................................................. III
ACKNOWLEDGEMENTS ....................................................................................................... IV
TABLE OF CONTENTS ............................................................................................................ V
LIST OF FIGURES .................................................................................................................... IX
LIST OF TABLES ....................................................................................................................... X
ABSTRACT…………………..………………………………………………………………..XI
CHAPTER ONE ........................................................................................................................... 1
INTRODUCTION......................................................................................................................... 1
1.1 BACKGROUND INFORMATION ................................................................................................. 1
1.2 PROBLEM STATEMENT AND JUSTIFICATION ............................................................................ 4
1.3 HYPOTHESIS ........................................................................................................................... 5
1.4 OBJECTIVES ........................................................................................................................... 6
1.4.1 General Objective .......................................................................................................... 6
1.4.2 Specific Objectives ........................................................................................................ 6
1.5 SIGNIFICANCE OF THE STUDY ................................................................................................. 6
1.6 SCOPE AND LIMITATIONS........................................................................................................ 7
CHAPTER TWO .......................................................................................................................... 8
LITERATURE REVIEW................................................................................................................ 8
vi
2.1 INTRODUCTION....................................................................................................................... 8
2.2 SOIL POLLUTION ..................................................................................................................... 9
2.3 WATER POLLUTION .............................................................................................................. 10
2.4 HEAVY METAL AND ENVIRONMENTAL POLLUTION ............................................................... 10
2.4.1 Introduction .................................................................................................................. 10
2.4.2 Soil pollution from heavy metals ................................................................................. 12
2.4.3 Heavy metals in water .................................................................................................. 13
2.5 HEAVY METALS AND THEIR EFFECTS .................................................................................... 15
2.5.1 Lead.............................................................................................................................. 15
2.5.2 Cd ................................................................................................................................. 17
2.5.3 Chromium .................................................................................................................... 19
2.5.4 Manganese ................................................................................................................... 22
2.5.5 Zinc .............................................................................................................................. 23
2.6 SAMBURU COUNTY .............................................................................................................. 25
2.7 METHODS FOR HEAVY METAL ANALYSIS .............................................................................. 26
2.8 ATOMIC SPECTROSCOPY ....................................................................................................... 27
2.9 ATOMIC ABSORPTION SPECTROSCOPY .................................................................................. 28
2.9.1 Principle of AAS .......................................................................................................... 28
2.9.2 Instrumentation of AAS ............................................................................................... 29
CHAPTER THREE .................................................................................................................... 35
MATERIALS AND METHODS .................................................................................................. 35
3.1 RESEARCH DESIGN ............................................................................................................... 35
3.2 STUDY AREA ........................................................................................................................ 35
vii
3.3 CHEMICALS REAGENTS......................................................................................................... 37
3.4 CLEANING OF GLASSWARE ................................................................................................... 37
3.5 SAMPLING ............................................................................................................................ 37
3.5.1 Soil sampling ............................................................................................................... 37
3.5.2 Water sampling and pre-treatment ............................................................................... 39
3.6 SAMPLE DIGESTION .............................................................................................................. 41
3.6.1 Water digestion ............................................................................................................ 41
3.6.2 Soil digestion ............................................................................................................... 41
3.7 PREPARATION OF STOCK SOLUTIONS AND STANDARDS ......................................................... 42
3.7.1 Lead stock solution and standards ............................................................................... 42
3.7.2 Zinc stock solution and standards ................................................................................ 42
3.7.3 Manganese stock solution and standards ..................................................................... 42
3.7.4 Cd stock solution and standards ................................................................................... 43
3.7.5 Chromium stock solution and standards ...................................................................... 43
3.8 METHOD VALIDATION ......................................................................................................... 43
3.9 SAMPLE ANALYSIS ............................................................................................................... 44
3.10 DATA ANALYSIS ................................................................................................................. 45
CHAPTER FOUR ....................................................................................................................... 46
RESULTS AND DISCUSSION ................................................................................................... 46
4.1 INTRODUCTION..................................................................................................................... 46
4.2 METHOD VALIDATION .......................................................................................................... 46
4.3 HEAVY METALS IN SURFACE AND GROUND WATER .............................................................. 48
4.3.1 Kirisia and Lorroki Divisions ...................................................................................... 48
viii
4.4 HEAVY METALS IN AGRICULTURAL AND ROADSIDE SOIL ...................................................... 63
4.4.1 Levels in individual regions ......................................................................................... 63
4.4.2 Levels in Kirisia and Lorroki region ............................................................................ 71
CHAPTER FIVE ........................................................................................................................ 77
CONCLUSIONS AND RECOMMENDATIONS ........................................................................ 77
5.1 CONCLUSIONS ...................................................................................................................... 77
5.2 RECOMMENDATIONS ............................................................................................................ 79
5.2.1 Recommendations from this study............................................................................... 79
5.2.2 Recommendations for further studies .......................................................................... 80
REFERENCES ............................................................................................................................ 81
APPENDICES…………………………………………………….…………………………...89
Appendix I: Calibration curve for manganese…………...………………………………………89
Appendix ii: Calibration curve for……………………….……………………………………..90
Appendix iii: Calibration curve for chromium…………..…………..…………………………..91
Appendix iv: Calibration curve for cadmium………..………………………………………….92
Appendix v: Calibration curve for lead……………………………………………….…………93
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LIST OF FIGURES
FIGURE 2.1: DIAGRAM TO ILLUSTRATE INSTRUMENTATION OF AAS.............................................. 29
FIGURE 2.2: A HOLLOW CATHODE LAMP ........................................................................................ 30
FIGURE 2.3: A MODEL OF A MONOCHROMATOR ............................................................................. 33
FIGURE 3.1: MAP OF SAMBURU COUNTY ....................................................................................... 36
PLATE 3.1: SOIL SAMPLING SITE FROM A MAIZE FARM IN LORROKI................................................ 38
PLATE 3.2: SOIL SAMPLING FROM WHEAT FARM IN LORROKI ......................................................... 39
PLATE 3.3: WATER SAMPLING SITE, PORRO DAM ........................................................................... 40
PLATE 3.4: WATER SAMPLING SITE, RAGAE ................................................................................... 40
FIGURE 4.1: LEVELS OF CD IN WATER IN KIRISIA AND LORROKI DIVISIONS. ................................. 51
FIGURE 4.2: LEVELS OF CHROMIUM IN WATER IN KIRISIA AND LORROKI DIVISION ....................... 53
FIGURE 4.4: LEVELS OF LEAD IN THREE WATER SOURCES IN KIRISIA AND LORROKI DIVISIONS ..... 59
FIGURE 4.5: LEVELS OF ZINC IN DIFFERENT WATER SOURCES IN KIRISIA AND LORROKI DIVISIONS.
............................................................................................................................................... 61
FIGURE 4.6: PERCENTAGE MEAN CD LEVELS IN SOILS ................................................................... 64
FIGURE 4.7: PERCENTAGE CHROMIUM LEVELS IN SOIL FROM THE FOUR SELECTED SUB REGIONS. .. 66
FIGURE 4.8: MEAN MANGANESE LEVELS IN SOIL FROM THE FOUR SELECTED SUB REGIONS. ........... 68
FIGURE 4.9: PERCENTAGE LEAD LEVELS IN SOIL ............................................................................ 69
FIGURE 4.10: PERCENTAGE ZINC LEVELS IN SOIL FROM THE FOUR SELECTED SUB REGIONS IN
KIRISIA AND LORROKI DIVISIONS. .......................................................................................... 71
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LIST OF TABLES
Table 2.1: Heavy metal limits in water set by different national and international organizations in
µg/l……………………………………………………………………………………………….14
Table 3.1: Elements and their conditions of analysis……………………………………………45
Table 4.1: Calibration curves correlations, detection limits and %recovery………….………...47
Table 4.2: Levels of heavy metals in wells, dams and boreholes in Kirisia and Lorroki……….48
Table 4.3: Levels of heavy metals in wells and dams in Lorroki and Kirisia…………………...50
Table 4.4: Heavy metal concentration (mg/l), mean and range values, compared with some
standard guideline values of drinking water…………………………………………………….62
Table 4.5: Heavy metals in different sub regions of Lorroki and Kirisia Divisions of
Samburu…………………………………………………………………………………………63
Table 4.6: Levels of heavy metals in combined region .……..………………………….…..…72
Table 4.7: Mean, range and WHO maximum allowed limits……………………………………73
Table 4.8: Mean values obtained in this study in comparison with the maximum allowed levels
for different countries……………………………………………………………………………75
Table 4.9: Relationship between individual heavy metals in water and in soils………………..76
xi
ABSTRACT
Heavy metal pollution in soil and water arising from anthropogenic sources continue to pose a
great challenge to human and animal population. In Samburu County conflicts arising from cattle
rustling, military trainings in the county which have led to heavy use and disposal of arms, a
growing population without proper sewerage facilities, increase in the number of aging
automobiles and fertilizers from the wheat and barley farms in the highlands of Lorroki are the
biggest contributors of heavy metals in the soil and water. Since heavy metals in the environment
have continued to increase there is need to determine their levels in the environment for efficient
environment management, hence the need to determine the levels of heavy metals in the soil and
water in Samburu County. The heavy metals that were analyzed included Zn, Pb, Cr, Mn and Cd.
136 water samples and 176 soil samples were collected from the agricultural, residential and
commercial areas of Kirisia and Lorroki Divisions of Samburu County. The soil samples were
digested using aqua regia while the water samples were digested using nitric acid and
hydrochloric acid. The soil and water digested samples were analyzed for heavy metals using
atomic absorption spectroscopy. The data was analyzed using ANOVA. From the results, means
of Cd, chromium, manganese, lead and zinc in wells in Kirisia in mg/l were 0.010±0.000,
0.050±0.010, 0.080±0.010, 0.130±0.080 and 0.050±0.010 mg/l respectively. While the mean
levels in dams were 0.020±0.010, 0.050±0.010, 0.050±0.010, 0.060±0.030 and 0.050±0.010
mg/l. Similarly the mean of the same metals in boreholes in Kirisia were BDL, 0.030±0.010,
0.090±0.020, 0.320±0.110 and 0.020±0.010 mg/l respectively. The mean levels of Cd, Cr, Mn,
Pb and Zn in Lorroki in wells were 0.003±0.001, 0.030±0.010, 0.040±0.010, 0.052±0.010 and
0.030±0.010 mg/l while the mean in dams were 0.004±0.001, 0.040±0.010, 0.050±0.010,
0.230±0.050 and 0.040±0.010 mg/l respectively. The mean levels of the same metals in soils in
the Kirisia and Lorroki divisions in mg/kg were 0.60±0.14, 2.65±0.30, 17.44±1.02, 55.33±5.93
and 376.35±46.64 mg/kg while the mean levels of the respective metals in the soils in Lorroki in
mg/kg were 0.570±0.13, 3.690.390, 21.91±1.82, 51.80±4.16 and 265.95±59.75 mg/kg. The mean
levels of the Pb in all the water sources were found to be above the WHO maximum
contamination level. With the exception of the level of lead in dams and wells in Kirisia and
Lorroki Divisions, there was no significant different between the levels of all the other analyzed
heavy metals in dams and wells in Kirisia and Lorroki Divisions. This study provides an
opportunity for frequent monitoring of heavy metals in this environment and hence providing an
opportunity to the stakeholders to help in curbing heavy metal pollution in Samburu County.
Though most levels of the heavy metals were within the WHO (2003) maximum recommended
contamination level, the level of lead in water was above this recommended level hence the need
to put mechanisms in place to reduce the contamination due this heavy metal.
1
CHAPTER ONE
INTRODUCTION
1.1 Background information
Pollution is a worldwide problem and its potential in influencing health of the human population
is great (Khan and Ghouri, 2011). The impact of pollution in the vicinity of overcrowded cities
and from industrial effluents and automobiles has reached a disturbing magnitude and is arousing
public awareness (Begum et al., 2009). Excessive levels of pollution are causing a lot of damage
to human and animal health, plants including tropical rain forests as well as the wider
environment (Khan and Ghouri, 2011). Pollution is the cause of many diseases, which affect not
only the old but also the young and the energetic and all animals and plants (Kanmony, 2009).
The WHO report points out that twenty million children worldwide suffer from pollution which
has become critical because of overpopulation (Kanmony, 2009; Pain, 2008). An estimated 1.2
billion people drink unclean water which is the source of water related diseases that kill between
five-ten million people mostly children around the world (Ahuja, 2009).
The natural substances which cause water pollution include, gases, soils, minerals, humus
materials, waste created by animals and other living organisms present in water. Water resources
continue to be scarce and insufficient in most areas to meet the growing demands of a rapidly
increasing population and because of this scarcity, the resources have continued to be
overexploited leading to its salinity, increased pollution and eutrophication due to intensive
agricultural practices (Al-Weher, 2008). Estimation indicates that more than fifty countries of the
2
world with an area of twenty million hectares area are treated with polluted or partially polluted
water including parts of all continents and this poor quality water causes health hazards and
death of human beings, aquatic life and also disturbs the production of different crops (Khan and
Ghouri, 2011).
The most common environmental pollutants in the world are heavy metals (Papatilippaki et al.,
2008). The presence of heavy metals at trace level and essential elements at elevated
concentration causes toxic effects if exposed to human population (Fong et al., 2008).The
knowledge of heavy metal accumulation in soils, the origin of these metals and their possible
interactions with soil properties are a priority in many environmental monitoring (Qishlaqi and
Moore, 2007). The accumulation of heavy metals in agricultural soils is of increasing concern
due to food safety issues and potential health risks as well as its detrimental effects on soil
ecosystems (Qishlaqi and Moore, 2007).
Food chain contamination by heavy metals has become a burning issue in recent years because
of their potential accumulation in biosystems through contaminated water, soil and air (Begum et
al., 2009). Heavy metals can accumulate in the soils to toxic levels as a result of long term
application of untreated waste waters and fertilizers. Soil irrigated by waste water accumulate
heavy metals in surface soils and when the capacity to retain heavy metals is reduced due to
repeated application of waste water, heavy metals leach into ground water or soil solution
available for plant uptake (Papatilippaki et al., 2008). Research findings indicate that application
3
of heavy doses of fertilizer, pollute ground water by nitrates and heavy metals through leaching
and this affects the quality of water (Mico et al., 2006).
Metal poisoning arise from heavy metals that have toxic properties leading to adverse effects on
human and ecosystem health (Voet et al., 2008). Although acute poisoning from heavy metal
poisoning is rare through ingestion or dermal contact chronic exposure to even small doses can
be disastrous (Sherameti and Varma, 2010). Chronic exposure to heavy metals leads to
accumulation in the food chain which leads to an increased stock in biota, therefore magnifying
the human dose (Voet et al., 2008). The chronic problems associated with long term heavy
metals exposure include; Serious hematological and brain damage, anaemia and kidney
malfunctioning (Sonayei et al., 2009). Heavy metals such as Pb and Cd are lethal even in very
small doses. Lead has a negative influence on the somatic development, decreases the visual
acuity and auditive thresholds (Simeonov et al., 2010). Acute exposure to lead causes brain
damage, neurogical symptoms, brain damage and could lead to death (Simeonov et al., 2010).
Cd exposure on the other hand, causes renal dysfunction, calcium metabolism disorders and also
increased incidence of some forms of cancer possibly due to the inhibition by Cd of DNA
mismatch remediation (Kumar, 2009). Malignant neoplasia and skin ulcers have been reported
due to various occupations with exposure to chromium compounds. Chromium (VI) inhalation is
responsible for bronchial asthma (Sakar, 2005). Manganese toxicity affects the central nervous
system, visual reaction time, hand steadiness and eye-hand coordination (Calkins, 2009). A
syndrome named manganism characterized by feelings of weakness and lethargy, tremors, a
masklike face and psychological disturbance. Respiratory effects have also been noted in
workers chronically exposed by inhalation. Impotence and loss of libido have also been noted in
4
male workers afflicted with manganism (Calkins, 2009). Zinc toxicity is rare, but at
concentrations in water up to 40 mg/l, may induce toxicity characterized by symptoms of
irritability, muscular stiffness and pain (Al-Weher, 2008).
In Samburu County, chemicals and agro-based wastes are the major source of pollution and this
arises from agro-chemicals and fertilizers used in the highlands of Lorroki and Kirisia Divisions
where wheat and barley is grown on large scale. Close to 6000 hectares are utilized for wheat
and barley growing in the divisions (NEMA, 2009). Pollution from small arms used in cattle
rustling and military training in the area is also evident.
1.2 Problem statement and justification
The environment has continued to suffer from pollution due to increased population and
industrialization (Goel, 2009). On the other hand resources like land have remained constant
leading to overcrowding of population around towns and main cities. The biggest challenge
resulting from this overcrowding is waste disposal. The overcrowding has led to domestic and
industrial wastes being disposed of in water bodies like rivers and dams and this has led to the
contamination of soil and the water bodies, especially from heavy metals (Lesamana, 2009).
In Samburu County, conflicts arising from cattle rustling have led to frequent use and disposal of
small fire arms. The military training in the area and the heavy use of fertilizers for wheat and
barley farming could be a source of heavy metal contamination in the soil and the waters
(Bhandari et al., 2007; NEMA, 2009). Lack of planning in Maralal town especially, has resulted
5
in overcrowding with no proper sewerage disposal system for waste and this could contribute to
heavy metal contamination of soil and water (Lesamana, 2009).
People in Samburu County rely on water from bore holes and the dams for domestic use and
farming. The absence of permanent rivers in Samburu County could have accumulative effect on
the heavy metals as rivers help carry some of the metals downstream hence reducing their
concentration. Some of the signs of heavy metal contamination among the population like mental
retardation and cancer are evident among the population (Lesamana, 2009). Samburu County is
riddled with poverty and therefore this community cannot afford to live with the effects of these
pollutants as this will be too costly for them to seek treatment. Preventive measures if taken
could be the best way to avert such expenses. Despite this, no work has been reported on the
level of heavy metals in water and soils of Samburu County. This study therefore proposes to
determine the levels of Cd, chromium, lead, zinc and manganese in soils and water from
Samburu County.
1.3 Hypothesis
The levels of heavy metals in soils and water in Kirisia and Lorroki divisions of Samburu County
are not significantly different and are below the recommended toxic levels.
6
1.4 Objectives
1.4.1 General Objective
To determine the levels of heavy metals in the soils and water in Lorroki and Kirisia Divisions
of Samburu County.
1.4.2 Specific Objectives
i.
To determine the levels of lead, chromium, Cd, zinc and manganese in wells, boreholes
and dam waters of Lorroki division and Kirisia divisions of Samburu County
ii.
To determine levels of lead, chromium, Cd, zinc and manganese in agricultural soils and
roadside soils in Lorroki and Kirisia divisions of Samburu County
1.5 Significance of the study
The determination of levels of manganese, zinc, lead, chromium and Cd in soils and water of
Samburu County will be used to sensitize the general population of Samburu County on the
importance of environmental conservation. The study will also inform the authorities in
environment management on the level of heavy metal pollution in Samburu County hence
providing a reference for future studies on the same. The results from the study will also be used
to determine the remedial action to be taken including treatment of the water to remove the
heavy metals where the levels are too high.
7
1.6 Scope and limitations
There are many heavy metals but this study considered only five metals which from literature are
prevalent in soils and water in Samburu County. The study also covered only two divisions of
Samburu County because of its expansiveness, inaccessibility and resource availability. Some
metals could be present in the underlying rocks and this could be reflected in the levels and
assumed to be from anthropogenic sources.
8
CHAPTER TWO
LITERATURE REVIEW
2.1 Introduction
Pollution includes natural as well as manmade substances or energy that may have an adverse
impact on human health or well being or on the natural or cultural heritage. Environmental
degradation due to pollution in poor countries is pervasive, accelerating and unabated (Farmer,
2002). In developed countries, a lot of resources have been used to ensure that there is cleaner
air, drinking water, sewage treatment, safe food laws and food refrigeration (Hill, 2010). It is
usually easy to see the effects of pollution on the earth and in plants and animals, but it is more
difficult to reduce the amount of pollution put into the environment (Shafi, 2005). For example it
is estimated that at least 1.6 million lives are lost each year through lack of access to sanitation
and drinking water (Farmer, 2002) and more millions of people are left chronically ill from the
water they must drink (Hill, 2010). It is important to note however that even a very small
concentration of persistent pollutants may cause irreparable damage to the ecosystem. Organisms
susceptible even to low concentration may get eliminated (Shafi, 2005). Scientific analysis is
important for those pollutants with threshold for impacts to determine the nature of the threshold
and for those without thresholds, to determine the significance at a level of “acceptable” impact
(Farmer, 2002).
The major sources of pollution include; burning fossil fuel in engines, waste disposal, accidental
spills of chemicals from factories and use of agricultural chemicals on farms (Greenaway et al.,
9
2002). There are several types of pollution including air pollution, water pollution and soil
pollution.
2.2 Soil pollution
Soil is a very important natural resource to man as it is a source of his life on this planet. Without
soil the earth would be as barren as the moon hence lifeless (Misra and Mani, 2009). Despite its
importance, soil is often contaminated by human activities and this is reflected in the high
horizontal and vertical variability brought about by the anthropogenic influence on soil formation
and development (Fong et al., 2008). A variety of human activities including municipal waste
disposal, industrial emissions, military testing and agricultural practices have left their impacts
on soils in the form of elevated and high level of toxicants (Van and Krivolutsky, 1996).
Materials that find their entry into the soil system persist and accumulate in toxic concentrations
becoming sources of pollution in the soil (Misra and Mani, 2009). The concentration of heavy
metals in soil and their impact on ecosystems can be influenced by many factors such as the
parent rock, climate and anthropogenic activities (Jia et al., 2010). Among the pollutants that
persist and accumulate in the soils include; inorganic toxic compounds for example fertilizers,
organic wastes, organic pesticides and radio cucleides (Misra and Mani, 2009; Jia et al., 2010).
The soil is thus becoming increasingly polluted with chemicals and other pollutants which can
reach the food chain, surface water or ground water and ultimately be ingested by man (Misra
and Mani, 2009).
10
2.3 Water pollution
Pollution of water still remains one of the most significant environmental problems of recent
times. Water can be regarded polluted when it gets changed in its quality or composition either
naturally or as a result of human activities so as to become less suitable for drinking, domestic,
agricultural, industrial, recreational, wildlife and other uses for which it would have been
otherwise suitable in its natural or unmodified state (Goel, 2009).
Gross pollution of water has its origin mainly in urbanization, industrialization, agriculture and
increase in human population being observed (Calhoun, 2005; Goel, 2009). In addition to toxic
chemicals, water pollutants occur in many other forms, including pathogenic microbes, excess
fertilizers and trash floating on streams, lakes and beaches. Water pollution can also take the
form of sediment eroded from stream banks, large booms of algae, low levels of dissolved
oxygen or abnormally high temperatures (Calhoun, 2005). Water pollution threatens our health
and environment and therefore we need to implement an expanding array of techniques for its
assessment, prevention and remediation (Calhoun, 2005).
2.4 Heavy metal and environmental pollution
2.4.1 Introduction
There are different types of pollution among which pollution caused by toxic level of heavy
metal pollutants is called heavy metal pollution (Bose and Hemantaranjan, 2005). Heavy metals
are elements having a density greater than 5 g/cm3 in their elemental form (Bose and
11
Hemantaranjan, 2005; Misra and Misra and Mani, 2009). Heavy metal pollution has received the
attention of researchers all over the world, mainly due to their harmful effects on living beings
(Misra and Misra and Mani, 2009).
Human biology is full of instances where heavy metal toxicity has led to mass deaths
(Shrivastav, 2001). All heavy metals are toxic to living organisms at excessive concentrations,
but some are essential for normal healthy growth and reproduction by plants at low but critical
concentrations (Bose and Hemantaranjan, 2005). The heavy metals essential in trace elements to
plants include Co, Cu, Fe, Mo and Zn and for animals are Cr, Ni and Sn. The heavy metals Cd,
Hg and Pb have not been shown to be essential for either plants or animals (Misra and Misra and
Mani, 2009).
It is important to note however that the concentrations of individual metals in living tissues must
be kept very low and should be maintained within narrow limits to permit the optimum
biological performance of most organisms (Misra and Mani, 2009). Heavy metals are nonbiodegradable and once they enter into an environment, they will stay there for a longtime (Voet
et al., 2008). Heavy metals are considered serious pollutants because of their toxicity, persistence
and nonbiodegrable conditions in the environment, thereby constituting a threat to human beings
and other forms of biological life (Adeleken and Abegunde, 2011). Heavy metals occur in
atmosphere basically in particulate form. Hence, the transfer of airborne particles to land or
water surfaces by dry, wet and occult deposition constitutes the first stage of atmospheric heavy
metals (Shrivastav, 2001).
12
Adeleken and Abegumde (2011) note that heavy metals have low environmental mobility as a
result of this, a single contamination could set a stage for a long term exposure of human,
microbial, fauna, flora and other edaphic communities to heavy metals. The problem of
atmospheric heavy metal pollution is not going to disappear overnight. On the contrary it will
remain a legacy of mass industrial activity for many generations and is likely to escalate further
in future. In this regard, the compilation of past and present catalogues of atmospheric heavy
metal concentration is an activity of great importance (Shrivastav, 2001).
2.4.2 Soil pollution from heavy metals
Heavy metal pollution in soils refers to cases where the quantities of the elements in soils are
higher than maximum allowable concentrations and this is potentially harmful to biological life
at such locations (Adeleken and Abegunde, 2011). Heavy metals occur at typical background in
all ecosystems, however, anthropogenic releases can result in higher concentrations of these
metals relative to their normal background values hence the pollution (Adeleken and Abegunde,
2011). Heavy metals released from vehicular emission can accumulate in surface soils and their
deposition over time can lead to abnormal enrichment, thus causing metal contamination of the
surface soils (Fong et al., 2008).
High concentrations usually occur in soils below or near landfills and agricultural lands that
have been irrigated with contaminated water (Mamtaz and Chowdhury, 2006). Studies have
shown that both long term and short term contamination of soils have effects on microbial
13
activity and enzyme activities of the soil (Adeleken and Abegunde, 2011). The toxicity and
mobility of heavy metals in soils depend not only on the total concentration but also on their
specific chemical form, bonding state, metal properties, environmental factors, soil properties
and organic matter content (Osu and Okoro, 2011). Exposure of children, generally accepted as
the highest risk group who have a higher adsorption rate of heavy metals because of their active
digestion system and sensitivity of haemoglobin, to heavy metals, can greatly increase ingestion
of metal laden soil particles via hand –to-mouth activities. In addition, adults may be exposed to
threat since inhalation is easier pathway for toxic metals to enter their body (Fong et al., 2008).
2.4.3 Heavy metals in water
The contamination of fresh waters with a wide range of pollutants has become a matter of great
concern over the last few decades (Al-Weher, 2008). The aquatic systems receive a large amount
of heavy metals from natural occurring deposits and natural processes and anthropogenic
activities (Wogu and Okaka, 2011). Anthropogenic sources arising from human activities such as
industrial, municipal effluents, as well as non-point source run off are the main sources of metals
in rivers (Sonayei et al., 2009).
Discharge of heavy metals into rivers or any other aquatic environment can change both aquatic
species diversity and ecosystems due to their toxicity and accumulative behaviour (Al-Weher,
2008). Heavy metals dissolved in water also endanger the lives of the public who use it for
drinking and also irrigation. When used for irrigation heavy metals have the danger of being
14
incorporated in food chain and therefore ingested by the public (Wogu and Okaka, 2011). Heavy
metals accumulate in the soils at toxic levels as a result of long term application of untreated
waste water and therefore soils irrigated by wastewater accumulate heavy metals in their soil
surface (Sonayei et al., 2009). When the capacity of the soil to retain heavy metals is reduced
due to repeated application of waste water, the metals leach into ground water or soil solution
available for uptake (Sonayei et al., 2009). Table 2.1 shows metal limits in water set by national
and international organizations.
Table 2.1 Heavy metal limits (µg/l) in water set by different national and international
organizations
Cd
Cr
Mn
Pb
Zn
USEPA
5
100
50
10
5000
EU
5
50
50
10
Nm
WHO
3
50
400
10
NGL
Iranian
10
50
500
50
Nm
Australian
2
50
500
10
3000
Indian
10
50
100
100
5000
New Zealand
4
50
400
10
1500
Nm- not mentioned
NGL – No guideline, because it occurs in drinking water at concentrations well below those at
which toxic effects may occur
Source; Mebrahtu and Zerabruk ( 2011)
15
2.5 Heavy metals and their effects
2.5.1 Lead
Lead has a negative influence on both children and adults. For children, Pb reduces the physical
growth and mental growth (Simeonov et al., 2010). The intelligent quotient of children is
diminished and symptoms of irritability and fatigue could be observed. Pregnant women exposed
to Pb have higher rates of infertility, miscarriage and still births (Ediin et al., 2000). Chronic
exposure to Pb can affect physical growth and can cause anaemia, kidney damage, headache,
hearing problems, speaking problems, fatigue or irritable mood (Simeonov et al., 2010). The
toxicity of Pb is multiple biochemical effects. It has the ability to inactivate enzymes, compete
with calcium for incorporation into bones and interfere with nerve transmission and brain
development (Ediin et al., 2000).
The WHO maximum allowed contaminant level in the water is 0.01 mg/l (Monudu and
Anyakora, 2010). The main sources of Pb in the environment include, dust from leaded paints
from older houses, leaded gasoline and tap water from soldered pipes (Ediin et al., 2000). Indoor
chemicals and indoor smoking is also a source (Simeonov et al., 2010). Mebrahtu and Zerabruk
(2011) in their study of concentration of heavy metals in drinking water from urban areas of the
Tigray Region, Northern Ethiopia using atomic absorption spectroscopy method of analysis
detected levels of Pb of 1.347 mg/l at Indasilase and a minimum of below detection limit in
drinking water samples from Alamata, Korem, Hagereselam, Zelambessa, Firewoini, Axum,
Adwa and Enticho. More than 70.15 % of the water samples analyzed contained lead
concentration within the WHO (2008) maximum allowable limit of lead in drinking water. In a
16
similar research carried out by Kaplan and Yildrimi (2011) at Tunceli in Turkey, Pb was only
detected in drinking water from one station, out of the sampled. The highest value of Pb detected
was 0.31µg/l and this was below the maximum permissible limit for lead in water. Similar results
were obtained by Wogu and Okaka (2011) in a study on heavy metals in Warri river in Nigeria.
They recorded a variation of Pb levels in water ranging from 0.0 to 0.001 mg/l which were below
the maximum WHO (2003) permissible limits of lead in drinking water of 0.01 mg/l. A similar
study by Raji et al. (2010) recorded the following Pb levels in water in the following stations;
station T1, 0.720 mg/l, station T2, 0.390 mg/l, station T3, 0.310 mg/l, station WB(R), 0.340 mg/l
and station WB(T), 0.350 mg/l.
In the soils, the maximum allowable limits of lead in UK and USA are 100 mg/kg and 200
mg/kg (Mamtaz and Chowdhury, 2006). A study carried out by Mico et al. (2006) on heavy
metal content of agricultural soils in a Mediterranean Semiarid Segura River Valley in Spain
recorded 19.6 mg/kg of Pb in the soil and a lead level range of 8.9 mg/kg-34.5 mg/kg. The soil
samples were analyzed by flame atomic absorption spectroscopy. A study by Ijeoma et al. (
2011), on heavy metal content in high traffic area soils of Pakistan, recorded a minimum lead
concentration of 10.06 mg/kg and a maximum Pb concentration of 29.71 mg/kg. A study by
Atiemo et al. (2010) recorded levels of Pb in road soils ranging from 33.640 mg/kg to 117.45
mg/kg. Similarly Jaradat and Momani (1999) recorded levels of Pb in roadside soils at different
distances from the road ranging from 3.700 mg/kg to 272.200 mg/kg.
17
2.5.2 Cd
Cd is a heavy metal characterized by high mobility in biological systems. It is emitted to the
atmosphere in combustion processes, mainly in the form of oxides (Wieczorek et al., 2004). Cd
uptake by plants is partly limited by presence of calcium, phosphorus and chelating compounds
in the soil (Wieczorek et al., 2004). The exposure of Cd and especially chronic exposure can
cause renal dysfunction, calcium metabolism disorders and also increased incidence of some
forms of cancer (Selinus and Alloway, 2005).
In plants, Cd induces oxidative stress in plant cells and inactivates some enzymes (Wieczorek et
al., 2004). Cd taken up by plants from the soil accumulates first of all in the roots, and then
transported in smaller quantities to stems and seeds (Wieczorek et al., 2004). Among the sources
of Cd in the environment include; mining and smelting of metal ores, fossil fuel combustion and
also phosphate fertilizers (Challa and kumar, 2009). Cd is also used in the production of nickelCd rechargeable batteries that become deposited in sewage sludge, thus raising environmental
levels of Cd (Challa and kumar, 2009). Farming practices such as tobacco growing also increases
the level of Cd in the environment as tobacco is known to accumulate in its tissues (Selinus and
Alloway, 2005). The sources of Cd in the urban areas are much less well defined than those of
Pb, but metal plating and tire rubber were considered the likely sources of Cd within Kirisia
Commercial area which houses Maralal town (Jaradat and Momani, 1999). Cd is also found in
lubricating oils as part of many additives and car tyres as a result of the vulcanization process. In
the absence of any major industry in the sampling sites, the levels of Cd could be due to
18
lubricating oils and/or old tires, that are frequently used, and the rough surfaces of the roads
which increase the wearing of tires (Jaradat and Momani, 1999).
At higher concentrations, it is known to have a toxic potential. The other sources of Cd are
industrial activities; the metal is widely used in electroplating, pigments, plastics, stabilizers and
battery industries (Mehbrahtu and Zerabruk, 2011). Cd is highly toxic and responsible for several
cases of poisoning through food. Small quantities of Cd cause adverse changes in the arteries of
human kidney. It replaces zinc biochemically and causes high blood pressures and kidney
damage (Mehbrahtu and Zerabruk, 2011).
The maximum contaminant level of Cd allowed in water by WHO is 0.003 mg/l (Monudu and
Anyakora, 2010).
The recommended concentration in the soils is 3 mg/l (Adeleken and
Abegunde, 2011). A study by Wogu and Okaka (2011) on Warri river water in the Delta region
of Nigeria, recorded a Cd mean level of 0.0072 mg/l in the water and a range of 0.0 to 0.04 mg/l
of Cd the water. The maximum value of Cd that was detected in the water was above the
maximum permissible level of Cd in drinking water. A similar study carried out by Singh and
Chandel (2006) on heavy metals of industrial effluents at Jaipur, Rejasthan in India, Cd was
undetected in all the samples that were tested.
A study by Kisamo (2003) on the environment hazards associated with heavy metals in Lake
Victoria Basin reported levels of Cd in soils ranging from 0.16 mg/l to 0.55 mg/l. The range
19
recorded in the above study was below the WHO maximum permissible limit of Cd set at 3 mg/l.
A similar study by Mwegoha and Kihampa (2010) on heavy metal contamination in agricultural
soils in Dar es Salaam city recorded values below detection limit in all the water samples
analyzed. Kaplan et al. (2011) recorded the following levels of Cd in the following stations;
station 1 1.27 µg/l, station II <0.05 µg/l, station III <0.05 µg/l and station IV 1.67µg/l. A similar
study by Mebrahtu and Zebrabruk (2011) recorded levels of Cd in water ranging from 14 µg/l to
21 µg/l in Makelle area with a mean of 17 µg/l.
A study by Delbari and Kulkarni (2011) recorded Cd values in agricultural soils ranging from
0.000 to 0.004 mg/l with a mean value of 0.002 mg/kg in summer season and 0,001 to 0.004
mg/kg with the mean value of 0.002 mg/kg in winter season. Similarly, Jaradat and Momani
(1999) recorded Cd levels in roadside soils ranging from 0.21 mg/kg to 0.75 mg/kg.
2.5.3 Chromium
Chromium is one of those heavy metals in the environment whose concentration is steadily
increasing due to industrial growth, especially the development of metals, chemicals and tanning
industries (Adeleken and Abegunde, 2011). The most common forms of chromium are
chromium VI and chromium III (Hilgenkamp, 2006). Chromium III is an important component
of a balanced human and animal diet and its deficiency causes disturbance to the glucose and
lipid metabolism in humans while chromium VI is carcinogenic (Chernoff, 2005). Although
chromium toxicity in the environment is rare, it still presents some risks to human health since
20
chromium can be accumulated on skin, lungs, muscle fat, in liver, dorsal spin, hair, nails and
placenta where it is traceable to various health conditions (Adeleken and Abegunde, 2011).
Among the health effects brought about by the exposure to chromium VI include lung cancer,
malignant neoplasia, chromium dermatitis and skin ulcers (Sarkar, 2005). Perforations and
ulcerations of the nasal septum and bronchial asthma have also been reported. In one of the
studies, a fourfold increase in childhood leukemia was attributed to possible consumption of
water with chromium VI levels above standard recommended value (Sarkar, 2005). The
prevalence of chromium in drinking water above 5 mg/l results in bleeding of the gastrointestinal
tract, cancer of the respiratory tract, ulcers of the skin and mucus membrane (Adeleken and
Abegunde, 2011).
The sources of chromium in the environment include, cement, leather, plastics, dyes, textiles,
paints, printing ink, cutting oils, photographic materials, detergents, wood preservatives among
others (Hilgenkamp, 2006). Other sources of chromium are water erosion of rocks, power plants,
liquid fuels, brown and hard coal and industrial and municipal wastes. Non biodegradability of
chromium is responsible for its persistence in the environment and once mixed with soil, it
undergoes transformation into various mobile forms before ending into environmental sink
(Adeleken and Abegunde, 2011).
21
The Environmental protection Agency (EPA) has set the limit for chromium in drinking water at
100 µg/l (Hilgenkamp, 2006) while maximum allowable limit of chromium in the soil set by
united kingdom is 300 mg/kg. In a study by Mebrahtu and Zerabruk (2011) in the Tigray region
of Ethiopia on heavy metals in drinking water, chromium was detected in 12 out of 16 of the
sampling areas. The mean levels of chromium detected in the 12 sampling areas ranged from
97µg/l to 146µg/l. The mean range was much higher than the WHO maximum admissible limit
of chromium in drinking water of 50 µg/l. Of all the analyzed samples, 64.18% contained
chromium above the WHO maximum admissible limit with the highest level of chromium
recorded in water samples from Makelle (mean concentration, 146µg/l). In a similar study by
Pandey et al. (2010), in river Ganja in India, chromium detected ranged from 1.2 to 29.6µg/l and
this was well below the 50 µg/l WHO maximum admissible limit. In a similar study by Wogu
and Okaka (2010) chromium levels ranging from 0.000-0.060 mg/l was recorded. Raji et al.
(2010) recorded values in drinking water ranging from 0.510-0.800 mg/l. The values were above
the WHO acceptable limit set in 2003.
A study by Adeleken and Abegunde (2011) on the levels of heavy metals contamination at
automobile mechanic villages in Ibadan, Nigeria reported levels of chromium in soil ranging
from 2.0 to 29.75 mg/l and this reported values were within the maximum allowable limit of
chromium in the soils set by United Kingdom. Similarly, a study by Delbari and Kulkarni
(2011), recorded chromium in the agricultural soils around Tehran ranging from 0.234 to 1.577
mg/kg with a mean value of 0.58 mg/kg.
22
2.5.4 Manganese
Manganese is essential for normal physiological functioning of humans and animals and
exposure to low levels of manganese in the diet is considered nutritionally essential in humans.
However chronic exposure to higher doses is detrimental to human health (Calkins, 2009). In
higher doses manganese is toxic and its toxicity varies with route of exposure, chemical species,
age, sex and animal species (EPA, 2004; Kohl and Medlar, 2007). The nervous system has been
determined to be the primary target organ with neurological effects generally observed (EPA,
2004). Syndrome called manganism may result from chronic exposure to higher levels of
manganese (EPA, 2004; Calkins, 2009). Manganism is characterized among other symptoms,
weakness, tremors, a masklike face and psychological disturbance (Calkins, 2009).
Manganese is naturally occurring in many surface and ground water sources and in soils that
erode into these waters. Human activities are also responsible for much of this manganese
contamination in water in some areas (EPA, 2004). Sources of manganese due to human
activities in the environment include; combustion of coal, residential combustion of wood, iron
and steel production plants and power plants (Calkins, 2009). The primary sources of manganese
for surface and ground water releases are industrial facility effluent discharge, landfill and soil
leaching and underground injection (EPA, 2004). Manganese in the form of potassium
permanganate may also be used in drinking water treatment to oxidize and remove iron,
manganese and other contaminants (EPA, 2004).
23
The WHO has put the maximum limit for manganese in drinking water at 0.4 mg/l (Calkins,
2009). In a study done by Mebrahtu and Zebrabruk (2011) on heavy metals in drinking water in
Tigray region of Northern Ethiopia, manganese levels varied from below detection in various
samples to 215 µg/l. None of the drinking water samples analysed, contained manganese above
WHO maximum admissible limit of 400 µg/l. Raji et al. (2010) recorded the following levels of
manganese in drinking water in Sokoto, Nigeria; station T1 0.670 mg/l, station T2 0.800 mg/l,
station T3 0.550mg/l, station WB(R) 0.550 mg/l and WB(T) 0.510 mg/l. A similar study done by
Oyugi (2000) on heavy metals in sea water along the Mombasa Coastline reported the following
levels of manganese in these stations; Nyali Bridge (166.74 mg/l), KMC Mombasa (219.99),
Vanga (1100.02 mg/l), Marine Park (648.21 mg/l).
2.5.5 Zinc
Zinc is an essential trace element for plants, animals and humans found in virtually all food and
potable water in the form of salts or organic complexes (Swaminathan et al., 2011). Although
drinking water seldom contains zinc above 0.1 mg/l, levels in tap water can be considerably
higher because of the zinc used in plumbing material (Swaminathan et al., 2011). The average
adult body contains between 2-3 g of zinc (Miculescu et al., 2011). Zinc is used to form
connective tissues like ligaments and tendons (Miculescu et al., 2011).
Zinc toxicity is rare but at concentrations of up to 40 mg/l, it may induce toxicity characterized
by symptoms of irritability, muscular stiffness and pain (Al-Weher, 2008). Some of the
24
anthropogenic sources of zinc in soil and water include, discharges of smelter slag and wastes
and the use of commercial products such as fertilizers, paints and wood preservatives containing
zinc (Lew, 2008). There is no guideline for zinc in drinking water; however, drinking water
containing zinc levels above 3 mg/l may not be acceptable to consumers. A guideline value of 3
mg/l was suggested by WHO for zinc content in drinking water (Swaminathan et al., 2011).
A study carried by Raji et al. (2010), recorded the following zinc level range in tap, well and
pure water in Sokoto, Metropolis values within the maximum acceptable WHO limit. A similar
study carried out by Reza and Singh (2010) in India on heavy metal contamination and its
indexing approach for river water, found relatively higher values of zinc of 80.1 µg/l and 75 µg/l
and was attributed to the unused remains of zinc sulphate fertilizer, however this level did not
exceed the highest permitted value for zinc in water tentatively set at 300 mg/l by WHO
(Swaminathan et al., 2011). In a similar study by Jia et al. (2010) on levels of heavy metals in
soils of Yucheng city in China, recorded levels of zinc ranging from 48.49-124.30 mg/l with a
mean level of 71.94 mg/l. A similar study by Kar et al. (2008) recorded zinc values in surface
water ranging from 0.012 to 0.370 mg/l. Similarly, a study by Papafilippaki et al. (2008)
recorded levels of zinc in river water ranging from 16 µg/l to 142 µg/l during warm season and
0.000 to 11.000 µg/l during wet season. Kisamo (2003) recorded values of zinc ranging from
0.040 to 0.080 mg/l. Okonola et al. (2007) recorded values of zinc in soils ranging from 41.66
mg/kg to 237.96 mg/kg. Similarly, a study by Yahoya et al. (2010) recorded zinc values in
roadside soils ranging from 30.2 mg/kg to 131.06 mg/kg during wet season and 73.3 mg/kg to
202.4 mg/kg during dry season.
25
2.6 Samburu County
Samburu County is situated in the northern half of Rift Valley province of Kenya. The County
lies between latitudes 0º 40’ north and 2º50’ north of equator and longitudes 36º20’ east and
38º10’ east of prime meridian (Nanyingi et al., 2008). It lies within the semi arid areas of the
country and has a total population of approximately 21,120.5 km2 (Nanyingi et al., 2008). The
county has four divisions and of the four divisions, Kirisia Division has the highest population
due to its good climate, fertile soils and many trading centres. Maralal town is the main urban
centre in this division (Lesamana, 2009). The highlands of Lorroki Divisions have a much
favourable climate sand soils and have thousands of hectares under wheat and barley farming
(Nema, 2009).The major types of wastes in Samburu is solid wastes and is more profound in
urban centres. Major sources of water pollution in the county are farm herbicides, wild life and
livestock wastes, soil erosion and human wastes (NEMA, 2009).
Maralal town, for example has no sufficient wastes disposal management. There are no
dumpsites in this town and even the villages. The increase on the consumer activity of the
population of Maralal also entails more wastes and further pressure on sanitary facilities. This,
therefore leads to environmental degradation through pollution of soil and water (Lesamana,
2009). According to NEMA (2009) the main sources of water in Samburu County are boreholes,
springs, wells, sand dams, dams, rivers. In addition to other pollutants, small arms used in cattle
rustling and other illegal activities are also known to pollute these water sources and soils in this
26
county Ruto et al., 2010). Charcoal being the main source of energy has also contributed to the
environmental degradation and pollution of the water in this county.
2.7 Methods for heavy metal analysis
Several techniques for the determination of heavy metal elements are currently in use. These
include flame atomic absorption spectroscopy, inductively coupled plasma atomic emission
spectroscopy (ICP-AES) (Sonayei et al., 2009), inductively coupled plasma –mass spectroscopy
(ICP-MS) (Nassef et al., 2006), X-ray fluorescence and neutron activation analysis (Magdaleno
et al., 2011). The AAS was used in this study because of its simplicity, reliability and sensitivity
(Sarkar, 2005). A lot of studies on heavy metals in water, soil plants and animals have used
atomic absorption spectroscopy as the method of analysis for the heavy metals. A study by
Begum et al. (2009) in the analysis of lead, iron, zinc, nickel and copper in soil and plants
employed the method for analysis. Similarly, Fong et al. (2008) in the analysis of copper, Cd,
manganese, lead and zinc in urban roadside soils used atomic absorption spectroscopy in their
analysis. Other researchers who have employed atomic absorption spectroscopy in their analysis
of heavy metals include, Mamtaz and Chowdhury (2006) who studied iron, copper, manganese
and zinc levels in urban solid waste, Awokunmi et al. (2010) in their study of Cd, cobalt,
chromium, copper, lead, manganese, nickel and zinc levels in soils from a dumpsite, Mico et al.,
(2006) employed atomic absorption spectroscopy method in analysis of Cd, cobalt, chromium,
copper, iron, manganese, nickel, lead and zinc in the agricultural soils of Segura River Valley in
Spain. Al weher (2008), analysed levels of Cd, copper and zinc in three species of fish using
atomic absorption spectroscopy method. Similarly Wieczorek et al. (2005) employed the same
27
method of analysis in determining the levels of lead in cereal grains and soils adjacent to
roadways.
2.8 Atomic spectroscopy
This technique is applicable to most gas phase elements over a wide range of concentrations and
involves detecting, measuring and analyzing radiation that is either absorbed or emitted from the
atoms or ions of the element of interest (McMahon, 2007). It involves three techniques:
Absorption, emission and fluorescence. In all the above, the sample is decomposed by intense
heat into hot gases consisting of free atoms and ions of the element of interest (McMahon, 2007).
As atoms are the simplest and purest form of matter and cannot rotate or vibrate as a molecule
does when subjected to high energy radiation, electrons within the atom undergo transitions. The
high energy radiation is commonly produced by
a. Flame in flame atomic absorption spectroscopy (FAAS)
b. Electrothermal furnace in flameless graphite furnace atomic absorption spectroscopy
(GFAAS)
c. Plasma in inductively coupled plasma-optical emission spectroscopy (ICP-OES)
d. X-ray in X-ray fluorescence spectroscopy (XRF) ((Lajunen and Paavo, 2007))
The above four belong to one of three major types of atomic spectroscopy namely absorption,
emission and fluorescence ((Lajunen and Paavo, 2007)).
28
2.9 Atomic absorption spectroscopy
2.9.1 Principle of AAS
An atom is made up of positively charged nucleus surrounded by a number of negatively charged
particles necessary to provide neutrality. These atoms occupy discrete energy levels but it is
possible for an electron to be moved from one level to another by introduction of energy. Such
transitions will only occur if the available energy is equal to the difference between the two
levels. Energy levels and the energies associated with electron transitions are unique for each
element. When light (energy) of a characteristic wavelength enters an analytical system, outer
shell electrons of corresponding atoms within the light path will be excited as energy is absorbed.
The amount of light transmitted through the system from a source to the detector will be less.
The loss of light is proportional to the number of atoms. The measurement of the radiation
transmitted (using Beer-Lambert’s law) in such a transition form the basis of AAS. BeerLambert’s law relates absorbance, a to the concentration of metallic atoms in the atom cell, c as
follows
LogT-1= a b c
Where
a is the absorptivity in grams per litre-centimetre
b is the atom width in centimeters
c is the concentration of atoms
The AAS involves the measurement of the drop in light intensity of initial radiation Io to final
radiation I depending on the concentration of the metal. Modern instruments automatically
29
convert logarithmic values into absorbance (Nollet, 2011). Figure 2.1 below illustrates AAS
instrumentation.
Figure 2.1: Diagram to illustrate instrumentation of AAS
2.9.2 Instrumentation of AAS
Any atomic absorption spectrometer consists basically of alight source which emits the sharp
line spectrum of elements to be determined, a method to produce atomic vapour of the sample to
be analyzed, a monochromator for the spectral dispersion of the source radiation, a detector
connected to an amplified read out system and a computer
30
2.9.2.1 Light source
A continous source of radiation is required. A series of sources which can give sharp emission
lines for a specific element are used. A hollow cathode glow discharge lamp is used. A hollow
cathode lamp has two electrodes; one is cup shaped and made of a specific element. The metal
used for the cathode is the same as the metal to be analyzed. The lamp is filled with noble gas at
low pressure. It will produce a glow discharge from the hollow cathode. Metal atoms are
evaporated by sputtering. The atoms accept energy of excitation and emit radiation with the lines
of the metal. Hollow cathode lamps made out of several elements are available (Khopkar, 1998).
The figure 2.3 below shows one of the light source used by AAS machine; a hollow cathode
lamp
Figure 2.2: A hollow cathode lamp
31
2.9.2.2 Atomization
Several types of atomizers are used for atomization. These include flame, electrothermal, cold
vapour technique for mercury and hydride generation (Nielsen, 2010). The flame atomizers
consist of a nebulizer and a burner. The nebulizer is designed to convert the solution into a fine
mist or aerosol. In flame atomization, atomization is carried out by flame. Heat energy is utilized
to convert the metallic element to atomic dissociated vapour. The temperature should be
controlled very carefully to convert it to atomic vapour. At too high or too low temperatures,
atoms will be ionized and they will not be absorbed.
In atomization, fuel and oxidant gases are fed into a mixing chamber which passes through
baffles to the burner head. A flame is produced and the sample is aspirated through the air into
the mixing chamber. Only droplets of a small size pass through the baffles to the burner head. A
narrow burner is therefore preferred and careful readjustment of the gas (Khopkar, 1998;
Nielsen, 2010).
In electrothermal atomization, electrothermal atomizers are used. Electrothermal atomizers are
typically cylindrical graphite tubes connected to an electric power supply. The sample is
introduced into the tube through a small hole using a microlitre syringe. The system is flushed
with an inert gas to prevent the tube from burning and exclude air from the sample compartment.
The tube is heated electrically to evaporate the solvent, the sample is then ashed and further
heated to quickly vapourized and atomize the sample (Nielsen, 2010). Cold vapour technique of
32
atomization works for mercury only. In this technique, mercury compounds in a sample are
reduced to elemental mercury by the action of stannous chloride, a strong reducing agent. The
elemental mercury is then carried in a stream of air or argon into an absorption cell where
absorption takes place (Nielsen, 2010). In hydride generation technique of atomization, volatile
hydrides of elements are formed by reacting samples with sodium borohydride. The hydrides are
carried into an absorption cell and heated to decompose them into free atoms. The atomic
absorption measurements are then carried out (Nielsen, 2010).
2.9.2.3 A monochromator
A monochromator produces monochromatic light by removing unwanted wavelengths from the
source light beam. It isolates a single atomic resonance line from the spectrum of lines emitted
by hollow cathode lamp. Essentially it is an adjustable filter that selects a specific, narrow region
of spectrum for transmission to the detector and excludes all wavelengths outside this region.
A monochromator comprises an entrance slit, a dispersion device and an exit slit.
i.
The entrance slit selects a defined beam of light from the source
ii.
The dispersion device causes the different wavelength of light in the source beam to be
dispersed at different angles
iii.
The exit slit enables selection of a particular wavelength to produce the required
monochromatic light
Figure 2.3 below shows a model of a monochromator used by an AAS machine
33
Figure 2.3: A model of a monochromator
There are two types of monochromators; prism and grating systems. Prisms and grating systems
separate various wavelengths of light in different fashions. Prisms refract light at the interface of
two surfaces with differing refraction indexes creating angular dispersion. Prisms have
limitations, their resolution is significantly lower than a grating system and their separation
technique is non-linear which creates mechanical problems with focusing a specific wavelength
on the exit slit.
Diffraction gratings are materials with a large number of parallel and closely spaced slits or
ridges. Diffraction causes constructive interference at unique points for each wavelength. The
separated wavelengths are collimated with a concave mirror towards the exit slit. The tilt angle
34
of the grating device determines the band of wavelength exiting the monochromator and
reaching the detector.
2.9.2.4 The detector
Two detectors are used in atomic absorption spectrometers; photomultiplier tubes and solid state
detectors (Nielsen, 2010). Detectors convert the radiant energy reaching it into an electrical
signal. The signal is processed to produce either an analogue or digital read out. Modern
instruments are interfaced with computers for data collection, manipulation and storage. The
photomultiplier tubes are the most common types of detectors used.
35
CHAPTER THREE
MATERIALS AND METHODS
3.1 Research design
Purposive nonprobability sampling design was used in this study where the cases best
contributing to the information needs of the study were selected. Two divisions of Samburu
County were selected, Lorroki division representing large scale wheat and barley farming and
Kirisia division representing heavy human activities such as construction, wrong disposal of
sewerage and locomotives.
3.2 Study Area
The Figure 3.1 shows a map of Samburu County showing the areas of study, Kirisia and Lorroki
divisions of the county. Samburu County, falls within latitudes 0° 40” and 2° 50” north and 36°
20” and latitudes 38° 10” East of Prime Meridian (Nanyingi et al., 2008). Kirisia division has a
relatively higher population since it houses Maralal town which is the County headquarter.
Lorroki division on the other hand is a very rich agricultural area with more than 6,000 hectares
under wheat and barley plantations (NEMA, 2009). Livestock farming is also practised in the
two divisions. Heavy use of fertilizers and acaricides is therefore evident in the two divisions.
The two divisions also have the highest number of aging auto mobiles plying its roads which
contribute greatly to the sources of heavy metals in the environment. Kirisia division hosts
Maralal town which is the county headquarters and the key source of contamination in Kirisia
Division. Maralal town is poorly planned with very poor sewerage system and sewerage facilities
36
especially around the slum areas of Loikas and this contributes to heavy metal pollution
especially in water (Lesamana, 2009).
Figure 3.1: Map of Samburu County
Source: Nanyingi et al. (2008)
37
3.3 Chemicals reagents
Chemicals and reagents used were of analytical grade. They included; nitric acid, hydrochloric
acid, distilled water, hydrogen peroxide, lead nitrate, zinc nitrate, Chromium oxide, manganese
powder, ammonium chloride and Cd nitrate. The chemicals were purchased from Lemah
Laboratories in Nairobi which buys its chemicals from Sigma Laboratories in the United States
of America.
3.4 Cleaning of glassware
All apparatus were initially washed with detergents then soaked in 2 M nitric acid for 24 hours
then washed thoroughly. They were rinsed with aqua regia, followed by tap water and then
rinsed in distilled water. The glassware was then dried in a hot oven at 1050C.
3.5 Sampling
3.5.1 Soil sampling
Sampling sites were chosen in line with anthropogenic sources of heavy metals. At each
sampling point, approximately 0.5 kg of soil was collected 0-10 cm in depth using a stainless
steel sampler. Soil samples along the roads were collected at a distance of one metre away from
the road and within an area of one square metre. Three samples were collected from each point,
thoroughly mixed in a clean plastic container to obtain a representative sample dried, crushed
and sieved with 2 mm mesh before being stored in labeled polythene bags prior to the analysis.
38
The soil samples were labeled according to the regions from which they were obtained. Plate 3.1
and 3.2 show some of soil sampling sites
Plate 3.1: Soil sampling site from a maize farm in Lorroki
39
Plate 3.2: Soil sampling from wheat farm in Lorroki
3.5.2 Water sampling and pre-treatment
Water from bore holes was pumped for 2 minutes before obtaining a 500 ml sample for analysis.
Water from the dams was sampled 10-15 cm below the water surface using labeled acid washed
plastic containers to avoid unpredictable changes in characteristic as per standard procedures
(Reza and Singh, 2010). The water was labeled according to the source from which it was
obtained and also the region from which it was obtained. The water was acidified with 2 ml of
analytical grade nitric acid in order to preserve metals and avoid precipitation (Kar et al., 2008).
The water samples were stored at a 5ºC temperature awaiting the transportation to the laboratory
for analysis. The pictures in the plates 3.3 and 3.4 show some of the water sampling sites.
40
Plate 3.3: Water sampling site, Porro dam
Plate 3.4: Water sampling site, ragae
41
3.6 Sample digestion
3.6.1 Water digestion
The water sample bottles were shaken thoroughly in their plastic containers by use of hand. A
volume of 100 ml of the sample was measured using a 100 ml volumetric flask and put in a
conical flask and 5 ml of concentrated nitric acid was then added. The mixture was heated slowly
on a hot plate and evaporated to about 20 ml ensuring that the water did not boil. A further 5 ml
of concentrated nitric acid was added and the beaker was covered with a watch glass while
heating continued. Nitric acid continued to be added until the solution appeared light coloured
and clear. Lastly, 2 ml of concentrated hydrochloric acid was added and heated slightly to
dissolve any remaining residue. Few drops of hydrogen peroxide were then added to ensure
complete digestion had take place. The solution was filtered and the filtrate was transferred to a
100 ml volumetric flask to cool and the filtrate was made up to the mark with distilled water
(Radojovenic and Bashkin, 2006).
3.6.2 Soil digestion
Well mixed samples of 1 g each were weighed using a scientech Zeta series electronic balance
manufactured in the year 2000. The samples were put into 250 ml glass beaker and digested with
24 ml of aqua regia and then evaporated to near dryness. The soil samples were then dissolved in
10 ml of 2% nitric acid, filtered and then diluted to 100 ml with distilled water (Begum et al.,
2009).
42
3.7 Preparation of stock solutions and standards
3.7.1 Lead stock solution and standards
Lead stock solution (1000 mg/l) was prepared by dissolving 1.59 g of lead (ii) nitrate in 500 ml
of distilled water and then made up to 1 litre of solution using distilled water. Through serial
dilutions, standard working solutions of lead of 1, 2, 3, 4 and 5 mg/l were made which were used
to generate a calibration curve for lead.
3.7.2 Zinc stock solution and standards
Zinc stock solution (100 mg/l) was prepared by dissolving 0.289 g of zinc nitrate salt in 300 ml
of distilled water and then made up to 1 litre of solution using distilled water. A working zinc
standard solution (20 mg/l) was made by diluting 20 ml of the stock solution to 100 ml of
solution. The calibration graph was made using solutions with the following concentrations; 0.5,
1, 1.5, 2, and 2.5 mg/l of zinc.
3.7.3 Manganese stock solution and standards
Manganese stock solution (100 mg/l) was prepared by dissolving 0.10 g of manganese metal
powder in 10 ml of concentrated hydrochloric acid mixed with 1 ml of concentrated nitric acid.
A 10 ml of nitric acid was then added and the solution finally diluted to 1000 ml with distilled
water. A working manganese standard solution (20 mg/l) was made by diluting 20 ml of the
43
stock solution to 100 ml of solution using distilled water. The calibration graph was made using
solutions with the following concentrations; 0.5, 1, 1.5, 2 and 2.5 mg/l of manganese.
3.7.4 Cd stock solution and standards
Cd stock solution (1000 mg/l) was prepared by dissolving 0.275 g of Cd nitrate salt in 500 ml of
distilled water and made up to 1 litre of solution using distilled water. A working Cd standard
solution (10 mg/l) was made by diluting 10 ml of the stock solution to 100 ml of solution with
distilled water. The calibration graph was made using solutions with the following
concentrations; 0.2, 0.4, 0.6, 0.8, and 1.0 mg/l of Cd.
3.7.5 Chromium stock solution and standards
Chromium stock solution (1000 mg/l) was prepared by dissolving 0.38 g of CrO3 in a solution of
20 ml water and 4 ml of concentrated nitric acid and diluted to 200 ml using distilled water.
Through serial dilution, standard working solutions of chromium were made. The calibration
graph was made using solutions with concentrations of 1, 2, 3, 4 and 5 mg/l.
3.8 Method Validation
The digestion method and atomic absorption spectroscopy analysis were validated by recovery
method. One gram of randomly selected soil powder was spiked with three different
concentrations of heavy metals one at a time (1.0, 1.5, 2.0 ppm) each run in with the AAS
44
machine. This was followed by the digestion of the spiked samples and determination of metal
concentration using AAS. Blank or unspiked samples were digested through the same process
and analyzed by same AAS. The amount that was recovered after digestion of the spiked samples
was used to calculate % recovery (Al-weher, 2008). A mean recovery of the matrix was
evaluated at 95% confidence level (Borosova et al., 2002).
3.9 Sample analysis
Buck scientific (210 VGF) flame atomic absorption spectrophotometer machine was used in this
analysis. Its parameters were set according to the specifications given in the manufactures
manual including lamp current and fuel system of air/acetylene flame. The AAS machine had a
picking meter that indicated when the optimum conditions had been realized. Its optimization
was automatic. The Table 3.1 below shows elements and their wavelength of analysis in air
acetylene flame.
45
Table 3.1: Elements and their conditions of analysis.
Element analyzed
Wavelength of analysis (nm)
Zinc
213.8
Chromium
357.9
Manganese
278.5
Lead
283.3
Cd
228.8
3.10 Data analysis
The data derived from various determinations was subjected to statistical analysis including
mean, Pearson Correlation, t-test and ANOVA. The means for the levels in water and soil in the
two divisions were determined. Using ANOVA and t-test, the means were compared to
determine whether they were significantly different. Pearson correlation was used to relate the
levels of heavy metals in water and soil.
46
CHAPTER FOUR
RESULTS AND DISCUSSION
4.1 Introduction
In this chapter the levels of heavy metals in water and soil from two divisions of Samburu
County are reported and discussed. The results of the analysis are presented and discussed in the
following subsections
4.2 Method validation
The analytical performance of the method of analysis was done using recovery test on some
samples to be analyzed. In all the calculations of percentage recovery cases, the method
produced a percentage recovery of between 95%-102% as shown in Table 4.1 hence making the
method reliable for this analysis (Magdaleno et al., 2011). The detection limits were also
calculated. Ten blank samples were run in the machine for each element that was being analyzed.
Their absorbancies were read. The mean of each ten blanks was calculated and hence the
detection limits determined for each element
47
Table 4.1: Calibration curves correlations, detection limits and %recovery
Element
Detection limit Detection limits Correlation
(mg/l)
(mg/l)
variance
% Recovery
(Current study)
(Theoretical)
Pb
0.011
0.010
0.999
98.000-99.300%
Mn
0.028
0.003
0.999
97.600-98.000%
Zn
0.003
0.0026
0.999
96.600-99.100%
Cr
0.031
0.003
0.996
96.700-101.000%
Cd
0.003
0.003
0.993
97.300-102.000%
The standards were also run in the machine before real analysis of each element and after the
analysis of the same element. Calibration curves were then drawn for all the elements to be
analyzed. Regression equations were then determined for every calibration curve. In all the cases
regression was found to be above 0.99. The regression and regression equations are shown in the
Table 4.1.
The detection limit was calculated by calculating the mean of the results of ten blank samples
inclusive of the outliers plus three times the standard deviation of the blanks (Reeuwijk, 1998).
The theoretical detection limits compare well with the detection limit of the machine used for
this analysis (Cantle, 1998). The calibration curves were drawn from standards prepared within
the linear range of the machine for each particular element. From the correlation variance, the
graphs were within the accepted linear range of above 0.99.
48
4.3 Heavy metals in surface and ground water
4.3.1 Kirisia and Lorroki Divisions
Table 4.2 presents the mean levels of Zn, Cd, Mn, Pb and Cr in wells, dams, and bore holes
water from Kirisia and Lorroki Divisions analyzed using the AAS
Table 4.2: Levels of heavy metals in wells, dams and boreholes in Kirisia and Lorroki
Divisions
Paramet
er
Wells n=24
mean±SE
(mg/l)
(Kirisia)
Cd
0.010±0.000 0.003±0.001
Cr
0.050±0.010
Mn
Wells
(n=24)
mean±SD
(mg/l)
(Lorroki)
Dams n=15
mean±SE
(mg/l)
(Kirisia)
Dams (n=48)
(mean±SD)
(mg/l)
(Lorroki)
Boreholes
n=15
mean±SE(m
g/l) (Kirisia)
MAL
(WHO
2003)
mg/l
0.004±0.001 BDL
0.003
0.030±0.010 0.050±0.010
0.040±0.010 0.030±0.010
0.050
0.080±0.010
0.040±0.010 0.050±0.010
0.050±0.010 0.090±0.020
0.400
Pb
0.130±0.080
0.052±0.010 0.060±0.030
0.230±0.050 0.320±0.110
0.010
Zn
0.050±0.010
0.030±0.010 0.050±0.010
0.040±0.010 0.020±0.010
3.000
0.02±0.010
Mean± Standard error
The mean concentration of Cd in wells in Kirisia was 0.010±0.000 mg/l while in dams was
0.020±0.010 mg/l. Cd was not detected in borehole water in Kirisia. The levels of Cd was
highest in dams followed by wells in the same region. The level of Cd detected in the water
samples from wells and dams was above the maximum allowed limit of WHO in Table 4.2. One
way ANOVA (p=0.05) revealed no significant difference between the mean level of Cd in
49
borehole water, well water and dam water withi Kirisia Division (p=0.077). The levels of Cd
obtained in well and dam water in Kirisia were similar to levels obtained in studies from other
regions. Kaplan et al. (2011) recorded values in drinking water ranging from 0.050 to 1.670 µg/l.
A similar study by Mebrahtu and Zerabruk. (2011) recorded values of Cd in drinking water
ranging from 2.000 to 10.000 µg/l in the Tigray region of Northern Ethiopia. Samuding et al.
(2009) recorded the highest value of Cd in ground water as 13.100 µg/l . Cd occurs mostly in
association with zinc and gets into water from corrosion of zinc coated (“galvanized”) pipes and
fittings (Mehbrahtu and Zerabruk, 2011).The levels of Cd recorded in the studies by Mebrahtu
and Zerabruk., (2011) and Samuding et al. (2009) were similar to the levels of Cd recorded in
this study.
The mean of Cd in wells in Lorroki was 0.003±0.001 mg/l and that in dams was 0.004±0.001
mg/l. These values were on the limit of the maximum allowed limit of WHO (2003) of 0.003
mg/l. Statistical analysis using ANOVA at 95% confidence level, revealed no significant
difference in the levels of Cd in the wells and dams in Lorroki Division (p=0.801). Comparison
in the levels of heavy metals in dams and wells in Kirisia and Lorroki is as revealed in the Tables
4.3.
50
Table 4.3 Levels of heavy metals in dams and wells in Lorroki and Kirisia Divisions
Parameter
Source
Kirisia (mg/l)
Lorroki (mg/l)
P-value
Cd
Wells
0.010±0.000
0.003±0.001
0.189
Dams
0.020±0.010
0. 004±0.001
0.151
Wells
0.050±0.010
0.030±0.010
0.323
Dams
0.050±0.010
0.040±0.010
0.619
Wells
0.080±0.010
0.040±0.010
0.051
Dams
0.050±0.010
0.050±0.010
0.999
Wells
0.130±0.080
0.052±0.010
0.391
Dams
0.060±0.030
0.230±0.050
0.038
Wells
0.050±0.010
0.030±0.010
0.323
Dams
0.050±0.010
0.040±0.010
0.618
Cr
Mn
Pb
Zn
51
Figure 4.1 compares the levels of Cd in the wells and dams in Lorroki and Kirisia divisions
Figure 4.1: Levels of Cd in water in Kirisia and Lorroki Divisions.
The mean levels of Cd in water in Kirisia Division were higher than the levels in Lorroki
Division. The dams in Kirisia had the highest levels of Cd followed by the wells from the same
division. Wells in Kirisia Division had higher levels of Cd than wells in Lorroki though the
levels were not significantly different (P=0.189). The mean level of Cd in borehole water in
Kirisia Division was the Lowest. The high levels of Cd in water from Kirisia division compared
52
to Lorroki results from sewage sludge from various sources including human excretion, domestic
produce and storm water containing particles of rubber tyres (Selinus and alloway, (2005)
produced within Maralal town. This area also has poor sanitary facilities and very few public
toilets coupled with an underdeveloped sewerage system (Lesamana, 2009). The surface runoff
when it rains propels these wastes into the water bodies hence elevating the levels of this heavy
metal in the water.
The mean level of Cr in Kirisia Division in wells was 0.050±0.010 mg/l in dams 0.050±0.010
mg/l and in boreholes 0.030±0.010 mg/l against the maximum allowed limit of 0.050 mg/l.
Comparably these values were lower than the WHO (2003) maximum allowed limits of Cr in
water. The levels of Cr were high in wells and dams compared to the levels in boreholes. There
was no significant difference between the levels of Cr in boreholes, wells and dams in Kirisia
Division (P=0.238) meaning that the levels of Cr in water in Kirisia Division was independent of
its source. However, the levels of Cr obtained in water from the division was lower than those
obtained in other regions with similar climatic conditions (Abulude et al., 2007; Raji et al.,
2010). A study done to determine the levels of heavy metals in the Tigris region of Northern
Ethiopia recorded the following mean levels; Alamata 0.11 mg/l, Mekelle 0.146 mg/l, Wekro
0.116 mg/l (Mebrahtu and Zebrabruk, 2011). These levels were higher than the levels recorded
in this study.
The mean levels of Cr in Lorroki division in wells and dams were 0.003±0.01 mg/l and
0.004±0.01 mg/l respectively. The levels differed slightly with the mean level of dams being
53
slightly more. These values were lower than the WHO maximum allowed limit of 0.05 mg/l for
Cr. ANOVA revealed that there was no significant difference between the mean levels of Cr in
well water and dam water within Lorroki Division (P=0.674). Lower levels of Cr were obtained
in a study by Wogu and Okaka (2011) in a study on surface water of Warri River, Nigeria where
Cr levels ranging from 0.0 mg/l-0.06 mg/l recorded. The levels of Cr in water in Lorroki and
Kirisia Divisions revealed the pattern shown in the Figure 4.2.
Figure 4.2: Levels of Cr in water in Kirisia and Lorroki Division
The levels of Cr in water in Kirisia were non significantly higher than the levels in Lorroki
Division. There was also a non significant variation in the levels of Cr in dam and borehole water
in Kirisia and Lorroki Division. The level of Cr in the borehole water was the lowest as
compared to the other sources of water. The levels of Cr in wells in Kirisia was nonsignificantly
54
higher than the levels in wells in Lorroki Division (P=0.323). Similarly the levels of Cr in dams
was nonsignificantly higher than the levels of Cr in dams in Lorroki (P=0.619). Sources of Cr in
water include; cement, dyes, paints, printing ink, cutting oils, detergents, wood preservatives
among others (Hilgenkamp, 2006). These sources are more common in Kirisia division which
generally has a high population and houses Maralal town hence the high levels of Cr in water
sources from Kirisia division. Excess of pesticides and fertilizers which are not used by plants
will percolate into the soil with the irrigation water. Consequently, they can reach the
groundwater wherever the permeability of the soil permits. Wrong farming activities such as uses
of large amounts of phosphate fertilizers in agriculture and many types of pesticides may also led
to the relatively high concentrations of Cr in water (Mandour and Azab, 2011). Other sources
include plastics and batteries use and disposal may also be considered additional reason for high
concentrations of Cr in water (Mandour and Azab, 2011).
Manganese mean levels in wells in Kirisia Division was 0.08±0.01 mg/l, 0.05±0.01mg/l in dams
and 0.09±0.02 mg/l in boreholes. Borehole water had the highest level of manganese while the
dams had the lowest level within the division. ANOVA revealed no significant difference
between the mean levels of manganese in well water, dam water and borehole water in Kirisia
division (P=0.130). The levels of manganese in dams, boreholes and wells were therefore
independent of the source. The levels of manganese in this study were lower than levels obtained
by Raji et al. (2010) and Wogu and Okaka (2011) but similar to a study done by Mebrahtu and
Zerabruk, 2011. Raji et al. (2010) in their study recorded a manganese range of 0.510-0.800 mg/l
in tap water, 0.510-1.200 mg/l in well water and 0.510-0.720 mg/l in pure sachet water. The
valuesof manganese obtained in thiss study were greater that the maximum recommended
55
contamination level of 0.400 mg/l. Similarly in their study, Wogu and Okaka (2011) recorded
values of manganese in river water ranging from 0.020-0.680 mg/l.
Mn mean levels in wells and dams in Lorroki Division were the second highest after lead levels.
Mn mean levels in wells were 0.040±0.010 mg/l while those of dams were 0.050±0.010mg/l.
Dams recorded a higher mean of Mn than wells within Lorroki division. Statistical analysis using
ANOVA revealed that there was no significant difference between the mean levels of Mn in the
wells and dams within the Division (P=0.478). A study done by Mebrahtu and Zebrabruk, 2011
on concentration of heavy metals in drinking water from urban areas of the Tigray Region,
Northern Ethiopia using atomic absorption spectrophotometry revealed levels ranging from
BDL-0.2 mg/l which were similar to the levels in this study. Figure 4.3 compares the levels of
Mn in the water in Lorroki and Kirisia division
56
Figure 4.3: Levels of Mn in Different sources of water in Lorroki and Kirisia
The mean level of Mn in borehole water in Kirisia division was the highest followed by the well
water and the dam water. The level of Mn in well water in this division was higher than that in
wells in Lorroki though the difference was not significant (P=0.051). Similarly the levels of this
element in dams in Kirisia were nonsignificantly higher than those in dam water in Lorroki
(P=0.999). In general the levels of Mn were higher in Kirisia Division than Lorroki Division.
The levels of Mn were also higher in ground water than in surface water because ground waters
contain Mn naturally derived from rock water interaction. Mn is also likely to be present in
ground water because ground water contains low dissolved oxygen. The reduced forms of Mn
which are promoted by low oxygen present in ground water are more soluble than oxidized
57
forms (Nath and Langdon, 2010). In addition Mn is consequently associated with slow moving
water a characteristic of ground water (Nath and Langdon, 2010).
The high mean levels of Mn in water sources in Kirisia division could be attributed to the
presence of Maralal Town within the division. The urban population heavily relies on charcoal as
the major source of fuel. There is no sufficient waste disposal management in Maralal town and
no dumpsites. Plastic bags and batteries are found everywhere within the town (Lesamana,
2009). Charcoal burning and wastes especially from batteries are known to be a major source of
Mn.
The mean of level of Pb in Kirisia division in wells was 0.13±0.08 mg/l, in dams 0.06±0.03 mg/l
and in boreholes 0.32±0.11 mg/l. These values were however, above the maximum allowed
limits of WHO of 0.01 mg/l of Pb levels in water. Borehole water had the highest levels of Pb in
Kirisia Division while dam water had the lowest. One way ANOVA revealed no siginificant
difference in the level of Pb in the dam, borehole and well water in Kirisia Division (P=0.151).
The levels of Pb in water in Kirisia division was thefore independent of its source. The levels of
Pb in water in Kirisia Division is particularly high due to the many sources of Pb within the
division. The sources of Pb in this division include; sewage, old houses which were painted with
Pbed paints, old automobiles and fertilizers. During rainy seasons the surface runoffs due to poor
vegetation in this region carries residues from the above mentioned source hence the to dams,
wells and sometimes boreholes hence the elevated levels.
58
Pb is the most significant of all the heavy metals because it is toxic, very common and harmful
even in small amounts (Mebrahtu and Zerabruk, 2011). Pb enters the human body in many ways.
It can be inhaled in dust from Pb paints, or waste gases from Pbed gasoline. It is found in trace
amounts in various foods, notably in fish, which are heavily subjected to industrial pollution.
Some old homes may have Pb water pipes, which can then contaminate drinking water. Most of
the Pb we take is removed from our bodies in urine; however, as exposure to Pb is cumulative
over time, there is still risk of buildup, particularly in children. Studies on Pb are numerous
because of its hazardous effects. High concentration of Pb in the body can cause death or
permanent damage to the central nervous system, the brain, and kidneys (Mebrahtu and
Zerabruk, 2011).
Lorroki division in the region sampled for analysis did not have boreholes. This region receives
enough rainfall and therefore the population relies on dams and wells for their water needs. The
mean of Pb in wells was 0.052±0.1 mg/l and in dams was 0.050±0.01mg/l. The mean level of
lead in dam water in Lorroki division was significantly higher than the mean level in well water.
Statistical analysis using ANOVA revealed a significant difference between the mean levels of
lead in dams and wells in Lorroki Division (P=0.023). A study done by Raji et al. ( 2010)
recorded mean values of lead in drinking water ranging from 0.30-0.39 mg/l and 0.3-0.54 mg/l in
wells water. Figure 4.4 shows how the mean levels of lead in wells, dams and boreholes compare
in Lorroki and Kirisia Divisions
59
Figure 4.4: levels of Lead in three water sources in Kirisia and Lorroki Divisions
The mean level of Pb in boreholes in Kirisia division was the highest in comparison to the dams
and wells in both Kirisia and Lorroki. The wells from Kirisia division had the lowest mean levels
of Pb. The wells in Kirisia had nonsignificantly higher levels of Pb than the wells in Lorroki
(P=0.391). On the contrary, the dams in Lorroki had significantly higher levels of Pb than the
wells in Kirisia (P=0.038). High levels of Pb in wells and dams in Lorroki division could be
attributed to heavy use of fertilizers, fungicides and pesticides on large scale barley and wheat
farms within the division. Lorroki division has over 6000 hectares of land under wheat and
barley (NEMA, 2009). During heavy down pour, Pb which dissolves in water is washed down
into the wells and dams and since most of them don’t have outlets, the levels accumulate leading
to increased levels. Conflict resulting from cattle rustling and land leads to the use of small arms
60
in this division as a common practice. This has also been found to be the biggest contributor of
Pb in soils and water (Pkalya et al., 2003; Bhandari et al., 2007). Kirisia division equally has
high levels of Pb in borehole water and dam water. This division is generally drier compared to
Lorroki division hence few agricultural activities take place. However, Kirisia division houses
Maralal town which is the county headquarters of Samburu County. It, therefore, has a higher
population compared to Lorroki Division, intensive housing facilities and more automobiles
compared to Lorroki Division. Due to this high population, Maralal town has a problem of waste
disposal. The town has a poor sewerage system and during rainy season most of this sewage ends
up in water sources (Lesamana, 2009). This also contributes to the levels of Pb in water in
Kirisia Division
The mean levels of Zn in Kirisia division in well, dam and borehole water were 0.05±0.01mg/l,
0.05±0.01 mg/l and 0.02±0.01 mg/l respectively. Statistical analysis using ANOVA at 95%
confidence level revealed no significant difference between the mean of zinc in dam, borehole
and dam water in Kirisia division (P=0.207). The levels of zinc obtained in this study were
similar to the levels obtained in studies in other regions (Kar et al., 2008; Papafilippaki et al.,
2008).
The mean levels of zinc in wells and dams in Lorroki Division were 0.03±0.01mg/l and
0.04±0.01mg/l respectively. ANOVA analysis revealed nonsignificant difference between the Zn
levels in wells and dams in Lorroki Division (P=0.688). Kisamo (2003) in his study on
environmental hazards associated with heavy metals in Lake Victoria Basin (East Africa),
61
Tanzania recorded similar levels of zinc in water. Kisamo recorded values of Zn ranging from
0.04-0.08 mg/l. Figure 4.5 shows how the mean values of Zn compare in different water sources
from Lorroki and Kirisia Divisions.
Figure 4.5: Levels of zinc in different water sources in Kirisia and Lorroki Divisions.
The mean levels of Zn in water in Kirisia Division were non significantly higher than the levels
observed in Lorroki Division. The wells and dams in Kirisia had higher levels of Zn than the
62
wells and dams in Lorroki Division. The higher values of Zn in wells and dams in Kirisia were
however not significantly different (wells P=0.323 and dams P=0.618).The high levels of Zn
observed in wells and dams in Kirisia division could be attributed to the high number of
anthropogenic sources of Zn within Kirisia division including paints from old houses within
Maralal town, wood preservatives, soaps and shampoos used by high population within Maralal
town (Lew, 2008). The levels in Lorroki are attributed to the fertilizers used in wheat and barley
farms in Porro Area of Lorroki Division. The Table 4.4 shows how the levels of the heavy metals
in this study compare with some standard guideline values of drinking water.
Table 4.4: Heavy metal concentration (mg/l), mean and range values, compared with some
standard guideline values of drinking water
Guidelines
Cd
Cr
Pb
Mn
Zn
Mean of
current
study
0.01
0.04
0.17
0.06
0.04
0.005
Standard
Organization
of
Nigeria
(2007)
0.05
0.01
0.20
-
WHO (2003)
0.003
0.05
0.01
0.04
3
EPA (2002)
0.003
0.05
0.05
0.02
-
Nd- not detected
Source: Wogu and Okaka ( 2011)
63
The concentration values of some of the heavy metals compared with standard guideline values
for drinking water are shown in Table 4.4. The result obtained in this study showed that lead and
Mn levels were greater than recommended values by the Environmental Protection Agency
(EPA) (2002), World Health Organization and Standard Organization of Nigeria (SON) (2007).
The concentration levels of these metals would markedly impair the portability of the water.
4.4 Heavy metals in agricultural and roadside soil
4.4.1 Levels in individual regions
The Table 4.5 below shows the mean levels of the elements obtained in the four regions of
Kirisia and Lorroki divisions.
Table 4.5: Heavy metals in different sub regions of Lorroki and Kirisia divisions of
Samburu County in mg/kg
Parameter Maralal
Loikas Village
Lorroki crop
Lorroki Livestock pTown(n=60)
Areas(n=30)
growing
Area(n=24)
value
Mean±SE
Mean± SE
area(n=60)
Mean± SE
Mean± SE
0.530±0.150
0.760±0.280
0.620±0.170
0.450±0.160
0.792
Cd
Cr
3.250±0.41b
1.460±0.270 a
3.480±0.480b
4.210±0.640b
0.008
Mn
19.480±1.220a
13.370±1.620 a
19.950±2.140a
26.830±3.290b
0.004
Pb
67.500±7.760b
31.000±6.930a
54.660±4.410ab
44.650±9.530 ab
0.005
Zn
403.300±44.340 322.440±108.990 305.990±83.030 165.990±16.820
0.260
Mean ±SE values followed by same letters within the same row are not significantly different (
p-value 0.05, SNK test)
64
The mean level of Cd in the soil within the four selected sub regions, ranged from 0.450-0.760
mg/kg. Loikas village area had the highest Cd mean of 0.760 mg/kg in the soil followed by
Lorroki crop growing area with a mean of 0.620 mg/kg. Lorroki livestock area had the lowest
mean of 0.450±0.160 mg/kg. Cd exhibited lower levels of contamination than those of other
metals in this study.
ANOVA indicated no significant difference between levels of Cd in soils from Maralal Town,
Loikas villaage, Lorroki crop growing area and Lorroki livestock area (P=0.792). A study by
Mico et al. (2006) on heavy metal content of agricultural soils recorded similar levels of Cd in
the soil ranging from 0.150-0.880 mg/kg. The recommended range of Cd in the soil is 0.070 –
1.100 mg/kg (Mico et al., 2006). Concentration above 0.500 mg/kg reflects the influence of
human activity (Mico et al., 2006). Figure 4.6 shows how the percentage levels of Cd from the
four sub regions within the two divisions compare.
Figure 4.6: Percentage Mean Cd levels in soils
65
Human activity can contribute to increased Cd levels as a result of urban-industrial activity
and/or agricultural practices (Mico et al., 2006). In Lorroki Division, fertilizers used to increase
productivity could be the Cd source. Mico et al. (2006) reported that Cd content was increased
due to the use of phosphatic fertilizers and other agrochemicals used on vegetable crops.
Wastewater insufficiently treated for soil irrigation is also a source of Cd contamination (Mico et
al., 2006).
The mean level of Cr in the soil within the four sub regions ranged from 1.460±0.270 to
4.210±0.604 mg/kg. Lorroki livestock area had the highest mean of 4.210±0.660 mg/kg followed
by Lorroki crop growing area with a mean of 3.480±0.480 mg/kg . The levels of Cr in the soil in
the four sub regions were much less compared to other regions in the world. ANOVA at 95%
revealed that the mean level of Cr in Loikas village was significantly different from the mean in
the other three sub regions. However the mean levels of Cr in Lorroki crop growing area, Lorroki
livestock area and Maralal town areas were not significantly different from each other at 95%
confidence level.
66
Figure 4.7 shows comparison of the mean levels of Cr compared in the four regions of Lorroki
and Kirisia divisions
Figure 4.7: Percentage Cr levels in soil from the four selected sub regions.
Cr is one of those heavy metals whose concentration is steadily increasing due to industrial
growth, especially the development of metal, chemical and tanning industries (Adelekan and
Abegunde, 2011). Other sources of Cr permeating the environment are air and water erosion of
rocks, power plants, liquid fuels, brown and hard coal, and industrial and municipal waste.
Although there is no risk of Cr contamination on a global scale, local permeation of the metal to
soil, water or the atmosphere might result in excessive amounts of this pollutant in
biogeochemical circulation (Adelekan and Abegunde, 2011).
Nonbiodegradability of Cr is
responsible for its persistence in the environment; once mixed in soil, it undergoes
transformation into various mobile forms before ending into the environmental sink (Adelekan
67
and Abegunde, 2011). The above sources of Cr are rare in Samburu County and perhaps that is
why the levels of Cr in this regions are generally lower than that the other regions of the world.
The mean levels of Mn in the soil in the four sub regions ranged from 13.370±1.620 to
26.830±3.290 mg/kg. Lorroki livestock area recorded the highest mean of 26.830±3.290 mg/kg
and Maralal Town area recorded a mean of 13.370±1.620 mg/kg. Maralal town area and Lorroki
crop growing area recorded similar mean levels of Mn in the soil. These levels of Mn recorded in
this sturdy were similar to those recorded by Al Yemen and Hashem (2006) in their study on
heavy metals and microbial analysis of soil samples. ANOVA at 95% confidence level revealed
a significant difference between the mean level of Mn in livestock area and the other three sub
regions (P=0.004). Fig 4.8 below compares the mean of Mn in soil in the four sub regions.
68
Figure 4.8: Mean Mn levels in soil from the four selected sub regions.
Soil generally contains 200 – 3000 mg/kg of Mn with an average value of 600 mg/kg (Okunola
et al., 2007). In the present study, amount of Mn ranged from 13.37 –26.83 mg/kg. The levels of
Mn in soils were relatively low, implying mild contamination of the metal in the soil.
The mean levels of lead in Maralal Town, Loikas village, Lorroki crop growing area and Lorroki
Livestock area are 67.50±7.76, 31.00±6.93, 54.66±4.41 and 44.65±9.53mg/kg respectively.
Loikas village had the highest mean of lead in the soil of the four sub regions. This could be
attributed to the surface runoff during rainy season why this carried to the dams and wells as
69
high levels are reflected in this water sources. The mean lead value in the soil in the four sub
regions were lower than those reported in most studies of soil heavy metals around the world
(Jaradat et al., 1999; Atiemo et al., 2011). The higher value of lead in agricultural area could be
due to high soil organic matter content. This soil component could possibly be responsible for
higher soil lead retention (Mico et al., 2006). Lead could also be from the application of
agrochemical and fertilizers in the agricultural area (Mico et al., 2006) eg urea and
superphosphate. Statistical analysis of the mean levels of lead in the soil in the four sub regions
using ANOVA revealed a significant difference between the level of lead in soils in Maralal
Town and Loikas villaage. There was no significant difference however in the mean level of lead
between Lorroki crop growing area and Lorroki livestock area. Figure 4.9 shows how the mean
levels of lead compared in the four sub regions of Kirisia and Lorroki divisions.
Figure 4.9: Percentage lead levels in soil
70
Maralal Town and Lorroki crop growing area had the highest mean level of lead in the soils. The
high level of lead in Maralal Town particularly was due to lead particulate matter emitted from
gasoline and wastes emitted from garages.
The mean levels of zinc in the soil within the four selected sub regions ranged from 165.99403.30 mg/kg. Maralal Town had the highest mean of 403.30±44.34 mg/kg while Lorroki
livestock area had the lowest mean of 165.99±16.82 mg/kg. Zinc exhibited higher levels of
contamination in the soil than those of other metals in this study. ANOVA revealed no
significant difference between the levels of zinc in the soil from Loikas village, Maralal Town,
Lorroki crop growing area and Lorroki livestock area (P=0.260). The mean values exhibited in
this study are higher than values exhibited in other studies (Jaradat et al., 1999; Okonola et al.,
2007; Yahaya et al., 2010). However, Awokunmi et al. (2010) recorded higher values of zinc in
soils than the values in this study. Awokunmi et al. (2010) recorded zinc values in soils ranging
from261.700 to 8100 mg/kg. Since no major industries exists in the study area such as metal
smelting, primary sources of zinc may assume are probably the attrition of motor vehicle tyre
rubber exacerbated by poor road surfaces and the lubricating oil in which zinc is found as part of
many additives (Okonola et al., 2007). A comparison between the levels of zinc in the four sub
regions is as shown in the Figure 4.10.
71
Figure 4.10: Percentage zinc levels in soil from the four selected sub regions in Kirisia and
Lorroki divisions.
It can be seen from the chart that Maralal town area had the highest mean of zinc followed by
Lorroki area. Lorroki area is basically an agricultural area and the levels of zinc in this area could
be attributed to excessive use of fertilizers in Wheat and Barley farms within the area ( Nema,
2009; Reza and Singh, 2010). Table 4.6 shows summary of means levels of heavy metals in
Kirisia and Lorroki divisions
4.4.2 Levels in Kirisia and Lorroki region
The Table 4.6 below shows the levels of the elements obtained in Kirisia and Lorroki divisions
72
Table 4.6: Levels of heavy metals in combined region
Parameter Kirisia
Mean± SE( mg/kg)
0.60±0.14
Cd
Lorroki
Mean± SE (mg/kg)
0.57±0.13
P value
0.859
Cr
2.65±0.30
3.69±0.39
0.033
Mn
17.44±1.02
21.91±1.82
0.033
Pb
55.33±5.93
51.80±4.16
0.626
Zn
376.35±46.64
265.99±59.75
0.144
SE- standard error
The mean levels of pollution of the selected heavy metals in Kirisia division were higher than
those in Lorroki division. The mean levels of Cd, lead and zinc were non significantly higher in
Kirisia division than Lorroki division. However, Mn and Cr levels were significantly higher in
soils of Lorroki Division than Kirisia division. The mean levels of Cd, lead and zinc in the soil
therefore were independent of the region of sampling but the mean levels of Mn and Cr were
dependent on the region of analysis.
Zinc had a mean of 376.35±46.64 mg/kg in Kirisia division. The means obtained in similar
studies around the world, indicate the mean of this study was generally higher ( Jaradat et al.,
1998; Okunula et al., 2007; Yahaya et al., 2010). The mean of Pb was the second highest with a
mean range of 51.80-55.33 mg/kg. This mean was in line with other studies done in other
countries (Okunola et al., 2007; Yahaya et al., 2010). The highest mean concentration of Cd was
obtained in Kirisia Division. The value was 0.60±0.14 mg/kg and this value was not significantly
(p>0.05) higher than mean value obtained from Lorroki Division. The source of Cd in soil may
be attributed to vehicular emissions. Cd is released as a combustion product in the accumulators
73
of motor vehicles or in carburetors (Ijeoma, 2011). Contamination of soil poses a serious threat
to the environment and there is a risk of transfer of toxic and available metals to biota (Ijeoma,
2011). Table 4.7 shows the overall mean of the heavy metals of the region studied, the range of
the levels of the metals and the WHO maximum recommended values in the soil.
Table 4.7: Mean and range of current study in comparison with WHO maximum allowed
limits
parameters
Mean±SE
WHO values
(Range)
(mg/kg)
of present study
in mg/kg
0.59±0.09
3.00
Cd
(0.00-5.91)
3.15±0.24
100.00
Cr
(0.00-18.59)
19.60±1.03
1000.00
Mn
(0.00-86.72)
53.63±3.66
100.00
Pb
(0.00-257.86)
323.07±37.73
300.00
Zn
(19.47-3121.92)
Source: Mamtaz and Chowdhury (2006); Atieno et al., 2011
Zinc had the highest mean and range in the study with a mean of 323.07±37.73 mg/kg which was
higher than the maximum permissible limit of 300 mg/kg recommended by the WHO. The range
of zinc in the present study was 19.47-3121.92 mg/kg. This clearly shows that not all the soils in
the two divisions in the county were polluted. However, the above range shows extreme
pollution in some areas of the county. The higher limit of the range of 312.92 mg/kg was above
WHO permissible limit of zinc in the soil raising concern as this could cause a lot of health
problems associated with excess zinc levels in soils for example, dust from these contaminated
74
sites could also pose great health problems especially on those people that live close to these
contaminated sites (Atiemo et al., 2011).
The range of Pb in this study was BDL-257.86 mg/kg and the mean value was 53.63 mg/kg. The
WHO maximum permissible limit of this element in the soil is 100 mg/kg. The mean is almost
half the value of the WHO permissible value of Pb in the soil. From the range it is clear that lead
was absent in some of the sites, but in some, it was present almost three times the WHO
maximum permitted value. Mn levels in the soil in this region ranged from BDL -86.72 mg/kg
and the mean was 19.60 mg/kg. The WHO maximum permissible level of Mn in the soil is 1000
mg/kg (Mamtaz and Chowdhury, 2006). All the soil sampled in this region was found to contain
Mn below the WHO maximum permissible level of 1000 mg/kg.
Cr had a mean of 3.15 mg/kg in the soils of this study and the range was BDL-18.59 mg/kg. The
WHO permissible value of Cr in the soil is 100 mg/kg. The mean value of Cr in the soils from
these study area was below the WHO maximum permissible contamination level. All the soils
sampled from this area were found to contain Cr below the WHO maximum permissible value.
Generally as regards to Cr in the soil in this study area, the soils are not polluted. The mean level
of Cd in the soils of Kirisia and Lorroki was 0.59 mg/kg and range of Cd in the soils from this
region was BDL-5.91 mg/kg. The WHO maximum permissible level of Cd in the soil is 3 mg/kg.
The mean value of Cd in the soil was found to below the WHO maximum permissible
contamination level. However, from the range, the levels in some areas exceeded the WHO
maximum permissible level of 3 mg/kg.
75
Different countries have different maximum allowed values for the heavy metals in the soils.
Table 4.8 shows the MAL for different countries in comparison to the levels obtained in the
study.
Table 4.8: Mean values obtained in this study in comparison with the maximum allowed
levels for different countries in mg/kg.
Element Australia Canada
Poland
Uk
Germany USA
Mean Obtained
In current study
Cd
5.000
8.000
3.000
3.000
-
0.7.000
Cr
100.000
75.000
100.000
50.000
200.000
1000.000 3.150
Pb
100.000
200.000
100.000
100.000 500.000
200.000
53.630
Zn
300.000
400,000
300.000
300.000 300.000
300.000
323.070
Mn
-
-
-
-
-
19.600
-
0.590
Source: Mamtaz and Chowdhury (2006).
The mean values of Cd, Cr and lead were below the MAL for all the countries listed above. The
levels of Zn, however, exceeded the MAL for all the countries with the exception of Canada.
When the mean levels of heavy metals in the soil and water in the Kirisia and Lorroki were
correlated the results were as tabulated in the Table 4.9.
76
Table 4.9: Relationship between individual heavy metals in water and in soils
From the Table 4.9, there was a positive correlation between the levels of lead and Cr in water
and in soils, however, the correlation was not significant. There was a negative correlation
between the levels of zinc, Cd and Mn in soils and water; but this correlation was not significant
P<0.05).
77
CHAPTER FIVE
CONCLUSIONS AND RECOMMENDATIONS
5.1 Conclusions
The study has shown that there was considerable amount of heavy metals in ground and surface
water, though the levels were below WHO maximum permissible levels for Mn, zinc and Cr. In
few cases the levels of Cd exceeded the WHO maximum permissible limit. The mean of lead
was above the WHO maximum permissible limits in ground and surface water from Kirisia and
Lorroki divisions.
The wells in Kirisia Division were more polluted than the dams and boreholes. This could be
attributed to the surface runoff of water during heavy down pour which led to heavy metals
depositing into the wells. In Lorroki Division, the dams had higher levels of the heavy metals
than the wells in the same region. There was no significant difference between levels of heavy
metals in dams, wells and boreholes in Kirisia Division (P<0.05>). However, in Lorroki
Division, there was a significant difference
between the levels of Pb in wells and dams.
However for the Zn, Mn, Cr and Zn there was no significant difference.
Kirisia had higher levels of heavy metals in surface and ground water than Lorroki Division.
This could be attributed to the many sources of anthropogenic origin being more in Kirisia
division than Lorroki division because the former houses the county headquarters and is
therefore more populated than Lorroki division. Kirisia division also lies at a lower altitude than
78
Lorroki Division and therefore likely to act as a collection point for surface runoff water during
heavy downpour hence the contamination.
The mean of the four analyzed heavy metals, Cd, Cr, Mn and lead in the soils in Kirisia and
Lorroki Divisions was below the WHO maximum permissible limits. However, the level of zinc
was above the world health organization permissible limit for Kirisia Division. The soil in
Lorroki was therefore not heavily polluted compared to the soil in Kirisia division. The mean
levels of Cd, lead and zinc in Kirisia Division, exceeded those of Lorroki Division by a
considerable margin. There was a positive correlation between the levels of lead and Cr in water
and in soils, however, the correlation was not significant. There was a negative correlation
between the levels of zinc, Cd and Mn in soils and water.
79
5.2 Recommendations
5.2.1 Recommendations from this study
The following may be recommended from this research and should be taken to the researchers in
this area
i.
The levels of lead and Cd in the water should be continuously monitored to check on
their levels. Lead levels in both the surface and ground water is already beyond the WHO
recommended maximum limit. The two heavy metals are very poisonous even in their
smallest quantities.
ii.
Sources of heavy metals in soils like inorganic fertilizers, pesticides and acaricides need
to be controlled. Fertilizers, pesticides and acaricides are known to be the sources of
some of the heavy metals like lead, zinc and Cd which have been detected both in soils
and water at high levels.
iii.
Kirisia Division had the highest contamination levels of lead in water and soils. Since
most of the water and soil sampling was done around Maralal town, there is need to
institute mechanisms to reduce the level of contamination including fixing the sewerage
system, building of toilets and checking on the conditions of automobiles that ply the
town routes.
80
5.2.2 Recommendations for further studies
i.
Further research similar to this one be carried out in other areas of the Samburu
County, especially the remotest parts that are riddled with conflicts arising from cattle
rustling.
ii.
Since there was a considerable level of the heavy metals studied in water and soil, a
research should be carried out in food crops to determine whether similar levels are
reflected in the food stuffs especially in Kirisia where the contamination of poisonous
metals like lead and Cd in water is high.
iii.
A further study should be done to include metals like copper, arsenic and mercury to
determine their contamination. This is because their anthropogenic origins like
acaricides, and lack of recommended dumpsites within the two districts exists.
81
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APPENDICES
Appendix I: Calibration curve for Mn
0.14
y = 0.046x + 4E-05
R² = 0.999
0.12
absorbance
0.1
0.08
0.06
0.04
0.02
0
0
0.5
1
1.5
concentration (ppm)
2
2.5
3
90
Appendix II: Calibration curve for zinc
1.4
y = 0.477x - 0.000
R² = 0.999
1.2
absorbance
1
0.8
0.6
0.4
0.2
0
-0.2
0
0.5
1
1.5
concentration (ppm)
2
2.5
3
91
Appendix III: Calibration curve for Cr
0.12
y = 0.020x + 0.001
R² = 0.996
Absorbance
0.1
0.08
0.06
Series1
0.04
Linear (Series1)
0.02
0
0
2
4
6
Concentration
.
92
Appendix IV: Calibration curve for Cd
0.06
y = 0.053x + 0.002
R² = 0.993
Absorbance
0.05
0.04
0.03
0.02
0.01
0
0
0.2
0.4
0.6
0.8
Concentration (ppm)
1
1.2
93
Appendix V: Calibration curve for lead
0.012
y = 0.001x + 0.000
R² = 0.999
Absorbance
0.01
0.008
0.006
Series1
0.004
Linear (Series1)
0.002
0
0
2
4
6
Concentration
.
ibrahim Abdulwaheed