PUMS 99:1

UNIVERSm MALAYSIA SABAH

BORANG PENGESAHAN STATUS TESIS @

JUDUL: Pemetaan Geostatistik Taburan Logam-Logam Berat (Cd, Cr &. Zn) Dalam Sedimen Di Lagun Salut, Sabah.

UAZAH: Sarjana Saln (Pengurusan Sekitaran)

SESI PENGAJIAN : 2004 - 2006

Saya, WONG VUI CHUNG @ WEBSTER WONG mengaku membenarkan tesis Sarjana ini disimpan di Perpustakaan Universiti Malaysia dengan syarat-syarat kegunaan seperti berikut:

1. Tesis adalah hakmilik Universiti Malaysia Sabah. 2. Perpustakaan Universiti Malaysia Sabah dibenarkan membuat salinan

untuk tujuan pengajian sahaja. 3. Perpustakaan dibenarkan membuat salinan tesis ini sebagai bahan

pertukaran antara institusi pengajian tinggi. 4. TIDAK TERHAD pr: IF" S -::·wJ,.,.1

UNIVERSITI MftLAV Iii. SABA

Disahkan oleh

(Penulis: ONG VUI CHUNG @ ) WEBSTER WONG)

Alamat Tetap: P.O.Box 12588, 88828 Kota Kinabalu, Sabah.

Tarikh: 23 Mac 2006

(DR. ANJA GASSNER)

Tarikh:

CATATAN: @ Tesis dimaksudkan sebagai tesis bagi Ijazah Doktor Falsafah dan Sarjana secara penyelidikan, atau disertasi bagi pengajian secara kerja kursus dan penyelidikan, atau Laporan Projek Sarjana Muda (LPSM).

GEOSTATISTICAL MAPPING OF HEAVY METALS (Cd, Cr & Zn) DISTRIBUTION IN THE SEDIMENTS

OFSALUTLAGOON,SABAH

WONG VUI CHUNG @ WEBSTER WONG

PERPU~TiV.AAN UNNERSITI MALAYSIA SAB J.l

THIS DISSERTATION IS SUBMITTED IN PARTIAL FULFILLMENT OF REQUIREMENT FOR THE DEGREE OF

MASTER OF SCIENCE (ENVIRONMENTAL MANAGEMENT)

SCHOOL OF SCIENCE AND TECHNOLOGY UNIVERSITI MALAYSIA SABAH

2006

DECLARATION

The materials in this dissertation are original except for quotations, excerpts, summaries

and references, which have been duly acknowledged.

WONG VUI CHUNG @ WEBSTER WONG PS04-001 (K)-028

23 March 2006

ii

ACKNOWLEDGEMENTS

I would like to take this opportunity to express my sincere thanks to my supervisor Dr.

Anja Gassner and my co-supervisor Assoc. Professor Dr. Saba Musta for their guidance,

advices, and encouragements throughout this dissertation. I am especially indebted to

Dr. Anja for painstakingly and patiently teaching me on the subject of geostatistics.

Gratitude also goes to my employer, the Minerals and Geosciences Department

of Malaysia and the Malaysian Government for providing me the scholarship.

I am also grateful to Environmental Action Committee Sabah (EAC) for funding

the chemical analyses and also the laboratory staff of Minerals and Geosciences

Department, especially Mr. S.Pasupati and Pn. Kapis, for their help.

I would also like to express my gratitude to all the member of the academic staff

involved in the MSc Environmental Management course in UMS and to everyone that's

directly or indirectly involved in the preparation of this dissertation.

Thanks also to Mr. Lim P.S., Wahi Abd Rashid, Faridah Ang and Jovita Sidi for

their advices and guidance.

Last but not least, I wish to thank my family, especially my wife, for their support,

encouragement and patience.

ABSTRAK

PEMET AAN GEOSTATISTIK TABURAN LOGAM·LOGAM BERA T (Cd, Cr & Zn) DALAM SEDIMEN 01 LAGUN SALUT, SABAH

iii

Lima puluh (50) sample sedimen permukaan yang digeokod telah dikutip dari Lagun Salut yang terletak 15 km Timur Laut Kota Kinabalu, Sabah. Jumlah sedimen tersebut telah dianalisis dengan menggunakan Spektrofotometer Serapan Atom (SSA). Objektif kajian tersebut adalah untuk menilai kepekatan serta taburan spatial logam-Iogam berat (Cd, Cr dan Zn) serta membandingkan peta-peta yang dihasilkan dengan menggunakan teknik geostatistik iaitu ordinary kriging dan indicator kriging. Penilaian atas taburan logam berat dalam jumlah sedimen lagun Salut menunjukkan bahawa kepekatan min bagi Cd, Cr and Zn adalah masing-masing 6.1 mg kg·\ 15.5 mg kg-1 dan 262 mg kg-1• Taburan spatial logam berat dalam sedimen lagun Salut adalah terutamanya dikawal oleh factor-faktor fiziko-kimia dan corak penggunaan tanah. Dengan mempertimbangkan geologi sedimen dan perbandingan dengan kawasan lain, sedimen permukaan di Lagun Salut mencatatkan kepekatan Cd dan In yang tinggi. Kedua-dua peta ordinary kriging dan indicator kriging bagi taburan kepekatan Cd, Cr and In telah dihasilkan. Peta Indicator kriging telah terbukti lebih sesuai digunakan dalam membuat keputusan dan tujuan pengurusan logam berat.

iv

ABSTRACT

GEOSTA TIS TICAL MAPPING OF HEA VY METALS (Cd, Cr & Zn) DISTRIBUTION IN THE SEDIMENTS OF SALUT LAGOON, SABAH

Fifty (50) geocoded surface sediment samples were taken from Salut Lagoon, which is situated about 15 km northeast of Kota Kinabalu, Sabah. These total sediments were analyzed by using Atomic Absorption Spectrometry method (AAS). The objective of this study was to assess the concentration and the spatial distribution of the heavy metal (Cd, Cr and Zn), and compare maps generated using geostatistical techniques i. e. ordinary and indicator kriging. Assessment on the concentration and spatial distribution of heavy metals in the surface sediments of Salut Lagoon showed that the mean concentration for Cd, Cr and Zn are 6.1 mg kg-1

, 15.5 mg kg-1 and 262 mg kg-1

respectively. The spatial distributions of the heavy metals in the surface sediments of Salut Lagoon are mainly control/ed by physico-chemical factors and landuse patterns. Considering the sedimentary geology of the area, and comparison with other areas indicates that the Salut Lagoon shows high levels of Cd and Zn in the surface sediments. Both ordinary and indicator kriging maps for Cd, Cr and Zn concentrations were generated. Indicator kriging maps have proven to be more robust and suitable for decision-making and heavy metals management purposes.

DECLARATION

ACKNOWLEDGEMENTS

ABSTRAK

ABSTRACT

CONTENTS

LIST OF TABLES

LIST OF FIGURES

CONTENTS

LIST OF ABBREVIATIONS AND SYMBOLS

CHAPTER 1 INTRODUCTION

1.1 Introduction

1.2 Background of Research Location

1.3 Research Statement

1.4 Objectives

1.5 Scope of Work

CHAPTER 2 LITERATURE REVIEW

2.1 Heavy Metals

2.2 Heavy Metals and Environment

2.3 Heavy Metals Monitoring and Assessment

2.4 Coastal Zone heavy Metals Monitoring and Assessment

2.5 Heavy Metals in Sediments and their Behaviour

PAGE

ii

iii

iv

v - viii

ix

x - xii

xiii

1

1

3

4

5

5

8

8

10

12

14

15

v

2.5.1 Ion Exchange

2.5.2 Grain Size

2.5.3 Organic Content

2.5.4 Redox Potential and pH

2.6 Definition of Risk Assessment

2.7 Geostatistical Techniques in Risk Assessment

2.8 Ordinary Kriging and Indicator Kriging

2.9 Case Study in Heavy Metals Risk Assessment

2.10 Conclusion

CHAPTER 3 MATERIALS AND METHODS

3.1 Site Descriptions

3.2 Geology, Landform and Drainage

3.3 Landuse

3.3.1 Kota Kinabalu Industrial Park (KKIP)

3.3.2 Kayu Madang Landfill

3.4 Erosion and Sedimentation

3.5 Sampling Methods

3.5.1 Sample Preparation

3.6 Laboratory Analyses

17

17

18

18

21

22

24

26

26

28

28

30

33

35

36

37

38

38

39

3.6.1 Solution Preparation 39

3.6.2 Flame Atomic Absorption Spectrometry (FAAS) Analysis 39

3.7 Data Analysis

3.7.1 Statistical Analysis

3.7.2 Geostatistical Analysis

a. Trend Analysis

39

40

40

40

vi

b. Semivariogram Analysis 41

c. Indicator Semivariogram Analysis 44

d. Semivariogram Models 46

e. Kriging 46

f. Validation 48

CHAPTER 4 RESULTS 49

4.1 Introduction 49

4.2 Statistical Analysis 49

4.3 Heavy Metals Distributions 53

4.4 Sediments distributions 55

4.5 Spatial Analysis 56

4.5.1 Variogram Analysis 58

4.5.2 Ordinary Experimental Variogram 58

4.5.3 Indicator Experimental Variogram 60

4.6 Ordinary and Indicator Kriging Maps 63

4.7 Grain size Indicator Map 65

4.8 Validation 66

CHAPTER 5 DISCUSSIONS 68

5.1 Comparing heavy metals concentration in the sediments of 68 Salut Lagoon with USEPA limits

5.2 Comparing heavy metals concentration in the sediments of 69 Salut Lagoon with sediments in Likas Estuary and research done in similar coastal environment.

5.3 Heavy Metals Concentration and Distributions 71

5.4 Heavy Metals Spatial Distributions Maps and Management Strategies 73

vii

CHAPTER 6 CONCLUSION AND RECOMMENDATIONS

REFERENCES

APPENDIXES

viii

77 -78

79 -84

85-88

ix

List of Tables

Page

Tables 2.1 Average abundances of elements in the earth crust, 8 three common rocks and sea water, in ppm (Krauskopf 1979)

Tables 2.2 Sources of heavy metal contamination in soils 9 (McLaughlin, 2002)

Tables 2.3 Comparison between natural and anthropogenic 10 rates of heavy metals input (French, 1997)

Tables 2.4 Minimum pH values for complete precipitation of 20 metal ions as hydroxides or other salts (Kelly, 1988).

Tables 2.5 Different kriging methods adopted by researchers in 24 assessing heavy metals in soils.

Tables 3.1 Major landuse in KKIP proposed Master Plan (1998). 35

Tables 4.1 Summary statistics of Cd, Cr and Zn concentrations 50 in the sediments of Salut Lagoon.

Tables 4.2 Curve estimation on the Cd, Cr and Zn 56 concentrations in the sediments of Salut Lagoon using SPSS.

Tables 4.3 Parameters used in finding the best fit modeling for 60 the ordinary experimental variogram.

Tables 4.4 Parameters used in finding the best fit modeling for 62 the indicator experimental variogram.

Tables 4.5 Standard error for ordinary and indicator kriging 67 method.

Tables 5.1 Comparison between the ERL and ERM limits for 68 metals adopted by EPA and the concentration in Salut Lagoon.

Tables 5.2 Concentration of Cd, Cr & Zn (mg kg·1) in total 70 sediments of Likas Estuary (Jovita Sidi , 2005).

Tables 5.3 The average concentration od Cd, Cr and Zn in the 70 two main sediment types of Ria de Vigo, Spain and Salut Lagoon, Sabah.

Tables 5.4 Levels of Cd, Cr and Zn (mg kg-1) in the sediments of 71 Thermaikos Gulf at different areas.

x

List of Figures

Page

Figure 1.1 Location map of the research area. 7

Figure 2.1 Typical concentration-response relationship for 11 essential and nonessential heavy metals in soils (McLaughlin, 2002).

Figure 2.2 Causes of estuarine and coastal pollution and the 12 various transport pathways (adapted from French, 1997).

Figure 2.3 Simplified dynamic equilibria reaction in soil (McBride, 16 1994).

Figure 3.1 Topographic map of the Mengkabong-Salut Area. 29

Figure 3.2 Patches (left) and narrow buffer (right) of mangrove 29 trees along the edge of Salut Lagoon.

Figure 3.3 Clearing of the mangrove trees at the northwestern 30 edge of the lagoon for mariculture.

Figure 3.4 Land reclamation for buildings of governmental 30 institutions at the edge of the lagoon.

Figure 3.5 Geological map of the Salut Lagoon Area (adapted 31 from Tating, 2003).

Figure 3.6 Landforms of the study area (Gassner et a/., 2004). 32

Figure 3.7 Landuse map of the Salut Lagoon area. 34

Figure 3.8 Left: Gayang Seafood Restaurant, viewing southeast 34 to the Salut Lagoon. Right: Prawn farm at Kg. Malawa pumping water from Salut Lagoon.

Figure 3.9 Left: Development along the tributary Salut River. 36 Right: Closer view showing sedimentation along the river.

Figure 3.10 Left: Cut slopes along the Sepanggar Road. 38 Right: Sedimentation besides the Salut Channel near sampling point S50.

Figure 3.11 An experimental semivariogram. 42

xi

Figure 3.12 Basic component of a semivariogram. 43

Figure 4.1 Histogram and box plot for Cd, Cr and Zn variables. 51

Figure 4.2 Scattered plot and correlation coefficient between Cd, 52 Cr and Zn.

Figure 4.3a Cd concentrations distribution in the sediments of 53 Salut Lagoon.

Figure 4.3b Cr concentrations distribution in the sediments of 54 Salut Lagoon.

Figure 4.3c Zn concentrations distribution in the sediments of 55 Salut Lagoon.

Figure 4.4 Generalized grain size distribution map. 56

Figure 4.5 Scattered plot of Cd, Cr and Zn in relation to northing 57 and easting and their respective R2 values.

Figure 4.6a Omnidirectional standardization ordinary experimental 58 variogram for Cd concentrations in the sediment of Salut Lagoon.

Figure 4.6b Omnidirectional standardization ordinary experimental 59 variogram for Cr concentrations in the sediment of Salut Lagoon.

Figure 4.6c Omnidirectional standardization ordinary experimental 59 variogram for Zn concentrations in the sediment of Salut Lagoon.

Figure 4.7a Omnidirectional standardization indicator 61 experimental variogram for Cd concentrations in the sediment of Salut Lagoon.

Figure 4.7b Omnidirectional standardization indicator 61 experimental variogram for Cr concentrations in the sediment of Salut Lagoon.

Figure 4.7c Omnidirectional standardization indicator 62 experimental variogram for Zn concentrations in the sediment of Salut Lagoon.

Figure 4.8a Ordinary kriging map for Cd concentrations in the 63 sediments of Salut Lagoon.

Figure 4.8b Indicator kriging map for Cd concentrations in the 63 sediments of Salut Lagoon.

xii

Figure 4.8c Ordinary kriging map for Cr concentrations in the 64 sediments of Salut Lagoon.

Figure 4.8d Indicator kriging map for Cr concentrations in the 64 sediments of Salut Lagoon.

Figure 4.8e Ordinary kriging map for Zn concentrations in the 65 sediments of Salut Lagoon.

Figure 4.8f Indicator kriging map for Zn concentrations in the 65 sediments of Salut Lagoon.

Figure 4.9 Omnidirectional indicator experimental variogram for 66 the coded sediment descriptions.

Figure 4.10 Indicator kriging map for grain size distribution. 66

Figure 4.11 Location of the ten validation samples. 67

mg kg-1

ppm

km

%

>

<

OK

IK

USEPA

KKIP

DOE

ECD

DBKK

LIST OF ABBREVIATIONS AND SYMBOLS

milligram per kilogram

parts per million

kilometer

percentage

more than

less than

Ordinary kriging

Indicator kriging

United States Environmental Protection Agency

Kota Kinabalu Industrial Park

Department of Environmental

Environmental Conservation Department

Dewan Bandaraya Kota Kinabalu

xiii

CHAPTER 1

INTRODUCTION

1.1 Introduction

Coastal zones have been the centre of intense housing, agricultural , fishery,

industrial, and tourism development and estuaries perhaps are the most polluted of

all marine environments (Garrison, 2005) mainly due to its unique characteristics for

industrial location. Estuaries provide extensive flat land for setting up industrial bases

and allow port developments which in turn ease the import and export of raw

materials. They normally have high potential of water supply for industrial uses and

historically they have been perceived as natural "waste disposal systems" (French,

1997). Thus the anthropogenic impact on the coastal and estuarine environmental is

far-reaching and the uncontrolled development and increasing human activities have

created a threat to these unique and economically valuable ecosystems. Among the

pollutants being released into estuaries environments are the heavy metals which are

particularly toxic in their chemically combined forms and some, notably mercury, are

toxic in the elemental form (McBride, 1994).

Heavy metals are naturally occurring metals from earth materials and volcanic

emanations. However these metals can also be introduced to the environment from

anthropogenic sources. The anthropogenic sources of heavy metal can be point

source or non-point source. Point sources may include discharges of waste effluents

from factories, contamination from a landfill site or mining and non-point source may

be due to agricultural practices surrounding the area. These pollutants can be

transported to the estuaries by a variety of pathways and mediums. Sediments are

by far the most significant medium in heavy metals distributions.

2

The behaviour of heavy metals in sediments depends on chemical and

physico-chemical as well as biological factors associated with the microbial activities.

It has been recognized that textural characteristics, organic matter content,

mineralogy composition as well as depositional environment of the sediments play an

important role in the concentration of heavy metals (Singh et a/., 1999; Rubio et a/.,

2000).

Although some heavy metals are essential (e.g. haemocyanin - blood

pigment of crustaceans, contains Cu) but increase concentration to toxic level will

impair biological processes such as enzyme function (Boaden & Seed, 1985).

Excessive concentrations of heavy metals in the sediments can affect marine

organism and pose risk to human through the food web. These heavy metals can be

absorbed by organisms from the surrounding water or ingested with their food. Thus

heavy metals have a high tendency to accumulate in the organism (bioaccumulation).

They often accumulate in the nervous system and brain, causing behavioural

disorder and diverse neurological problems, such as the Minamata Diseases. They

may also impair growth development and reproduction system, damage organs or

disrupt the immune system. The adverse biological effects are complex and

potentially fatal (Botkin & Keller, 2003).

The detrimental effects caused by the introduction of heavy metal pollutant

into the coastal zone such as estuary is well known. Assessment and monitoring of

these pollutants in environment like estuary is required to better manage and

minimize if not totally eliminate these pollutants. Good management decision based

on accurate risk assessment involved good understanding of the spatial variation and

distribution of the variable of interest. However, long term assessment and

monitoring is often synonymous with huge budget. Thus, an unbiased and good

estimation method is required to quantify and model the variation and performs

interpolation at un-sampled location and to delimit zones that need remedial

treatment.

3

In this regard, geostatistics has proved to be a good estimation method in

studying the environmental pollutants (Amstrong, 1998) especially when there is a

budget constraint or limited resources. Geostatistics has been widely used in the

mining sector for the past 40 years since its development in the 1960s due to the

need for a methodology in evaluating recoverable reserves on ore deposits

(Goovaerts, 1997). In recent years, geostatistics has also been successfully applied

in other disciplines such as soil science, petroleum, hydrology, oceanography, as

well as environmental science because geostatistical method incorporate the spatial

and temporal aspect of the variables of interest.

Kriging method is one of the geostatistical methods that are widely used. It is

an estimation method which gives the best unbiased linear estimates of point values

or block averages. Kriging also proved to be an exact interpolator because it takes

into account the number of samples, quality of the variables, spatial relationship of

the samples (position and distance), and also their spatial continuity (Amstrong,

1998). There are two kinds of spatial analysis in geostatistics, i.e. spatial interpolation

and uncertainty assessment. Commonly used spatial interpolator is Ordinary Kriging

(OK) while Indicator Kriging (IK) has been applied in uncertainty assessments. The

advantages of both methods are elaborated in Chapter 2.

Risk map generated from an appropriate kriging technique is useful in good

decision making and management especially in managing high risk areas of

contamination that needs immediate remedial action. Taking into account the

advantages of both the OK and IK techniques, it is the objective of this study to

assess the suitability of these two techniques in mapping the distribution of heavy

metals in an estuary setting such as Salut Lagoon.

1.2 Background of Research Location

Salut lagoon is located about 15km northeast of Kota Kinabalu (Figure 1.1), on the

west coast of Sabah. Towards the west, the Mengkabong-Salut Lagoon systems

4

developed into a five-kilometre beach before open up to the South China Sea,

whereas to the east of the system is bordered by mangrove buffer, which changes

into a secondary vegetation further inland, commonly found in the west coast of

Sabah. The lagoon systems comprise the best mangrove forest remaining near Kota

Kinabalu, Sabah and have been identified as important nursery and feeding grounds

for fish and shellfish and of high eco-tourism potential (Gassner at al., 2004).

With the expansion of KKIP just next to Salut lagoon as well as population

increase and extensive resource exploitation such as quarrying and industry

developments nearby, more pollutants will be brought into the estuary. These toxic

pollutants will subsequently be accumulated in the estuary. Hence, an appropriate

estimation technique is required to evaluate the level and distribution of the

contamination in the estuary in order to draw up a mitigation/management measures

as well as for monitoring purposes.

The Mengkabong-Salut lagoon Area has also been identified as a project

area by Global Environmental Centre with the objective to improve the quality and

status of biodiversity through community participated river management. Universiti

Malaysia Sabah (UMS) was given the responsibility as the lead agency for Working

Group 1-Monitoring, with the objective to monitor water quality, habitat and hydrology

in the Salut-Mengkabong estuary. The group focuses on the caring capacity of the

lagoon systems, which is related to the anthropogenic utilisation on the available

resources and services in the lagoon or their catchments, and has since started the

survey in 2004 (Gassner at al., 2004).

1.3 Research Statement

For environmental management of pollutants, the concentration and distribution of

the pollutants need to be quantified. As most environmental studies have the

constraint of funding and manpower, maximum information with minimum sample

density is needed. In many applications, the basic tool in geostatistics, the variogram

5

(Wackernagel, 1995 ; Goovaerts, 1997; Amstrong, 1998), is used to quantify spatial

correlation between observations and can be used to estimate values at un-sampled

points. However it is vital to choose the best geostatistical estimation technique for a

particular environmental pollutant at a study site. In this research, the heavy metal

concentrations in the surface sediments of Salut Lagoon will be studied by using

geostatistical mapping techniques.

1.4 Objectives

The objective of the study is to assess the concentration and distribution of the heavy

metals (Cd, Cr & Zn) and create spatial distribution maps using two different kriging

methods for the management of heavy metal contamination.

To accomplish the above objective the following tasks will be carried out:

a. To determine the concentration of Cd, Cr, and Zn in surface sediments

of the Salut Lagoon.

b. To model the spatial distribution of the heavy metals (Cd, Cr, & Zn)

using variography.

c. To create surface map of the heavy metals (Cd, Cr, & Zn) using

Ordinary Kriging and Indicator Kriging.

1.5 Scope of Work

To accomplish the objective of this research, a total of 50 sediment samples were

collected in Salut Lagoon. The samples were analyzed for heavy metals (Cd, Cr, &

Zn) by using Atomic Absorption Spectrometer (AAS) at Minerals and Geoscience

Department.

For the purpose of geostatistics, 40 samples were used for

variography and kriging (ordinary kriging and indicator kriging) while 10 samples

were used as validation set. Estimated values at the locations of the 10 samples

were compared with the laboratory results to test the appropriateness of the two

6

kriging techniques used. Software such as Variowin 2.21 and Surfer 7 were used to

do the variography, kriging and construct the heavy metals spatial distributions maps.

7 · 00' N

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116 ·OO'E 117 "Oo'E

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118 · OO'E 119 ·OO'E

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CHAPTER 2

LITERATURE REVIEW

2.1 Heavy Metals

Heavy metals are metallic element with relatively high atomic mass which density

exceeds 5 grams per cubic centimetre (Sparks, 1995) such as antimony, bismuth,

cadmium, copper, gold, lead, mercury, nickel, silver, tin, and zinc. A large number of

elements fall into this category. Heavy metals are generally present at trace

concentrations «100mglkg) in most soils, thus are sometimes tenned as "trace

metals". But the tenns cannot be synonymously used because some heavy metals

such as Cr, Fe and Mn may present at more than the trace concentrations level

(McLaughlin, 2002).

They are natural components of the Earth's crust (Krauskopf, 1979; Santos at

al. , 2005) or rocks. Different types of rocks (igneous, metamorphic or sedimentary)

contain different types and amount of heavy metals (Table 2.1).

Table 2.1: Average abundances of elements in the earth crust, three common rocks and sea water, in ppm (Krauskopf, 1979).

Element Crust Granite Basalt Shale Sandstone Seawater Sediments (Sperk., 1995J

AI 8.1 x 10" 7.7 X 10" 8.4 X 10" 9.2x10" - 0.002 7.2 x 10" Fe 5.4x10" 2.7 x 10" 8.6 X 10" 4.7 X 10" - 0.002 4.1 x 10" Mn 1,000 500 1,700 850 10-100 2 x 10~ 770 Cr 100 20 200 100 35 3 x 10~ 72 Ni 75 0.8 150 80 2 0.0017 52 Zn 70 50 100 90 16 0.0049 95 Cu 50 12 100 50 1-10 5 x 10~ 33 Co 22 3 48 20 0.3 5 x 10·" 14 Pb 12.5 20 3.5 20 7 3 x 10"" 19 Sn 2.5 3 2 6 - 1 x 10.0 4.6 As 1.8 1.5 2 10 - 0.0037 7.7 Sb 0.2 0.2 0.2 1.5 - 1.2 2.4 x 10~ Cd 0.15 0.1 0.2 0.3 - 0.17 1 x 10'" Ag 0.07 0.04 0.1 0.1 - - 4 X 10"" Se 0.05 0.05 0.05 0.6 0.05 0.42 2 x 10'" Hg 0.02 0.03 0.01 0.3 - 0.19 3 x 10-:1

9

Heavy metals weathered from these rock formations spread widely in the

environment, occurring in particulate or dissolved form in soils, rivers, lakes,

seawater and sea floor sediments. Other sources of heavy metals are volcanoes

where these heavy metals are being released into the atmosphere.

Background levels of heavy metals usually reflect the composition of the

parent rock materials. However the background levels are sometimes difficult to

determine because of anthropogenic inputs (McLaughlin, 2002).

Industries such as mining and ore processing, metallurgical procedures (e.g.

electroplating), paper manufacturing, petroleum refining etc. may cause heavy metals

such as cadmium, lead, tin, plutonium and mercury be released to the environment

(Murck at a/. , 1996). Some of the primary and secondary sources of heavy metals

contaminations are shown in Table 2.2.

Table 2.2: Sources of heavy metal contamination in soils (McLaughlin, 2002).

Source Main heaV¥ metals Prima!!/.. Sources

Fertilizers Cd, Cu, Mo, Pb, Zn Irrigation water Cd, Fe Manures and composts Cd, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Zn Pesticides Cu HQ, Pb Zn Sewage biosolids. (sludges) Cd, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Zn Soil amendments (lime, Cu, Mn, Pb, Zn gypsum, etc)

Secondary sources

Automobile aerosols Pb Coal combustion Pb Mine waste and effluents Cd, Cu, Fe, Hg, Mn, Ni, Pb, Zn Nonferrous smelter waste Cd, Cu, Hg, Mn, Ni, Pb, Zn Paint dispersal Cd, Pb Tire wear Cd,Zn Waste combustion Cd, Pb

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