BORANG PENGESAHAN STATUS

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.

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

v CONTENTS PAGE DECLARATION ACKNOWLEDGEMENTS ABSTRAK ABSTRACT CONTENTS LIST OF TABLES LIST OF FIGURES LIST OF ABBREVIATIONS AND SYMBOLS ii iii iv v - viii ix x - xii xiii CHAPTER 1 INTRODUCTION 1.1 Introduction 1.2 Background of Research Location 1.3 Research Statement 1.4 Objectives 1.5 Scope of Work 1 1 3 4 5 5 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 8 8 10 12 14 15

vi 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 17 17 18 18 21 22 24 26 26 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 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

vii 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

viii CHAPTER 6 CONCLUSION AND RECOMMENDATIONS REFERENCES APPENDIXES 77-78 79-84 85-88

ix List of Tables 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. Page 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 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 Page 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

xiii LIST OF ABBREVIATIONS AND SYMBOLS mg kg- 1 ppm km % > < OK IK USEPA KKIP DOE ECD DBKK 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

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.

116 OO'E 117 "Oo'E 118 OO'E 119 OO'E 7 00' N If 00' N _ p-p.o~-?<j V~~t ~-<..-?-?O SCALE 50 100 km RESEARCH LOCATION \ " fr -,.., FLftIiA :;::' "=" /' ~,- U.UTANP"SlFIC ltalllolnftnt. -=:: ~1Ml 1.I'IU :=,..... tgtan~~ '" -~"' SULUSEA 7.1 00' N 6 00' N 5" 00' N... W\ J Z.!c... ~I 1i m: q:' " r.. \ q:'... } r/)..... _.'-,-~...... -..,--.., " J..,.. KALIMANTAN CELEBES SEA 5" 00' N Figure 1.1 116 "Oo'E 117'bcrE Location map oftbe research area. 118 OO'E 119 OO'E

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 Prima!!/.. Sources Fertilizers Irrigation water Manures and composts Pesticides Sewage biosolids. (sludges) Soil amendments (lime, gypsum, etc) Main heav metals Cd, Cu, Mo, Pb, Zn Cd, Fe Cd, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Zn Cu HQ, Pb Zn Cd, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Zn Cu, Mn, Pb, Zn Secondary sources Automobile aerosols Coal combustion Mine waste and effluents Nonferrous smelter waste Paint dispersal Tire wear Waste combustion Pb Pb Cd, Cu, Fe, Hg, Mn, Ni, Pb, Zn Cd, Cu, Hg, Mn, Ni, Pb, Zn Cd, Pb Cd,Zn Cd, Pb

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