1 IMPACT OF GOLD MINING ACTIVITIES ON THE WATER QUALITY OF THE LOWER PRA RIVER BY OFFEI SAMUEL K. DWAMENA (10220952) A THESIS SUBMITTED TO THE CHEMISTRY DEPARTMENT OF THE UNIVERSITY OF GHANA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF MASTER OF PHILOSOPHY DEGREE IN CHEMISTRY JULY 2013 University of Ghana http://ugspace.ug.edu.gh 2 IMPACT OF GOLD MINING ACTIVITIES ON THE WATER QUALITY OF THE LOWER PRA RIVER A thesis submitted to the Department of Chemistry of the University of Ghana By Offei Samuel K. Dwamena (10220952) In partial fulfillment of the requirements for the award of Master of Philosophy Degree in Chemistry July 2013 University of Ghana http://ugspace.ug.edu.gh i DECLARATION I, Offei Samuel K. Dwamena of the Chemistry Department of the University of Ghana, do hereby declare that this thesis ‘Impact of Gold Mining Activities on Water Quality of the Lower Pra River’ is the outcome of research work undertaken by myself under the supervision of Prof. V. K. Nartey and Dr. R. K. Klake and that it has neither in part nor in whole been presented for another degree in this University or elsewhere except for references to works of other researchers which have been duly acknowledged. ……………………………………………… OFFEI SAMUEL K. DWAMENA 10220952 (STUDENT) ……………………………………………… PROF. VINCENT K. NARTEY (MAIN SUPERVISOR) …………………………………………… DR. RAPHAEL K. KLAKE (CO-SUPERVISOR) University of Ghana http://ugspace.ug.edu.gh ii DEDICATION To the glory of God And My family University of Ghana http://ugspace.ug.edu.gh iii ACKNOWLEDGEMENT With a heart full of thanks I am grateful to God for bringing me this far. It is His grace and strength that has kept me strong and active to this day. I express my profound gratitude and appreciation to my supervisors Prof. V. K. Nartey and DR. R. K. Klake for their able guidance, thorough reading of my thesis, constructive criticisms and helpful suggestions throughout the project. I also wish to express my deep sense of gratitude to Dr. Barima Antwi, Head of Department, Geography and Regional Planning, University of Cape Coast (U.C.C) for his help and contribution to my work especially in assembling a team for me during sampling that included Mr. Richard Adade who carefully selected sampling locations along the lower Pra River in the Mpohor Wassa- Shama catchment area. He is also credited with all map drawings in this thesis. My gratitude also goes to Air Commodore Evans Santrofi Griffiths of the Ghana Air Force and to Mr. Daniel Baidoo, Director of HRODD, University of Ghana, Legon for their immense support during the project and throughout the Mphil. Program. I am grateful for the help I received from the staff of the Chemistry Department, especially to the head of department, Prof. R. Kingsford-Adaboh, technicians such as Mr. Bob Essien and Mr. Attah and to Mrs Akaho, the department secretary. My sincere thanks to the laboratory technicians at Water Research Institute especially Mr. Michael Dorleku at the trace metal lab and Auntie Regina at the microbiology lab and to Mr. Bentil (Sir Nash) at the Ghana Atomic Energy Commission. These personalities made their equipment available to me during my work. University of Ghana http://ugspace.ug.edu.gh iv Words are inadequate in offering appreciation to my colleagues; Stephen (Affo), Kojo, Cephas, MacDonald, Anita, Chicowe, Eric (Shepard), Godwin, Sasah, Yikpo, Moscoh, Justice (Ghazi), Julie, Henry and especially Horatio who accompanied me on the second field visit. To all other persons who in diverse ways helped but were not specifically acknowledged by name, I say thank you. University of Ghana http://ugspace.ug.edu.gh v ABSTRACT This study was conducted to assess the extent of Mercury (THg) contamination at four locations within the Shama-Mporhor Wassa catchment area of the Lower Pra River. Water, fish and sediment samples were taken twice with the longitudinal transect method at Daboase, Beposo, Bokorkope and Shama during the minor rainy season in October and at the apex of the dry season in March. Careful investigation of the Shama-Mporhor Wassa catchment area revealed that two of the locations Daboase and Beposo had been continuously impacted by the activities of Artisanal Gold miners (AGM). From the study, Total Mercury (THg) levels were found to have persisted in River water several kilometers downstream the second Artisanal Gold mining (AGM) location at Shama estuary for both seasons. Ten trace elements Mercury (Hg), Selenium (Se), Copper (Cu), Chromium (Cr), Lead (Pb), Iron (Fe), Manganese (Mn), Nickel (Ni), Zinc (Zn) and Cadmium (Cd) were determined in water, fish and sediment samples using the Atomic Absorption Spectroscopy (AAS) equipped with both Hydride Generation (HGAAS) for Selenium (Se) and Cold Vapour (CVAAS) for Total Mercury (THg). The levels of Total Mercury (THg) were largely above the WHO and USEPA guidelines for drinking water (1µg/L) and sediments (200 µg/Kg) respectively for the four locations investigated. Total Mercury (THg) exceeded the WHO, 2011 guideline value of 0.5 mg/Kg for fish species Clarias submarginatus but was below the guideline value for Xenomystus nigri. Mean concentration of Cd and Fe exceeded the WHO, 2011 guideline values for drinking water for the wet season. The other trace elements Zn, Ni, Cu, Cr, Se, Mn, and Pb had their mean concentration below the WHO, 2011 guideline values for drinking water. Apart from the mean concentration of Cd that exceeded the Canadian Interim Sediment Quality (ISQG) guideline value of 0.6 mg/Kg for the wet season, Cr, Cu, Zn, Ni and Pb were below their respective guideline values for both seasons. Statistical University of Ghana http://ugspace.ug.edu.gh vi parameters such as the Coefficient of Variation and the Paired Sampled T- test were used to investigate the spatial and temporal variation of trace elements, water physico-chemical parameters and nutrients. Physico-chemical parameters such as total alkalinity, pH and Biochemical Oxygen Demand (BOD) were affected by seasonal variations as evident from the Paired Sampled T- Test. Environ metrics model Principal Component Analysis (PCA) proved to be an effective tool for identifying the possible sources (natural and anthropogenic) of trace elements and their relationship with water physico-chemical parameters. The model showed that Total Suspended Solids (TSS) had a major role to play in the distribution of Total Mercury (THg) and Selenium (Se) across the four locations in the study area. Generally, the Lower Pra River was found to be polluted and of poor water quality in terms of Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Total Suspended Solids (TSS), Total Dissolved Solids (TDS) and microbes such as E. coli, Total Coliform (TC), Fecal Coliform (FC), and Total Heterotrophic Bacteria (THB). Microbial contamination was also found to be connected to human activities along the banks of the river. University of Ghana http://ugspace.ug.edu.gh vii ACRONYMS AGM Artisanal Gold Mining Activities APHA American Public Health Association AWWA American Water Works Association BAF Bioaccumulation Factors BOD Biochemical Oxygen Demand Co.V Coefficient of Variation CRM Canadian Reference Material DO Dissolved Oxygen DOM Dissolved Organic Matter EDTA Ethylenediaminetetra-acetic Acid EPA Environmental Protection Agency FC Faecal Coliform HMWC High Molecular Weight Complex ISQG Canadian Interim Sediment Quality Guidelines PCA Principal Component Analysis QC Quality Control TC Total Coliform TDS Total Dissolved Solids THB Total Heterotrophic Bacteria TSS Total Suspended Solids USEPA United States Environmental Protection Agency WEF Water Environmental Federation WHO World Health Organization University of Ghana http://ugspace.ug.edu.gh viii TABLE OF CONTENTS DECLARATION…………………………………………………………………………………..i DEDICATION…………………………………………………………………………………….ii ACKNOWLEDGEMENT………………………………………………………………………..iii ABSTRACT……………………………………………………………………………………… v ACRONYMS…………………………………………………………………………………….vii LIST OF TABLES……………………………………………………………………………...xiii LIST OF FIGURES AND PLATES...…………………………………………………………..xiv CHAPTER ONE ............................................................................................................................. 1 1.0 INTRODUCTION ............................................................................................................ 1 1.0.1 Background to study ................................................................................................. 1 1.1 PROBLEM STATEMENT .............................................................................................. 5 1.1.1 Research hypothesis .................................................................................................. 6 1.1.2 Study objectives ........................................................................................................ 7 CHAPTER TWO ............................................................................................................................ 9 2.0 LITERATURE REVIEW ................................................................................................. 9 2.1 DEFINITION AND PROPERTIES OF HEAVY METALS .......................................... 9 2.2 SOURCES OF HEAVY METALS ............................................................................... 10 2.3 AN ENVIRONMENTAL CLASSIFICATION OF METALS ..................................... 10 2.4 OVERVIEW OF RESEARCH OF MERCURY IN GHANA ...................................... 12 2.5 MERCURY .................................................................................................................... 13 2.5.1 Chemical fate ........................................................................................................... 13 2.5.2 Mercury in mine effluents and receiving waters ..................................................... 16 2.5.3 Interactions with Other Mineral Element ................................................................ 17 2.5.4 Mercury environmental cycle .................................................................................. 17 2.6 SELENIUM ................................................................................................................... 18 2.6.1 General Fate Information ........................................................................................ 18 2.6.2 Selenium and Mercury in Organisms: Interactions and Mechanisms ..................... 20 2.7 CADMIUM .................................................................................................................... 27 University of Ghana http://ugspace.ug.edu.gh ix 2.7.1 Chemical fate ........................................................................................................... 27 2.7.2 Toxicity of Cadmium .............................................................................................. 28 2.8 LEAD ............................................................................................................................ 29 2.8.1 Chemical fate ........................................................................................................... 29 2.8.2 Toxicity of lead ....................................................................................................... 30 2.9 IRON ............................................................................................................................. 30 2.9.1 Chemical fate ........................................................................................................... 30 2.9.2 Toxicity of Iron ....................................................................................................... 31 2.10 WATER .......................................................................................................................... 34 2.10.1 Importance of good water quality ........................................................................... 34 2.10.2 Freshwater Physico-Chemistry ............................................................................... 35 2.10.3 Dissolved oxygen (DO) .......................................................................................... 35 2.10.4 Total Alkalinity ....................................................................................................... 36 2.10.5 Biochemical oxygen demand (BOD) ...................................................................... 37 2.10.6 Electrical conductivity ............................................................................................ 37 2.10.7 Turbidity and suspended matter in the hydrosphere ............................................... 38 2.10.8 Total hardness ......................................................................................................... 38 2.10.9 The effect of nutrients on freshwater ecosystems ................................................... 39 2.10.9.1 Nitrogen cycle ................................................................................................. 40 2.10.9.2 Nitrogen fixation ............................................................................................. 40 2.10.9.3 Denitrification ................................................................................................. 41 2.10.9.4 Ammonification .............................................................................................. 41 2.10.9.5 Nitrification ..................................................................................................... 41 2.10.9.6 Sulfur in freshwater ......................................................................................... 42 2.10.9.7 Phosphorous in freshwater .............................................................................. 43 2.10.10 Microbial Quality of Drinking Water ..................................................................... 44 2.10.10.1 Total heterotrophic bacteria (THB) ................................................................. 45 2.10.10.2 Total coliform bacteria .................................................................................... 45 2.10.10.3 Faecal coliform ................................................................................................ 46 2.10.10.4 Escherichia coli (E. coli) ................................................................................. 46 2.11 ANALYTICAL METHOD FOR DETERMINATION OF HEAVY METALS ......... 47 University of Ghana http://ugspace.ug.edu.gh x 2.11.1 Hydride Generation Atomic Absorption Spectrometry (HGAAS) ........................ 48 2.11.2 Cold Vapour Atomic Absorption Spectrometry (CVAAS) ................................... 48 2.12 FISH SPECIES ............................................................................................................. 49 CHAPTER THREE ...................................................................................................................... 51 3.0 METHODOLOGY ......................................................................................................... 51 3.1 DESCRIPTION OF STUDY AREA .............................................................................. 51 3.1.1 Pra River Catchment............................................................................................... 51 3.1.2 Climate and Geology of the Catchment Area ......................................................... 51 3.1.3 Catchment Divisions ............................................................................................... 53 3.1.4 Site Selection for Monitoring.................................................................................. 53 3.2 SAMPLING ................................................................................................................... 56 3.2.1 Sample Collection ................................................................................................... 57 3.2.2 Sample Preparation ................................................................................................. 59 3.2.2.1 Cleaning of Glassware .................................................................................... 59 3.2.2.2 Water Samples................................................................................................. 59 3.2.2.3 Sediment Samples ........................................................................................... 59 3.2.2.4 Fish Samples ................................................................................................... 59 3.2.3 Instrumental Models ............................................................................................... 60 3.2.4 Analysis of Soil Physicochemical Parameters ........................................................ 61 3.2.4.1 Soil pH............................................................................................................. 61 3.2.4.2 Electrical Conductivity .................................................................................... 61 3.2.5 Physicochemical Parameters of Water.................................................................... 61 3.2.5.1 Dissolved Oxygen (DO) .................................................................................. 62 3.2.5.2 Biochemical Oxygen Demand (BOD) ............................................................. 62 3.2.5.3 Total Water Hardness ...................................................................................... 63 3.2.5.4 Total Alkalinity................................................................................................ 63 3.2.5.5 Total Suspended Solids (TSS) ......................................................................... 63 3.2.5.6 Total Dissolved Solid (TDS) ........................................................................... 64 3.2.5.7 Microbial Studies ............................................................................................. 64 3.2.5.8 Sodium (Na) and Potassium (K) ...................................................................... 64 3.2.5.9 Quality Control ................................................................................................ 65 University of Ghana http://ugspace.ug.edu.gh xi 3.3 DATA ANALYSIS ....................................................................................................... 67 CHAPTER FOUR ......................................................................................................................... 68 4.0 RESULTS AND DISCUSSION .................................................................................... 68 4.1 RESULTS ....................................................................................................................... 68 4.1.1 Physical Parameters of Water and Sediments ......................................................... 68 4.1.1.1 Temperature .................................................................................................... 68 4.1.1.2 Conductivity .................................................................................................... 69 4.1.1.3 pH .................................................................................................................... 69 4.2 DISTRIBUTION OF MERCURY AND SELENIUM IN WATER AND SEDIMENTS ………………………………………………………………………………………….71 4.2.1 Mercury levels ........................................................................................................ 71 4.2.2 Selenium levels ....................................................................................................... 72 4.3 MERCURY AND SELENIUM INTERACTION IN AQUATIC ECOSYSTEM ........ 74 4.3.1 Sediments ................................................................................................................ 74 4.3.2 River water .............................................................................................................. 76 4.4 TRACE ELEMENTS IN FISH SPECIES ..................................................................... 78 4.4.1 Bioaccumulation factor (BAF) in fish species ........................................................ 81 4.4.2 Mercury-Selenium concentrations and Bioaccumulation Factors (BAF) in fish parts ………………………………………………………………………………….….81 4.4.3 Mercury and Selenium molar ratios ........................................................................ 84 4.4.4 Relationship between Total Mercury and Selenium in fish species ....................... 85 4.4.5 Selenium association with other elements in fish tissues (Cd, Fe, Zn)................... 87 4.5 MERCURY RELATIONSHIP WITH IRON AND MANGANESE ............................ 90 4.6 SELENIUM RELATIONSHIP WITH IRON AND MANGANESE ............................ 90 4.7 MERCURY RELATIONSHIP WITH TSS AND SULFATE ....................................... 93 4.8 OTHER HEAVY METAL DISTRIBUTIONS ............................................................. 94 4.8.1 Sediments ............................................................................................................... 94 4.8.2 Water samples ........................................................................................................ 98 4.9 WATER NUTRIENTS AND MACRO ELEMENTS (IONS) .................................... 102 4.10 STATISTICAL ANALYSIS ........................................................................................ 104 4.10.1 Coefficient of Variation (Co.V/%) ....................................................................... 104 University of Ghana http://ugspace.ug.edu.gh xii 4.10.2 pH versus Heavy metal content (One way ANOVA) ........................................... 106 4.10.3 Paired Sample T-Test ............................................................................................ 107 4.10.4 Other Physico-Chemical Parameters of Water ..................................................... 108 4.10.4.1 Total Alkalinity............................................................................................. 108 4.10.4.2 Total Hardness .............................................................................................. 108 4.10.4.3 Total Suspended Solids (TSS) ...................................................................... 109 4.10.4.4 Total Dissolved Solids (TDS)....................................................................... 109 4.10.5 Principal Component Analysis (PCA) .................................................................. 111 4.11 DISCUSSION.………………………………………………………………………..115 CHAPTER FIVE ........................................................................................................................ 124 5.0 CONCLUSION AND RECOMMENDATIONS ......................................................... 124 5.1 CONCLUSIONS .......................................................................................................... 124 5.2 RECOMMENDATIONS ............................................................................................. 125 REFFERENCES ......................................................................................................................... 126 APPENDICES ............................................................................................................................ 152 University of Ghana http://ugspace.ug.edu.gh xiii LIST OF TABLES Table 2.1: Summary on the literature review of some trace metals and macro elements ............. 33 Table 3.1: Certified and measured values for standard reference material SO-1 soil .................. 65 Table 3.2: Certified and measured values for standard reference material 1646 A ...................... 66 Table 4.1A: pH Distributions in Water and Sediments Samples .................................................. 70 Table 4.1B: Physical parameters of water and Sediment Samples………………………………70 Table 4.2: Concentrations of trace elements in the dorsal tissues of Clarias submarginatus (Mudfish) ...................................................................................................................................... 79 Table 4.3: Concentrations of trace elements in the different tissues of Xenomystus nigri ........... 80 Table 4.4: Bioaccumulation Factors (BAF) in the tissue parts of Xenomystus nigri .................... 82 Table 4.5: Bioaccumulation Factors in the dorsal tissue parts of Clarias submarginatus ........... 82 Table 4.6: Total Mercury-Selenium molar ratio in Fish Species (Mudfish) ................................. 84 Table 4.7: Total Mercury-Selenium molar ratios in Xenomystus nigri ........................................ 85 University of Ghana http://ugspace.ug.edu.gh xiv LIST OF FIGURES AND PLATES Figure 2.1: Environmental classification of metals courtesy Nieboer and Richardson, 1980.. .... 11 Figure 2.2: Major components of the environmental cycle of mercury ....................................... 17 Figure 2.3: An illustration of the possible mechanism of interaction between selenite and Hg2+ in blood courtesy Yang et al., 2008 .................................................................................................. 22 Figure 3.1: Map of the Lower Pra River and its adjoining tributaries. ......................................... 52 Plate 3.1: A section of the Lower Pra River at Daboase which is a current AGM site ................ 54 Plate 3.2: A section of the Lower Pra River at Beposo which is a current AGM site .................. 55 Plate 3.3: A section of the Lower Pra River at Bokorkope currently not known for AGM operations ...................................................................................................................................... 55 Plate 3.4: A section of the Lower Pra River at Shama estuary which is a coastal plain estuary .. 56 Figure 3.2: Map showing the four sampling site at the lower catchment regions of the Lower Pra River. ............................................................................................................................................. 58 Figures 4.1A-B: Mean concentrations of Total mercury (THg) in sediments (A) and water (B) for both Dry and Wet season for the four locations ........................................................................... 72 Figures 4.2A-B: Mean concentrations of Selenium (Se) in sediments (A) and water (B) for both Dry and Wet season for the four locations in the Study Area. ..................................................... 73 Figures 4.3A-B: Projected bar chart of individual sampling sites showing THg-Se concentration in sediments for both seasons ....................................................................................................... 74 Figures 4.4A-B: Scatter plot diagram showing THg as a function of Se for individual sampling points of sediment for both seasons .............................................................................................. 75 Figures 4.5A-B: Projected bar chart of individual sampling sites showing THg-Se concentration in water for both seasons............................................................................................................... 76 University of Ghana http://ugspace.ug.edu.gh xv Figures 4.6A-B: THg - Se correlation curves of individual sampling sites of water for both seasons .......................................................................................................................................... 77 Figure 4.7: Mercury (THg) and Selenium (Se) Concentrations in the dorsal tissues of Mudfish (Clarias submarginatus) ............................................................................................................... 83 Figure 4.8: Mercury (THg) and Selenium (Se) Concentrations in the different tissues of Xenomystus nigri. ......................................................................................................................... 83 Figure 4.9: Scatter diagram showing the molar concentrations of THg as a function of the molar concentrations of Selenium (Se) across the different tissues of Xenomystus nigri ....................... 86 Figure 4.10: Scatter diagram showing the molar concentrations of THg as a function of the molar concentrations of Selenium (Se) in the dorsal tissues of Mudfish (Clarias submarginatus) ....... 86 Figure 4.11: Scatter diagram showing the logarithm transformation of BAF of THg as a function of the BAF of Se in the different tissues of Xenomystus nigri...................................................... 87 Figure 4.12: Scatter diagram showing the logarithm transformation of BAF of THg as a function of the BAF of Se in the dorsal tissues of Mudfish (Clarias submarginatus) ............................... 87 Figures 4.13 A-C: Scatter diagram showing a plot of Fe, Zn and Cd as a function of Se in various tissue parts of Xenomystus nigri ................................................................................................... 88 Figures 4.14A-C: Scatter diagram showing a plot of Fe, Zn and Cd as a function of Se in the dorsal tissues of Mudfish (Clarias submarginatus). ..................................................................... 89 Figures 4.15A-H: Scatter diagrams showing the correlation curves of THg with Mn and Fe in sediments and water for dry and wet seasons ............................................................................... 91 Figures 4.16A-H: Scatter diagrams showing the correlation curves of Mn and Fe with Se in sediments and water for dry and wet seasons ............................................................................... 92 University of Ghana http://ugspace.ug.edu.gh xvi Figures 4.17A-B: Scatter diagram of averaged THg of locations as a function of Dissolved SO42- (A) and TSS (B) in water for the two seasons .............................................................................. 93 Figures 4.18A-G: Distribution of trace elements in sediments for both seasons .......................... 96 Figures 4.19A-G: Distribution of trace elements in water for both seasons ............................... 100 Figures 4.20A-E: Distribution of ions PO43-, NO3-, K+, SO42-, and Na+ in water ....................... 104 Figures 4.21A-C: Coefficient of variations of studied elements and ions along the watercourse ..................................................................................................................................................... 106 Figures 4.22A-D: Distribution of Physicochemical parameters in the Study Area .................... 110 Figures 4.23: Principal component analysis diagram showing the rotated factor loadings of the principal component (PC1, PC2 and PC3) to a descriptor space of three dimensions. Plot 1 is for sediments for the dry season. Plot 2 is for sediments for the wet season. .................................. 113 Figures 4.24: Principal component analysis diagram showing the rotated factor loadings of the principal component (PC1, PC2 and PC3) to a descriptor space of three dimensions. Plot 3 is for river water for the dry season. Plot 4 is for river water for the wet season. A1, B1, and C1 are for water nutrients NO3-, SO42-, and PO43- respectively. .................................................................. 114 University of Ghana http://ugspace.ug.edu.gh 1 CHAPTER ONE 1.0 INTRODUCTION 1.0.1 Background to study Environmental pollution is one of the major problems nations are facing around the world. In recent times this problem has become more difficult in light of increasing population and industrialization. This increase in population has brought about massive urbanization, industrialization and the depletion of natural resources (Chamie, 2004). Industrial waste may contain contaminants that destroy or alter the environment we inhabit. Many countries ignore industrial waste management since it is expensive. Heavy metals are by- products from many industrial processes and varying amounts are released into the atmosphere, marine and freshwater environment. They affect not only the ecosystems, but also human life through Bio-accumulation and Bio-augmentation in the food chain. They are present in environmental compartments such as water (fresh water and marine systems), soil or sediments and biota but are mostly hazardous when they enter the food chain (Robson and Neal, 1997). Heavy metals are toxic even at very low concentrations (Volesky, 1990; Alkorta et al., 2004). Mineral elements are required by living organisms for growth and development. Mineral elements can be divided into two main groups: essential and non-essential minerals. Each of these groups can be further divided into major (macro) and trace (micro) elements. An essential element is one required for maintenance of life and its deficiency results in an impairment of a function from optimal to suboptimal (Mertz, 1981; Nyarko, 2012). Essential elements needed in large quantities are referred to as macro-element examples are: Hydrogen (H), Carbon (C), University of Ghana http://ugspace.ug.edu.gh 2 Nitrogen (N), Oxygen (O), Magnesium (Mg), Carbon (C), Sodium (Na), Phosphorous (P), Sulfur (S) and Potassium (K). Essential elements are usually bound to proteins and in abnormal quantities are deemed toxic to the organism. These elements include Copper (Cu), Vanadium (V), Magnesium (Mg), Calcium (Ca), Phosphorous (P), Sulfur (S), Potassium (K), Boron (B), Manganese (Mn), Iron (Fe), and Zinc (Zn). Non-essential elements are neither beneficial nor harmful if present in sufficiently low amounts but their deleterious effect begins to show with the gradual accumulation in biological tissues. Examples are heavy metals such as Cadmium (Cd), Mercury (Hg), Arsenic (As), Lead (Pb) among others. These metals are said to be cumulative poisons (Nyarko, 2012). Harrison and De Mora, 1996 reported of a complex relationship between the total concentration of heavy metals in the environment and its ability to cause toxic effect in organisms. Two constraints they identified are the speciation of the element and the condition of the organism. Elemental speciation especially it’s partitioning between host association in aqueous and particulate phase influences bioavailability. Most heavy metals are damaging to marine organisms in their organometallic form. Mercury is a classic example which is mostly bioavailable and toxic as methyl mercury (CH3Hg+). The environmental location and conditions affect the potentially toxic substance in the organism. Specific environmental conditions such as temperature, dissolved oxygen, chemical oxygen demand and pH affect metal-organism interaction. The release of Mercury (Hg) into the environment can be through natural means such as volcanic eruption and weathering as well as a variety of anthropogenic sources such as mining, burning of fossil fuel, and combustion of municipal and medical waste (Oduro et al., 2012; Jackson and University of Ghana http://ugspace.ug.edu.gh 3 Jackson, 1995). Due to its persistence and high mobility, Mercury (Hg) exhibits an age related accumulation and strong bio-magnification in the food web (Nigro and Leonzio, 1996). Artisanal small-scale gold mining (AGM) is the single largest contributor to intentional discharge of mercury (Hg) to the environment with a global estimate of 650-1000 tons of mercury (Hg) released per annum (AMAP/UNEP, 2008). The only source of contamination for areas not known for having direct mercury input is through atmospheric deposition. It is therefore, normally transported from likely sources of emission such as mining and smelter sites to locations remote from the pollution centers (Schroeder and Munthe, 1998). Artisanal Gold miners use simple primitive technology to extract gold from soils and river sands. This process begins with the dredging of river sand and centrifugal separation of the crushed gold ore to produce a concentrate. The concentrate is mixed with mercury in amalgamation drums. Mercury binds to gold in a solution known as an amalgam and this solution is separated from the concentrate matrix by panning (Telmer and Veiga, 2006). Mercury is then recovered from the amalgam by roasting it in partially enclosed retorts or even in the open air. Pure gold produced contains up to 5% mercury (Hg). Mercury not recovered properly adds to atmospheric release especially in towns where Artisanal gold mining (AGM) activities occur. Public concern over mercury pollution reached its peak in the 1970’s following a number of incidents where the discharge of elemental mercury into water bodies was linked to fatalities and severe health problems in local residents (Jackson and Jackson, 1995). The effect of mercury (Hg) pollution may therefore not just be limited to the geographical location of the discharge point (local pollutant) but several kilometers radius (global pollutant) of the point of original discharge (Harada et al., 2001). Mercury (Hg) concentration in sediments have been found to University of Ghana http://ugspace.ug.edu.gh 4 have a strong correlation with soil organic matter since this element in question has the tendency to bind with humate ligands. An abundant organic matter environment favors mercury methylation due to bacteria action (Pak and Bartha, 1998; Gilmour et al., 1992). Several studies have reported that the level of one element is affected by the presence of the other one (Feroci et al., 2005). Parizek, 1978 proposed a direct or indirect interaction (or combination) for complexes of some elements (i.e., Hg and Se). Direct interactions are mainly test-tube type reactions of the elements in question without the involvement of living matter. In other cases, a metabolic conversion of at least one of the interacting elements (compounds) would have to occur within the organism to make the interaction possible. An indirect interaction may involve effects by one element or compound on any metabolic function affecting the other. Membrane function may be impaired by one element or compound, causing an alteration of membrane passage of the other. This eventually results in an increase or decrease of the toxic form of the element or compound at the receptor sites (Skerfving, 1978). The antagonistic phenomenon between selenium (Se), both an essential and a toxic trace element and mercury (Hg) was first reported by Parizek and Ostadalova, 1967. Several mechanisms have been proposed for mercury (Hg) and selenium (Se) interaction. The most prominent is the formation of an inorganic and (or) protein Hg-Se complex although this complex formation remains unclear. Numerous other studies have been conducted between the two elements in mammals and the findings tend to support an antagonistic effect between selenium (Se) and mercury (Hg). Since most of the studies have been conducted on mammals with an almost 1:1 Hg/Se molar ratio established in various mammalian organs, the study of Hg and Se especially in fish food University of Ghana http://ugspace.ug.edu.gh 5 and in aquatic environment will provide more information on the antagonistic effect of Se on Hg especially the bioaccumulation of Hg in the presence of Se in Hg contaminated water bodies. 1.1 PROBLEM STATEMENT The Pra river system, the longest in south western Ghana, takes its source from the Kwahu plateau and flows 240 km into the Gulf of Guinea through its estuary at Shama (Ayibotele and Nerquaye-Tetteh, 1989, Oduro et al., 2012). The river is divided into two parts which is the Upper and Lower Pra. The upper part of the main Pra river watercourse and its main tributaries are known to have direct input of mercury due to Artisanal Gold Mining (AGM) operators popularly known as galamsay operators and the mode of extraction of gold is through amalgamation (Bonzongo et al., 2003; Spiegel, 2009; Donkor et al., 2006a, b). According to Donkor et al., 2006b, the communities along the lower reaches of River Pra were widely acclaimed to have no direct Hg input source since these areas were not known for AGM activities. From their studies, traces of Hg were found in sediments and in River water at areas of the lower catchment regions of the Lower Pra River not known for AGM activities. There is even a greater worry as these AGM operators pollute the water body with their effluent and destroy the entire ecosystem. When they are done, they migrate to new areas along the watershed to continue their activities. Presently AGM activities are found in areas such as Beposo and Daboase located in the lower region of the Lower Pra catchment area and previously not known for AGM operations. In their operations, they make use of mobile rigs which constitute rafts with mechanized dredging equipment mounted on them. They also heap piles of sand into the river which aids in their operations (Oduro et al., 2012). University of Ghana http://ugspace.ug.edu.gh 6 The discharges of Hg from mining effluent into the river along with other contaminants affect the water quality thereby increasing the cost of water treatment at the water treatment plant located at Daboase. In June of 2013, the Minerals’ Commission together with the Ghana Military raided certain AGM sites especially at Beposo and Daboase in the Shama and Mpohor Wassa district respectively in an attempt to clamp down on the activities of illegal gold miners (Ghana News Agency, 2013). Selenium (Se) has been known to have an antagonistic effect on Hg from polarography studies where investigations into the standard redox potential of mercurous salts and various organic selenium compounds in unbuffered systems clearly exhibited this phenomenon (Feroci et al., 2005). However few studies have been conducted in natural systems especially in aquatic environments on this phenomenon. The investigation of both Se and Hg in various aquatic components will shed more light on the relationship between the two elements (possible antagonism) and the relationship the two elements have with other trace elements. This study firstly is aimed at assessing the levels of Hg pollution in the Lower Pra Shama - Mpohor Wassa catchment area river water to explore the possible impact of Hg pollution on water supply and secondly to investigate the possible antagonistic effect of Se on the toxicity of Hg in various aquatic components such as fish, sediments and river water. 1.1.1 Research hypothesis This study was carried out on the bases of the following hypothesis  Ho : Hg is used by AGM operators in the extraction of gold Ha : Hg is not used by AGM operators in the extraction of gold University of Ghana http://ugspace.ug.edu.gh 7  Ho : Hg is known to travel several kilometers from source of pollution Ha : Hg is not known to travel several kilometers from source of pollution  Ho : Se plays an important role in the antagonism of Hg Ha : Se does not play an important role in the antagonism of Hg  Ho : Water physicochemical parameters differs significantly with seasonal changes Ha : Water physicochemical parameters do not differ significantly with seasonal changes 1.1.2 Study objectives The main objective of the study are to determine the concentration levels of Hg and Se in water, fish, and sediment samples from the lower catchment regions of the Lower Pra River and how these elements if present affect each other. Specifically, the study seeks to:  Determine the concentration of Mercury (Hg) together with Selenium (Se), Cadmium (Cd), Lead (Pb), Copper (Cu), Iron (Fe), Manganese (Mn), Nickel (Ni), Chromium (Cr), and Zinc (Zn) in the major environmental compartments: water, sediment and fish  Assess the relationship of Hg and Se on other elements and certain Physico-Chemical parameters like pH in the study area  Assess the spatial and temporal variation of trace elements and water Physico- Chemical parameters along the water course  Investigate the levels of microbial contamination in water as a potential cause of waterborne diseases University of Ghana http://ugspace.ug.edu.gh 8  Determine the overall quality of water as source for direct consumption and for the water treatment plant situated at Daboase University of Ghana http://ugspace.ug.edu.gh 9 2 CHAPTER TWO 2.0 LITERATURE REVIEW 2.1 DEFINITION AND PROPERTIES OF HEAVY METALS Different definitions have been proposed for the term heavy metals – some based on density or specific gravity, some on atomic number or weight and some on chemical properties or toxicity. Bjerrum, 1936 defined heavy metal as metals with elemental densities above 7 g/cm3 whereas Morris, 1992 based his definition on greater than 5 g/cm3. The terminology is sometimes applied indiscriminately and it is not unusual to find a list of heavy metals that includes elements like aluminum (Atomic mass 26.98 gmol-1 and specific gravity of 2.7). Some studies have used the terms trace or toxic elements in place of heavy metals. Glanze, 1996 reported of 35 metals of environmental concern due to occupational or residential exposure; 23 of these were "heavy metals": antimony (Sb), arsenic (As), bismuth (Bi), cadmium (Cd), cerium (Ce), chromium (Cr), cobalt (Co), copper (Cu), gallium (Ga), gold (Au), iron (Fe), lead (Pb), manganese (Mn), mercury (Hg), nickel (Ni), platinum (Pt), silver (Ag), tellurium (Te), thallium (Tl), tin (Sn), uranium (U), vanadium (V) and zinc (Zn). Heavy metals exist either in the solid phase or in solution as free ions and are associated with several soil components which determines their bioavailability (Track et al., 2006). They have variable oxidation states, paramagnetic and form colored complex ions. Heavy metals are non- biodegradable, non-thermodegradable, possess long biological half-lives and residence times. University of Ghana http://ugspace.ug.edu.gh 10 2.2 SOURCES OF HEAVY METALS A natural source of heavy metals into the environment is volcanic eruption through volcanic ash. Nriagu, 1990 reported that volcanic activity is one major source of atmospheric cadmium and it is estimated to contribute about 820 metric tons each year. Heavy metals occur as constituents of primary and secondary minerals through the process of inclusion, adsorption and solid solution formation termed as co-precipitation (Sposito, 1989). Atmospheric depositions as a result dust storms and wild forest fires are other natural source of heavy metal pollution (Nriagu, 1990; Nadiu et al., 1997). Anthropogenic sources of heavy metals include Agricultural activities such as pesticide, fertilizer, herbicide application, and contaminated irrigation water sources. Also industrial activities such as mining and smelter, the use of lead and manganese as anti-knock agents in gasoline, exhaust fumes from cars (Nriagu, 1990; Kakulu, 2002), heavy metal additives in building materials like paints, aerosol and sewage discharge, among others, contribute to the pollution load in the environment (Manoj et al., 2012). 2.3 AN ENVIRONMENTAL CLASSIFICATION OF METALS A more recent attempt at classifying environmentally important metals has been made by Richardson and Nieboer, 1980. Their system builds on the earlier concepts of Ahrland et al., 1958 but takes into account bonding due to both covalent and ionic interactions. The covalent index X2mr (Xm = metal ion electronegativity, r = ionic radius of metal) is a reflection of the ability of the metal to accept electrons from a donor ligand. This is the chemical parameter used in differentiating between classes A, B and borderline metals as suggested by Ahrland et al., 1958. Values for the index are smallest for class A and largest for class B ions. The ionic index University of Ghana http://ugspace.ug.edu.gh 11 Z2/r measures the possibility of ionic bond formation and thus more highly charged species tend to be found on the right-hand side of the diagram. Elements such as potassium (K) and calcium (Ca) which serve as macro-nutrients for micro- organisms, plants and animals are found in class A. When dissolved in water and in their interaction with complexing ligands, they are usually found to be associated with oxygen electron donors. Most biological micronutrients such as manganese (Mn), copper (Cu), and zinc (Zn) are found in the borderline group. Borderline ions form stable complexes with a variety of electron donor atoms such as oxygen, nitrogen, and sulfur. Class B metals include several that Figure 2.1: Environmental classification of metals courtesy Nieboer and Richardson, 1980. Subdivisions are based on Ahrland et al., 1958, classification indicated by horizontal lines. University of Ghana http://ugspace.ug.edu.gh 12 are known to be toxic to organisms. Toxicity increases in the order Class A< borderline < Class B metals. While Class B ions have a stronger affinity for sulfur donor atoms, they also form more stable complexes with oxygen-donating compounds than do borderline and Class A metals (Figure 2.1). The ability to form methylated derivatives that are stable in aqueous solutions is another feature that is characteristic of metals in this class (eg mercury (Hg)). Methyl derivatives of Class A metals decompose in water and the same is true of most of most borderline metals. 2.4 OVERVIEW OF RESEARCH OF MERCURY IN GHANA Artisanal gold mining (AGM) is one such anthropogenic activity that has resulted in the use of an enormous amount of metallic mercury (Appoh, 2010). A lot of studies have been carried out worldwide to investigate the impact of AGM operations on the environment in locations known to have gold deposits. Several studies have been carried out on mercury in Ghana particularly in areas known for gold mining. Most of the researches have been based on rivers and streams particularly in the southwestern belt of Ghana due to the alluvial deposits of gold by these water bodies. For instance Donkor et al., 2006b and Oduro et al., 2012 all studied total mercury (THg) in the Lower Pra River which serves as source for drinking water for communities along the basin. Donkor et al., 2006b reported that THg levels in drinking water were below the WHO guideline values of 1000 ng/L but were above the standard of 12 ng/L set by the USEPA for the protection against chronic effect to aquatic wildlife. Oduro et al., 2012 reported of THg levels in drinking water above the WHO guideline limits in communities where the studies were carried out. Bannerman et al., 2003 reported of THg and Arsenic (As) contaminations in water and sediments University of Ghana http://ugspace.ug.edu.gh 13 in gold mining regions in the Ankobra river basin. Hayford et al., 2008 investigated the presence of toxic elements including THg in samples of cassava, plantain and soil from mining communities around Tarkwa. They reported that THg levels in cassava, plantain and soil were higher than the permissible values proposed by the FAO for food and the WHO for soil. Some studies have also been conducted on fish species, human head hair, urine and blood in gold mining areas. Voegborlo et al., 2010 assessed both THg and methyl mercury (MeHg) in human head hair to evaluate the extent of human exposure to mercury. They reported that 97% of Hg in the human head hairs was in its toxic form which is MeHg. THg was also assessed in muscles of fish by Ntow and Khwaja, 1988 from various coastal towns and Agorku et al., 2009 from water reservoirs for hydroelectric power generation. Both studies reported that THg levels in fish muscles were below WHO limit of 0.5 µg/g since the aquatic environment have not been significantly impacted with mercury. In spite of all these studies, there is still a need for a continuous environmental assessment of mercury and this time around its interaction with selenium since the relationship between the two elements remains unclear to several researchers and hence the result obtained will provide an insight at a possible relationship between the two elements. 2.5 MERCURY 2.5.1 Chemical fate Mercury is generally found at very low concentrations generally less than 10ng/g in crustal materials such as granites, feldspars and clays (Davis et al., 1997), and in the range of 40 to 200ng/g in soils and sediments that are not directly impacted by anthropogenic discharges (NRC, University of Ghana http://ugspace.ug.edu.gh 14 2002). Mercury is found generally in aquatic systems in its organic form (about 95 to 99%) and in sediments rather than the dissolved phase. Mercury (Hg) occurs in traces in ore deposits and together with sulfur as Cinnabar (HgS). Anthropogenic sources of mercury (Hg) include various industrial discharges and abandoned mines, coal combustion and medical waste incineration. Inorganic mercury exists in three known oxidation states: as elemental mercury (Hg°), as mercurous ion (Hg+) and as mercuric ion (Hg2+). The oxidation state of mercury in an aqueous environment is depends on the redox potential, the pH, and the nature of the anions and other chemical forms present with which mercury may form stable complexes (Reimers et al., 1974). Mercurous compounds (Hg+) are not common as they are rapidly oxidized to mercuric forms (Hg2+) by hydrolysis (Booer, 1944). The presence of organic matter in the sediments can either enhance or retard mercury mobility by either forming soluble organic complexes or the precipitation of mercury as mercuric sulfides (HgS). In highly anaerobic systems, the mercuric sulfide may be reduced to elemental mercury and sulfide, whereas under alkaline conditions with high levels of sulfides the more soluble mercuric disulfide complex (HgS22-) may exist. In general, the sediment water interface tends to accumulate inorganic mercury, and both pore water and the water column are possible sites for mercury methylation since these sites are rich in organic ligands (NRC, 2002). An important characteristic of mercury is its low solubility as a result of its high probability to coagulate, i.e., to be removed from the soluble aqueous phase. This occurs through a number of physicochemical processes such as precipitation as mercuric sulfide, co-precipitation with hydrated iron and manganese oxides and complexation with organic matter. The solubilization /coagulation of mercury depends on the forms of mercury University of Ghana http://ugspace.ug.edu.gh 15 present, the amounts and nature of the organic and inorganic matter present, as well as on the environmental conditions, e.g., pH, chloride levels (NRC, 2002). Balogh et al., 1998 showed that total mercury levels in water are strongly correlated with total suspended solids concentrations, suggesting that mercury can remain suspended in the water column attached to colloidal and particulate matter. Pak and Bartha, 1998, reported that in aquatic systems, dissolved mercury can be partitioned between inorganic and organic forms largely controlled by rates of methylation and demethylation by microorganisms. Organic mercury complexes remain important influences on the mobility and bioavailability of mercury. Dissolved mercury in natural water systems exists mostly in organic forms and a high level of mercury in fish tissues is observed by Gill and Bruland, 1990. Mercury methylation is a biologically mediated process between dissolved inorganic mercury and, primarily, sulfate reducing bacteria (Driscoll et al., 1994). Factors affecting methylation of mercury aquatic system include the amount of dissolved inorganic mercury and physicochemical characteristics of the aquatic system such as pH, organic matter, dissolved sulfate and sediment sulfide (Pak and Bartha, 1998). For example, mercury methylation activity in sediments was found to be positively correlated with the level of organic matter (Driscoll et al., 1994). Methylation occurs under anaerobic conditions via a pathway which involves the transfer of a methyl group from methylcobalamin, a derivative of vitamin B12 to the mercury atom under reducing conditions. methyl Cobalamin (ATP)+ Hg2+Co Co + CH3Hg+ or (CH3)2Hg [1] The relative abundance of methylated mercury species is of particular concern since these compounds are highly toxic, bioavailable and can enter the food chain by direct uptake from Courtesy Nutifafa, 2007 University of Ghana http://ugspace.ug.edu.gh 16 solution (Driscoll et al., 1994). Methyl mercury is unique since the methyl group induces lipophilicity whiles Hg (II) has a tendency to bind with sulfhydryl (or selenol) groups (Craig, 1986; Carty and Malone, 1979). The bond between mercury and the methyl group is stable, while methyl mercury is membrane permeable and thiol reactive, properties which contribute to the toxicity, long biological half-time, and the tendency toward bioaccumulation of mercury in aquatic organisms (NRC, 2002). The organomercuric salts exhibit properties and reactions similar to those of inorganic mercuric salts, and thus do not bioaccumulate as well as methyl mercury. Organomercuric compounds other than methyl mercury species are volatile, thermally unstable, light sensitive and decompose by ultraviolet radiation to elemental mercury and free radicals (NRC, 2002). 2.5.2 Mercury in mine effluents and receiving waters Effluent from mines most likely contains dissolved inorganic species of mercury. Depending on the pH two species of inorganic mercury may exist. At high pH, hydrated mercuric oxide (HgO·H2O) is the dominant form whiles mercuric chloride (HgCl2) exists at low pH and aerobic conditions. However, at high concentrations of chlorides (and low pH), the very stable and water-soluble mercuric tetrachloride complex (HgCl4) will form. A variety of biogeochemical conditions may influence the behavior of mercury in the receiving environment. The formation and dissolution of inorganic Hg solids is controlled by redox and pH conditions and redox conditions in particular occur over a wide range in surface water environments (NRC, 2002). University of Ghana http://ugspace.ug.edu.gh 17 2.5.3 Interactions with Other Mineral Element Dissolved mercury adsorbs strongly to sediment and suspended solids including organic material and Fe or Mn oxy-hydroxides (Balogh et al., 1998). Gagnon and Fisher (1997) reported the binding strength of mercury to sediments to be very high at near neutral pH values and little desorption (less than 10%) at lower or acidic pH values (pH <5). The tendency of inorganic mercury and mercury bound organic complexes to adsorb onto these iron oxy-hydroxide surfaces decreases mercury mobility in water (Schutler, 1997). 2.5.4 Mercury environmental cycle Biosphere Plants, Fish average concentration 100- 200ngg-1 Atmosphere Atmospheric global concentration 0.05 to 5ng m-3 Hg0 (g), (CH3)2Hg0(g) Hg Hydrosphere Lithosphere Precipitation Volatilization Precipitation Coal Combustion Volatilization Decomposition Uptake Uptake, CH3Hg+ Decomposition Sea salt Spray Seawater average 1ngL-1 HgCl3-, HgCl4- Freshwater Hg (OH)20, HgCl20 Leaching Sedimentation Crustal average abundance 89 ngg-1 HgS, Hg0 Soil average concentration 60ngg-1 Figure 2.2: Major components of the environmental cycle of mercury (Mason et al., 1994; Mason and Sheu, 2002) University of Ghana http://ugspace.ug.edu.gh 18 2.6 SELENIUM Total selenium concentrations in natural waters have been reported to be in the range of 0.1 to 1.5 mg/L (Demayo et al., 1979). Natural selenium concentrations in solids range from 0.05 mg/g in ultramafic to felsic igneous rocks, up to 0.08 mg/g in limestone and as high as 0.6 mg/g in shale’s (Faure, 1991). Selenium is a metalloid and resembles sulfur in many of its properties and often occurs together with or substituted for sulfur in soils and rocks. For example, selenide can substitute for sulfides in pyrite and is known to accumulate to 300 mg/g in sedimentary pyrite. Selenate can also substitute for sulfate in very hydrous sulfate salts such as jarosite, but does not substitute for sulfate in less hydrous sulfate salts such as gypsum. Anthropogenic sources of selenium include copper, lead and nickel refining and sulfuric acid manufacturing. Selenium is an essential element, with a recommended daily intake of 1.7 mg/Kg body weight for infants, and 0.9 mg/kg body weight for adults. Most of the natural human intake arises from food (approximately 75%) with the remainder coming mainly from drinking water (WHO, 1996). 2.6.1 General Fate Information Selenium exists in four oxidation states in the natural environment - selenide (Se2-), elemental selenium (Se0), selenite (Se4+) and selenate (Se6+). Selenium cycling in the environment is controlled by biogeochemical processes. Microbial methylation is an important pathway of the biogeochemical selenium cycle (Doran, 1982). Organic forms of selenium include seleno amino acids, methyl selenides, methyl seleninic esters, methyl selenones, and methylselenonium ions (Cooke and Bruland, 1987). These organic compounds occur as products of bio-methylation and are more volatile than inorganic forms of selenium (Atkinson et al., 1990). Bacterial selenium methylation occurs in temperate lake sediments (Chau et al., 1976) and is stimulated by organic University of Ghana http://ugspace.ug.edu.gh 19 carbon and temperature (Chau et al., 1976; Doran, 1982; Thompson-Eagle and Frankenberger, 1990a, 1990b). The greatest proportion of total selenium in lakes and streams can normally be found in the sediments, reflecting a net removal of selenium from the water column (Cutter, 1989; Lemly and Smith, 1987). Cutter (1985, 1989) examined sedimentary selenium by sequential extraction of sediments. The selenide (Se2-) plus elemental selenium (Se0) fraction (calculated as the difference between 'total' selenium and (selenite plus selenate) accounted for more than 93% of sedimentary selenium in five lakes. Sequential extraction has also shown that more than 90% of the sedimentary selenium is associated with organic matter and is identified as Se-2 plus Se0, while less than 10% of the sedimentary selenium is associated with iron and manganese oxides (Cutter, 1989). Rudd et al., 1980 studied selenium scavenging by sediments and demonstrated that selenium sedimentation was effectively halted by sealing off the bottom of an experimental mesocosm from the sediments. These results suggest further that selenium can be effectively scavenged by natural sediments and that sediments are an important sink for selenium loadings from mining. Dissolved inorganic selenium occurs in mining effluents as both selenite (Se4+) and selenate (Se6+) oxidation states. Inorganic selenium speciation is controlled by redox conditions, pH, and complexation with metals and interactions with solids such as sorption processes. Selenate (SeO42-) predominates under alkaline oxidizing conditions whilst under moderately oxidizing conditions, the selenious acid species selenite (SeO32-) and biselenite (HSeO3-) predominate. Elemental selenium (Se0) is relatively stable at all pH values in waters that are free of oxidizing and reducing agents (Faust and Aly, 1981). Selenide, primarily as hydrogen selenide University of Ghana http://ugspace.ug.edu.gh 20 (HSe-) can form in environments with a large reservoir of free electrons, such as organic rich sediments. An important process regulating the dissolved concentration and mobility of inorganic selenium is adsorption onto solid surfaces (Balistrieri and Chao, 1990). Selenite (Se4+) efficiently adsorbs onto both iron and manganese oxides. Selenite (Se4+) adsorption decreases with increasing pH and is further inhibited by the presence of dissolved phosphate, silicate, and molybdate (Balistrieri and Chao, 1990). Selenate (Se6+) rather adsorbs weakly to clays and Fe oxy- hydroxides and does not adsorb to manganese oxides. Selenate adsorption (Se6+) is further limited by competitive effects with sulfate at neutral pH. Therefore, sorption reactions can reduce concentrations of dissolved selenite but do not significantly influence selenate concentrations, particularly in sulfate rich waters. 2.6.2 Selenium and Mercury in Organisms: Interactions and Mechanisms There are numerous possible mechanisms for the interaction between mercury and selenium. In principle, the interaction may be direct or indirect (or a combination). A direct interaction may involve formation of complexes between some chemical form of selenium and some chemical form of mercury, the simplest possibility being mercury selenide (Hg-Se), although different complexes may be anticipated. Also, selenium and mercury may compete for binding sites in proteins (most probably thiols) or other compounds. A competition may occur at the "receptor sites" where mercury and selenium exert their toxic effects, but a complex binding or a competition at other binding sites may also affect the metabolism (absorption, distribution, biotransformation or excretion) which may affect the "receptor site" concentration secondarily (Skerfving, 1978). University of Ghana http://ugspace.ug.edu.gh 21 An indirect interaction may involve effects by one compound on any metabolic function affecting the other. A competition may occur on the "receptor sites" where mercury and selenium exert their toxic effects, but a complex binding or a competition at other binding sites may also affect the metabolism (absorption, distribution, biotransformation or excretion) which may affect the "receptor site" concentration secondarily. There are numerous possibilities. Enzyme systems performing biotransformation of one compound may be affected by the other, or membrane function may be impaired by one compound, causing an alteration of membrane passage of the other (Skerfving, 1978). Parizek and Ostadalova, 1967 reported the toxicity of Hg2+ to be reduced when Hg2+ doses of 0.002 mmol/Kg body weight was administered to rats followed by the same dose of selenite (SeO32-) one hour later. It was observed by Burk et al., 1974 that the intravenous co- administration of rats with mercuric chloride and sodium selenite resulted in an increased presence of Hg and Se in the bloodstream and this was caused by the presence of a single compound with a Hg:Se molar ratio of 1:1. Burk et al., 1974 and later Naganuma and Imura, 1980 proposed that both elements bind to a single plasma protein to form high molecular weight complexes (HMWC). Burk et al., 1974 and Naganuma et al., 1984 proposed that the interaction between Hg2+ and selenite which occurred primarily in the blood stream resulted in HMWC assimilation by the liver (Imura and Naganuma, 1985). HMWC might undergo proteolytic processes to form insoluble inert Hg-Se complexes that subsequently accumulate in liver tissue (Nagamuna and Imura, 1981). Selenoprotein-P in plasma was found to bind Hg and Se when Hg2+, selenite (SeO32-), and glutathione (GSH) were added to serum of rats. This complex is described as {(Hg- Se)n}m-Selenoprotein-P, where n is the number of atoms forming the colloidal mercuric- University of Ghana http://ugspace.ug.edu.gh 22 selenide complex and m as the number of binding sites for the mercuric selenide complexes on Selenoprotein-P ( Yoneda and Suzuki, 1997). After entering the bloodstream selenite is rapidly taken up by erythrocytes and reduced by glutathione (GSH) to selenide (HSe-), which effluxes and reacts in plasma with albumin bound Hg2+ (Gailer et al., 2000) to form the {(Hg-Se)n}m-Selenoprotein-P complex in blood. Extended studies showed that the (Hg-Se) complex had a five molecule GSH bounded to it and this made it water soluble. Two molecules of -GSH could be stripped off, and therefore the final complex would be {(Hg-Se)100(GS)3}35-selenoprotein-P (Yang et al., 2008). A synergistic toxicity between dimethylselenide ((CH3)2Se) and Hg2+ has also been reported when selenite was given 1hr before Hg2+, causing the death of a rat (Parizek 1980; Naganuma et SeO32- HSe- 5GSH SeO32- (Injection) Blood GI-tract (Reduction) Erythrocyte (Absorption) SeO32- Hg2+ Hg2+-albumin (HgSe)100(GS)5 [(HgSe)100(GS)3]35 - Selenoprotein P Selenoprotein P 35× (HgSe)100(GS)5 35× 2GSH Figure 2.1: An illustration of the possible mechanism of interaction between selenite and Hg2+ in blood courtesy Yang et al., 2008 University of Ghana http://ugspace.ug.edu.gh 23 al., 1984). The dead animal showed symptoms of dimethylselenide intoxication, and the death was thought to be caused by the synergistic effect of Hg2+ and dimethylselenide generated from selenite metabolism. Dimethylselenide in the presence of Hg2+ have been shown to be more than 10000 times toxic than when administered alone (Parizek, 1980). Three other Se compounds, selenite, selenocystine, and selenomethionine, have been less frequently used than selenite (SeO32-) in studies on the antagonism with Hg2+. Since all of the above forms of selenium could be transformed to Se2-, a metabolic intermediate generated in vivo and which will interact with Hg2+ to form Hg-Se complexes (Yang et al., 2008). Methyl mercury might undergo hemolysis in the body to form .CH3 radicals and inorganic Hg (Hg0 and Hg2+), which lead to the generation of reactive oxidative species (ROS) and the inhibition of oxidative enzymes (Ganther 1978; Atchison and Hare, 1994; Garg and Chang, 2006). The formation of the non-bioavailable Hg-Se complex affects selenium availability for selenoprotein synthesis. Sufficient selenium should not only guarantee the amount needed for selenoprotein synthesis, but also bind to Hg2+ released from CH3Hg+ breakdown to form Hg-Se in vivo. Selenium could be a scavenger of inorganic mercury resulting from the demethylation of methyl mercury (CH3Hg+). It was proposed by Watanbe, 2002 that Se2- can co-exist close to CH3Hg+ and react with the demethylated Hg2+ to form Hg-Se complex. Reaction mechanisms for the breakdown of methyl mercury (CH3Hg+) by radical attack are summarized below: University of Ghana http://ugspace.ug.edu.gh 24 Selenium may be actively involved in the demethylation process. Magos et al., 1979 reported of a decomposition of (CH3Hg)2Se resulted in the loss of mercury (Hg) and the formation of HgSe. Iwata et al., 1982 reported of a gradual demethylation to generate inorganic mercury (Hg) when methyl mercury chloride (CH3HgCl) was incubated with GSH and sodium selenite. Similar observations were reported when L-cysteine, 2-mercatoethanol or sodium selenite was used. Reactions are summarized below: In vivo tests showed that CH3Hg+ may act as a methyl donor for the methylation of selenium, rendering it demethylated. Yamane et al., 1977 found that the carbon atom in the 14C-labeled CH3Hg+ appeared to end up as a 14CH3-Se-14CH3 compound in rats treated with methylated [2] CH3Hg+ ·CH3 + ·Hg+ [3] 2Hg [4] 2·Hg+ Hg0 + Hg2+ Hg2+ [5] Oxidation Oxidation [6] Selenocompounds Metabolism Se2- [7] Se2- + Hg2+ HgSe deposits [8] Selenocompounds [with – SeH groups] + Hg2+ Hg- selenocompounds + 2H+ Yang et al., 2008 Reduction (by GSH, L-cysteine, 2- mercatoethanol) or Na2S [9] SeO32- Se2- [10] Se2- + 2CH3Hg+ CH3Hg-Se-HgCH3 HgSe + CH3HgCH3 University of Ghana http://ugspace.ug.edu.gh 25 chloride and sodium selenide. Se2- and compounds with –SeH groups produces superoxide radicals (Spallholz, 1994), which may attack CH3Hg+ to form inorganic mercury. It is not expected that selenium at normal levels inside the cell would produce significant levels of radicals to initiate demethylation. However higher levels of superoxides are produced when selenium is supplemented in diet leading to toxicity. R -SeH GSH GSSH H2Se O2 .O2 - - Inorganic Hg CH3Hg + Se[11] The methylation of Hg2+ in the environment to CH3Hg+ mainly happens in aquatic and wetland systems and the most important factors that influence this process include temperature, pH, organic material content, redox conditions, microbiological activity, salinity and sulfide concentration (Ullrich et al., 2001). Recent field studies on aquatic organisms by Belzile et al., 2006 and Chen et al., 2001 at different trophic levels have shown that both Hg and CH3Hg+ concentrations decreased with increasing concentrations of total dissolved selenium in lake waters and total selenium in tissues of the studies biota. Possible mechanisms to explain the interactions in aquatic systems include: [12] Hg2+ + Se2- HgSe [13] Hg0 + Se0 HgSe It is possible for Hg2+ to react first with Se2- ions to form the inert Hg-Se complex (eqn 12). Mercuric selenide is also expected to form when Hg0 and Se0 come into contact (eqn 13). In consequence, the methylation of mercury (Hg) in aquatic systems would be stopped or at least University of Ghana http://ugspace.ug.edu.gh 26 greatly reduced if precipitation occurs. Se2- (or HSe-) and Se0 is generated in aquatic systems through the metabolisms mediated by microorganisms (Heider and Bock, 1993; Losi and Frankenberger, 1997; Hockin and Gad, 2003). Elemental selenium can also be produced abiotically, for example by the reduction of selenite under anoxic conditions in the presence of Fe2+ or dissolved sulfide (Trulong et al., 2005). Photolysis is one of the most significant abiotic demethylation processes in the environment reported by Ullrich et al., 2001 and sulfides were found to stimulate such a process. Methyl mercury (CH3Hg+) in the form of CH3HgS-, (CH3Hg)2S, and CH3Hg-thiol complexes can decompose much faster under U.V. radiation to generate mercuric sulfides (HgS) precipitate. Other forms such as methyl mercury hydroxide (CH3HgOH) or methyl mercury chloride cannot undergo decomposition due to their weak absorption capacity (Baughman et al., 1973). Studies have also found that organisms living in lakes with higher concentration of selenium (Se) assimilated higher concentration of selenium (Se) in their body (Chen et al., 2001; Belzile et al., 2006). However, there was no biomagnification of se along the aquatic food chain but rather a decrease in concentration was noticed due to biomass dilution (Yang et al., 2008). Ganther and Corcoran, 1969 found that selenite (SeO32-) can react with –SH groups of ribonuclease, to form – S-Se-S bond. This prevents CH3Hg+ from binding to these blocked sites therefore promoting its excretion. [14] HS + 2CH3Hg+ H3CHg-S-HgCH3 H3C-Hg-CH3 + HgS University of Ghana http://ugspace.ug.edu.gh 27 2.7 CADMIUM 2.7.1 Chemical fate Cadmium (Cd) is a soft, ductile, silver-white metal that belongs together with zinc (Zn) and mercury (Hg) to group IIb in the Periodic Table. It has relatively low melting (320.9 °C) and boiling (765 °C) points and a relatively high vapour pressure. The average concentration in the earth’s crust is about 0.2 mg/Kg widely distributed in rocks, sediments and soils (Manson and Moore, 1982). Cadmium (Cd) is rapidly oxidized in air into cadmium oxide. Cadmium (Cd) is widely distributed in the earth’s crust and rarely found as a pure metal. Cadmium (Cd) and zinc (Zn) frequently undergo geochemical processes together. Cadmium (Cd) is also an inevitable by-product of zinc (Zn), lead (Pb) and copper extraction (ATSDR, 1999). Cadmium (Cd) exists in water as hydrated ion, as inorganic complexes such as carbonates (CO32-), hydroxides (OH-), chlorides (Cl-) or sulfates (SO42-), or as organic complexes with humic acids (Sauve et al., 1999). Cadmium (Cd) may enter aquatic systems through weathering, erosion of soils and bedrock, and atmospheric deposition or direct discharge from industrial operations. Much of the cadmium (Cd) entering fresh waters from industrial sources may be rapidly adsorbed by particulate matter, and thus sediment may be a significant sink for cadmium emitted to the aquatic environment (WHO, 1992a, b). Once cadmium (Cd) enters sediments, it can react with sulfur and form relatively insoluble cadmium sulfides (CdS). Partitioning of cadmium (Cd) between the adsorbed-in-sediment state and dissolved-in-water state is, therefore, an important factor in the bioavailability of cadmium. Non-ferrous metal smelting contributes approximately 76% of the anthropogenic cadmium (Cd) emissions, while fossil fuel combustion accounts for the remaining 24% (Nriagu, 1980). University of Ghana http://ugspace.ug.edu.gh 28 Cadmium (Cd) also has a long residence time in the atmosphere which aids its long range atmospheric transport. Anthropogenic emissions of cadmium are usually associated with the release of nitrogen and sulfur oxides. Cadmium (Cd) concentration in freshwater is typically inversely related to pH (Breder, 1988; Stephenson and Mackie, 1988) and may be retained for longer periods in the water column of acidified lakes relative to non-acidified lakes. Cadmium (Cd) is normally partitioned to the particulate phase and rapidly deposited to sediments (Breder, 1988). 2.7.2 Toxicity of Cadmium (Cd) Cadmium (Cd) bioaccumulates in terrestrial and aquatic species. Accumulation half-life is in order of years to decades (Eisler, 1985; Norberg et al., 1985; WHO, 1992a, b). Bioaccumulation primarily takes place in target organs such as the kidney and liver (Nordberg et al., 1985). In fish, the gill is the target organ of toxicity under conditions of acute waterborne exposure. The toxicity and bioaccumulation of cadmium is a function of free ion activity (Sprague, 1985) and is therefore affected by interactions with other inorganic elements particularly calcium (Ca), magnesium (Mg), zinc (Zn), copper (Cu), and iron (Fe) (Spivey-Fox, 1988). More importantly the toxicity of cadmium (Cd) ultimately involves the disruption of calcium (Ca) metabolism. Low-dose exposure to elevated cadmium (Cd) over a long period can cause adverse health effects such as gastrointestinal, hematological, musculoskeletal, renal and respiratory effects. Cadmium (Cd) poisoning may lead to cardiac failure cancers, osteoporosis, proteinuria, emphysema and cerebrovascular infarction associated with long term exposure to cadmium (Cd) (Hallenbeck, 1894), cataract formations in the eyes (Ramakrishma et al., 1995) and kidney University of Ghana http://ugspace.ug.edu.gh 29 diseases (Jarup et al., 2000). Cadmium (Cd) has been classified as a carcinogen (Achanzar, 2001), developmental toxicant (Turgut et al., 2005) and reproductive toxicant (Correa, 1996). 2.8 LEAD 2.8.1 Chemical fate The atomic number of lead (Pb) is 82 and atomic mass is 207.2 g/mol. It has a melting point of 327 ˚C, a boiling point of 1755 ˚C and a density of 11.34 g/cm3 at 20 ˚C. The main lead (Pb) mineral is galena (PbS), which contains 86.6 % lead. Other common varieties are cerussite (PbCO3) and anglesite (PbSO4). Lead (Pb) is a class B metal and therefore has the ability to form stable complexes with oxygen-donating compounds. Pb 2+ + OH HM COOH HM O O Pb 2-(0)O + 2H+[15] Lead (Pb) has many industrial and commercial uses. For instance, it is used in metal products, cables and pipelines to improve durability, additives in paints, and in pesticides. It is a major constituent of the lead-acid car batteries. It is used as a coloring element in ceramic glazes as projectiles and in some candles to treat the wick. It is the traditional base metal for organ pipes, and it is used as electrodes in the process of electrolysis. One of its major uses is in the glass of computer and television screens, where it shields the viewer from radiation. Balba et al., 1991 reported that automobiles (leaded gasoline), industrial wastewater (lead mining and smelting) and pesticides are the major anthropogenic sources of lead (Pb) in the environment. University of Ghana http://ugspace.ug.edu.gh 30 2.8.2 Toxicity of lead Exposure to lead (Pb) can have a wide range of effects on a child’s development and behavior. Growing evidence suggests that lead (Pb) in a child’s body, even in small amounts, can cause disturbances in early physical and mental growth and later in intellectual functioning and academic achievements. There is accumulated epidemiological evidence, which indicates that lead (Pb) exposure in early childhood causes discernible deficit in cognitive development during childhood years (Tong et al., 2000) resulting in lower Intelligent Quotient (IQ)(Adeyeye, 1993). Particularly, dangerous to all forms of life are the organic lead (Pb) compounds. As a result of their comparatively high affinity for proteins, the lead (Pb) ions consumed bond with the haemoglobin and the plasma protein of the blood. This leads to inhibition of the synthesis of red blood cells and thus of the vital transport of oxygen. If the bonding capacity here is exceeded, lead (Pb) passes into the bone-marrow, liver and kidneys. In adult, lead (Pb) may accumulate in bone and lie dormant for years, and then pose a threat later in life during events such as pregnancy, lactation, osteoporosis and hyperparathyroidism which mobilizes stores of lead (Pb) (Grant and Davies, 1989). Lead (Pb) toxicity causes reduction in haemoglobin synthesis, disturbance in the functioning of kidney and chronic damage to the central and peripheral nervous systems (Ogwuebu and Muhanga, 2005). 2.9 IRON 2.9.1 Chemical fate Iron (Fe) is a lustrous, ductile, malleable, silver-gray metal belonging to group VIII of the periodic table. It is known to exist in four distinct crystalline forms. Iron (Fe) rusts in dump air, but not in dry air. It dissolves readily in dilute acids. Iron (Fe) is chemically active and forms two University of Ghana http://ugspace.ug.edu.gh 31 major series of chemical compounds, the bivalent iron (II) (Fe2+), or ferrous compounds and the trivalent iron (III) (Fe3+), or ferric compounds. Iron (Fe) is believed to be the tenth most abundant element in the universe. Iron (Fe) is also the most abundant (by mass, 34.6%) element making up the Earth; the concentration of iron in the various layers of the Earth ranges from high at the inner core to about 5% in the outer crust. Most of this iron (Fe) is found in various iron oxides, such as the minerals hematite, magnetite, and taconite (Morgan and Anders, 1992). The earth's core is believed to consist largely of a metallic iron (Fe)-nickel (Ni) alloy. Iron is the most common metal in use today due to its abundance and strength. They form part of machine tools, automobiles, building and machine parts. They are also used as catalyst in many processes, food containers and screwdrivers. Iron (Fe) is essential to most life forms and to normal human physiology. It is an integral part of many proteins and enzymes that maintain good health. Dallman, 1986 explains that in humans, iron (Fe) is an essential component of proteins involved in oxygen transport. Andrews, 1999 and Bothwell et al., 1979 indicate its essentiality in the regulation of cell growth and differentiation. 2.9.2 Toxicity of Iron (Fe) Iron (Fe) is needed in the body in small amount to help cell growth, differentiation and also to boost the immune system. It forms the bases of many proteins and enzymes. It is an important component of proteins both in the regulation of cell growth, oxygen transport and a major component of haemoglobin and myoglobin. Chronic inhalation of excessive concentrations of iron oxide fumes or dusts may result in development of a benign pneumoconiosis, called siderosis, which is observable as an X-ray change. Inhalation of excessive concentrations of iron oxide may enhance the risk of lung cancer University of Ghana http://ugspace.ug.edu.gh 32 development in workers exposed to pulmonary carcinogens. In recent years, excess iron (Fe) intake and storage, especially in men, has been implicated as a cause of heart disease and cancer. Overdose has been reported by Corbett, 1995 to be one of the leading causes of fatality from toxicological agents in children younger than 6 years. University of Ghana http://ugspace.ug.edu.gh 33 Table 2.1: Summary on the literature review of some trace metals and macro elements Elements Physical/Chemical properties Sources/Uses Toxicity Manganese (Mn) A-54.93 gmol-1 Z-23 Pinkish gray, hard to melt but easily oxidized, melting point of 1247 ˚C, boiling point of 2061 ˚C, density of 7.43 g/cm3 at 20 ˚C Occurs as Pyrolusite (MnO2)/ Rhodochrosite (MnCO3), Component in alloys and additive in fuels Respiratory disorders, Parkinson diseases, Hallucinations and forgetfulness, symptom’s such as schizophrenia Copper (Cu) A-63.55 gmol-1 Z-29 Melting point of 1083 ˚C, boiling point of 2595 ˚C, density of 8.9 g/cm3at 20 ˚C Naturally as chalcopyrite (CuFeS2), chalcocite (Cu2S), used for electrical equipment, industrial machinery Dermatitis, liver cirrhosis, neurological disorders, renal diseases etc. Chromium (Cr) A-51.99 gmol-1 Z-24 Melting point of 1907 ˚C, boiling point of 2672 ˚C, density of 7.19 g/cm3 at 20 ˚C Naturally through volcanic eruptions as chromite (FeCr2O4), components in alloys and metal ceramics Allergic dermatitis, skin lesions, respiratory problems and tumor formations Nickel (Ni) A-58.71 gmol-1 Z-28 Silvery-white, hard, malleable and ductile metal, melting point of 1453 oC, boiling point of 2913 oC, density of 8.9 g/cm3 at 20 oC Occurs with sulfur as millerite, with arsenic as niccolite, component in alloys for gas turbines and rocket engines Skin rash, swelling of the brain and liver and various type of cancers Zinc (Zn) A-65.37 gmol-1 Z-30 Lustrous bluish-white metal, melting point of 420 oC, boiling point of 907 oC, density of 7.11 g/cm3 at 20 oC Occurs as zinc sulfides (sphalerite), used in the galvanization of steel and also a major component in alloys Arteriosclerosis, disturbs protein metabolism, stomach cramps and skin irritations Sodium (Na) A-22.98 gmol-1 Z-11 Soft metal, melting point of 97.81oC, density of 0.971 at 25 oC, produces yellow flame. Associated with many minerals in the earth crust, natural brines, many industrial uses High levels in soil affects plant growth, heart failure, neurological damage, Potassium (K) A-39.0983 gmol-1 Z-19 Melting point of 63.65 oC, density of 0.862 g/cm3 at 20 oC, Produces violet flame Associated with aluminosilicate minerals such as feldspar, many industrial applications Elevated levels will lead to death by heart failure University of Ghana http://ugspace.ug.edu.gh 34 2.10 WATER 2.10.1 Importance of good water quality Water is man’s most important resource and from history it has been the key to most civilization’s development. Water defines population growth and is a key factor in human settlements. Society will enjoy good health basically from disease and toxin free water sources. Modern civilization classifies natural bodies of fresh water according to intended use, for example public water supply, fish propagation, recreation, transportation, agriculture and industrial or domestic use. The largest demand and use of water worldwide is for industrial and agricultural purposes. Agricultural uses of water are mainly through irrigation and in the application of agro-chemicals. Water for agriculture continues to increase worldwide due to high demand for food. Water is used in industries mainly for power generation, transportation of waste materials and in many industrial products such as beverages and solvents for chemicals. Water pollution has impacted negatively on the economy of many developing countries especially in the area of human health and ecosystem disruption. Any physical, biological or chemical change in water quality that adversely affects living organisms or makes water unsuitable for desired use could be considered as being polluted. Sedimentation from erosion and poisoned springs contribute to natural sources of water contaminant. Anthropogenic sources of water contaminant include sewage from industries, pesticides and other agro-chemical runoff from farmlands and faecal pollution. Faecal pollution of drinking water has frequently caused water borne diseases such as cholera which has decimated several populations. Water quality is a term used to describe water’s physical, chemical and biological characteristics. The term is usually used to describe water’s suitability for a particular purpose (i.e., drinking University of Ghana http://ugspace.ug.edu.gh 35 water, recreation and aquatic life) (USGS, 2005). For freshwater systems, stream flow affects many issues related to water quality and quantity such as pollutant concentration and water temperature (Richter, 2003). Urbanization, industrialization and various modern agricultural practices has greatly affected our environment and the quality of water. The assessment of water quality is therefore the best in ensuring that it is safe for its intended user, particularly uses which may affect human health and the health of aquatic systems. 2.10.2 Freshwater Physico-Chemistry Aquatic communities, species and their way of life are directly influenced by the Physico- Chemistry of the hydrosphere they inhabit. Physico-Chemical parameters include physical parameters such as pH, temperature, turbidity, total dissolved and suspended solids (TDS and TSS) and chemical parameters such as dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), alkalinity and hardness. Extreme changes in water Physico-Chemistry can have adverse effects on aquatic systems and organisms. Physico-Chemical parameters to investigate are temperature, dissolved oxygen (DO), biochemical oxygen demand (BOD), pH, electrical conductivity/salinity (EC), total dissolved and suspended solids (TDS and TSS), microbial activity and dissolved ions (water nutrients). 2.10.3 Dissolved oxygen (DO) Oxygen is essential to all forms of aquatic life. The amount of oxygen in water is known as dissolved oxygen. Dissolved oxygen (DO) is critical for sustenance of aquatic life in order for aerobic species to be able to survive and carry out their ecological functions. The oxygen content of natural water varies with temperature, salinity and atmospheric pressure. University of Ghana http://ugspace.ug.edu.gh 36 Under natural freshwater conditions, DO concentrations ranges from 15 mg/L at 0˚C to 8 mg/L at 25˚C (Manaham, 1991). Lack of DO can lead to anaerobic decomposition of organic matter, resulting in unpleasant odours that are indicative of formation of hydrogen sulfides (H2S) and ammonium (Schindler, 1981). Dissolved oxygen (DO) determination is a fundamental part of water quality assessment since oxygen is involved in or directly influences nearly all chemical and biological processes within water bodies (Fianko, 2003). 2.10.4 Total Alkalinity It measures the presence of carbonates, bicarbonates, phosphates and hydroxides and also a measure of the buffering capacity of an aquatic ecosystem (Fianko, 2003). Phosphate and orthophosphates contribute to 0.1 % of total alkalinity. At a specific pH, carbonate/bicarbonate ions can be formed from the dissociation of carbonic acid. Alkalinity is controlled by carbonate/bicarbonate species, and is represented as mg/L CaCO3 (Dallas and Day, 2004). Alkalinity is important for fish and other aquatic life in fresh water system because it buffers pH changes. Alkalinity components such as carbonate/bicarbonate species will complex toxic heavy metals thereby reducing their toxicity significantly (Fianko, 2003). The WHO in their 2011 report has no stated guideline value for alkalinity because high concentrations of carbonate/bicarbonate species in drinking water does not pose any health concern (WHO, 2011). However EPA’s secondary drinking water regulations limits alkalinity only in terms of TDS (500 mg/L) and to some extent by the limitation on pH. University of Ghana http://ugspace.ug.edu.gh 37 2.10.5 Biochemical oxygen demand (BOD) Biochemical oxygen demand, or BOD, measures the amount of oxygen consumed by microorganisms in decomposing organic matter in water bodies. BOD also measures the chemical oxidation of inorganic matter (i.e., the extraction of oxygen from water via chemical reaction) (USEPA, 2013). The rate of oxygen consumption in a water body is affected by a number of variables: temperature, pH, the presence of certain kinds of microorganisms, and the type of organic and inorganic material in the water. High concentrations of oxidizable materials lead to anoxic conditions-stagnant water that does not support higher life forms such as fish. BOD directly affects the amount of dissolved oxygen in rivers and streams. The greater the BOD, the more rapidly oxygen is depleted in a water body. This means less oxygen is available to higher forms of aquatic life. The consequences of high BOD are the same as those for low dissolved oxygen: aquatic organisms become stressed, suffocate, and die. Water of poor quality has high BOD. 2.10.6 Electrical conductivity Electrical conductivity (EC) estimates the amount of total dissolved salts/solids (TDS), or the total amount of dissolved ions in the water. Dissolved salts or ions are electrically charged and their ionic strength determines water conductivity. The EC in freshwater ecosystems is regulated by rocks’ mineral composition, size of the watershed and other sources of ions (Hudson-Edwards et al., 2003; Nielsen et al., 2003). A bigger watershed means relatively more water flow and more contact with soil will result in more salt/ion extraction from the sediment hence contributing to high electrical conductivity (Vega et al., 1998). Wastewaters from industries, sewage treatment works and septic tanks, and non-point sources from settlements and agriculture are other sources that contribute to in-stream EC (Roelofs, 1991; Nielsen et al., 2003). University of Ghana http://ugspace.ug.edu.gh 38 2.10.7 Turbidity and suspended matter in the hydrosphere Suspended material consists of typical soil minerals and organic matter, especially those in the fine (clay-size) fraction. The elements present in such inorganic and organic structures usually include relatively high concentrations of alkali and alkaline earth metals, aluminum (Al), and iron (Fe), along with smaller amounts of other metals depending on the particular materials involved. Some elements of interest particularly those found in traces are associated with sediments as adsorbed species on the surface of the fine particles. The surface-absorbed elements are more available than structural elements; for example, when a sediment-bearing river discharges water into an estuary, most of the adsorb ions are displaced by sodium ions via an ion-exchange reaction and become part of the solution phase. The American Public Health Association (APHA), 1989 explains turbidity as a representation of the optical property of water that causes light scattering or absorption. Light scattering results from suspended matter (clay, silt, organic and inorganic matter, plankton and other microorganisms). Turbidity is caused by runoffs from non-point (e.g. irrigation schemes) and point sources (e.g. STW effluent). Higher turbidity can affect benthic, invertebrates and fish communities (Wood and Armitage, 1997). 2.10.8 Total hardness Hardness of water is a measure of the mineral content especially calcium and magnesium mainly in combination with bicarbonate (HCO3-), sulfates (SO42-) and chloride (Cl-). Other divalent or trivalent ions can contribute to hardness such as iron (Fe), barium (Ba), and/or strontium (Sr) though their contributions are small and difficult to define. Because the concentrations of Ca2+ and Mg2+ are usually much greater than the concentrations of other group 2 ions, hardness can be equated to the total calcium (Ca2+) and magnesium (Mg2+) ions present. University of Ghana http://ugspace.ug.edu.gh 39 Limestone is a mixture of calcium and magnesium carbonate, CaCO3 and MgCO3. Surface or ground water often contains CO2 and thereby making the water slightly acidic by the formation of carbonic acid (USEPA, 2013). Slightly acidic groundwater reacts with the basic limestone, and a neutralization reaction occurs resulting in the formation of soluble Ca2+, Mg2+ bicarbonates which will contribute to water hardness. It is normally expressed as mg CaCO3 per litre. There are two types of water hardness; permanent and temporary hard water. Permanent hardness in water is hardness due to the presence of the chlorides (Cl-), nitrates (NO3-) and sulfates (SO42-) of calcium (Ca2+) and magnesium (Mg2+), which will not be precipitated by boiling. For temporary hardness, calcium (Ca2+) and magnesium (Mg2+) form salt with bicarbonates (HCO3-). These compounds are unstable and will decompose when heated. Boiling the water will cause the precipitation of calcium and magnesium carbonate which also removes the hardness. Hardness is used to determine how usable water resources are for drinking and domestic purposes. Hard water forms fur and scales in boiler and leaves scum in clothes in addition to wasting of soap. The WHO recommends that hardness should not exceed 200 mg/L CaCO3 but levels of 50-100 mg/L CaCO3 are generally acceptable (WHO, 2011). 2.10.9 The effect of nutrients on freshwater ecosystems Nutrients such as nitrates (NO3-), sulfate (SO42-) and phosphate (PO43-) exist as either inorganic anionic species or a part of very huge organic structures in freshwaters. Nutrients attached to organic compounds are broken down through a series of biochemical reactions and released into the aquatic environment. Nutrients occur in small amounts in a healthy freshwater system but in large quantities, they can cause water pollution problems. Domestic sewage, industrial waste and storm drainage into water bodies contribute to an overload of nutrients in freshwater systems. Higher nitrates (NO3-) and phosphates (PO43-) nutrients contribute to the acceleration of natural University of Ghana http://ugspace.ug.edu.gh 40 eutrophication in freshwater systems, a process called cultural eutrophication (Campbell et al., 1992). 2.10.9.1 Nitrogen cycle In the hydrosphere and on land, nitrogen (N) in various forms is an essential nutrient for plant and animals and excessive concentrations of inorganic species in the hydrosphere leads to eutrophication. Nitrogen undergoes a number of processes in terrestrial, aquatic and atmospheric environments which includes nitrogen fixation, denitrification, ammonification and nitration. 2.10.9.2 Nitrogen fixation Atmospheric nitrogen is relatively unreactive, and is converted to NH3/NH4+ by nitrogen fixing microorganisms. The conversion requires breaking of strong N≡N triple bond therefore a large energy input is required. However, in freshwaters, nitrogen can occur in different forms which include dissolved molecular nitrogen, organic compounds from proteins, recalcitrant anthropogenic compounds and inorganic nitrogen (ammonia, nitrite and nitrate) (Dowd et al., 2000; Wetzel, 2001; Kubiszewski et al., 2008). The availability of atmospheric ammonia is mainly due to nitrogen fixing bacteria that use unreactive nitrogen to form ammonia that normally fall into freshwaters, thus increasing ammonium concentrations in water (Bowden, 1987; Roscher et al., 2008). Cyanobacteria are responsible for most nitrogen fixation in freshwater systems due to their heterocysts (specialized nitrogen fixation cells). Marine organisms like the blue-green algae, azotobacter, and clostridium also contribute to nitrogen fixation. University of Ghana http://ugspace.ug.edu.gh 41 2.10.9.3 Denitrification It occurs mostly in stagnant fresh water and in deep, organic-rich Sea waters. Several biochemical reactions occur where oxidized nitrogen anions are biochemically reduced to nitrogen: [16] NO3- → NO2- → NO → N2O → N2 Nitrate (NO3-) is able to act as electron acceptor for the oxidation of organic matter. Heterotrophic bacteria such as species of Pseudomonas and Achromobacter facilitate the process. Ammonium can be oxidized by Planctomycete species (anammox bacteria) (Kuenen, 2008), using nitrite as the electron acceptor. [17] NH4+ + NO2- + HCO3- + H+→ N2 + NO3- + H2O + CH2O0.5N0.15 2.10.9.4 Ammonification When organic matter decomposes in water and soil, the nitrogen is first released in a reduced form as ammonium ions or ammonia, depending on the ambient pH. This conversion of nitrogen from organic to inorganic forms is a type of mineralization called ammonification. Carbon nitrogen bonds are reactive and ammonification is therefore a rapid reaction: [18] 2CH3NHCOOH + 3O2 + 2H3O+ →2NH4+ + 4CO2 + 4H2O 2.10.9.5 Nitrification Ammonium ion, present in water or in soil as a result of ammonification is subjected to oxidation in an aerobic environment. The optimum environmental pH for nitrification is between 6.5 and 8, and reaction rate decreases when pH falls below 6. The reaction takes place in two steps and the process is mediated by autotrophic bacteria: University of Ghana http://ugspace.ug.edu.gh 42 [19] 2NH4+ + 3O2 +2H2O Nitrosomonas 2NO2- + 4H3O+ [20] 2NO2- + O2 +H2O Nitrobacter 2NO3- Overall reaction: [21] NH4+ + 2O2+ H2O→NO3- + 2H3O+ The consequence of nitrification is the release of hydroxonium ions into the local environment causing the local environment to be acidified. Inorganic nitrogen in freshwater within the range 0.5 – 2.5 mg/L has been reported to result in eutrophication. Concentrations above this range lead to species loss, and hence decreased biodiversity, and stimulate excessive algal and aquatic plant growth. Any inorganic nitrogen concentrations > 10 mg/L can result in the significant loss of species diversity and lead to water becoming toxic to animals and humans (DWAF, 1996; Bongumusa, 2010). 2.10.9.6 Sulfur in freshwater Sulfur chemistry has a major influence on the process in all the compartments of the Earth’s environment. In the atmosphere, oxidation reactions convert lower oxidation state species into sulfate, sulfate aerosols and sulfuric acid. Sulfur in the hydrosphere is present in many inorganic and organic forms and exhibits oxidation states from -2 to +6. The most important reduced and oxidized mineral forms of the element are sulfides, including pyrite (FeS2), and sulfates, including gypsum (CaSO4.2H2O). The concentration in unimpacted fresh water is much less than 0.12 mmol-1 but none the less one of the principal ionic species in lakes and rivers. In reducing environment sulfur is obtained in the -2 oxidation state. In organic matter, sulfur exists as both carbon-bonded and oxygen-bonded forms: C-bonded R-CH2SH hydrosulfide in amino acids R3C-S-S-CR3 disulfide University of Ghana http://ugspace.ug.edu.gh 43 O-bonded S=O sulfoxide R-OSO2OH sulfonic acid When organic matter undergoes microbial decomposition, the sulfur-containing groups within the organic compounds are simultaneously transformed. Sulfides are mainly formed during the decomposition of organic matter and it is easily oxidized under aerobic conditions. Chemoautotrophic bacteria such as Thiobacillus thiooxidans is responsible for sulfide oxidation and is found in most oxygen-containing waters, sediments, and soils. The reaction also produces hydroxonium ions and is also an acidifying process. [22] HS- + 2O2 + H2O→ SO42- + H3O+ In an organic-rich, reducing aquatic environment, sulfate is readily reduced to species in the -2 or, less commonly, 0 oxidation state. Many marine, estuarine, and fresh water sediments as well as waterlogged soils contain sulfate-reducing bacteria. The sulfide species generated are toxic to aquatic life; they may also react with metals present in the sediment/soil, such as iron (II), to produce insoluble sulfides that are components of marine shales. [23] SO42- + 2{CH2O} + H3O+ → HS- + 2CO2 + 3H2O [24] 2SO42- + 3{CH2O} + 4H3O+ → 2S0 + 3CO2 + 9H2O 2.10.9.7 Phosphorous in freshwater Phosphorous occurs in natural and wastewater almost solely as phosphates. They are classified as orthophosphate, condensed phosphate (pyro-, meta- and polyphosphate) and organically bound phosphates. It naturally occurs by the weathering of phosphate bearing rocks and the decomposition of organic matter. Anthropogenic activities contribute to elevated phosphorus in freshwaters through agricultural runoffs, domestic and industrial sewages (Baron et al., 2003). University of Ghana http://ugspace.ug.edu.gh 44 Polyphosphate when they enter water bodies are slowly transformed into phosphate ions (orthophosphate). [25] P3O105- + 2H2O → 3PO43- + 4H+ Orthophosphate/soluble reactive phosphate (SRP), H2PO4 and HPO4-2 are the only soluble forms of inorganic phosphorus and hence are readily available to aquatic life. Orthophosphate is taken up by algae, cyanobacteria, heterotrophic bacteria and larger aquatic plants and forms the basics of aquatic food chain. Phosphorus enhances aquatic plants and algal growth (Manaham, 1991). Concentrations of dissolved phosphorus below 0.005 mg/L stimulate moderate levels of species diversity, low productivity, rapid nutrient cycling, and no algal and aquatic plant growth. Phosphorus concentrations between 0.005 and 0.025 mg/L PO43- can enhance species diversity; promote moderate primary production, algal and water plant growth. Concentrations above 0.025 mg/L result in decreased species diversity, high productivity, and high growth of nuisance aquatic plants and algal blooms (Camargo et al., 2007). Phosphorus concentrations are used to measure ecosystem eutrophication with the concentration of 0.1 mg/L PO43- indicative of a eutrophic system (Campbell et al., 1992). 2.10.10 Microbial Quality of Drinking Water There is the need to determine the microbial quality of drinking water since the microbial quality affects the overall quality of the water. Waterborne diseases are caused by enteric pathogens such as bacteria, viruses and parasites that are transmitted by faecal oral route. Water supplies that are unprotected are susceptible to microbial and other external contamination from surface runoff, human/animal faecal pollution and unsanitary collection methods. Faecal contamination of water is common in communities with poor sanitation. University of Ghana http://ugspace.ug.edu.gh 45 The survival of microorganisms such as bacteria in a given environment depends on many factors such as temperature, pH, electrolyte concentration and nutrient supply. Detection of each pathogenic microorganism in water is extremely difficult and instead indicator organisms are routinely used in the assessment of microbial quality of water (Grabow, 1996). They include the heterotrophic plate count (THB), total coliform bacteria (TC), faecal coliform bacteria (FC), E. coli, faecal enterococci, C. perfringens and male specific F-RNA bacteriophages. Four indicator organisms are considered for this study which includes THB, TC, FC, and E. coli. 2.10.10.1 Total heterotrophic bacteria (THB) Heterotrophic microorganisms are naturally present in the environment and can be found in soil, sediment, food, water and in human and animal faeces. Heterotrophs include bacteria, yeast and molds that require organic carbon for growth. Although generally harmless, some are considered as opportunistic and could have viral characters and could affect the health of consumers (Lye and Dufour, 1991). They also survive in biofilms inside water distribution systems, reservoirs and household storage containers. The pour plate, membrane filtration or the spread plate methods are used routinely with Yeast-extract agar, Plate count agar, Tryptone Glucose agar or R2A agar, and incubation periods 5 to 7 days at room temperature (25 °C) (APHA AWWA WEF, 1995). 2.10.10.2 Total coliform bacteria (TC) Total coliform bacteria are defined as aerobic or facultative anaerobic, gram negative, non-spore forming, rod shaped bacteria, which ferments lactose and produce gas at 35 °C (APHA AWWA WEF, 1995). They include bacteria of known faecal origin such as E. coli as well as others which do not originate from faecal sources such as klebsiella sp., Citrobacter sp., and Enterobacter sp. University of Ghana http://ugspace.ug.edu.gh 46 The recommended test for total coliform is membrane filtration using mEndo agar and incubation at 35 to 37 °C for 24 hours to produce colonies with golden-green metallic shine. The presence of total coliform in water samples gives an indication of bacteria such as klebsiella sp which are causal agents for diseases such as typhoid fever, dysentery and cholera (APHA AWWA WEF, 1995). 2.10.10.3 Faecal coliform (FC) Faecal coliform bacteria are gram negative bacteria. They are also called thermo-tolerant coliforms or presumptive E. coli. They are considered to be a more specific indicator of the presence of faeces (Maier et al., 2000). The recommended test for faecal coliform is membrane filtration using mFC agar and incubation at 44.5 °C for 24 hours to produce blue colored colonies. They are generally used to indicate unacceptable microbial water quality and could be used as an indicator in the place of E. coli (APHA AWWA WEF, 1995). 2.10.10.4 Escherichia coli (E. coli) E. coli is used as a preferred indicator of faecal pollution. It is a gram negative bacterium and they are found in the intestines of warm blooded animals and humans. E. coli is used to indicate recent faecal pollution of water samples. Testing for the enzyme β-glucuronidase is one confirmatory test for the presence of E. coli. Also growth media containing the fluorogenic substrate 4-methyl-umbelliferyl-β-D-glucuronidase (MUG) is used in the isolation and identification of E. coli from water samples. E. coli and related bacteria possess the ability to transfer DNA via bacterial conjugation, transduction or transformation, which allows genetic material to spread horizontally through an existing population (APHA AWWA WEF, 1995). University of Ghana http://ugspace.ug.edu.gh 47 2.11 ANALYTICAL METHOD FOR DETERMINATION OF HEAVY METALS A variety of analytical techniques have been employed in the determination of the heavy metals. These techniques included Atomic Absorption Spectroscopy (AAS), Atomic Fluorescence Spectroscopy (AFS), Graphite Furnace Atomic Absorption Spectroscopy (GFAAS), Hydride Generation Atomic Absorption Spectroscopy (HGAAS), Inductively Coupled Plasma-Emission Spectrometry (ICP-AES), Inductively Coupled Plasma-Mass Spectrometry (ICP-MS), X−ray fluorescence (XRF), Electron Microprobe (EM) Flame Photometry (FP) and Instrumental Neutron Activation Analysis (INAA). These instruments accurately measure elements in environmental samples to parts per billion (ppb) concentrations i.e. µg L-1 and µg Kg-1 in liquids and solids samples respectively. Before any element is determined with any of these instruments, pre-treatment with acidic extraction or acidic oxidation digestion and in some cases chelation may be required. The significance of pre- treatment is that all elemental species are converted into the inorganic form for easier detection and measurement. One advantage of INAA is the ability to measure trace amounts of elements without destroying the sample. FP uses flame atomic emission and a filter to quantify Li, Na, K and Ca in liquid samples (Xudong et al., 2011). AAS is a technique in which the absorption of light by free gaseous atoms in a flame or furnace is used to measure the concentration of atoms. In analyzing any given metal, a lamp is chosen that produces a wavelength of light that is absorbed by that element. Sample solutions are aspirated to a nebulizer system. The sample then mixes with an oxidant gas drawn under pressure into a burner to form aerosol. The flame which uses either air-acetylene or nitrous-oxide acetylene operates at a temperature of 2400 oC and 2800 oC respectively. University of Ghana http://ugspace.ug.edu.gh 48 Within the flame, the aerosol undergoes processes such as evaporation of the solvent and excitation of the gaseous metallic element. If any gaseous atoms of the given element are present in the flame, they absorb light produced by the lamp before it reaches the detector (photomultiplier tube). The amount of light absorbed is proportional to the concentration of metal ions following Beer-Lambert law. Absorbance values for unknown samples are compared to calibration curves prepared by running known standards. Elements like mercury (Hg) and selenium (Se) need specialized compartments like the Cold Vapour AAS and the Hydride Generation AAS respectively for their analysis. 2.11.1 Hydride Generation Atomic Absorption Spectrometry (HGAAS) Elements like selenium (Se) may exist in solution as oxyanions and may not undergo complete atomization. Their hydrides however decompose very easily into the atoms. Problems encountered with the conventional AAS such as interferences, poor reproducibility and poor detection limits are however corrected. The gaseous hydride is then swept (by inert gas) into a sampling cell in the light path of the AA for atomization by the flame. The oxidation state of the metalloid is very important during the hydride generation. For example, selenium (Se) requires an oxidation state (IV) selenite for successful hydride generation. Higher oxidation states give erratic results. Samples are first oxidized with HNO3 to the Se (VI), and then reduced to selenium (Se) (IV) by boiling with HCl, before reacting with borohydride. Hydride generation pre-concentrates the metalloid thus removing interfering species and improving detection limit. 2.11.2 Cold Vapour Atomic Absorption Spectrometry (CVAAS) Most atoms for atomic spectroscopy analysis cannot exist in the free, ground state at room temperature; therefore, samples must be heated in order to liberate atoms for analysis. Hg University of Ghana http://ugspace.ug.edu.gh 49 however exists as free atoms at room temperature and can be analysed by AAS without employing a flame or graphite furnace to atomize it. The Hg in the sample is oxidised to Hg2+, the reduced to Hg0. [26] Hg2+ + 2e → Hg0 The free Hg atoms are swept into an absorption cell for absorbance measurement and therefore no need for a flame. Reducing agents used are: SnCl2 / NaBH4 + HCl. The reaction quantitatively releases Hg from solution which is carried by a stream of argon into the AA for absorbance measurement (Xudong et al., 2011). 2.12 FISH SPECIES Fish species were identified as Xenomystus nigri (African knife fish) and Clarias submarginatus (Mudfish). Xenomystus nigri is a predator fish which belongs to the Notopteridae family. It feeds on meaty food such as bloodworm, insect, crustacean and small snails. It grows up to (30 cm) in the wild (Günther, 1868). It is flat and elongated with an arched back. It has a continuous fin along the underside formed by a joining of the caudal and anal fin. It is a graceful swimmer which prefers still waters and where its fin allows it to move both forwards and backwards. These fish species have no dorsal fins. They are freshwater fish which are mainly found in West Africa and prefer water conditions of temperatures ranging from 22 ºC to 28 ºC and pH ranges of 6-8 (Günther, 1868). Clarias submarginatus (Mudfish) is a demersal fish which belongs to the Clariidae family. It is a freshwater fish also found in West Africa. It grows up to a maximum length of 16 cm. The head is short and rather rounded in dorsal outline with eyes dorsally located. Its frontal fontanelles are University of Ghana http://ugspace.ug.edu.gh 50 extremely short and oval-shaped and also have its occipital fontanelle oval-shaped. The tooth plates are relatively broad. Its pectoral spines are slightly curved with long and slender gill rakers which are distantly set. It also has well developed suprabranchial organ (Peters, 1882). University of Ghana http://ugspace.ug.edu.gh 51 3 CHAPTER THREE 3.0 METHODOLOGY 3.1 DESCRIPTION OF STUDY AREA 3.1.1 Pra River Catchment The Pra River system is the longest in South Western Ghana. This river takes its source from the Kwahu plateau and flows through a distance of 240 km into the Gulf of Guinea through its estuary at Shama. The river has a drainage area of 23188 km2 and an estimated mean annual discharge of 214 m3s-1 (Akrasi and Ansah-Asare, 2008). The river is divided into two main catchment regions namely the Upper Pra which is located in the Eastern Region and the Lower Pra which flows through the Central and the Western regions. The Upper Pra starts from the Kwahu plateau and flows to join the Birim River at around Akroso. The Lower Pra River is formed from the Upper Pra River and its two major adjoining tributaries, the Birim and Offin River flowing from the eastern and western parts of the middle belt region of the country respectively. The Lower Pra River flows through towns like Twifo Praso in the Central Region and Daboase in the Western Region until it enters the sea through its estuary at Shama in the Western Region. People living at the banks of the river depend on this river body for their livelihood through fishing, transportation and farming activities. 3.1.2 Climate and Geology of the Catchment Area The geology in this region is pre-cambrian and is classified into the Birimian and Tarkwaian formations (Junner, 1940; Kesse, 1985). The area is quite humid (relative humidity 60–95%) with annual rainfall in the range of 1500 – 2000 mm. The average minimum and maximum University of Ghana http://ugspace.ug.edu.gh 52 temperature ranges from 21 °C to 32 °C. The basin is always strongly under the influence of the moist south-west monsoons during the rainy season and as a result there is a pro-longed rainy season from April through to October/November each year. The primary vegetation consists of moist semi-deciduous forest and the soil type is mainly the forest ochrosol (Brammer, 1962). Figure 3.1: Map of the Lower Pra River and its adjoining tributaries. The areas in the violet, green and red captions represents the upper stream, mid-stream and downstream catchment regions of the Lower Pra River respectively. The part of the Lower Pra River under study is captured in the red caption. University of Ghana http://ugspace.ug.edu.gh 53 3.1.3 Catchment Divisions The Lower Pra River is divided into three main catchment regions which are the upper stream regions, the middle portions and the lower stream regions. The upper stream catchment of the Lower Pra River stretches from the point where the Offin River joins with the Upper Pra River at Awisam through Twifo Praso to areas around Enyinabrim. The middle portion of the Lower Pra River stretches from downstream Enyinabrim to areas around Sekyere Herman. Most of the areas in the middle portions are un-navigable due to the large forest reserve in the area and the rocky nature of the river bed. The lower stream areas stretch from Daboase (DB) through Beposo (BP) to the estuary where the river enters the sea. Towns in the upper stream catchment have been reported for artisanal illegal small scale gold mining (AGM) and their activities affect the communities in the lower catchment region. However in this study, the lower catchment region is isolated for monitoring since the activities of illegal gold miners have reached towns further downstream such as Beposo (BP) and Daboase (DB). 3.1.4 Site Selection for Monitoring An investigation was carried out in the Shama district of the lower stream catchment region to isolate towns noted for illegal gold mining operations. From the investigation, four towns along the watershed were considered. Three towns selected were in the Shama district whiles one other town was selected further upstream in the Mpohor Wassa East district. Two of these towns, Beposo (BP) and Daboase (DB) were noted for illegal gold mining operations as at October 2012 whilst two more towns, Bokorkope (BK) and Shama (SH) estuary selected further downstream are not known for recent illegal gold mining but have a history of University of Ghana http://ugspace.ug.edu.gh 54 illegal gold mining. Samples were taken from the main river because there were no adjoining tributaries in the area of study. The distance of the river from Daboase to Shama is about 20 km. Site 1 Daboase: Upstream Lower Catchment Region (N 05° 08´ 29.0´´, W 001° 39°´ 09.5´´) This site is located in the Daboase Township in the Mpohor Wassa East district. The major anthropogenic activity that takes place in this area is the illegal mining of gold by galamsay operators. Their activity bothers on piling of heaps of sand and using of a mobile rig on the water bed for winning the metal from the heaps. The local water works that supplies the water in the Western Region is situated in this area. The water body is turbid and muddy on sight since the operators wash their heaps direct into the river. Site 2 Beposo: Midstream Lower Catchment Region (N 05° 07´ 24.5´, W 001° 36°´ 59.8´) This site is located 5 km downstream site one. The site is impacted by a lot of anthropogenic activities especially the illegal mining of gold. The processes and equipment used are the same as stated in site one. Unlike site one, people live on the banks of the river here and depend on the river so much for their livelihood. Important landmarks here are the bridge which connects Accra to Takoradi with very high vehicular traffic and a busy market. Plate 3.1: A section of the Lower Pra River at Daboase which is a current AGM site. Piles of sand located at the center of the river which aids in AGM operations. University of Ghana http://ugspace.ug.edu.gh 55 Site 3 Bokorkope: Midstream Lower Catchment Region (N 05° 04´ 22.2, W 001° 37°´ 00.8) This site is located 6 km downstream site two. This site is located in a forest with rural settlement mainly engaged in farming and fishing. There is no recent known illegal gold mining activity. The flow rate and direction of flow of the river is however interesting depending on the tide at the Shama estuary. The flow of river water in this particular location is against the direction of water current during high ocean tides. Site 4 Shama Estuary: Downstream Lower catchment region (N05°00´49.2, W001°37°´50.0) The Lower Pra River enters the Gulf of Guinea at this location. It is a typical fishing community characterized by a lot of anthropogenic activities such as the discharge of effluents either from homes or small artisan shops into the river. Recent illegal gold mining is absent at this site. The Plate 3.2: A section of the Lower Pra River at Beposo which is a current AGM site Plate 3.3: A section of the Lower Pra River at Bokorkope currently not known for AGM operations University of Ghana http://ugspace.ug.edu.gh 56 estuary at Shama is a coastal plain estuary. Coastal plain estuary is formed by the sea level rising and filling an existing river valley. It is also classified as a well-mixed estuary due to strong tidal mixing and low river flow that mix the sea water throughout the shallow estuary. Mixing is so complete that the salinity is the same top to bottom and decreases from the ocean to the river (Tufour et al., 2007). 3.2 SAMPLING Sampling was done twice in the month of October during the minor rainy season and at the apex of the dry season in March to represent the dry and wet seasons of the southern belt of the country. Water, Sediments and Fish species were sampled at the four sites. For each sampling site, water samples were collected at different points up to a kilometer headwater upstream from isolated sampling locations (Donkor et al., 2006a, b). Water was collected at about 30 cm below water surface with the aid of an improvised water sampler. Water samples were collected into acid (2 mL Conc. HNO3) pre-treated poly-teflon bottles using the ultra-clean free-metal sampling protocol (EPA, 1996). Sediment was sampled from the riverbed and this was done by divers. Both dried and wet fish samples were obtained Plate 3.4: A section of the Lower Pra River at Shama estuary which is a coastal plain estuary University of Ghana http://ugspace.ug.edu.gh 57 from natives living at the banks of the river. In the study area it was observed that fish is consumed after smoking with wood fire and this process allows the villagers to store large amounts of fish (Donkor et al., 2006b). 3.2.1 Sample Collection Sediments were sampled in triplicates, collected into acid pre-treated poly-ethylene bags and then aggregated to form a composite sample. Fish samples were collected into pre-treated poly- ethylene bags, sealed and placed in an ice chest together with water and sediment samples and brought to the lab for further preparation and analysis. For water samples, physicochemical parameters such as temperature, pH and electrical conductivity were recorded on the field using a Hanna’s portable dual purpose pH-conductivity meter which was pre-calibrated in the laboratory. Azide modification of the Winkler method was used to fix oxygen on the field for dissolved oxygen analysis (DO). Water samples for biochemical oxygen demand (BOD) were collected into BOD 300mL dark bottles with the same azide modification/Winkler principle. Water samples for other parameters such as hardness, alkalinity, total solids (TS, TSS, and TDS) and water nutrients were fetched into different treated poly-ethylene bottles (1.5 L), stored under ice and analyzed immediately upon arrival at the laboratory. Water samples for microbial studies were collected into sterilized bottles and frozen prior to analysis. University of Ghana http://ugspace.ug.edu.gh 58 Figure 3.2: Map showing the four sampling sites at the lower catchment regions of the Lower Pra River. Samples were taken from locations at Daboase, Beposo, Bokorkope and Shama in the Shama and Mpohor Wassa East district of the western region. The distance of River water understudy is about 20 km. University of Ghana http://ugspace.ug.edu.gh 59 3.2.2 Sample Preparation 3.2.2.1 Cleaning of Glassware Glassware were treated by washing under deionised running water, soaking and boiling in nitric acid bath (20 % v/v) overnight and dried in an oven. 3.2.2.2 Water Samples Approximately 100 mL of sampled water which had already been acidified with Conc. HNO3 during sampling was further acidified and transferred into a beaker and gently heated for five minutes on a hot plate. The solution was then filtered with Whatman no. 42 filter paper and made up to the 100 mL mark with deionized water for analysis. 3.2.2.3 Sediment Samples Sediments were air dried and broken down into finer particles using a porcelain mortar and pestle and then passed through a 2 mm sieve. The < 2 mm fine sample was further ground with pestle and mortar and passed through a 325 μm mesh sieve. Approximately 1 g of each sediment sample was digested with 20 ml acid mixtures (3:7 v/v) HNO3:HClO4 and (9:3:1 v/v) HNO3: HCl: H2O2 (EPA, 1995) on a hot plate. 3.2.2.4 Fish Samples Fish samples were identified at the Department of Oceanography and Fisheries at the University of Ghana, Legon. Fish species were classified as Clarias submarginatus and Xenomystus nigri. Dried fish samples were first washed, further oven dried, and milled. Approximately 0.5 g of each dried fish sample was digested with 10 mL (5:2 v/v) HNO3 / H2O2. Fresh fish from the freezer was partly thawed then lengths and weights were recorded. Steel scissors and forceps University of Ghana http://ugspace.ug.edu.gh 60 were used to remove the skin and a steel knife was further used to dissect the fish into various parts. Fish tissues were homogenized on a steel plate and ground in a porcelain mortar. Approximately 0.5 g of fresh fish sample was digested using the same procedure as done for the dried fish sample. After digestion, the digestate was allowed to cool completely and then diluted, filtered and made up to the 100 mL mark with de-ionized water in a volumetric flask (Ntow and Khwaja, 1988). 3.2.3 Instrumental Models Heavy metals such as Cd, Cu, Pb, Zn, Ni, Fe, Cr and Mn in the filtrate of digested samples were analyzed with Atomic Absorption Spectrophotometer (Model AAnalyst 400, Perkin Elmer Inc., Norwalk, CT, USA and VARIAN, AA240FS, product of USA/AUSTRALIA) present at the Ghana Atomic Energy Commission (GAEC), Kwabenya and AGILENT 270 FS present at the Water Research Institute (WRI), Council for Scientific and Industrial Research (CSIR) located at Airport Residential Area, Accra. The instrument was calibrated manually with prepared standard solution of concentrations 1 mg/L, 2 mg/L, and 5 mg/L of the respective salts of heavy metals. An air/acetylene flame mixture was used for volatilizing the sample. However for Hg and Se, AAS equipped with both cold vapour (CVAAS) and hydride generation (HGAAS) compartments was used. Alkali metals Sodium (Na) and Potassium (K) were analyzed using the Flame photometer. University of Ghana http://ugspace.ug.edu.gh 61 3.2.4 Analysis of Soil Physicochemical Parameters 3.2.4.1 Soil pH Approximately 20 g of the sieved air-dried soil sample was put into a 100 mL beaker and 50 mL distilled water added. The suspension was agitated vigorously for 5 min using a mechanical shaker and then allowed to settle for 2 hours. The pH was measured with the Hanna pH meter. For precise measurements, the pH meter was pre-calibrated using a two point calibration with standard buffer solutions of 4.0 and 9.0. 3.2.4.2 Electrical Conductivity Approximately 50 mL distilled water was added to 20 g of the sieved air-dried soil sample in a 100 mL beaker. The suspension was mixed vigorously for 5 min. using a mechanical shaker and then allowed to settle for 2 hours. The conductivity meter was calibrated with 0.01 M KCl standard solution. The conductivity measurement was taken after the electrodes of the conductivity meter were immersed into the suspension. 3.2.5 Physicochemical Parameters of Water Parameters such as pH, conductivity, and temperature were recorded at the field with the Hanna’s portable dual purpose pH-conductivity meter. Parameter such as dissolved oxygen (DO), biochemical oxygen demand (BOD), water hardness, total alkalinity, total dissolved and suspended solids (TDS & TSS) and water nutrients were also determined using various titrimetric and volumetric analysis in the laboratory. Microbial activity such as total coliform (TC), faecal coliform (FC), total heterotrophic bacteria (THB) and E. coli counts were determined at the microbiology laboratory at CSIR, Water Research Institute. University of Ghana http://ugspace.ug.edu.gh 62 3.2.5.1 Dissolved Oxygen (DO) Water sample for dissolved oxygen determination was collected into 300 mL BOD bottles. The BOD bottle was carefully immersed into the water so that water gently fills the bottle without creating bubbles. Approximately 2 mL of Winkler I (480 g MnSO4 .4H2O in distilled water filter and dilute to 1 L) is introduced by submerging the tip of the pipette into the sampled water. This was followed by the introduction of Winkler II (Alkali-iodide-azide reagent; 500 g NaOH, 150 g KI, 10 g NaN3 in 40 mL of distilled water diluted to 1 L). The formation of reddish brown precipitate indicates the fixing of oxygen in the sampled water. The stopper was then placed into the BOD bottle. Prior to titration, 2mL of conc. H2SO4 was introduced to dissolve the precipitate and to liberate iodine. Approximately 100 mL of water sample was titrated against 0.015 M standardized thiosulfate solution (APHA AWWA WEF, 1998). 3.2.5.2 Biochemical Oxygen Demand (BOD) Dilutions must result in a sample with a residual DO (after 5 days of incubation) of at least 1 mg/L and a DO uptake of at least 2 mg/L. Approximately 40 ml of water sample was diluted with aerated water into a 1 L volumetric flask. Mixed diluted water sample was siphoned into three separate BOD 300 ml bottles, and stoppered to prevent entry of air. The initial dissolved oxygen was determined on one bottle whilst the other two were incubated at 27 °C for five days. BOD was computed as the difference between the DO for day-1 and day-5 per the decimal volumetric fraction of sample used (APHA AWWA WEF, 1998). University of Ghana http://ugspace.ug.edu.gh 63 3.2.5.3 Total Water Hardness Ethylenediaminetetra-acetic acid (EDTA) di-sodium salt (3.723 g di-sodium salt of EDTA was dissolved in distilled water and diluted to 1 L) of 0.01 M stock solution was standardized with standard calcium carbonate (CaCO3) solution. About 2 mL of buffer solution (16.9 g NH4Cl dissolved in 143 mL conc. NH4OH and diluted to the 250 mL) was added gradually to 10 mL of water sample to give it a pH between 10.0 and 10.1. Two drops of Eriochrome Black T indicator were added to the water sample to give a reddish tinge colour. The water sample was titrated against standardized EDTA solution to a blue colour endpoint (APHA AWWA WEF, 1998). 3.2.5.4 Total Alkalinity Stock solution of 0.01 M HCl was standardized against 0.05 M of Na2CO3 with methyl orange as the indicator. Two to three drops of bromocresol green indicator were added to 10 mL sampled water and then titrated against standardized HCl from blue to yellow colour change at the endpoint (Vogel, 1978). 3.2.5.5 Total Suspended Solids (TSS) Filter paper (Whatman 42) was placed on to a filter assembly and washed with deionized water. The filter paper was placed in an aluminum dish and dried in an oven at 80 °C for 30 minute, cooled in a desiccator and weighed to achieve a constant weight. The filtration apparatus was assembled using the washed dried and weighed filter paper and was made wet in order to seat it. Sampled water was stirred with a magnetic stirrer and while stirring, 100 mL water sample was measured on to the filter apparatus using a pipette and then suctioned. The filter paper was washed with distilled water and suction was continued for about a minute. The filter paper was University of Ghana http://ugspace.ug.edu.gh 64 then carefully removed, placed into an aluminum dish, dried, cooled and reweighed (APHA AWWA WEF, 1998). 3.2.5.6 Total Dissolved Solid (TDS) The same procedure as stated for TSS determination was followed except that the total filtrate was transferred to a weighed evaporating dish and evaporated to dryness in an oven at around 100 °C. The evaporating dish was cooled in a desiccator and reweighed (APHA AWWA WEF, 1998). 3.2.5.7 Microbial Studies Microbial parameters consisting of, Total Coliform (TC), Faecal Coliform (FC), E. coli, and Total Heterotrophic Bacteria (THB) were carried out at the Water Research Institute (WRI), CSIR at Achimota. The American Public Health Association (APHA) protocols 9222A, 9222D, 9260F, and 9215B were employed in the analysis of TC, FC, E. coli, and THB respectively. 3.2.5.8 Sodium (Na) and Potassium (K) Determinations of these metals were done photometrically using the Advance Technical Service (ATS) Flame Photometer (FP). The intensities of sodium (Na) and potassium (K) were measured at wavelengths of 598 nm and 766.5 nm respectively after calibrating the instrument with serially diluted standards prepared from salts of the two elements. Five drops of Ionization suppressor Cesium Chloride (CsCl) were added to the solution to prevent the ionization of sodium (Na) and potassium (K) after which the solution was aspirated into the flame for readings to be taken. University of Ghana http://ugspace.ug.edu.gh 65 3.2.5.9 Quality Control Appropriate quality control procedures and precautions were taken to avoid contamination and ensure the reliability of the data. Samples were carefully handled to avoid contamination. Analytical grade reagents were used in this study. Deionized water was used throughout the study. Standard solutions of heavy metals were used to calibrate instruments. Various reagent blanks were prepared and measurements were done to account for interferences by other species and traces of analyte found in reagents (impurities) used for sample preservation, preparation and analysis. For validity of analytical procedure, certified reference material (CRM) Estuarine Sediment 1646A and SO-1 reference soil from the Canadian reference material project were analyzed against sediment samples. All samples were analyzed in triplicates and the results averaged. Results of certified and measured values of standard reference material SO-1 soil and Estuarine Sediment 1646A are presented in Tables 3.1 and 3.2 respectively. Table 3.1: Certified and measured values for standard reference material SO-1 soil Element Certified values/ mg/Kg Measured values/ mg/Kg Cd - - Cr 160.1 ± 0.1 155.0 ± 0.8 Cu 61 ± 2 52.0 ± 0.7 Fe 6.00 ± 0.07 5.5 ± 0.8 Mn 0.089 ± 0.04 0.066 ± 0.009 Ni 139 ± 2 121 ± 5 Pb 21 ± 2 17 ± 1 Zn 146 ± 4 144.0 ± 0.6 University of Ghana http://ugspace.ug.edu.gh 66 Hg 0.022 ± 0.005 0.023 ± 0.009 Se - - Table 3.2: Certified and measured values for standard reference material 1646 A Element Certified values/ mg/Kg Measured values/ mg/Kg Cd 0.148± 0.007 0.142 ± 0.009 Cr - - Cu 10.0± 0.3 9.0 ± 0.1 Fe 2.01± 0.04 1.98 ± 0.05 Mn 235 ±3 224 ± 2 Ni 2.3± 0.2 1.8 ± 0.5 Pb 12 ±1 1 ± 2 Zn 49 ±2 42.7 ± 0.9 Hg 0.040 ±0.003 0.037 ± 0.007 Se 0.19 ±0.03 0.18 ± 0.01 Percentage recoveries on reference material 1646A and SO-1 ranged from 78% to 99% and 74% to 104.5% respectively. Recoveries above 70% show the reproducibility of the analytical method in this project. University of Ghana http://ugspace.ug.edu.gh 67 3.3 DATA ANALYSIS Statistical analysis was performed using the statistical package SPSS (v 16.0, SPSS Inc., Chicago, IL, USA) and Microsoft Excel 2010 (Microsoft Corp.). University of Ghana http://ugspace.ug.edu.gh 68 4 CHAPTER FOUR 4.0 RESULTS AND DISCUSSION 4.1 RESULTS The results of field and laboratory analyses are presented in the form of figures and tables in this section. Tabulated mean results of the parameters studied are presented alongside safe limits where necessary. Statistical analysis and models such as descriptive and discriminant analysis, one-way ANOVA, Pearson correlation and regression analysis, and principal component analysis (PCA) (environmetrics) were applied to the results obtained to highlight the relationship between elements and other parameters as well as to identify the various sources of these elements. 4.1.1 Physical Parameters of Water and Sediments 4.1.1.1 Temperature The results of various physical parameters for water and sediment samples are presented in Tables 4.1A and 4.1B. Recorded mean temperature of water for the wet season was 28.6 °C. Temperature ranged from 27.5 °C to 29.5 °C for river water in the study area for the wet season. Maximum temperature for the wet season was recorded at Bokorkope with the minimum temperature recorded at Shama (Table 4.1B). There was a rise in temperature in the dry season with recorded mean value of 31.3 °C and a range from 30.8 °C to 32.0 °C. Minimum temperature of water in the dry season was recorded at Daboase with the maximum temperature recorded at Shama. Cooling effect from rainfall resulted in lower temperature readings in the wet season (Table 4.1B). University of Ghana http://ugspace.ug.edu.gh 69 4.1.1.2 Conductivity Recorded mean conductivity of water in the wet season was 25.85 ms/cm. Minimum conductivity (11.60 ms/cm) was recorded at Daboase while a maximum conductivity (36.90 ms/cm) was recorded at Bokorkope. In the dry season, minimum conductivity of 152 µS/cm was recorded at Daboase with an overall mean conductivity of 2386.13 µS/cm recorded for the study area (Table 4.1B). Mean sediment conductivity was higher in the dry season (544.83 µS/cm) than in the wet season (133.125 µS/cm). Sediment conductivity generally increased moving downstream along the water course in the dry season with the highest reading of 1548 µS/cm recorded at Shama (Table 4.1B). 4.1.1.3 pH The water samples recorded a mean pH value of 7.2 in the wet season and a value of 7.7 in the dry season (Table 4.1A). The pH of river water was fairly neutral for the two seasons. The highest pH in the wet season was recorded at Shama with a value of 7.38 and the lowest of 6.98 recorded at Daboase. The highest pH in the dry season was recorded at Beposo with a value of 8.31 with minimum pH of 6.73 recorded at Daboase. There was a general increase in pH moving downstream for the wet season. The pH of river water for both seasons were within the WHO and USEPA safety limits of 6.5-8 and 6.5-8.5 respectively. The pHs of sediments for both seasons were below the value of 7 and classified as acidic (Table 4.1A). Maximum pH values of 6.0 and 6.1 were both reported at Shama for the wet and dry seasons respectively. University of Ghana http://ugspace.ug.edu.gh 70 Wet Season Dry Season Location Temp /°C Water Cond./ mS/cm Sediment Cond./ µS/cm Temp /°C Water Cond./ µS/cm Sediment Cond./ µS/cm Daboase 29.0 11.6 146.0 30.8 152.0 53.3 Beposo 28.5 33.0 101.4 31.0 1394.5 164.3 Bokorkope 29.5 36.9 72.1 31.4 >3999 413.8 Shama 27.5 21.9 213.0 32.0 >3999 1548.0 Max. 29.5 36.9 213.0 32.0 >3999 1548.0 Min. 27.5 11.6 72.1 30.8 152.0 53.3 Mean 28.63 25.85 133.13 31.3 2386.13 544.83 Locations River Water Sediments Wet Season Dry Season Wet Season Dry Season Daboase 6.98±0.01 6.73±0.07 5.56±0.01 4.7±0.8 Beposo 7.01±0.01 8.31±0.01 5.77±0.05 5.46±0.05 Bokorkope 7.23±0.01 7.51±0.01 5.53±0.01 4.1±0.3 Shama 7.38±0.01 8.23±0.01 6.0±0.1 6.1±0.4 Mean 7.150 7.695 5.725 5.085 SD (3 Sig) 0.164 0.638 0.204 0.756 Range 6.98-7.38 6.73-8.31 5.53-6.00 4.1-6.1 Mean ± SD (1 Sig) 7.2±0.2 7.7±0.6 5.2±0.2 5.1±0.8 *WHO safe limits 6.5-8, USEPA 6.5-8.5 Table 4.1A: pH Distributions in Water and Sediments Samples Table 4.1B: Physical Parameters of Water and Sediment Samples University of Ghana http://ugspace.ug.edu.gh 71 4.2 DISTRIBUTION OF MERCURY AND SELENIUM IN WATER AND SEDIMENTS 4.2.1 Mercury levels The distributions of THg in water and sediment for the four locations are illustrated in Figures 4.1A and 4.1B. THg concentration in sediment and River water showed an unusual pattern for both seasons moving downstream from the first AGM site at Daboase. In the wet season, mean THg concentration of 1.2 µg/L was recorded in the water at Daboase. THg concentrations were below detection limits in the river water at Beposo, an AGM site 6 km downstream Daboase. Mean THg concentration of 0.97 µg/L was recorded 6 km further downstream at Bokorkope which had increased to 1.3 µg/L over a distance of 8 km at Shama (Figure 4.1B). In the dry season, the highest concentration of THg was recorded at Shama (2.4 µg/L) 20 km from the first AGM site at Daboase. Minimum concentration of 1.1 µg/L was recorded at Daboase. Concentration of THg in water was generally higher in the dry season for the four locations with an overall mean concentration of 1.7 µg/L compared to 0.7 µg/L for the wet season. Both AGM sites at Daboase and Beposo recorded THg concentration of 302 µg/Kg and 500 µg/Kg in the sediments respectively for the wet season. However THg concentrations were below the detection limits in the sediments at Bokorkope and Shama for the wet season. THg concentration in sediments was generally higher in the dry season with minimum concentration of 297 µg/Kg recorded at Bokorkope and a maximum concentration of 2568 µg/Kg recorded at Beposo. An overall mean concentration of THg in sediments was 205 µg/Kg in the wet season compared to an overall mean concentration of 1111 µg/kg in the dry season for the four locations (Appendix B18). University of Ghana http://ugspace.ug.edu.gh 72 4.2.2 Selenium levels The distributions of Se in water and sediment samples for the four locations are illustrated in Figures 4.2A and 4.2B. Selenium levels in river water gradually decreased over a distance of 12 km downstream Daboase with a minimum average concentration of 0.65µg/L recorded at Bokorkope. There was a marginal rise in the concentration of Se 8 km further downstream Bokorkope at Shama (0.7 µg/L). The maximum average concentration of Se in the wet season was recorded at Daboase (1.1 µg/L) with an overall mean concentration of 0.7 µg/L for the study area. Selenium levels were relatively higher in water for the dry season than the wet season with maximum average concentration recorded at Shama (12 µg/L) and minimum average concentration recorded at both Daboase (5 µg/L) and Bokorkope (5 µg/L) (Figure 4.2B). -1000 0 1000 2000 3000 4000 Daboase Beposo Bokorkope ShamaM ea n C o n ce n tr a ti o n o f T o ta l M er cu ry (T H g ) in S ed im en ts /µ g /K g Locations Wet Season Dry Season Seasons A Figures 4.1A-B: Mean concentrations of Total Mercury (THg) in sediments (A) and water (B) for both Dry and Wet season for the four locations. Sampling locations not drawn to scale. Error bars set at 1 standard deviation. -0.5 0 0.5 1 1.5 2 2.5 3 Daboase Beposo Bokorkope Shama T o ta l m er cu ry co n ce n tr a ti o n i n ri v er w a te r/ µ g /L Locations Wet season Dry season Seasons B University of Ghana http://ugspace.ug.edu.gh 73 Selenium levels in sediments were abundantly high in the two AGM sites Beposo and Daboase with overall mean concentrations of 58 mg/Kg and 70 mg/Kg respectively for the wet season. Selenium was below detection limit further downstream at Bokorkope and Shama. The least concentration of selenium in sediments for the dry season was recorded at Daboase (0.4 mg/Kg) with the highest recorded at Shama (1.8 mg/Kg). Selenium profile in sediments was similar for the two seasons both showing a wide distribution along the water course (Figure 4.2A). Figures 4.2A-B: Mean concentrations of Selenium (Se) in sediments (A) and water (B) for both Dry and Wet season for the four locations in the Study Area. Sampling locations not drawn to scale. Error bars are set at 1 standard deviation. 0 10 20 30 40 50 60 70 80 Daboase Beposo Bokorkope Shama M ea n C o n ce n tr a ti o n o f S el en iu m ( S e) i n S ed im en t/ m g /K g Locations Wet Season Dry Season Seasons A 0 2 4 6 8 10 12 14 16 Daboase Beposo Bokorkope ShamaS el en iu m c o n ce n tr a ti o n i n R iv er w a te r/ µ g /L Locations Wet season Dry season Seasons B University of Ghana http://ugspace.ug.edu.gh 74 4.3 MERCURY AND SELENIUM INTERACTION IN AQUATIC ECOSYSTEM 4.3.1 Sediments Selenium concentration in sediments was generally higher than mercury in the wet season with the highest concentrations of Se reported at individual sampling sites SBP1 and SDB4 (Figure 4.3B). However in the dry season, there were some sampling sites with THg concentrations higher than Se. Sampling sites DSDB1, DSDB2, DSBP1, DSBP2, DSBK1, DSBK2, DSSH1, and DSSH2, all reported higher levels of THg than Se (Figure 4.3A). Figures 4.3A and 4.3B illustrate the THg-Se concentrations in sediment for dry and wet seasons respectively. Figures 4.3A-B: Line charts showing the longitudinal distribution of THg-Se concentrations in Riverbed sediments for both seasons. Broken green line in Fig. 4.3A set at the maximum concentration of Se. DSDB1-GSSH2 are the sampling sites of sediments for the dry season (A). SBP1-SSH6 are the sampling sites of sediments for the wet season (B). DB-Daboase, BP-Beposo, BK-Bokorkope, SH-Shama 0 1000 2000 3000 4000 5000 6000 C o n ce n tr a ti o n o f T o ta l m er cu ry ( T H g ) a n d S el en iu m (S e) /µ g /K g Sampling Points not drawn to scale Hg Se A 0 200 400 600 800 1000 1200 1400 S D B 1 S D B 2 S D B 3 S D B 4 S D B 5 S D B 6 S B P 1 S B P 2 S B P 3 S B P 4 S B P 5 S B P 6 S B K 1 S B K 2 S B K 3 S B K 4 S B K 5 S B K 6 S S H 1 S S H 2 S S H 3 S S H 4 S S H 5 S S H 6 C o n ce n tr a ti o n s o f T o ta l m er cu ry ( T H g ) a n d se le n iu m ( S e) µ g /K g Sampling Points not drawn to scale Se Hg B University of Ghana http://ugspace.ug.edu.gh 75 Figures 4.4A and 4.4B are the projected scatter diagrams from the two line charts of individual sampling point of sediments for both seasons. The regression analysis and Pearson correlation studies differed for the two seasons. There was a strong positive relationship between THg and Se for the sediments in the wet season (n = 24, r2 = 0.9781, r = 0.989) (Figure 4.4B) and a weak inverse relationship between the two in the dry season (n = 16, r2 = 0.072, r = - 0.269) (Figure 4.4A). The relationship between THg and Se were significant for both seasons which is indicative of the possible association between both elements in sediments (Jin et al., 1999). y = -0.563x + 1304.2 r² = 0.0727 r = -0.269 0 1000 2000 3000 4000 5000 6000 0 500 1000 1500 2000 2500 T o ta l m er cu ry ( T H g ) C o n ce n tr a ti o n / µ g /k g Selenium (Se) Concentration/ µg/Kg A y = 0.0073x + 0.0719 r² = 0.9781 r = 0.989 0 0.2 0.4 0.6 0.8 1 1.2 1.4 0 20 40 60 80 100 120 140 160 180T o ta l m er cu ry ( T H g ) co n ce n tr a ti o n /m g /K g Selenium (Se) concentration/mg/Kg B Figure 4.4A: Scatter plot diagram showing THg as a function of Se for individual sampling points of sediment for Dry Season Figure 4.4B: Scatter plot diagram showing THg as a function of Se for individual sampling points of sediment for Wet Season University of Ghana http://ugspace.ug.edu.gh 76 4.3.2 River water Selenium concentrations in water samples were generally higher than THg for the two seasons. Total mercury concentrations were higher for individual sampling sites WDB2, WDB5, WBK1, WBK2, WSH2, WSH4 and WSH5 in the wet season (Figure 4.5B). Individual sampling points DWDB2, DWSH1 and DWSH2 had THg concentration higher than Se for the dry season (Figure 4.5A). Line charts for THg-Se concentrations in water for both seasons are illustrated in the Figures 4.5A and 4.5B below. Figures 4.5A-B: Line charts showing the longitudinal distribution of THg-Se concentration in surface water for both seasons. Broken green line in Fig. 4.5A set at the maximum concentration of THg. Broken green line in Fig. 4.5B set at the minimum detected concentration of Se. GWDB1-GWSH2 are the sampling sites of water for the dry season (A). WBP1-WSH6 are the sampling sites of surface water for the wet season (B). DB-Daboase, BP-Beposo, BK-Bokorkope, SH-Shama 0 2 4 6 8 10 12 14 16 18 20 T o ta l M n er cu ry (T H g ) a n d S el en iu m ( S e) co n ce n tr a ti o n / µ g /L Sampling Points not drawn to scale Hg Se A 0 0.5 1 1.5 2 2.5 3 T o ta l M er cu ry ( T H g ) a n d S el en iu m ( S e) co n ce n tr a ti o n i n W a te r/ µ g /L Sampling Points not drawn to scale Se Hg B University of Ghana http://ugspace.ug.edu.gh 77 y = 0.1687x + 0.6651 r² = 0.5246 r = 0.724 0 0.5 1 1.5 2 2.5 3 3.5 4 0 2 4 6 8 10 12 14 16 18 20 T o ta l M er cu ry ( T H g ) co n ce n tr a ti o n / (µ g /L ) Selenium (Se) Concentration/µg/L A y = -0.4654x + 1.3238 r² = 0.0896 r = 0.0635 0 0.5 1 1.5 2 2.5 3 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 T o ta l M er cu ry ( T H g ) co n ce n tr a ti o n /µ g /L Selenium (Se) concentration/µg/L B Figures 4.6A and 4.6B are the scatter diagrams from the line charts of individual sampling sites of surface water for both seasons. A strong positive relationship was observed for THg and Se in the dry season for water (n = 19, r2 = 0.5246, r = 0.724) (Figure 4.6A). In Figure 4.6A, an increase in mercury across the individual sampling sites is characterized by a decrease in selenium. However no relationship was observed for THg and Se in the wet season for water (n = 20, r2 = 0.0895, r = 0.0635) (Figure 4.6B). Clearly the regression and correlation studies showed that the relationship between the two elements differed for both seasons. Figure 4.6A: THg - Se correlation curves of individual sampling sites of water for Dry Season Figure 4.6B: THg - Se correlation curves of individual sampling sites of water for Wet Season University of Ghana http://ugspace.ug.edu.gh 78 4.4 TRACE ELEMENTS IN FISH SPECIES Ten trace elements Hg, Se, Cd, Cu, Fe, Mn, Pb, Cr, Ni, and Zn were measured in different tissue parts of Xenomystus nigri and in the dorsal tissues of Clarias submarginatus (Mudfish). Cu and Cd were below the detection limit in Mudfish (Table 4.2). Fe recorded the highest average concentration in Mudfish (372 mg/Kg dry weight). Zn recorded an average concentration of 105 mg/kg dry weight for dorsal tissues of Mudfish. Mn recorded an average concentration of 55 mg/kg dry weight for Mudfish. Ni, Pb, Hg and Se recorded average concentrations of 12 mg/Kg, 33 mg/Kg, 1 mg/Kg and 155 mg/Kg dry weight respectively in dorsal tissues of Mudfish (Table 4.2). Trace elements were in decreasing order of: Fe > Se > Zn > Mn > Pb > Ni > Cd > Hg > Cu ≈ Cd Mn and Cu were below the detection limit in different tissues of Xenomystus nigri. Fe recorded the highest average concentration in Xenomystus nigri (7 mg/Kg wet weight). Hg and Se recorded an average concentrations of 315 µg/Kg and 786 µg/Kg wet weights in Xenomystus nigri respectively. Pb, Cd, Cr, Zn and Ni recorded average concentrations of 3.4 mg/Kg, 0.62 mg/Kg, 0.8 mg/Kg, 1.1 mg/Kg and 2.0 mg/Kg wet weights in Xenomystus nigri (Table 4.3). Trace elements were in decreasing order of: Fe > Pb > Ni > Zn > Cr > Se > Cd > Hg > Mn ≈ Cu Concentrations of trace elements in Mudfish were relatively higher than in Xenomystus nigri (Tables 4.2 and 4.3). The mode of preservation of Clarias submarginatus such as air drying or smoking with wood fire by locals may have accounted for elevated levels of trace elements since trace elements are introduced into the fish tissues through these processes. University of Ghana http://ugspace.ug.edu.gh 79 Table 4.2: Concentrations of trace elements in the dorsal tissues of Clarias submarginatus (Mudfish) CODES/ mg/Kg Fe Mn Pb Cu Cd Cr Zn Ni Hg Se F1 455.8 56 12.4 BDL 0.4 BDL 90 BDL 1.6 197.4 F2 332.8 55.8 64 BDL BDL BDL 108 BDL 0.2 BDL F3 336.6 56.2 12.6 BDL 0.2 BDL 121.4 0.2 2.2 347.8 F4 336.6 55.2 68.4 BDL 2.4 BDL 106.8 2.2 0.2 17.8 F5 386.8 55.6 17.6 BDL 2.2 BDL 103.8 BDL 1.2 172.6 F6 387.2 52.4 21.4 BDL 0.6 BDL 104.2 33.6 0.4 41.8 Max. 455.8 56.2 68.4 - 2.4 - 121.4 33.6 2.2 347.8 Min. 332.8 52.4 12.6 - BDL - 90 BDL 0.2 BDL Mean 372.633 55.2 32.7 - 1.16 - 105.7 12 0.9667 155.48 S.D 43.804 1.29 23.89 - 0.94 - 9.177 15.29 0.7608 119.09 Mean ±SD 372±44 55±1 33±24 - 1.1±0.9 - 105±9 12±15 1.0±0.8 155±119 * BDL- below detection limit, detection limit Cu- 0.2 mg/Kg, Cd-0.2 mg/Kg, Ni-0.2 mg/Kg, Se-0.2 mg/Kg Fish Species: Mudfish (Clarias submarginatus) (Peters, 1882) n=8 (mg/Kg dry weight) Fish length (6±1) cm, Fish weight (23±7) g, dorsal part muscle tissues University of Ghana http://ugspace.ug.edu.gh 80 Table 4.3: Concentrations of trace elements in the different tissues of Xenomystus nigri SAMPLE ID/(mg/Kg) Fe Mn Pb Cu Cd Cr Zn Ni Hg/ (µg/Kg) Se/ (µg/Kg) F1Dr 12.8 BDL BDL BDL BDL 1.2 BDL 2.8 248 278 F2In 2.8 BDL BDL BDL BDL 0.2 BDL 2.0 BDL 330 F3Dr 12.6 BDL BDL BDL BDL 1.3 1.2 2.6 38 324 F4V BDL BDL BDL BDL BDL BDL 0.4 0.6 460 822 F5Ts BDL BDL 3.5 BDL 0.6 BDL BDL 1.4 BDL 1136 F6V BDL BDL BDL BDL 0.7 BDL BDL BDL 500 BDL F7In 2.8 BDL BDL BDL BDL 0.2 BDL 2.2 BDL 242 F8V BDL BDL BDL BDL 0.6 BDL 1.8 2.0 500 624 F9Dr 13.6 BDL BDL BDL BDL 1.2 BDL 2.6 144 1076 F10Ts 2.4 BDL 3.2 BDL 0.6 BDL BDL BDL BDL 2242 Max 13.6 - 3.5 - 0.6 1.3 1.8 2.8 500 2242 Min BDL - BDL - BDL BDL BDL BDL BDL BDL Mean 7.83 - 3.35 - 0.625 0.82 1.13 2.025 315 786 S.D. 5.17 - 0.15 - 0.043 0.51 0.57 0.681 182.54 608.226 Mean± S.D 7±5 - 3.4±0.2 - 0.62±0.04 0.8±0.5 1.1±0.6 2.0±0.7 315±183 786±608 * BDL- below detection limit, detection limit Fe-1.2 mg/Kg, Mn-0.4 mg/Kg, Cu- 0.2 mg/Kg, Cd-0.2 mg/Kg, Ni-0.2 mg/Kg, Pb-0.2 mg/Kg, Cr-0.2 mg/Kg, Zn-0.2 mg/Kg, Se-2 µg/Kg, Hg-2µg/Kg Fish species: Xenomystus nigri (Günther, 1868) n=4, (mg/Kg, µg/Kg wet weight) Fish length (25.7±0.9) cm, Fish weight (174±2) g University of Ghana http://ugspace.ug.edu.gh 81 4.4.1 Bioaccumulation factor (BAF) in fish species The bioaccumulation factor of the fish was calculated as follows: BAF= Cfish /Cwater Cfish and Cwater refer to the concentration of a metal in fish and water respectively. Bioaccumulation of trace metals was observed in the dorsal tissues of Mudfish (Clarias submarginatus) and in various tissue parts of Xenomystus nigri. Cu was not detected in either fish species. Mn and Cr were not detected in the tissues of Xenomystus nigri and Mudfish. Calculated BAF showed that Se and Ni bioaccumulated the highest in Mudfish and Xenomystus nigri respectively. BAF in a decreasing order of trace metals in Mudfish was; Se (1.75E5) > Pb (3667.7) > Zn (1875) > Hg (1346.1) > Mn (1100) > Ni (600) > Cd (183.3) > Fe (62) Cu ≈ Cr BAF in a decreasing order of trace metals in Xenomystus nigri was; Ni (1666.7) > Cr (160) > Cd (156) > Hg (95.87) > Se (93.07) > Zn (78.57) > Pb (68) > Fe (10) > Mn ≈ Cu 4.4.2 Mercury-Selenium concentrations and Bioaccumulation Factors (BAF) in fish parts The concentration of THg-Se and BAF of fish tissues in both Mudfish and Xenomystus nigri are presented in Tables 4.2 to 4.5. Selenium (Se) concentration was relatively higher than THg concentration in the tissue parts of both fish species. F2 recorded the lowest concentration for both THg and Se in Mudfish (Table 4.2). F3 recorded the highest concentration and BAF of THg and Se in Mudfish with BAF of 3.07E3 and concentrations of 2.2 mg/Kg for THg and BAF of 4.71E5 and concentrations of 347.8 mg/Kg for Se (Tables 4.2 and 4.5). University of Ghana http://ugspace.ug.edu.gh 82 Mercury had bioaccumulated the highest in the ventral tissue than the dorsal tissue in Xenomystus nigri (Figure 4.8). Mercury was however below the detection limit in the internal organs and tail section tissues of Xenomystus nigri (Figure 4.8). Highest concentration and BAF was recorded in ventral tissue parts F6v and F8v (500 µg/Kg, 261.7) (Table 4.4). Selenium had bioaccumulated the highest in the tail section tissues F10ts (2242 µg/Kg, 295) and was below the detection limit in F6v (Figure 4.8). Both mercury (Hg) and selenium (Se) showed a wide distribution in different tissues of Xenomystus nigri with Coefficient of variation (CoV/%) of 58% and 77% respectively and a wide distribution of 80% and 76% respectively for the dorsal tissue of Mudfish. Table 4.4: Bioaccumulation Factors (BAF) in the tissue parts of Xenomystus nigri Fish parts Hg Se Log BAF Se Log BAF Hg F1Dr 129.84 36.57 1.56 2.11 F2In 0 43.42 1.63 - F3Dr 5 42.60 1.63 0.69 F4V 240.8 108.15 2.03 2.38 F5Ts 0 149.47 2.17 - F6V 261.7 0 - 2.41 F7In 0 31.84 1.50 - F8V 261.7 82.10 1.91 2.41 F9Dr 59.68 141.57 2.15 1.77 F10Ts 0 295 2.46 - Table 4.5: Bioaccumulation Factors in the dorsal tissue parts of Clarias submarginatus Fish parts Hg/E3 Se/E3 Log BAF Se Log BAF Hg F1 2.23 267.84 2.427 0.348 F2 0.27 0 0 -0.568 F3 3.07 471.9 2.673 0.487 F4 0.28 24.15 1.380 -0.554 F5 1.67 234.19 2.369 0.223 F6 0.56 56.71 1.753 -0.253 University of Ghana http://ugspace.ug.edu.gh 83 0 50 100 150 200 250 300 350 400 F1 F2 F3 F4 F5 F6 E le m en ta l C o n ce n tr a ti o n /m g /K g D ry w ei g h t Fish Dorsal part Hg Se 0 500 1000 1500 2000 2500 F1Dr F9Dr F3Dr F4V F8V F6V F7In F2In F5Ts F10Ts E le m en ta l C o n ce n tr a ti o n /m g /K g W et w ei g h t Hg Se Fish parts: V-Ventral Dr-Dorsal In-Inner Organs Ts-Tail Section Figure 4.7: Mercury (THg) and Selenium (Se) Concentrations in the dorsal tissues of Mudfish (Clarias submarginatus) Figure 4.8: Mercury (THg) and Selenium (Se) Concentrations in the different tissues of Xenomystus nigri. Fish parts: V-Ventral, Dr-Dorsal, In-Inner Organs, Ts-Tail Section University of Ghana http://ugspace.ug.edu.gh 84 4.4.3 Mercury and Selenium molar ratios A 1:1 molar ratio between Se and Hg has been reported in organs (mainly liver) of some mammals (Koerman et al., 1975). For a protective effect of selenium to be noticed in the detoxification of mercury, threshold concentrations of selenium must be reached especially in fish parts. The selenium/mercury (Se/Hg) molar ratio was obtained by using the molecular weight (200.59 for Hg and 78.9 for Se). Average (Hg/Se) molar ratios in Xenomystus nigri (0.196) were higher than in Mudfish (0.003) (Tables 4.6 and 4.7). Average (Se/Hg) molar ratios in Mudfish (261.09) were higher than in Xenomystus nigri (5.116) (Tables 4.6 and 4.7). Codes Hg(µmol/Kg) Se(µmol /Kg) Hg:Se Se:Hg F1 8 2498.70 0.0032 312.33 F2 1 - - - F3 11 4402.53 0.0025 400.18 F4 1 225.30 0.0044 225.30 F5 6 2184.80 0.0027 364.13 F6 2 529.11 0.0037 264.50 Average 4.833 1968.088 0.0033 261.09 Table 4.6: Total Mercury-Selenium molar ratio in Fish Species (Mudfish) University of Ghana http://ugspace.ug.edu.gh 85 Codes Hg(µmol/Kg) Se(µmol /Kg) Hg:Se Se:Hg F1Dr 1.24 3.51 0.35 2.83 F2In 0 4.17 - - F3Dr 0.19 4.1 0.05 21.57 F4V 2.3 10.4 0.22 4.7 F5Ts 0 14.3 - - F6V 2.5 0 - - F7In 0 3.06 - - F8V 2.5 7.89 0.31 3.136 F9Dr 0.72 13.62 0.05 18.91 F10Ts 0 28.37 - - Average 0.945 8.942 0.196 5.1146 From Tables 4.6 and 4.7 total mercury-selenium ratios (Hg/Se, Se/Hg) varied for the two fish species. The highest Se:Hg molar ratio in Xenomystus nigri was recorded for F3Dr (21.57) which corresponded to the lowest Hg:Se molar ratio 0.05. The 1:1 molar ratio complex as reported in marine mammals is not supported by the data in Tables 4.6 and 4.7. 4.4.4 Relationship between Total Mercury and Selenium in fish species Regression analysis and Pearson’s correlation for THg and Se in the two fish species showed a strong direct association in mudfish and a weak association and an inverse relationship in the different tissues of Xenomystus nigri. Mercury was positively correlated with Selenium in the dorsal tissues of Mudfish (r2 = 0.98, r = 0.99) (Figure 4.10) and negatively correlated in the fish tissues of Xenomystus nigri (r2 = 0.0987, r = -0.314) (Figure 4.9). Logarithm transformation of bioaccumulation factors was applied to normalize the data set for regression analysis. This was because the data set was not normally distributed. Logarithm transformation of the bioaccumulation factors also gave similar trends in both Mudfish (r2 = 0.55, r = 0.74) (Figure 4.12) and Xenomystus nigri (r2 = 0.121, r = -0.349) (Figure 4.11). An increase in THg was Table 4.7: Total Mercury-Selenium molar ratios in Xenomystus nigri University of Ghana http://ugspace.ug.edu.gh 86 characterized by the increase in Se in Mudfish. An increase in Se corresponded to a decrease in THg across the different tissues of Xenomystus nigri. An increase in the bioaccumulation of Se was characterized by a decrease in the bioaccumulation of Hg across the different tissues in Xenomystus nigri. y = -0.0417x + 1.3179 r² = 0.0987 r = -0.314 0 0.5 1 1.5 2 2.5 3 0 5 10 15 20 25 30 T o ta l M er cu ry T H g /µ m o l/ K g Selenium (Se)/ µmol/Kg A y = 0.0024x + 0.8713 r² = 0.9806 r = 0.99 0 2 4 6 8 10 12 14 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 T o ta l M er cu ry (T H g )/ µ m o l/ K g Selenium (Se)/µmol/Kg B Figure 4.9: Scatter diagram showing the molar concentrations of THg as a function of the molar concentrations of Selenium (Se) across the different tissues of Xenomystus nigri Figure 4.10: Scatter diagram showing the molar concentrations of THg as a function of the molar concentrations of Selenium (Se) in the dorsal tissues of Mudfish (Clarias submarginatus) University of Ghana http://ugspace.ug.edu.gh 87 4.4.5 Selenium association with other elements in fish tissues (Cd, Fe, Zn) Apart from mercury, it has been found that selenium also interacts with other heavy metals in certain biological systems (Parizek, 1978; Feroci et al., 2005). Its presence either reduces the availability of other heavy metals such as cadmium (Cd) whiles its deficiency causes an overload of iron (Fe) and an unbalanced in vivo distribution of other elements such as zinc (Zn), magnesium (Mg), copper (Cu) and calcium (Ca) (Chareonpong-Kawamoto et al., 1995). Regression analysis between selenium and heavy metals (Cd, Fe, Zn) in the tissue parts of Clarias (0.03 ≤ r2 ≤ 0.08) and Xenomystus nigri (0.0133 ≤ r2 ≤ 0.109) all resulted in virtually no significant relationships (Figures 4.13A-C and 4.14A-C). y = -0.5834x + 2.1712 r² = 0.1219 r = -0.349 0 1 2 3 0 0.5 1 1.5 2 2.5 3 L o g B A F H g Log BAF Se A y = 0.1924x + 1.4084 r² = 0.5547 r = 0.74 0 1 2 3 0 1 2 3 4 5 6 L o g B A F H g Log BAF Se B Figure 4.11: Scatter diagram showing the logarithm transformation of BAF of THg as a function of the BAF of Se in the different tissues of Xenomystus nigri Figure 4.12: Scatter diagram showing the logarithm transformation of BAF of THg as a function of the BAF of Se in the dorsal tissues of Mudfish (Clarias submarginatus) University of Ghana http://ugspace.ug.edu.gh 88 Xenomystus nigri y = 0.0002x + 0.1348 r² = 0.109 0 0.2 0.4 0.6 0.8 0 500 1000 1500 2000 2500 C a d m iu m (C d ) co n ce n tr a ti o n / m g /K g w et w ei g h t Selenium (Se) concentration/µg/Kg A y = -0.0001x + 0.4427 r² = 0.0223 0 0.5 1 1.5 2 0 500 1000 1500 2000 2500 Z in c (Z n ) co n ce n tr a ti o n /m g /K g w et w ei g h t Selenium (Se) concentration/ µg/Kg B y = -0.001x + 5.4266 r² = 0.0133 0 5 10 15 0 500 1000 1500 2000 2500 Ir o n ( F e) co n ce n tr a ti o n /m g /K g w et w ei g h t Selenium (Se) concentration/µg/Kg C Figures 4.13 A-C: Scatter diagram showing a plot of Fe, Zn and Cd as a function of Se in various tissue parts of Xenomystus nigri. Figure A – Cd against Se, Figure B – Zn against Se, Figure C- Fe against Se. Fe, Cd, and Zn are the dependent variables. Se is the independent variable University of Ghana http://ugspace.ug.edu.gh 89 Mudfish (Clarias submarginatus) y = -0.0017x + 1.1878 r² = 0.0478 0 0.5 1 1.5 2 2.5 3 0 50 100 150 200 250 300 350 400 C a d m iu m ( C d ) co n ce n tr a ti o n / D ry W ei g h t m g /K g Selenium (Se) concentration A y = 0.0219x + 102.87 r² = 0.0861 0 50 100 150 0 50 100 150 200 250 300 350 400 Z in c (Z n ) co n ce n tr a ti o n / D ry w ei g h t m g /K g Selenium (Se) concentration B y = 0.0692x + 363.67 r² = 0.0378 0 100 200 300 400 500 0 50 100 150 200 250 300 350 400Ir o n ( F e) c o n ce n tr a ti o n / D ry w ei g h t/ m g /K g Selenium (Se) concentration C Figures 4.14A-C: Scatter diagram showing a plot of Fe, Zn and Cd as a function of Se in the dorsal tissues of Mudfish (Clarias submarginatus). Figure A – Cd against Se, Figure B – Zn against Se, Figure C- Fe against Se. Zn, Cd, and Fe are the dependent variable. Se is the independent variable. University of Ghana http://ugspace.ug.edu.gh 90 4.5 MERCURY (THg) RELATIONSHIP WITH IRON (Fe) AND MANGANESE (Mn) Dissolved mercury has been found to adsorb strongly to Fe- or Mn-oxyhydroxides (Balogh et al., 1998). A statistically significant positive relationship was found between THg and aqueous total Fe in water and sediment (Warner et al., 2005). The relationship between Fe and THg in sediment for both seasons was statistically insignificant in this study (0.009 ≤ r2 ≤ 0.16) (Figures 4.15C and 4.15E). The same could be said of Fe and THg in River water (0.0153 ≤ r2 ≤ 0.233) (Figures 4.15F and 4.15H). A weak relationship was observed between Mn and THg for sediments (0.0289 ≤ r2 ≤ 0.2586) (Figures 4.15B and 4.15D) and river water (0.0068 ≤ r2 ≤ 0.178) (Figures 4.15A and 4.15G) for both seasons. THg relationship with Fe and Mn although statistically not significant varied in river water and sediments for the two seasons. 4.6 SELENIUM RELATIONSHIP WITH IRON (Fe) AND MANGANESE (Mn) Selenium species depending on pH adsorb onto oxides of Mn and Fe (Ballistrieri and Chao, 1990). Statistically significant relationships were observed for Se with Fe and Mn in sediments for both seasons. A moderately positive relationship was observed between Se and Mn (0.2708 ≤ r2 ≤ 0.4251) in sediments for both seasons (Figures 4.16A and 4.16B). A moderately strong relationship between Se and Fe was observed for sediments in the dry season (r2 = 0.4251) (Figure 25D) with a weak relationship in the wet season (r2 = 0.0128) (Figure 4.16E). Weak relationships were observed in River water for both seasons between Se and Fe (0.007 ≤ r2 ≤ 0.06) (Figures 4.16C and 4.16F) and between Se and Mn (0.016 ≤ r2 ≤ 0.095) (Figures 4.16G and 4.16H). Statistically significant relationship between Se and Fe/Mn suggests an association in sediments than in River water. University of Ghana http://ugspace.ug.edu.gh 91 y = -9.0945x + 1.1871 r² = 0.178 0 1 2 3 0 0.05 0.1 0.15 T H g / µ g /L Mn/mg/L H2O/WETA y = 47.3x + 194.79 r² = 0.2586 0 100 200 300 0 0.5 1 1.5 M n / m g /K g THg/ mg/Kg SED/WETB y = 99.588x + 5488.5 r² = 0.009 0 2000 4000 6000 8000 0 0.5 1 1.5 F e /m g /K g THg /mg/Kg SED/WET C y = -2.5834x + 2698.6 r² = 0.1621 0 2000 4000 6000 0 500 1000 1500 T H g / µ g /K g Fe/ mg/Kg SED/DRYE y = -22.122x + 1241.7 r² = 0.0289 0 2000 4000 6000 0 10 20 30 40 T H g / µ g /K g Mn / mg/kg SED/DRYD y = -0.2919x + 2.6082 r² = 0.233 -1 0 1 2 3 0 5 10 15 TH g/ µ g /L Fe/mg/L H2O/WETF y = 14.659x + 1.5748 r² = 0.0068 0 2 4 0 0.01 0.02 0.03 T H g / µ g /L Mn/mg/L H2O/DRYG y = 0.2396x + 1.6031 r² = 0.0157 0 2 4 0 1 2 3 T H g / µ g /L Fe/mg/L H2O/DRYH Figures 4.15A-H: Scatter diagrams showing the correlation curves of THg with Mn and Fe in sediments and water for dry and wet seasons. Figures: A-THg vrs Mn water wet season, B- Mn vrs THg sediments wet season, C-Fe vrs THg sediments wet season, D-THg vrs Mn sediments dry season, E-THg vrs Fe sediments dry season, F-THg vrs Fe water wet season, G-THg vrs Mn water wet season, H-THg vrs Fe water dry season University of Ghana http://ugspace.ug.edu.gh 92 y = 0.0085x + 16.856 r² = 0.4251 0 10 20 30 40 0 1000 2000 3000 M n / m g /K g Se/ µg/Kg SED/DRYA y = 0.3559x + 197.81 r² = 0.2708 0 100 200 300 0 50 100 150 200 M n m g /K g Se/ mg/Kg SED/WET B y = -0.0326x + 0.8914 r² = 0.0601 0 1 2 3 0 5 10 15 20 F e /m g /L Se/µg/L H2O/DRYC y = 0.874x + 5490.9 r² = 0.0128 0 5000 10000 0 50 100 150 200 F e/ m g /K g Se/ mg/kg SED/WET D y = 0.1744x + 621.4 r² = 0.4347 0 500 1000 1500 0 1000 2000 3000 F e /m g /K g Se/µg/Kg SED/DRYE y = -0.0002x + 0.0138 r² = 0.0168 0 0.01 0.02 0.03 0 5 10 15 20 M n / m g /L Se/µg/L H2O/DRYG y = 0.0195x + 0.0374 r² = 0.0956 0 0.05 0.1 0.15 0 0.5 1 1.5 2 M n / m g /L Se/ µg/L H2O/WETH y = 0.1881x + 6.343 r² = 0.007 0 5 10 15 0 0.5 1 1.5 2 F e/ m g /L Se/µg/L H2O/WETF Figures 4.16A-H: Scatter diagrams showing the correlation curves of Mn and Fe with Se in sediments and water for dry and wet seasons. Figures: A- Mn vrs Se sediment dry season, B- Mn vrs Se sediment wet season, C- Fe vrs Se water dry season, D- Fe vrs Se sediment wet season, E- Fe vrs Se sediment dry season, F-Fe vrs Se water wet season, G-Mn vrs Se water wet season, H-Mn vrs Se water wet season University of Ghana http://ugspace.ug.edu.gh 93 4.7 MERCURY RELATIONSHIP WITH TSS AND SULFATE Mercury being a soft metal (B class) shows a pronounced preference for ligands of sulfur especially attached to dissolved organic matter (DOM) (Ravichandran, 2004). In this study, there was a weak positive relationship (r2 = 0.1038, r = 0.322) between dissolved sulfates and THg in River water (Figure 4.17A). Mercury methylation is particularly aided by sulfur reducing bacteria and a weak positive correlation highlights the affinity of mercury to sulfur containing compounds. TSS on the other hand had a weak inverse relationship (r2 = 0.08, r = -0.287) with THg contrary to what was observed by Balogh et al., 1998 and Warner et al., 2005 (Figure 4.17B). y = 0.0058x + 1.133 r² = 0.1038 r = 0.322 0 0.5 1 1.5 2 2.5 3 0 20 40 60 80 100 120 140 T H g /µ g /L Dissolved SO4 2- /mg/L A y = -0.0013x + 1.6208 r² = 0.0829 r = -0.287 0 0.5 1 1.5 2 2.5 3 0 100 200 300 400 500 600 T H g /µ g /L TSS/mg/L B Figures 4.17A-B: Scatter diagram of averaged THg of locations as a function of Dissolved SO42- (A) and TSS (B) in water for the two seasons. TSS is a physicochemical parameter whilst SO42- is a water nutrient. University of Ghana http://ugspace.ug.edu.gh 94 4.8 OTHER HEAVY METAL DISTRIBUTIONS 4.8.1 Sediments Eight other metals namely Fe, Mn, Pb, Cr, Cu, Ni, Cd, and Zn were determined in sediments. Fe was the most abundant in sediments for the two seasons. Overall mean concentration of Fe in sediments was 5738 mg/Kg in the wet season and 773 mg/Kg in the dry season. Minimum average level of Fe in the wet season was recorded at Beposo (5470 mg/kg) whiles the highest levels was reported at Shama (6388 mg/Kg). Minimum level in the dry season was recorded at Bokorkope (675 mg/Kg) whiles the highest was recorded at Shama (895 mg/Kg) (Figure 4.18A). Overall mean concentration of Mn in sediments in the dry season (24 mg/Kg, range: 15.2-30 mg/Kg) was far less than what was recorded for the wet season (213 mg/Kg, range: 156-274 mg/Kg). Bokorkope and Shama recorded the minimum average concentration and highest average concentration respectively for the sampling locations for both seasons (Figure 4.18B). Overall mean concentration of Pb in the dry season was 8 mg/Kg (range: 0.9-13.6 mg/Kg) which was generally less than the overall mean concentration for the wet season (14 mg/Kg, range: 7- 31 mg/Kg). The highest average concentrations of Pb for both seasons was recorded at Shama (Figure 4.18C). Overall mean concentration of Cu in the study area in the wet season was 2.8 mg/Kg (range: 2-4 mg/Kg) which had increased to 5 mg/Kg (range: 2.6-7 mg/Kg) in the dry season with concentrations for each location generally higher in the dry season than in the wet season (Figure 4.18F). Zn was generally higher for all four locations in the wet season (55 mg/Kg, range: 41-82 mg/Kg) than in the dry season (4 mg/Kg, range: 3.1-7.4 mg/Kg). The highest average concentration of Zn was recorded at Shama for both seasons (Figure 4.18E). University of Ghana http://ugspace.ug.edu.gh 95 Ni in sediments were generally high in the wet season than the dry season with an overall mean concentrations of 7 mg/Kg (range: 5-8 mg/Kg) in the wet season and 1.6 mg/Kg (range: 0.9-2.8 mg/Kg) in the dry season (Figure 4.18G). Cr concentrations was below the detection limit in sediments for the wet season but the dry season recorded an overall mean concentration of 1.9 mg/Kg (range: 1.2-3 mg/Kg) (Figure 4.18H). Cd on the other hand was below detection limit in sediment for the dry season but recorded an overall mean concentration of 0.8 mg/Kg (range: 0.3-1.3 mg/Kg) in the wet season (Figure 4.18D). Heavy metals was in the decreasing order of Fe > Mn > Zn > Pb > Ni > Cu > Cd > Cr in the wet season and a decreasing order of Fe > Mn > Pb > Cu > Zn > Ni > Cr > Cd in the dry season. University of Ghana http://ugspace.ug.edu.gh 96 0 1000 2000 3000 4000 5000 6000 7000 Daboase Beposo Bokorkope ShamaM ea n c o n ce n tr a ti o n s o f Ir o n ( F e) i n S ed im en t S a m p le s/ (m g /K g ) Locations Wet Season Dry Season Seasons A 0 50 100 150 200 250 300 350 Daboase Beposo Bokorkope ShamaM ea n C o n ce n tr a ti o n o f M a n g a n es e in S ed im en t sa m p le s/ (m g /K g ) Locations Wet Season Dry Season Seasons B 0 5 10 15 20 25 30 35 Daboase Beposo Bokorkope Shama M ea n c o n ce n tr a ti o n o f L ea d i n S ed im en t sa m p le s/ (m g /K g ) Locations Wet Season Dry Season Seasons C 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Daboase Beposo Bokorkope Shama M ea n C a d m iu m (C d ) co n ce n tr a ti o n s in se d im en t/ m g /K g Locations Wet Season Dry Season Seasons D Figures 4.18A-D: Distribution of Pb, Cd, Mn, and Fe in sediments. Sampling locations are not drawn to scale. Error bars are set at 1 standard deviation. Fig. A - Fe, B - Mn, C - Pb, D - Cd University of Ghana http://ugspace.ug.edu.gh 97 0 20 40 60 80 100 Daboase Beposo Bokorkope ShamaM ea n C o n ce n tr a ti o n o f Z in c( Z n ) in S ed im en ts /m g /K g Locations Wet Season Dry Season Seasons E 0 2 4 6 8 Daboase Beposo Bokorkope ShamaM ea n c o n ce n tr a ti o n s o f C o p p er ( C u ) in S ed im m en t/ m g /K g Locations Wet Season Dry Season Seasons F 0 2 4 6 8 10 Daboase Beposo Bokorkope ShamaM ea n C o n ce n tr a ti o n o f N ic k el ( N i) i n S ed im en t/ m g /K g Locations Wet Season Dry Season Seasons G 0 1 2 3 4 Daboase Beposo Bokorkope ShamaM ea n C o n ce n tr a ti o n o f C h ro m iu m (C r) i n S ed im en t/ m g /K g Locations Wet Season Dry Season Seasons H Figures 4.18E-H: Distribution of Zn, Cr, Ni, and Cu in sediments. Sampling locations are not drawn to scale. Error bars are set at 1 standard deviation. Fig. E - Zn, F - Cu, G - Ni, H - Cr University of Ghana http://ugspace.ug.edu.gh 98 4.8.2 Water samples The overall mean concentration of 6 mg/L (range: 5.6-9 mg/L) was recorded for Fe in the wet season with an overall mean concentration of 0.7 mg/L (range: 0.04-1.44 mg/L) recorded for the dry season. The minimum average concentration of Fe for wet season was recorded at Daboase (5.6 mg/L) and for the dry season was recorded at Bokorkope (0.04 mg/L) respectively (Figure 4.19H). The maximum average concentration of Fe for wet season was recorded at Beposo (9 mg/L) and for the dry season was recorded at Daboase (1.44 mg/L) (Appendix B1). Concentrations of Fe were generally higher for the wet season than the dry season for all locations (Figure 4.19H). Maximum average concentration of Mn in the wet season was recorded at Beposo (0.11 mg/L) with a reported mean of 0.05 mg/L (range: 0.022-0.11 mg/L) in the wet season and a dry season mean concentration of 0.013 mg/L (range: 0.007-0.020 mg/L) (Appendix B4). Overall mean concentration of Pb was 0.009 mg/L (range: BDL-0.02 mg/L) in the wet season with a recorded mean of 0.05 mg/L (range: BDL-0.082 mg/L) in the dry season. Pb was largely below the detection limit at Daboase for both seasons but a recording of the metal was made at sampling site WDB1 at Daboase in the wet season with a value of 0.007 mg/L (Appendix B5). Overall mean concentrations of Cu for both seasons were comparable with mean values of 0.026 mg/L (range: 0.021-0.036 mg/L) and 0.02 mg/L (range: 0.006-0.038 mg/L) for the dry and wet season respectively (Figures 28C). Recordings of copper were made at particular sampling sites WBP1 at Beposo (0.006 mg/L) and WBK5 at Bokorkope (0.006 mg/L) in the wet season (Appendix B7). Cd was largely below the detection limit in the dry season but recordings of 0.004 mg/L were made at two sites DWBK 1 and DWBK 2 (Appendix. B7). University of Ghana http://ugspace.ug.edu.gh 99 Zn recorded an overall mean concentration of 0.056 mg/L (range: 0.04-0.07 mg/L) for the wet season and an overall mean concentration of 0.014 mg/L (range: 0.0095-0.0245 mg/L) in the dry season far less than what was recorded for the wet season (Appendix B11, Figure 4.19E). Mean maximum concentration of the metal was recorded at Shama in the wet (0.07 mg/L) and dry season (0.0245 mg/L) (Appendix B11). Concentrations of Ni in river water for the four locations were generally higher in the wet season than the dry season with an overall mean concentrations of 0.02 mg/L (range: 0.009-0.013 mg/L) recorded for the wet season and 0.012 mg/L (range: 0.007-0.002 mg/L) recorded for the dry season (Appendix 13, Figure 4.19B). Concentrations of Ni were highest at Shama for the two seasons (Figure 4.19B). Cr was largely below the detection limit in the wet season but particular recordings were made at sampling sites at Beposo (0.004 mg/L) and Bokorkope (0.004 mg/L) in the dry season (Appendix B15). Heavy metal levels were in the decreasing order of Fe > Zn > Mn > N i≈ Cu > Pb > Cd > Cr in the wet season and a decreasing order of Fe > Pb > Cu > Zn > Mn > Ni > Cr > Cd in the dry season. University of Ghana http://ugspace.ug.edu.gh 100 0 0.002 0.004 0.006 0.008 0.01 0.012 Daboase Beposo Bokorkope Shama M ea n C o n ce n tr a ti o n s o f C h ro m iu m ( C r) i n w a te r/ m g /L Locations Wet Season Dry Season Seasons A 0 0.01 0.02 0.03 0.04 0.05 0.06 Daboase Beposo Bokorkope Shama M ea n C o n ce n tr a ti o n s o f N ic k el (N i) i n w a te r/ m g /L Locations Wet Season Dry Season Seasons B 0 0.01 0.02 0.03 0.04 0.05 Daboase Beposo Bokorkope Shama M ea n c o n ce n tr a ti o n s o f C o p p er ( C u ) in w a te r /m g /L Locations Wet Season Dry Season Seasons C 0 0.002 0.004 0.006 0.008 0.01 Daboase Beposo Bokorkope Shama M ea n c o n ce n tr a ti o n o f C a d m iu m ( C d ) in w a te r/ m g /L Locations Wet Season Dry Season Seasons D Figures 4.19A-D: Distribution of Cr, Ni, and Cu, Cd in water. Sampling locations are not drawn to scale. Error bars are set at 1 standard deviation. Fig. A - Cr, B - Ni, C - Cu, D - Cd University of Ghana http://ugspace.ug.edu.gh 101 0 0.02 0.04 0.06 0.08 Daboase Beposo Bokorkope ShamaM ea n C o n ce n tr a ti o n o f Z in c( Z n ) in w a te r/ m g /L Locations Wet Season Dry Season Seasons E 0 0.02 0.04 0.06 0.08 0.1 Daboase Beposo Bokorkope Shama M ea n c o n ce n tr a ti o n o f L ea d ( P b ) in w a te r/ (m g /L ) Locations Wet Season Dry Season Seasons F 0 0.05 0.1 0.15 Daboase Beposo Bokorkope ShamaM ea n C o n ce n tr a ti o n o f M a n g a n es e in w a te r/ (m g /L ) Locations Wet Season Dry Season Seasons G 0 2 4 6 8 10 Daboase Beposo Bokorkope ShamaM ea n c o n ce n tr a ti o n o f F e in w a te r /( m g /L ) Locations Wet Season Dry Season Seasons H Figures 4.19E-H: Distribution of Zn, Pb, Mn and Fe in water. Sampling locations are not drawn to scale. Error bars are set at 1 standard deviation. Fig. E – Zn, F – Pb, G – Mn, H - Fe University of Ghana http://ugspace.ug.edu.gh 102 4.9 WATER NUTRIENTS AND MACRO ELEMENTS (IONS) Three water nutrients PO43-, SO42- and NO3- and two macro elements were Na+ and K+ determined in this study. Four of the ions Na+ ,K+, SO43- and NO3- had their overall mean concentrations for the study area higher in the dry season than in the wet season. Overall mean concentration of PO43- for the dry and wet season were comparable with values of 0.28 mg/L for the wet season and 0.2 mg/L for the dry season (Appendix C4). Na+ had a minimum concentration of 19.9 mg/L recorded for Bokorkope in the wet season and the highest of 12,490 mg/L recorded for Shama in the dry season (Appendix C1, Figure 4.20B). Minimum concentration of K+ for the dry season was recorded at Daboase (4.3 mg/L) with the highest concentration of 563 mg/L recorded at Shama also in the dry season for the entire study period (Appendix C2, Figure 4.20A). Mean concentration of NO3- in the wet season was 1.1 mg/L (range: 0.509-1.969 mg/L) which had increased to 2 mg/L (range: 0.392-4.113 mg/L) in the dry season. Minimum concentration of 0.041 mg/L PO43- was recorded for Shama in the dry season with maximum concentration of 0.499 mg/L recorded at Beposo also in the dry season for the entire study period (Appendix C4, Figure 4.20E). SO42- levels were higher for all four locations in the dry season than in the wet season with mean concentration of 56 mg/L (range: 11.304-121.118 mg/L) for the dry season and 11 mg/L (range: BDL-16.894 mg/L) for the wet season (Appendix C5, Figure 4.20D). Ions were in the increasing order PO43- < NO3- < K+ < SO42- < Na+ for the wet season and an increasing order of PO43- < NO3- < SO42- < K+ < Na+ for the dry season. University of Ghana http://ugspace.ug.edu.gh 103 0 200 400 600 800 Daboase Beposo Bokorkope ShamaM ea n C o n ce n tr a ti o n o f P o ta ss iu m ( K ) in w a te r/ m g /L Locations Wet Season Dry Season Seasons A 0 2000 4000 6000 8000 10000 12000 14000 Daboase Beposo Bokorkope ShamaM ea n C o n ce n tr a ti o n o f S o d iu m ( N a ) in w a te r/ m g /L Locations Wet Season Dry Season Seasons B 0 1 2 3 4 5 Daboase Beposo Bokorkope ShamaM ea n C o n ce n tr a ti o n o f N it ra te (N O 3 - ) i n w a te r/ m g /L Locations Wet Season Dry Season Seasons C 0 20 40 60 80 100 120 140 Daboase Beposo Bokorkope ShamaM ea n C o n ce n tr a ti o n o f S u lp h a te (S O 4 2 - ) i n w a te r/ m g /L Locations Wet Season Dry Season Seasons D University of Ghana http://ugspace.ug.edu.gh 104 4.10 STATISTICAL ANALYSIS 4.10.1 Coefficient of Variation (Co.V/%) Coefficient of variation is employed to determine the nature of distribution and patterns of dispersion of studied elements and ions along the watercourse. It was calculated as follows: Co.V = Standard Deviation/Mean It is expressed as the relative standard deviation which is in percentages. All elements in a population are considered including outliers for coefficient of variation. Distributions are classified close or narrow and wide or scattered when Co.V is below or above 50% respectively. For studied ions, Na+ recorded a wide or scattered distribution in the river water moving downstream for both seasons with Co.V of 107% and 140% for wet and dry seasons respectively. The other ions NO3- (62.8%), PO43- (78%), SO42- (79.17%) and K+ (140%) also recorded scattered or widely dispersed moving downstream for the dry season (Figure 4.21A). PO43- (27.8%) and K+ (39.9%) however had a close distribution in river water moving downstream for the wet season (Figure 4.20A). In sediments, Pb (71.42%, 62.5%), Hg (104.9%, 78.12%), and Se (84.3%, 58.3%) all recorded scattered distribution for the wet and dry seasons 0 0.2 0.4 0.6 Daboase Beposo Bokorkope Shama M ea n C o n ce n tr a ti o n o f P h o sp h a te ( P O 4 3 - ) in w a te r/ m g /L Locations Wet Season Dry Season Seasons E Figure 4.20A-E: Distribution of ions PO43-, NO3-, K+, SO42-, and Na+ in water. Sampling locations are not drawn to scale. Fig. A – K+, B – Na+, C – NO3-, D – SO42-, E – PO43- University of Ghana http://ugspace.ug.edu.gh 105 respectively moving downstream. All the other elements recorded Co.V below 50% and were very narrowly distributed in sediments moving downstream for the four locations. Hg recorded the highest Co.V in sediment for both seasons (Figure 4.21B). Fe (94.37%) and Cr (80%) all recorded scattered distributions moving downstream the four locations for the dry season. Hg (114.3%), Se (80.05%), Ni (80%), and Mn (69.23%) were widely dispersed in river water along the watercourse for the wet season. Pb was widely dispersed in the river water along the watercourse for the two seasons with Co.V of 66.7% and 80% for wet and dry seasons respectively (Figure 4.21C). 54.5 27.8 50.1 107 39.9 62.8 78 79.2 140 144 0 20 40 60 80 100 120 140 160 Nitrate Phosphate Sulphate Sodium Potassium C o ef fi ci en t o f V a ri a ti o n (C o . V ) / % Ions Wet Season Dry Season A 69.23 19.38 66.7 33.3 0 50 80 14.2 114.3 80.05 38.46 94.37 80 0 80 23 41.6 42.8 34.8 37.12 0 20 40 60 80 100 120 140 Mn Fe Pb Cd Cr Cu Ni Zn Hg Se C o ef fi ci en t o f v a ri a ti o n (C o .V )/ % Elements (Sediments) Wet Season Dry Season B University of Ghana http://ugspace.ug.edu.gh 106 4.10.2 pH versus Heavy metal content (One way ANOVA) Analysis of variance (ANOVA) is a technique used to compare the means of multiple unrelated groups. One way (ANOVA) was performed to find out if pH had a significant effect on the linear variation of trace elements along the watercourse. Trace elements were entered as dependent variables and the pH for the sites were entered as a factor variable. The significance level was set at 95%. Variations are significant if (P < 0.05) and not significant if (P > 0.05). For water, there were significant variations (P < 0.05) between the group means of Pb (P = 0.00), Zn (P = 0.001), Mn (P = 0.000), Fe (P = 0.00), Ni (P = 0.00), Hg (P = 0.00) and Se (P = 0.011) with site-pH (0.00 ≤ P ≤ 0.011) (Appendix D2). Site-pH does not account for any significant variation (P > 0.05) between the group means of Cu (P = 0.428) and Cr (P = 0.477) for river water (Appendix D2). For sediments, there were significant variations (P < 0.05) between the group means of Pb (P = 0.018), Cu (P = 0.001), Zn (P = 0.00), Mn (P = 0.00), Fe (P = 0.00) and Hg (P = 0.012) with 19.67 6.2 71.42 37.5 0 30 14.3 27.2 84.3 104.9 12.5 11.47 62.5 0 36.8 20 50 40.3 58.5 78.12 0 20 40 60 80 100 120 Mn Fe Pb Cd Cr Cu Ni Zn Se Hg C o ef fi ci ee n t o f V a ri a ti o n / C o .V /% Elements (Water) Wet Season Dry Season C Figure 4.21A-C: Coefficient of variations of studied elements and ions along the watercourse. Broken green line set at 50% limit of variation. Figure 4.21A – Co.V for ions, Figure 4.21B – Co. V for elements in sediments, Figure 4.21C – Co. V for elements in water. Affum et al., 2008 University of Ghana http://ugspace.ug.edu.gh 107 site-pH (0.00 ≤ P ≤ 0.018) (Appendix D3). No significant variations (P > 0.05) were observed for Se (P = 0.419), Cr (P = 0.742), Cd (P = 0.578), and Ni (P = 0.065) with pH (0.065 ≤ P ≤ 0.742) (Appendix D3). It was observed from this study that pH affected the distribution patterns and mobility of heavy metals like Pb, Mn, Fe and Hg in both sediments and water along the sampling sites. pH also affected the variations of Se in water along the sampling sites. 4.10.3 Paired Sample T-Test A paired sample t-test was applied to compare the means of the physicochemical and nutrients data for the dry and wet seasons. Physicochemical and ions data for dry and wet season are entered as paired variables with the confidence interval set at 95%. The hypothesis was set as: Ho: Water physicochemical and ion parameters differ significantly with seasonal changes Ha: Water physicochemical and ion parameters did not differ significantly with seasonal changes For ions, it was observed that NO3-, Na+, K+, SO42- had paired values of (0.002 ≤ P ≤ 0.049) and were significant (P < 0.05). PO43- had a paired value of (P = 0.329). Hence the measured values were not significant. The null hypothesis is rejected when P < 0.05 and accepted when P > 0.05. The null hypothesis is rejected for NO3-, Na+, K+, SO42- but is accepted for PO43-. For physicochemical parameters, it was observed that dissolved oxygen had a paired value P = 0.015 which was significant. Physicochemical parameters such as temperature, total hardness, total alkalinity, pH, BOD, TSS and TDS had their paired values above the level of significance (P > 0.05) were insignificant (0.108 ≤ P ≤ 0.291). The null hypothesis is rejected for dissolved oxygen and it is accepted for the other Physico-Chemical parameters. University of Ghana http://ugspace.ug.edu.gh 108 4.10.4 Other Physico-Chemical Parameters of Water 4.10.4.1 Total Alkalinity Total Alkalinity was closely dispersed along the watercourse with Co.V of 28.36% and 10.18% for wet and dry seasons respectively. Maximum average level for the wet season was recorded for Daboase with a value of 91 mg/L and a minimum average value of 47 mg/L recorded for Shama. The minimum average concentration of 34 mg/L was recorded in the dry season for the first three locations along the watercourse with a gradual rise to 42.5 mg/L recorded at Shama (Appendix A5, Figure 4.22A). The current guidelines for total alkalinity have not been established but overall average levels were below the WHO, 1996 guideline value of 400 mg/L and the EPA’s secondary regulation of 500 mg/L for drinking water (Appendix A5, Figure 4.22A). 4.10.4.2 Total Hardness River water was classified as moderately hard to very hard (61 mg/L-180 mg/L) along the watercourse for both seasons (USEPA, 2005). There was a general increase in the level of hardness moving downstream the four locations for both seasons. The minimum hardness level was recorded at Daboase with a value of 53 mg/L and a maximum level of 105 mg/L recorded at Shama in the wet season (Appendix A4). In the dry season, minimum hardness level was recorded at Beposo with a value of 51 mg/L and a maximum value of 2970 mg/L recorded at Shama. Total hardness was widely dispersed along the watercourse for the four locations in the dry season with Co.V of 127.5% and narrowly distributed in the wet season with Co.V of 28.9% (Appendix A4, Figure 4.22C). University of Ghana http://ugspace.ug.edu.gh 109 4.10.4.3 Total Suspended Solids (TSS) Total suspended solids (TSS) were narrowly dispersed along the watercourse of the four locations in the wet season with Co.V of 46.4%. This was not the case for the dry season as TSS distribution was scattered along the watercourse with Co. V of 84%. The wet season recorded an average TSS of 322 mg/L (range: 91-509 mg/L) whiles the dry season recorded average levels of 160 mg/L (range: 14-376 mg/L) (Appendix A6). Shama recorded the highest TSS for the dry season (376 mg/L) whilst Beposo recorded the highest for the wet season (509 mg/L) (Appendix A6, Figure 4.22B). 4.10.4.4 Total Dissolved Solids (TDS) Total dissolved solids (TDS) were generally higher than total suspended solids (TSS) in both seasons. Overall mean concentration of 1,012 mg/L TSS was recorded in the wet season and the dry season recording an overall mean concentration value of 7527 mg/L. TDS was narrowly dispersed throughout the watercourse in the wet season with a Co.V of 15.8% (Appendix A8). There was a gradual rise in TDS for the first three locations with a sharp rise recorded at Shama with an average concentration of 20,764 mg/L for the dry season (Appendix A8, Figure 4.22D). TDS recorded a wide distribution along the watercourse in the dry season with Co.V of 94.4% (Appendix A8). Water is regarded as unpalatable when TDS concentration is greater than 1,200 mg/L. Water with TDS concentration below 600 mg/L is considered as good for drinking (WHO, 1984) (Figure 4.22D). University of Ghana http://ugspace.ug.edu.gh 110 0 100 200 300 400 500 600 Daboase Beposo Bokorkope Shama T o ta l S u sp en d ed S o li d s (T S S )/ m g /L Locations Wet Season Dry Season Seasons B 0 1000 2000 3000 4000 Daboase Beposo Bokorkope Shama T o ta l H a rd n es s m g C a C O 3 /L Locations Wet Season/(mg/l) Dry Season/(mg/l) Seasons C 0 20 40 60 80 100 120 Daboase Beposo Bokorkope Shama T o ta l A lk a li n it y /m g /L Locations Wet Season/(mg/l) Dry Season/(mg/l) Seasons A 0 5000 10000 15000 20000 25000 Daboase Beposo Bokorkope ShamaT o ta l D is so lv ed so li d s (T D S )/ m g /L Locations Wet Season Dry Season Seasons D Figures 2.22A-D: Distribution of Physicochemical parameters in the Study Area. Sampling locations are not drawn to scale. Figure A- Total Alkalinity, Figure B-TSS, Figure C-Total Hardness and Figure D- TDS University of Ghana http://ugspace.ug.edu.gh 111 4.10.5 Principal Component Analysis (PCA) Principal component analysis was performed to identify the possible sources of environmental variables (Heavy metals, Water nutrients, Physicochemical parameters). The major aim of the PCA is the auto-scaling of data to better describe the relationship between variables. First, the mean is subtracted from each data dimension to produce a data set whose mean is zero from which the co-variance matrix is extracted. Eigen values are calculated from Eigen factors which are derived from the co-variance matrix. Eigen vectors are unit vectors with their length equal to one. Therefore the selection of the number of principal components is based on the Kaiser criterion with Eigen value higher than one (Ackah, 2012; Manoj et al., 2012). Three principal components were selected since all the other components with Eigen values less than one are regarded as less significant. The three components selected were subjected to varimax rotation with Kaiser-normalization and then three components (factors) are extracted. The factor loadings are the correlation coefficients between variables and factors. Factor loading values greater than 0.75, between 0.75-0.5, and 0.5-0.3 are classified strong, moderate and weak based on their absolute values. Variables with factor loadings above 0.5 within same principal component group (PC1, PC2 or PC3) are associated and this strongly suggests that they have a similar source (Ackah, 2012; Manoj et al., 2012). The cumulative variance is the percentage of data variability that was accounted for during the data reduction processes. For plot 1, the three components extracted accounted for 88% of all data variation with only a 12% loss of information (Appendices E1 and F1). Plot 2 accounted for 80% of all the data variation with a 20% loss of data (Appendices E2 and F2). Plot 3 accounts for 86% of all data variation with a 14% loss of data (Appendices E3 and F3). Plot 4 accounted for 86% of all data variation with a 14% loss of data (Appendices E4 and F4). University of Ghana http://ugspace.ug.edu.gh 112 For plot 1, PC1 with variance of 41.35% comprises Pb, Mn, Se, Zn, and Fe. PC2 with a 31.95% variance consists of Pb, Cr, Mn, Cu, Fe, and Ni. PC3 with a 14.74% variance comprises Hg (Appendices E1 and F1). Pb, Mn, and Fe belonging to both PC1 and PC2 implies that they are coming from both natural and anthropogenic sources or from similar anthropogenic sources in the study area. Atmospheric deposition could be coming from traffic sources as well as the natural and artificial weathering of rocks since the study area is known for alluvial deposits. AGM activities at the study site may be accounting for only Hg in sediments for the study area for the dry season. For plot 2, PC1 with 36.39% variance comprises Pb, Mn, Zn, and Fe. PC2 with 26.85% variance consists of Cu, Hg and Se with high factor loadings. PC3 with 17.5% variance is made up of Fe and Ni (Appendices E2 and F2). Fe and Ni in PC3 could be accounted for by natural input since it is accompanied by Fe. Both PC1 and PC2 are from different anthropogenic input especially for PC2 which are mostly from mining effluents from AGM sites. Fe in both PC1 and PC2 is indicative of mixed sources of input into sediments in the wet season (Appendices E2 and F2). For plot 3, PC1 with 37% of the total variance comprises Zn, Hg, TSS, TDS, Se, Ni, Na, K, and Cu (Appendices E3 and F3). PC1 showed that TSS and TDS were associated with the distribution of Hg and Se in the river water and sediments for the dry season. TSS and TDS were also associated with other elements such as Zn, Na, K and Ni. Total variance of 32.62% for PC2 comprises Fe, Mn, Cr, NO3-, and PO43- which indicated natural sources of weathering evident by the alluvial deposits which are carried in river water. Total variance of 16.37% for PC3 comprises Hg and NO3-. Hg in PC1 and PC2 is mainly attributed to the effluents that are discharged from the AGM sites into the river in the dry season. University of Ghana http://ugspace.ug.edu.gh 113 Plot 3 and Plot 4 were similar for PC1 which affirms the fact that both TSS and TDS were responsible for the distribution of THg and Se in the study area although THg showed a weak inverse correlation with TSS (Figure 4.17B). PC2 for plot 4 with 32.5% of total variance comprises Pb, Cr, Na and TDS. PC3 with 15.45% of total variance comprises PO43-, Hg, and NO3-. Hg in PC1 and PC3 highlights the various sources of effluents discharged into the river from AGM sites for the wet season which is the same as in the dry season (Appendices E3 and E4, F3 and F4). PLOT 1 PLOT 2 Figures 4.23: Principal component analysis diagram showing the rotated factor loadings of the principal component (PC1, PC2 and PC3) to a descriptor space of three dimensions. Plot 1 is for sediments for the dry season. Plot 2 is for sediments for the wet season. University of Ghana http://ugspace.ug.edu.gh 114 PLOT 3 PLOT 4 Figures 4.24: Principal component analysis diagram showing the rotated factor loadings of the principal component (PC1, PC2 and PC3) to a descriptor space of three dimensions. Plot 3 is for river water for the dry season. Plot 4 is for river water for the wet season. A1, B1, and C1 are for water nutrients NO3-, SO42-, and PO43- respectively. University of Ghana http://ugspace.ug.edu.gh 115 4.11 DISCUSSION This study highlights the relationship between total mercury (THg) and selenium (Se) in various aquatic components, their association with other heavy metals and other physicochemical parameters at the lower catchment regions of the Lower Pra River. Concentrations of THg and Se were determined in sediments, fish species and river water for the minor wet season of 2012 and the dry season of 2013. From the studies, THg and Se were found in sediments and river water at sites isolated for AGM activities. Dilution of THg was not observed as concentrations were higher in water and sediments about 20 km further downstream from the first AGM sites at Shama estuary for both seasons. THg was widely dispersed from point source in the wet season for river water and widely dispersed in sediments for both season. Some factors that may have accounted for these observations include atmospheric deposition and resuspension of mercury particulates from point source, river flow factors and anthropogenic input. The entire Lower Pra River catchment is noted for AGM activities and the operators are known to move from one location to the other for their operations. Mercury is used by these operators because its use is accessible and highly effective in the capture of gold. Mercury is released into the river through mining effluent or emitted into the atmosphere when the mercury- gold amalgam is heated or roasted. Mercury together with other mine tailings pollutes the river which serves as source for drinking water. Also persistent and historic mining accounts for levels of mercury in locations not noted for AGM activities (Donkor et al., 2006a, b; Oduro et al., 2012). THg levels in sediments and in river water were relatively higher in this study compared to previous studies conducted by Donkor et al., 2006a, b and Oduro et al., 2012. The high THg levels may be attributed to the fact that AGM University of Ghana http://ugspace.ug.edu.gh 116 activities in the Lower Pra river basin have intensified particularly last year accounting for higher levels of THg observed in this study. Concentrations of THg generally exceeded the USEPA 2004 permissible limit of 200 µg/Kg for sediments and 1 µg/L for drinking water for most of the sampling sites except for Borkorkope. THg was largely below the detection limit in sediments and in river water for the wet season in this location. This is because the location was not largely impacted by a lot of anthropogenic activities. THg had no significant relationship with TSS, Fe and Mn although other studies by Warner et al., 2005 and Balogh et al., 1998 suggested otherwise. THg in river water had a significant relationship with dissolved sulfate highlighting a possible methylation process. Methylation is favored under anoxic conditions in the presence of sulfur reducing bacteria. Studies on two fish species Xenomystus nigri and Clarias submarginatus (Mudfish) showed that THg had bioaccumulated in the tissue parts of the two fish species (Tables 4.4 and 4.5). Mercury had bioaccumulated in the dorsal tissues of Mudfish and in the dorsal and ventral tissues of Xenomystus nigri. THg content in the ventral tissues was relatively higher than in the dorsal tissues of Xenomystus nigri (Figure 4.8 and Table 4.3). From the studies, length and weight did not affect the THg content for the two fish species. Clarias submarginatus (Mudfish) which were smaller in length and in weight had higher THg content in their tissues than that of Xenomystus nigri (Table 4.2 and 4.3). Studies conducted on various fish species by Ntow and Khjawa found no correlation between THg content and size, weight and length of fish species under investigation. THg content and rate of accumulation differs for every fish species since various fish species have different migratory and feeding habits as well as different metabolic and excretion rates (Ntow and Khwaja, 1988). University of Ghana http://ugspace.ug.edu.gh 117 Bioamplification in food chain increases the concentration of mercury especially methylmercury which is the most abundant in fish species (Voegborlo et al., 2010). The highest concentrations of mercury in the food chain is observed in the secondary and tertiary trophic levels (Dix, 1891; Hamilton, 1971) and at these levels mercury toxicity is greatly felt. Other elemental content such as Cd, Mn, Pb, Fe, Zn, Se and Ni were generally higher in Mudfish than in Xenomystus nigri (Table 4.2 and 4.3). Copper was not detected in the two fish species. The higher elemental content in Mudfish is due to the mode of preservation for the Mudfish. The local indigenes in the area preserve fish by smoking and drying and this could have accounted for the elevated mineral content. Correlation and regression studies between THg and Se for river water showed a moderately strong positive correlation for the two elements for the dry season (n = 24, r2 = 0.521, r = 0.724) and a no relationship for the wet season (n = 24, r2 = 0.0895, r = 0.0635) (Figures 4.6A and 4.6B). This implied that THg increased as Se increased in river water in the dry season but no pattern was observed for the wet season. For sediments, there was a weak inverse relationship between the two elements in the dry season (n = 16, r2 = 0.072, r = -0.269) and a moderately direct correlation in the wet season (n = 24, r2 = 0.978, r = 0.989) (Figures 4.4A and 4.4B). This implied that as THg increases across the sediment in the dry season there was a slight decrease in Se and in the wet season an increase in THg was accompanied with an increase in Se. Although Se appeared generally higher than THg in most of the individual sites that were examined, the patterns of correlation were not definite but statistically significant relationships between the two elements in sediments and in river water for both seasons suggests the possible association between the elements. The antagonism between Se and Hg however remains unclear. University of Ghana http://ugspace.ug.edu.gh 118 There was a near perfect correlation between THg and Se for dorsal tissue parts of mudfish (r2 = 0.98, r = 0.99) and a weak inverse relationship between the two elements in the various fish tissue parts in Xenomystus nigri (r2 = 0.0987, r = - 0.314). The logarithm transformation of the bioaccumulation factors also gave the same results (Figure 4.11 and 4.12). In Xenomystus nigri, an increase in the molar ratios of Se in fish tissue parts was characterized by a decrease in the molar ratios of THg (Figure 4.9). Se contamination in river water accounted for elevated Se levels in fish and it was evident from the calculated bioaccumulated factors. A near 1:1 Hg:Se/Se:Hg molar ratio has been observed in organs of marine mammals suggesting a possible antagonism taking place between the two elements (Koeman et al., 1975; Caurant et al., 1996) but this molar ratio was not supported in this studies. Se:Hg were in average ratios of 261:1 for mudfish and 5:1 for Xenomystus nigri (Tables 4.6 and 4.7). Higher Se:Hg molar ratios in fish species have been reported in walleyes by Yang et al., 2010 suggesting the antagonistic effect of Se on Hg. Yang et al., 2010 suggested that threshold concentrations of Se must be reached before a clear protective role of Se on Hg can be noticed. Se:Hg molar ratios have been found to decrease along the food web due to biomass dilution (Chen et al., 2001). From the study, several questions remained unanswered. Although Se is an essential element for living organisms, other forms of this element can be toxic and can magnify the toxicity of mercury (Parizek, 1980). Since there is a small difference between essential and toxic levels of Se (Feroci et al., 2005) and this differs with various fish species, the particular form of Se will provide more insight on an antagonism or a synergism phenomenon. University of Ghana http://ugspace.ug.edu.gh 119 Both Hg/Se speciation in fish will give more insight as to the antagonistic nature of Se on THg. Se is also known to have certain other interactions with elements such as Cd, Zn and Fe. Feroci et al., 2005 conducted polarographic studies on Hg, Cd, and Zn with different selenium compounds. From the studies, it was found out that THg interacts more significantly with Se and oxy-selenium compounds and that Zn and Cd displayed very weak interactions. The observation made by Feroci et al., 2005 was largely supported by the regression studies of Se on Zn and Cd in fish species as no significant relationship was established ( Figures 4.13A-C and 4.14A-C). One way ANOVA studies showed that pH had an effect on the linear variation of THg in sediments and in river water along the watercourse (p < 0.05) (Appendices D2 and D3). pH in sediments were found to be acidic for both seasons thus highlighting the acidic nature of effluents released from AGM sites into the river body. The effluents released from AGM sites include oxides of nitrogen and sulfur which tend to lower pH (Figure 4.23 and 4.24). This affects the acid-base balance of water body thereby having an adverse effect on aquatic life (Fianko, 2003). Principal Component Analysis (PCA) was used to identify the sources of pollution, apportion to natural, anthropogenic or mixed contributions. PCA results showed that THg in mining effluent was accompanied by Se and Cu and they adsorb onto sediments evident in plot 2 (Figure 4.23). Fe and Mn can be accounted for by mixed sources either through natural or artificial weathering contributing mainly to alluvial nature of the study area. Fe and Mn were found to be accompanied by TSS and TDS in plot 3 (Figure 4.24). Sand winning by AGM operators and quarrying of rocks is found to increase the TSS and TDS of the river water by introducing dissolved and suspended particulates which are mainly rich in Fe and Mn. Fe and Mn was also accompanied by water nutrients such as phosphate from phosphorous bearing rocks evident in University of Ghana http://ugspace.ug.edu.gh 120 plot 3 (Figure 4.23). Pb was found to be accompanied by Mn and Fe either from mixed natural and anthropogenic sources as displayed in plot 1 (Figure 4.23) or mainly from anthropogenic sources displayed in plot 2 (Figure 4.23). Average concentration of Cd in river water for the wet season exceeded the WHO guideline value of 0.003 mg/L for drinking water whilst concentrations levels were largely not detected in the dry season. Average concentrations of Fe also exceeded the WHO value of 0.3 mg/L in the wet season. Average concentration of Pb was close to the WHO guideline value of 0.01 mg/L in the wet season and far exceeded the guideline value for the dry season. Levels of Ni, Cu, Cr, Se, Mn, and Zn were all below the WHO guideline for value for both seasons (Appendices B1-B20) (WHO, 2011). Average levels of Pb in Xenomystus nigri (3.4 mg/Kg) and in Mudfish (33 mg/Kg) exceeded the WHO guideline value of 2 mg/Kg for fish (Tables 4.2 and 4.3). Average Cr levels in Xenomystus nigri (0.8 mg/Kg) was close to the guideline limit of 1 mg/Kg. Cd, Hg and Zn all had average concentrations below the WHO guideline limit of 2 mg/Kg, 500 µg/Kg and 50 mg/Kg respectively for Xenomystus nigri but were above the WHO guidelines for Mudfish (Tables 4.2 and 4.3) (WHO, 2011). Overall mean concentration of Cd in sediments for wet season (0.8 mg/Kg) exceeded the Canadian Interim Sediment Quality (ISQG) threshold effect level (TEL) guideline value of 0.6 mg/Kg. Overall mean concentrations of Pb, Zn, Ni, Cr and Cu were below the ISQG threshold effect guideline values for the two seasons (Appendices B1-B20) (Burton, 2002). Safe drinking water is defined by WHO as that water having acceptable quality in terms of its physical, chemical and bacteriological parameters. Bacteriological parameters, especially E. coli University of Ghana http://ugspace.ug.edu.gh 121 and total coliform (TC) have been used to determine the general quality of drinking water worldwide. Microbial investigations carried out further upstream at Daboase and further downstream at Shama revealed that total coliform (TC), total heterotrophic bacteria (THB), faecal coliform (FC) and E. Coli counts were above the WHO guideline value for drinking water. Based on WHO risk categories, river water was classified as low to intermediate risk for purposes of drinking (Appendices A1 to A3). Higher microbial population in these two sites highlights the disposal of faecal matter into the river and this affects water quality. Microbial contamination of water sources for drinking purposes results in the outbreak of waterborne diseases such as Cholera, Typhoid fever, Dysentery, Vibrio illness and many others. Biochemical Oxygen Demand (BOD) and Dissolved Oxygen (DO) are important parameters in the determination of water quality. BOD and DO investigations were carried out at the first and the last sampling locations, Daboase and Shama. These two towns selected were highly populated with human activities affecting the general water quality of the river. DO recorded at Shama was 13.11 mg/L in the dry season and 6.60 mg/L in the wet season. DO recorded at Daboase was 13.22 mg/L and 6.40 mg/L in the dry and wet seasons respectively. BOD recorded at Daboase was 6.60 mg/L in the dry season and 3.50 mg/L in the wet season. Shama recorded BOD of 4.84 mg/L in the dry season and 2.66 mg/L in the wet season (Appendices A1 to A3). BOD was above the WHO guideline value of 3 mg/L for drinking water for the two locations for both seasons. DO on the other hand was below the recommended WHO, 2011 guideline value of 7 mg/L in the wet season and above the guideline value in the dry season. DO concentrations below 7 mg/L can have an effect on aquatic life through oxygen starvation. This is because oxygen is needed in a biochemical process like respiration. Higher BOD could be as a result of higher organic matter content in effluents either from domestic purposes or from mines that are University of Ghana http://ugspace.ug.edu.gh 122 discharged into the river water from these two communities. Microbes introduced into the water utilize more of the DO in the breakdown of organic matter thereby decreasing the DO concentration. Concentration of DO was higher the dry season because the AGM activities had been abandoned due to the raids by the military and minerals commission at the two isolated AGM site (Appendices A1 to A3). There was an elevated level of TSS and TDS in water due to the winning of sand by AGM operators. TSS was higher in the wet season than the dry season (Figure 4.21B) because of runoffs during rainfall. TDS and ions such as Na+ and K+ were found to be very high in river water at downstream locations Bokorkope and Shama especially for the dry period. Elevated levels of TDS, Na+ and K+ at these locations were due to the influx of seawater inland. This could be attributed to the differences in tides at the estuary, flow rate and direction of river current which are affected by the differences in seasons. Water nutrients PO43-, NO3- and SO42- had their overall mean concentrations lower than the WHO, 2011 guideline values for drinking water for both seasons (Appendices C1 to C5). The dry season generally recorded higher values of NO3- and SO42- than the wet season (Figures 4.20A-E). PO43- recorded higher values in the dry season than the wet season for the first two AGM sites (Figure 4.20E). Excessive evaporation of river water leading to pre-concentration of ions in the dry season could have accounted for elevated nutrients levels in water. A survey conducted by the Water Research Institute (WRI) in 2011 on the surface water quality at selected towns including Daboase reported total alkalinity, total hardness, TDS and DO at levels of 40 mg/L, 52 mg/L, 58.9 mg/L and 6.49 mg/L respectively. Average concentration of total hardness for both seasons was higher in this study at Daboase than what was reported in the University of Ghana http://ugspace.ug.edu.gh 123 survey (Appendix A4). Total alkalinity was higher in the wet season for this study than what was reported (Appendix A5). TDS was higher in this study for the two seasons than what was reported in the survey at Daboase (Appendix A7). Levels of DO at Daboase in this study for the wet season were comparable to what was reported in the survey but was higher than what was reported in the survey for the dry season (Appendix A3) University of Ghana http://ugspace.ug.edu.gh 124 CHAPTER FIVE 5.0 CONCLUSIONS AND RECOMMENDATIONS 5.1 CONCLUSIONS  THg largely exceeded the WHO guideline value for drinking water for both seasons and exceeded the USEPA guideline value for sediments in the dry season for the four locations which is an indication that amalgamation with mercury is the technique used by illegal gold miners.  THg levels were higher in sediments and in river water for this study than in other studies carried out by Donkor et al., 2006a, b and Oduro et al., 2012 in other selected sites along the Lower Pra River and this as a result of the intense activities of illegal gold miners especially in the lower catchment regions of the Lower Pra River.  THg levels were detected in river water at Shama estuary which was the last sampling location, several kilometres from Daboase which was the second selected location for sampling and known for AGM activities as at the time of study.  A strong association characterized by a weak inverse and a strong direct relationship was observed between THg and Se in Xenomystus nigri and Clarias submarginatus respectively but an antagonism effect of Se on THg was not clearly established. The null hypothesis in this case could not be supported.  It was observed from the Principal Component Analysis (PCA) that TSS had a role in the distribution of THg and Se for the four locations in the study area. Furthermore TSS accounted for the scattered distributions of Pb, THg and Se across the longitudinal transect for both seasons evident from the co-efficient of variation in Figure 4.21C and Principal University of Ghana http://ugspace.ug.edu.gh 125 Component Analysis (PCA) plot 3 and 4 which show the association between TSS, Pb, THg and Se.  From the paired sampled T-test, physicochemical parameters such as temperature, total hardness, total alkalinity, pH, BOD, TSS and TDS were affected by the changes in seasons which validates the null hypothesis.  Human activities along the banks of the river and the inflow of effluents from domestic and AGM activities appear to have great impact on the quality of water as source for drinking. 5.2 RECOMMENDATIONS  Elemental speciation will provide more insight on the antagonistic nature of Se on Hg. 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University of Ghana http://ugspace.ug.edu.gh 152 APPENDICES APPENDIX A A1: Wet Season Microbial Studies A2: Dry Season Microbial Studies Location TC/ CFU/100mL FC/CFU/100mL E. coli/CFU/100mL THB/CFU/100mL Daboase 90 45 16 37 Shama 66 52 28 73 n=1, for each location, where n is the number of samples A3: DO and BOD Location Dissolved Oxygen (DO) (mg/L) Biochemical Oxygen Demand (BOD)(mg/L) Dry Season Wet Season Dry Season Wet Season Daboase (Upstream) 13.22 6.40 6.60 3.50 Shama (Downstream) 13.11 6.60 4.84 2.66 n = 1 DO for each location, n = 3 BOD for each location WHO, 2011: BOD – 3 mg/L; DO – 7 mg/L Location TC/ CFU/100ml FC/CFU/100ml E. coli/CFU/100ml THB/CFU/100ml Daboase 120 4 558 780 Shama 7 1 392 5616 WHO, 2011 Guideline values: 0 CFU/ 100ml, 0 CFU/100 ml (conformity), 1-10 CFU/100ml (low risk), 10-100 CFU/100ml (intermediate risk), 100-1000 CFU/ml (high risk) University of Ghana http://ugspace.ug.edu.gh 153 APPENDIX A A4: Total Hardness Location Wet Season/(mg/L) Dry Season/(mg/) Daboase 53±7 59±6 Beposo 57±13 51±6 Bokorkope 71±8 683±17 Shama 105±12 2970±104 Mean 71.5 940.65 SD 20.72722 1199.525 Co. V/% 28.9 127.5 Range 53-105 51-2970 Mean± SD corrected to nearest whole number 72±21 941±1200 n = 3 for each location *WHO 2011 – 200 mg/L A5: Total Alkalinity Location Wet Season/(mg/L) Dry Season/(mg/L) Daboase 91±53 34±7 Beposo 52±27 34±9 Bokorkope 56±39 34±7 Shama 47±5 42.5±5 Mean 61.445 36.125 SD 17.43775 3.680608 Co. V/% 28.36 10.18 Range 47-91 34-43 Mean± SD corrected to nearest whole number 61±17 36±4 n = 3 for each location A6: Total Suspended Solids Location Wet Season/(mg/L) Dry Season/(mg/L) Daboase 91±12 94±4 Beposo 509±167 156±47 Bokorkope 339±97 14±5 Shama 348±98 376±62 Mean 321.75 160 SD 149.4111 134.4842 Co. V/% 46.4 84 Range 91-509 14-376 Mean± SD corrected to nearest whole number 322±149 160±134 University of Ghana http://ugspace.ug.edu.gh 154 APPENDIX A A7: Total solids (TSS + TDS), n = 3 for each location *WHO 2011 – 1500 mg/L A8: Total Dissolved Solids Location Wet Season/(mg/L) Dry Season/(mg/L) Daboase 757±67 752±89 Beposo 1132±145 2007±157 Bokorkope 1164±132 6584±467 Shama 998±112 20764±2345 Mean 1012.75 7526.75 SD 160.252 7106.032 Co. V/% 15.8 94.4 Range 757-1164 752-20764 Mean± SD corrected to nearest whole number 1013±160 7527±7106 *WHO – 600 mg/L Location Wet Season/(mg/L) Dry Season/(mg/L) Daboase 848±79 846±93 Beposo 1641±312 2162±204 Bokorkope 1503±229 6598±472 Shama 1346±210 21140±2407 Mean 1334.5 7686.5 SD 299.6452 8054.409 Co. V/% 22.45 104.78 Range 848-1503 846-21140 Mean± SD corrected to nearest whole number 1335±300 7687±8054 University of Ghana http://ugspace.ug.edu.gh 155 APPENDIX B Heavy Metal Analysis B1: Mean Concentration of Iron (Fe) in River Water Location Wet Season/(mg/L) Dry Season/(mg/L) Daboase 5.6±0.7 1.44±0.01 Beposo 9±1 1.3±0.6 Bokorkope 5.9±0.4 0.04±0.02 Shama 5.6±0.6 0.05±0.04 Min 5.6 0.04 Max 9 1.44 Co.V/% 19.38 94.37 Range (5.6-9) 0.04-1.44 Mean ± SD Nearest whole number 6±1 0.7±0.6 *WHO 2011 – 0.3 mg/L B2: Mean Concentration of Iron (Fe) in Sediment samples Location Wet season/(mg/Kg) Dry Season/(mg/Kg) Daboase 5567±515 704±157 Beposo 5470±207 818±266 Bokorkope 5703±710 675±47 Shama 6388±333 896±13 Min 5470 675 Max 6388 895 Co.V/% 6.20 11.47 Range 5470-6388 675-895 Mean ± SD Nearest whole number 5738±360 773±89 Locations Wet Season/(mg/Kg) Dry Season/(mg/Kg) Daboase 195±32 21±8 Beposo 223±32 29±11 Bokorkope 156±36 15.2±0.9 Shama 274±26 30±3 Min 156 15.2 Max 274 30 Co.V/% 19.67 11 Range 156-274 15.2-30 Mean ± SD Nearest whole number 213±42 30±3 Mean Concentration of Manganese (Mn) in Sediment samples B3: University of Ghana http://ugspace.ug.edu.gh 156 *Detection limit 0.006 mg/L *WHO 2011 – 0.4 mg/L *Detection limit – 0.001 mg/L *WHO 2011 – 0.01 mg/L *ISQG – 35 mg/Kg Locations Wet Season/(mg/L) Dry Season/(mg/L) Daboase 0.007 BDL Beposo 0.02±0.01 0.02±0.01 Bokorkope BDL 0.08±0.04 Shama 0.014±0.009 0.082±0.006 Min BDL BDL Max 0.02 0.082 Co.V/% 66.7 80 Range BDL-0.02 BDL-0.082 Mean ± SD Nearest whole number 0.009±0.006 0.05±0.04 Location Wet Season/(mg/L) Dry Season/(mg/L) Daboase 0.05±0.01 0.020±0.003 Beposo 0.11±0.01 0.019±0.007 Bokorkope 0.022±0.009 0.007±0.002 Shama 0.025±0.006 0.010±0.007 Min 0.022 0.007 Max 0.11 0.020 Co.V/% 69.23 38.46 Range 0.022-0.11 0.007-0.020 Mean ± SD Nearest whole number 0.05±0.04 0.013±0.005 Locations Wet Season/(mg/Kg) Dry Season/(mg/Kg) Daboase 7±3 13.6 Beposo 11±8 6±4 Bokorkope 8±5 0.9 Shama 31±19 10±2 Min 7 0.9 Max 31 13.6 Co.V/% 71.42 62.5 Range 7-31 0.9-13.6 Mean ± SD Nearest whole number 14±10 8±5 B4: Mean Concentration of Manganese (Mn) in River Water B5 Mean Concentration of lead (Pb) in River Water B6: Mean Concentrations of Lead (Pb) in Sediment samples University of Ghana http://ugspace.ug.edu.gh 157 B7: Mean Concentration of Cadmium (Cd) in River Water *Detection limit – 0.002 mg/L B8: Mean Concentration of Cadmium (Cd) in Sediment samples *Detection limit – 0.2 mg/Kg *ISQG – 0.6 mg/Kg B9: Mean Concentration of Copper in River Water Locations Wet Season(mg/L) Dry Season/(mg/L) Daboase 0.038±0.001 0.025±0.003 Beposo 0.006 0.023±0.004 Bokorkope 0.006 0.021±0.007 Shama 0.032±0.004 0.036±0.004 Min 0.006 0.021 Max 0.038 0.036 Co.V/% 50 23 Range 0.006-0.038 0.021-0.036 Mean ± SD Nearest whole number 0.02±0.01 0.026±0.006 *WHO 2011 – 2 mg/L Locations Wet Season/(mg/L) Dry Season/(mg/L) Daboase 0.003±0.002 BDL Beposo 0.008 0.004±0.002 Bokorkope 0.007±0.003 BDL Shama 0.005 BDL Min 0.003 BDL Max 0.007 0.003 Co.V/% 33.3 - Range 0.003-0.007 BDL-0.004 Mean ± SD Nearest whole number 0.006±0.002 - Locations Wet Season/(mg/Kg) Dry Season/(mg/Kg) Daboase 0.8±0.7 BDL Beposo 0.3±0.2 BDL Bokorkope 0.9±0.7 BDL Shama 1.3 BDL Min 0.3 - Max 1.3 - Co.V/% 37.5 - Range 0.3-1.3 - Mean ± SD Nearest whole number 0.8±0.3 - University of Ghana http://ugspace.ug.edu.gh 158 B10: Mean concentration of Copper (Cu) in Sediment *ISQG – 37.3 mg/Kg B11: Mean Concentration of Zinc (Zn) in River samples Locations Wet Season/(mg/L) Dry Season/(mg/L) Daboase 0.04±0.01 0.0095±0.0005 Beposo 0.05±0.02 0.013±0.003 Bokorkope 0.058±0.003 0.010±0.007 Shama 0.07±0.02 0.0245±0.0005 Min 0.04 0.0095 Max 0.07 0.0245 Co.V/% 14.2 42.8 Range 0.04-0.07 0.0095-0.0245 Mean ± SD Nearest whole number 0.056±0.009 0.014±0.006 *WHO 2011 – 3 mg/L B12: Mean Concentration of Zinc (Zn) in Sediment samples Locations Wet Season/(mg/Kg) Dry Season/(mg/Kg) Daboase 47±6 3.1±0.8 Beposo 51±5 3.3±0.9 Bokorkope 41±7 3.65±0.05 Shama 82±8 7.4±0.3 Min 41 3.1 Max 82 7.4 Co.V/% 27.2 40.3 Range 41-82 3.1-7.4 Mean ± SD Nearest whole number 55±1 4±2 *ISQG – 123 mg/Kg Locations Wet Season/(mg/Kg) Dry Season/(mg/Kg) Daboase 3.0± 0.8 5 ±2 Beposo 4 ±1 7± 1 Bokorkope 3 ±1 4.75± 0.05 Shama 2.0± 0.6 2.6± 0.2 Min 2 2.6 Max 4 7 Co.V/% 30 20 Range 2-4 2.6-7 Mean ± SD Nearest whole number 2.8± 0.9 5± 1 University of Ghana http://ugspace.ug.edu.gh 159 B13: Mean Concentrations of Nickel (Ni) in River Water Locations Wet Season/(mg/L) Dry Season/(mg/L) Daboase 0.009 ±0.006 0.008 Beposo 0.05 ±0.02 0.02 Bokorkope 0.013 0.007 ±0.001 Shama 0.013± 0.007 0.014± 0.004 Min 0.009 0.007 Max 0.013 0.02 Co.V/% 80 41.6 Range 0.009-0.013 0.007-0.02 Mean ± SD Nearest whole number 0.02±0.02 0.012±0.005 *WHO 2011 – 0.07 mg/L B14: Mean Concentration of Nickel (Ni) in Sediment Locations Wet Season/(mg/Kg) Dry Season/(mg/Kg) Daboase 8±4 2.8±0.9 Beposo 6±2 1.7±0.7 Bokorkope 8±5 0.9±0.2 Shama 5±3 1.1±0.5 Min 5 0.9 Max 8 2.8 Co.V/% 14.3 50 Range 5-8 0.9-2.8 Mean ± SD Nearest whole number 7±1 1.6±0.8 *ISQG – 18 mg/Kg B15: Mean Concentrations of Chromium (Cr) in River Water and Sediments Locations Wet Season/(mg/L) Dry Season/(mg/L) Daboase BDL 0.010±0.003 Beposo BDL 0.004 Bokorkope BDL 0.004 Shama BDL BDL Min - BDL Max - 0.010 Co.V/% - 80 Range - BDL-0.010 Mean ± SD Nearest whole number - 0.005±0.004 *Detection limit – 0.001 mg/L *WHO 2011 - 0.05 mg/L University of Ghana http://ugspace.ug.edu.gh 160 B16: Mean Concentrations of Chromium (Cr) in Sediments *Detection limit – 0.1 mg/Kg *ISQG-37.3 mg/Kg Mercury and Selenium concentration in Sediments and River Water along the Water shed B17: Sediments (Selenium (Se)) Locations Wet Season/(mg/Kg) Dry Season/(mg/Kg) Daboase 70±46 0.4 ±0.2 Beposo 58±61 1±0.8 Bokorkope - 0.5±0.1 Shama - 1.8±0.2 Min BDL 0.4 Max 70 1.8 Co.V/% 83.44 55.55 Range BDL-70 0.4-1.8 Mean ± S.D 65±54 0.9±0.5 *Detection limit – 0.1 mg/Kg B18: Total Mercury (THg) Locations Wet Season/(µg/Kg) Dry Season/(µg/Kg) Daboase 320± 349 762±25 Beposo 500±406 2568±2004 Bokorkope - 297±120 Shama - 849±913 Min BDL 297 Max 500 2568 Co.V/% 104.9 78.12 Range BDL-500 297-2568 Mean ± S.D 205±215 1111±869 Locations Wet Season/(mg/Kg) Dry Season/(mg/Kg) Daboase BDL 2±2 Beposo BDL 3±1 Bokorkope BDL 1.4 Shama BDL 1.2±0.2 Min - 1.2 Max - 3 Co.V/% - 36.8 Range - 1.2-3 Mean ± SD Nearest whole number - 1.9±0.7 University of Ghana http://ugspace.ug.edu.gh 161 *Detection limit – 1 µg/Kg *USEPA – 200 µg/Kg *ISQG – 0.17 mg/Kg B19: Total Mercury (THg) River water Locations Wet Season/(µg/L) Dry Season/(µg/L) Daboase 1.2±0.8 1.1±0.7 Beposo BDL 2.3±0.7 Bokorkope 0.97±0.06 1.28 Shama 1.3±0.8 2.4±0.9 Min BDL 1.1 Max 1.3 2.4 Co.V/% 114.3 34.8 Range BDL-1.3 1.1-2.4 Mean ± S.D 0.7±0.8 1.7±0.6 *Detection limit – 0.01 µg/L USEPA - 1µg/L B20: Selenium (Se) Locations Wet Season/(µg/L) Dry Season/(µg/L) Daboase 1.1±0.6 5±2 Beposo 0.9±0.4 7±1 Bokorkope 0.65 5±1 Shama 0.7±0.4 12±6 Min 0.65 5 Max 1.1 12 Co.V/% 80.05 37.12 Range 0.65-1.1 5-12 Mean ± S.D 0.7±0.6 8±3 *WHO 2011 – 0.04 mg/L University of Ghana http://ugspace.ug.edu.gh 162 APPENDIX C Concentrations of Water Nutrients along the Water shed C1: Sodium (Na) Locations Wet Season/(mg/L) Dry Season/(mg/L) Daboase 27.8 21.4 Beposo 23.8 44 Bokorkope 19.9 2130 Shama 180 12490 Min 19.9 21.4 Max 180 12490 Co.V/% 107 140 Range 19.9-180 21.4-12490 Mean ± SD Nearest whole number 63±68 3671±5163 *WHO 2011 – 200 mg/L for Na+ C2: Potassium (K) Locations Wet Season/(mg/L) Dry Season/(mg/L) Daboase 6.3 4.3 Beposo 7.5 7.6 Bokorkope 5.8 72.1 Shama 14.2 563 Min 5.8 4.3 Max 14.2 563 Co.V/% 39.9 144 Range 5.8-14.2 4.3-563 Mean ± SD Nearest whole number 8±3 162±233 *WHO 2011 – no value listed C3: Nitrate (NO3-) Locations Wet Season/(mg/L) Dry Season/(mg/L) Daboase 0.509 1.72 Beposo 1.969 4.113 Bokorkope 0.629 0.392 Shama 1.204 2.242 Min 0.509 0.392 Max 1.969 4.113 Co.V/% 54.5 62.8 Range 0.509-1.969 0.392-4.113 University of Ghana http://ugspace.ug.edu.gh 163 Mean ± SD Nearest whole number 1.1±0.6 2±1 * WHO 2011 – 50 mg/L C4: Phosphate (PO43-) Locations Wet Season/(mg/L) Dry Season/(mg/L) Daboase 0.215 0.295 Beposo 0.383 0.494 Bokorkope 0.193 0.088 Shama 0.32 0.041 Min 0.193 0.041 Max 0.383 0.494 Co.V/% 27.8 78 Range 0.193-0.383 0.041-0.494 Mean ± SD Nearest whole number 0.28±0.08 0.2±0.2 * WHO 2011 – 0.3 mg/L C5: Sulfate (SO42-) Locations Wet Season/(mg/L) Dry Season/(mg/L) Daboase 3.602 11.304 Beposo 12.671 19.006 Bokorkope <0.001 121.118 Shama 16.894 73.043 Min <0.001 11.304 Max 16.894 121.118 Co.V/% 50.1 79.17 Range <0.001-16.894 11.304-121.118 Mean ± SD Nearest whole number 11±6 56±44 *Detection limit – 0.001 mg/L WHO 2011 – 500 mg/L University of Ghana http://ugspace.ug.edu.gh 164 APPENDIX D D1: Statistical Analysis Paired Samples Test Paired Differences t df Sig. (2- tailed) Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 Nitrates (Wet) - Nitrates (Dry) - 1.039000 E0 .886072 .255787 -1.601983 -.476017 -4.062 11 .002 Pair 2 Phosphates (Wet) - Phosphate (Dry) .048250 .163714 .047260 -.055769 .152269 1.021 11 .329 Pair 3 Sulphate (Wet) - Sulphate (Dry) - 2.339533 E1 24.572381 8.190794 -42.283337 -4.507330 -2.856 8 .021 Pair 4 Sodium (Wet) - Sodium (Dry) - 3.608475 E3 5323.311607 1536.707695 - 6990.745831 -226.204169 -2.348 11 .039 Pair 5 Potassium (Wet) - Poatssium (Dry) - 1.533000 E2 240.214438 69.343935 -305.924973 -.675027 -2.211 11 .049 University of Ghana http://ugspace.ug.edu.gh 165 *0.05 significant level One way ANOVA for water samples with pH as the factor variable D2: ANOVA (One way) Sum of Squares df Mean Square F Sig. Pb Between Groups .022 6 .004 56.303 .000 Within Groups .002 23 .000 Total .024 29 Cd Between Groups .000 4 .000 3.187 .034 Within Groups .000 21 .000 Total .000 25 Cu Between Groups .001 7 .000 1.081 .428 Within Groups .001 13 .000 Total .002 20 Zn Between Groups .013 7 .002 5.169 .001 Within Groups .009 25 .000 Total .022 32 Cr Between Groups .000 3 .000 2.248 .447 Within Groups .000 1 .000 Total .000 4 Mn Between Groups .042 7 .006 54.208 .000 Within Groups .003 24 .000 Total .044 31 Fe Between Groups 236.132 7 33.733 46.618 .000 Within Groups 17.366 24 .724 Total 253.498 31 Ni Between Groups .006 7 .001 4.700 .010 Within Groups .002 12 .000 Total .008 19 University of Ghana http://ugspace.ug.edu.gh 166 *0.05 significant level One way ANOVA for Sediment with pH as the factor variable D3: ANOVA Sum of Squares df Mean Square F Sig. Pb Between Groups 2723.089 7 389.013 3.118 .018 Within Groups 2869.990 23 124.782 Total 5593.079 30 Cd Between Groups .931 3 .310 .689 .578 Within Groups 4.958 11 .451 Total 5.889 14 Cu Between Groups 63.741 7 9.106 5.137 .001 Within Groups 46.087 26 1.773 Total 109.827 33 Zn Between Groups 24510.996 7 3501.571 80.673 .000 Within Groups 1128.510 26 43.404 Total 25639.506 33 Cr Between Groups 4.533 3 1.511 .429 .742 Within Groups 17.627 5 3.525 Total 22.160 8 Mn Between Groups 293978.861 7 41996.980 43.802 .000 Within Groups 24928.628 26 958.793 Total 318907.489 33 Ni Between Groups 205.144 7 29.306 2.224 .065 Within Groups 342.672 26 13.180 Total 547.815 33 Fe Between Groups 1.804E8 7 2.578E7 105.716 .000 Within Groups 6339973.912 26 243845.150 Total 1.868E8 33 University of Ghana http://ugspace.ug.edu.gh 167 D5: Paired Samples Test comparing pH of wet season to the dry season Paired Differences t df Sig. (2- tailed) Mean Std. Dev. Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 H2O pH Wet Season H2O pH Dry Season .54500 .67461 .33731 -.52846 1.61846 1.616 3 .205 Pair 2 Soil pH Wet Season - Soil pH Dry Season -.62500 .66536 .33268 -1.68373 .43373 -1.879 3 .157 D4: Paired t-test comparing the TSS-TDS of Dry Season to the Wet Season Paired Samples Test Paired Differences t df Sig. (2-tailed) Mean Std. Dev. Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 WET SEASON TSS - DRY SEASON TSS 1.61750E 2 205.24355 102.62178 -164.83830 488.33830 1.576 3 .213 Pair 2 WET SEASON TDS- DRY SEASON TDS - 6.51400E 3 9148.91655 4574.45827 - 21071.96783 8043.96783 -1.424 3 .250 University of Ghana http://ugspace.ug.edu.gh 168 D6: Paired t-test for DO/BOD Wet and Dry season Paired Samples Test Paired Differences t df Sig. (2-tailed) Mean Std. Dev. Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 DO/Wet - DO/Dry -6.66500 .21920 .15500 -8.63446 -4.69554 -43.000 1 .015 Pair 2 BOD/Wet - BOD/Dry -2.64000 .65054 .46000 -8.48485 3.20485 -5.739 1 .110 University of Ghana http://ugspace.ug.edu.gh 169 D7: Paired t-test for Total Alkalinity, Total Hardness and Total Solids (TS) with Seasonal variations Paired Differences t df Sig. (2- tailed) Mean Std. Dev. Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 Total Hardness/Wet - Total hardness/Dry -8.69250E2 1361.42802 680.71401 -3035.58578 1297.08578 -1.277 3 .291 Pair 2 TS/Wet - TS/Dry -6.35200E3 9249.16735 4624.58367 - 21069.48923 8365.48923 -1.374 3 .263 Pair 3 Total Alkalinity/Wet - Total Alkalinity/Dry 2.53750E1 22.37325 11.18663 -10.22584 60.97584 2.268 3 .108 University of Ghana http://ugspace.ug.edu.gh 170 APPENDIX E E1: Rotated Component Matrixa PLOT 1 Component 1 2 3 Soil-Pb .774 .536 .047 Soil-Cr .245 .884 .235 Soil-Mn .781 .573 -.121 Soil-Hg -.109 .058 .987 Soil-Se .895 -.127 -.089 Soil-Zn .876 -.177 -.224 Soil-Cu -.119 .884 .119 Soil-Fe .738 .523 -.358 Soil-Ni -.094 .829 -.273 pH .847 -.076 .393 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 4 iterations. University of Ghana http://ugspace.ug.edu.gh 171 E2: Rotated Component Matrixa PLOT 2 Component 1 2 3 Pb .775 .012 -.122 Cd -.349 .353 -.105 pH .939 -.111 -.128 Mn .875 .194 .287 Cu -.015 .721 .478 Zn .939 -.111 .058 Hg -.013 .980 -.010 Se .029 .981 .014 Fe .600 -.172 .743 Ni -.167 .147 .917 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations. University of Ghana http://ugspace.ug.edu.gh 172 E3: Rotated Component Matrixa PLOT 3 Component 1 2 3 Fe -.151 .948 -.042 Mn -.002 .882 -.118 Cr -.150 .600 -.647 Zn .901 -.038 .159 Cd -.546 -.685 -.046 Hg .579 .203 .745 TSS .872 .048 .405 TDS .797 -.559 .207 pH .331 -.148 .888 Se .819 -.099 .430 Ni .636 .175 .239 Na .852 -.463 .186 K .870 -.414 .201 Cu .917 .065 -.073 Nitratre .177 .684 .690 Pb .282 -.716 .314 Sulphate -.080 -.930 -.103 Phosphate -.389 .842 .357 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations. University of Ghana http://ugspace.ug.edu.gh 173 E4: Rotated Component Matrixa PLOT 4 Component 1 2 3 Fe -.145 -.913 .260 Pb .281 .778 .076 Cr -.549 .636 -.248 Cu .934 -.103 -.108 Cd -.175 -.741 -.363 Ni .682 -.141 .161 Zn .923 .060 .065 Se .801 .256 .432 Na .837 .517 .062 K .854 .477 .096 TSS .857 .106 .444 TDS .788 .607 .036 Nitrate .190 -.444 .854 Sulphate -.062 .821 -.457 Phosphate -.374 -.703 .581 Hg .578 .050 .794 Mn .017 -.892 .122 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 5 iterations. University of Ghana http://ugspace.ug.edu.gh 174 APPENDIX F F1: Principal Component Analysis (PCA) Elemental variables of sediments for Dry Season (PLOT 1) Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 4.744 47.441 47.441 4.744 47.441 47.441 4.135 41.349 41.349 2 2.622 26.217 73.658 2.622 26.217 73.658 3.196 31.958 73.308 3 1.439 14.392 88.051 1.439 14.392 88.051 1.474 14.743 88.051 4 .573 5.734 93.784 5 .312 3.115 96.900 6 .255 2.553 99.453 7 .034 .341 99.793 8 .013 .129 99.922 9 .008 .078 100.000 10 1.798E-16 1.798E-15 100.000 Extraction Method: Principal Component Analysis. University of Ghana http://ugspace.ug.edu.gh 175 F2: Principal Component Analysis (PCA) Elemental Variables of Sediments for Wet Season (PLOT 2) Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 3.763 37.629 37.629 3.763 37.629 37.629 3.639 36.391 36.391 2 2.804 28.042 65.671 2.804 28.042 65.671 2.683 26.825 63.217 3 1.505 15.047 80.718 1.505 15.047 80.718 1.750 17.501 80.718 4 .886 8.857 89.575 5 .544 5.444 95.019 6 .236 2.356 97.375 7 .130 1.299 98.673 8 .092 .917 99.590 9 .034 .339 99.929 10 .007 .071 100.000 Extraction Method: Principal Component Analysis. University of Ghana http://ugspace.ug.edu.gh 176 F3: Principal Component Analysis Dry Season River water Elemental Variables and Physicochemical parameters (PLOT 3) Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 8.367 46.485 46.485 8.367 46.485 46.485 6.661 37.007 37.007 2 5.387 29.926 76.411 5.387 29.926 76.411 5.872 32.624 69.631 3 1.827 10.151 86.562 1.827 10.151 86.562 3.048 16.931 86.562 4 1.060 5.888 92.450 5 .844 4.687 97.137 6 .253 1.407 98.544 7 .149 .830 99.373 8 .113 .627 100.000 9 3.199E-16 1.777E-15 100.000 10 2.591E-16 1.439E-15 100.000 11 1.241E-16 6.897E-16 100.000 12 8.963E-17 4.980E-16 100.000 13 5.333E-17 2.963E-16 100.000 14 -1.686E-17 -9.369E-17 100.000 15 -1.033E-16 -5.737E-16 100.000 16 -2.677E-16 -1.487E-15 100.000 17 -3.502E-16 -1.946E-15 100.000 18 -5.443E-16 -3.024E-15 100.000 Extraction Method: Principal Component Analysis. University of Ghana http://ugspace.ug.edu.gh 177 F4: Principal Component Analysis Wet Season River water Elemental Variables and Physicochemical parameters (PLOT 4) Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 7.960 46.826 46.826 7.960 46.826 46.826 6.562 38.601 38.601 2 5.331 31.362 78.188 5.331 31.362 78.188 5.528 32.519 71.121 3 1.427 8.391 86.579 1.427 8.391 86.579 2.628 15.459 86.579 4 1.048 6.164 92.743 5 .763 4.487 97.231 6 .247 1.456 98.686 7 .128 .752 99.438 8 .095 .562 100.000 9 4.368E-16 2.570E-15 100.000 10 2.974E-16 1.749E-15 100.000 11 1.742E-16 1.025E-15 100.000 12 3.265E-17 1.920E-16 100.000 13 -6.044E-17 -3.555E-16 100.000 14 -8.314E-17 -4.891E-16 100.000 15 -2.498E-16 -1.469E-15 100.000 16 -4.528E-16 -2.664E-15 100.000 17 -7.090E-16 -4.171E-15 100.000 Extraction Method: Principal Component Analysis. University of Ghana http://ugspace.ug.edu.gh 178 APPENDIX G Chemical Reactions and Calculations Total Alkalinity: Calculation mg CaCO3 / L = A ×t ×1000 ml of sample Where A = mL standard acid used t = titer of standard acid, mg CaCO3/ mL Chemical Reactions HCO3 − + H+ → H2CO3 CO3 2− + 2H+ → H2CO3 HCO3 − + CO3 2− + 3H+ → 2H2CO3 Total Hardness: Calculation (EDTA) as mg CaCO3/ L = A×B×1000 ml of sample Where A = mL titration for sample B = mg CaCO3 equivalent to 1.00 mL EDTA titrant Chemical Reactions Y is the disodium salt of EDTA (Na2H2C10H12N4O8) Ca2+ + H2Y 2− → CaY2− + 2H+ Mg2+ + H2Y 2− → MgY2− + 2H+ MgY2− + Ca2+ → CaY2− +Mg2+ University of Ghana http://ugspace.ug.edu.gh 179 Total Solids (TS) Dried at 100˚C - 105˚C: Calculation mg Total Solids (TS)/ L = (A−B) × 1000 sample volume, ml Where A = weight of dried residue + dish, mg B = weight of dish, mg Total Dissolved Solids (TDS) Dried at 100˚C: Calculation mg Total Dissolved Solids (TDS)/ L = (A − B) × 1000 sample volume, ml Where A = weight of dried residue + dish, mg B = weight of dish, mg Total Suspended Solids (TSS) Dried at 100˚C: Calculation mg Total Suspended Solids (TSS)/ L = (A − B) × 1000 sample volume, ml Where A = weight of dried residue + dish, mg B = weight of dish, mg Na and K (Flame Photometric Method) (APHA AWWA WEF, 1998): Calculation From the calibration curve mg Na/L or K/L = (mg Na/L or K/L in portion) × D University of Ghana http://ugspace.ug.edu.gh 180 Where D = dilution ratio D = ml sample+ml water ml sample Sulphate (𝐒𝐎𝟒 𝟐−) (Turbidimetric Method) (APHA AWWA WEF, 1998): Calculation mg SO4 2− L = mg SO4 2−×1000 ml sample Concentration range for calibration curve: 5mg/L to 40 mg/L of Sodium Sulphate (Na2SO4) Nitrate (𝐍𝐎𝟑 −) (UV Spectrophotometric Method) (APHA AWWA WEF, 1998): Calculation mg NO3 − L = mg NO3 −×1000 mL Sample Concentration range for calibration curve: 1mg/L to 7mg/L of NO3 − − N prepared by diluting to 50 mL the following volumes of intermediate solution: 1.00, 2.00, 4.00,…., 35mL. Phosphate (𝐏𝐎𝟒 𝟑−) (Ascorbic Acid Method) (APHA AWWA WEF, 1998): Calculation mg PO4 3− L = mg PO4 3−×1000 mL Sample Concentration range for calibration curve: 2 mg/L to 10 mg/L of PO4 3− prepared by serially diluting 50 mL of anhydrous KH2PO4. University of Ghana http://ugspace.ug.edu.gh 181 Dissolved Oxygen (DO) (Azide Modification of Winkler Method) Chemical Equations Mn2+ + 2OH− → Mn(OH)2 2Mn(OH)2 + 1 2 O2 + H2O → 2MnO(OH)2 Oxidation of Mn (II) to Mn (III) 2Mn(OH)3 + 2I − + 6H+ → 2Mn2+ + I2 + 6H2O Oxidation of I − to I2 I2 + I − ↔ I3 − Standardization with Potassium Iodate (KIO3) IO3 − + 8H+ + 6H+ → 3I3 − + 3H2O I3 − + 2S2O3 2− → 3I− + S4O6 2− Oxidation of S2O3 2− to S4O6 2−, reduction of I3 − to I− Biochemical Oxygen Demand (BOD) Calculation BOD5, mg L = D1−D2 P D1 = DO of diluted sample immediately after preparation, mg/L, D2 = DO of diluted sample after 5 days incubation at 27℃, mg/L, P = decimal volume fraction of sample used Microbial Activity Total Coliforms (TC) (APHA 9222A, Membrane Filter Technique) Calculation of Coliform Density CFU 100mL = Coliform Colonies Counted×100 mL Sample Filtered University of Ghana http://ugspace.ug.edu.gh 182 Total Heterotrophic Bacteria (THB) (APHA 9215B, Pour Plate Procedure) Calculation of Coliform Density CFU 1mL = Colonies Counted Actual volumes of samples in dish,mL Faecal Coliform (FC) (APHA 9222D, Membrane Filter Technique) Calculation of Coliform Density FC 1 g dry weight = Colonies Counted Dilution Factor×(% Dry Solids) E. coli (APHA 9260F, Modification of Standard Total Coliform (TC) Fermentation Technique) Calculation of Coliform Density CFU 100mL = Coliform Colonies Counted×100 mL Sample Filtered University of Ghana http://ugspace.ug.edu.gh