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Heavy Metals Geochemistry and Pollution Status of Coastal Sediments in Ayetoro Area, Southwestern Nigeria

Olusiji Samuel Ayodele*, Idowu Victor Ayodeji

Department of Applied Geology, The Federal University of Technology Akure, Nigeria

Abstract: Coastal sediments from Ayetoro, South-western Nigeria were systematically sampled and analysed for their heavy metals concentration. Fifteen costal sediment samples were taken using a Vanveen grab at sampling thickness and density of 10cm and 100 m respectively, while the depth of sampling was determined using single point Echo sounder. The heavy metals analysed were Cadmium (Cd), Lead (Pb), Copper (Cu), Nickel (Ni), Iron (Fe), Manganese (Mn) and Zinc (Zn) with Model 210 VGP Buck Scientific Atomic Absorption Spectrophotometer. The results showed that the respective locations are contaminated with metals from both geogenic and anthropogenic sources. SS15 (Eyin-more) is shown to be very strongly polluted with Cd and Pb whereas, PLI values of 1.06, 1.10 and 2,76 indicates that SS1, SS6 and SS16 have very high level of metal toxicity while other locations remain unpolluted. The average concentration of the heavy metals range from Fe with the highest concentration (15313.05 - 38399.11) mg/kg, followed by Pb (17.94-165.57) mg/kg; Zn (28.81-125.59) mg/kg; Cu (16.73-112.59) mg/kg, Cd (0.05-22.75) mg/kg and Ni (3.75-17.96) mg/kg with the lowest concentration. The average Enrichment Factor values showed that Cd and Pb has significant enrichment (7.67 and 5.71), followed by Cu, Ni, Zn having deficiency to minimal enrichment (1.31, 0.17, 1.02) whereas Cd and Pb is significantly enriched in all locations. This could be as a result of oil pollution from exploration and exploitation activities, improper waste disposal and industrial effluents which can result to brain damage, increasing the biological oxygen demand (BOD) of living organisms in the sea, destruction of the ecosystem and their food chain and web relationships, infant mortality as well as pollution of domestic and portable water sources. The dominance of Fe-Zn-Pb-Ni metal associations signified zinc ores or massive sulphide mineralization in the studied area. The coastal town of Ayetoro should be given more attention in terms of Environmental Safety Enforcement by the government.

Keywords: Ayetoro, coastal sediments, heavy metals, pollution status, mineralization

Received July 23, 2020; Revised August 25, 2020; Accepted September 03, 2020

Citation: Olusiji Samuel Ayodele, Idowu Victor Ayodeji, Heavy Metals Geochemistry and Pollution Status of Coastal Sediments in Ayetoro Area, Southwestern Nigeria. Journal of Environment Pollution and Human Health, 8 (2). 98-110. January 2020. doi:10.12691/jephh-8-2-7

1. Introduction

Sediments are defined as loose particles of clay, silt, sand and other substances suspended in the water bodies, which subsequently settle below the water bodies. According to Ademoroti (1996) [2], sediments are usually preferred in usage as pollution indicator to water samples, this is due the fact that there is higher concentration of toxic substances that are deposited on the water bed than in water column [11]. Elewa et al. (1990) [12] and Soltan (1980) [20] reported that the bottom sediments acts as accumulator for heavy metals by adsorption onto particles and rate of accumulation which depends on the environmental parameters such as pH, temperature, salinity, hardness, dissolved oxy-gen etc. and also on grain size, organic matter, mineralogy and depositional environment of the sediments [13]. Naturally, heavy metals has its compounds originated from rocks, volcanoes etc. referred to as geogenic, while anthropogenic sources are from human activities such as domestic waste disposal, industrial wastewater discharge, agricultural run-off of pesticides and fertilizers, land use/land cover change, atmospheric pollutants deposition, fossil fuel combustion etc. which leads to the contamination of the marine environment. In addition, rapid population growth and urbanization in southwestern Nigeria is envisage to have led to the increasing pollution of aquatic environment, due to largely uncontrolled contaminants discharge into the rivers ecosystem and has being found magnifying over the last decades [9]. The purity of marine environment is of major concern because it determines the water quality, conservation of the aquatic habitat and the survival of living organisms. The pollution of sediments, soils and organisms by toxic metals is of serious issue, mainly in of developed countries around the world, because they bioaccumulate and cause diseases when they enter the body of the organism including humans that feed on them. Severe imbalances of metal proportions caused by exposure to elevated concentrations of these elements can induce death of organisms [4] and adverse health effect on human and the environment [14]. The effects of heavy metals on the environment actually depends on several factors such as concentration of the metals in the sediments, the forms of existence of the trace metal in the sediment, as well as sediment and ground water chemistry [6]. As a result of the deleterious effects and concern it amounts, various researchers and environmentalist all across the world and in particular Nigeria has put together efforts and pay more attention to study the nature and concentration of heavy metals in sediment and suggested measures to combat the increasing level of its concentration. However, there has been inadequate information about mobility, bioavailability and toxicity of metals. Ayetoro, being a coastal town located in Ilaje, Ondo State, and Southwestern Nigeria is densely populated having over 20 settlements dispersed within the area and several oil and gas sector infrastructure sited there. Therefore, there is need to know the pollution status of the sediments using the indices of assessment; determine the relationships between the heavy metals and their physico-chemical interactions with the environments of deposition using methods such as Principal Component Analysis, Cluster analysis, Factor analyses to express their levels of enrichment.

2. Description of Study Area

2.1. Location and Accessibility of Study Area

Figure 1. Study area map of Ilaje, Ondo State, South-western Nigeria (Idowu, 2019)

Figure 2. Map of Drainage system of the studied location (Idowu, 2019)

Ayetoro is one of the coastal towns in Ilaje local government area of Ondo State. Ilaje lies between latitude 50 45’N - 60 90’N and longitude 40 30’E - 50 07’E (Figure 1) while the sampled locations in Ayetoro also lies between latitude 60 0’ N - 60 15’ and longitude 40 40’E to 40 52’E respectively (Figure 2). It shares boundary in the north with Okitipupa, the south with the Atlantic Ocean, the west with Ogun State and east with Delta State. Ilaje communities are made up of about 500 towns and villages covering 3,200km² [15]. Also, Ilaje is blessed with many rivers, lagoons, tributaries, lakes and a very long coastline of about 180km which depicts Ondo State as a coastal state with the longest coastline in Nigeria, with a land cover of 1,318km². The people are predominantly fishermen, other occupational activities include canoe making, lumbering, net making, mat making, farming and trading etc.

2.2. Topography and Drainage

The geologic setting of the study area influences the relief as well as the land forms which are relatively flat with some undulations Ayetoro is on a low land which is less than fifteen meters (15m) above sea level. The geomorphological units of the creek and surrounding riversides include sand ridges, swamp flats, creeks and the anatomizing distributaries of the western Niger delta. The area is a low energy depositional environment of mud material (Figure 5) and sediment from different sources, most especially the Atlantic Ocean. This involves the ocean water bringing more sediment to fill the shelf and the water ways, as the area is viewed to be a depositional environment in the geologic past while the environment is observed to be an erosional environment presently, Also, most of the communities landscapes are chopped-off by waves and currents. The drainage systems in the study area is a function of the topography. The drainage pattern in the study area is the parallel type (Figure 3). The major rivers in these areas, for example Ugbo, Ayetoro and Mahin lake flow southwards towards the Atlantic Ocean [10] while the drainage systems which include the rivers and some minor inland flow of water serve as a means of transportation in which the direction of flow of current is determined by the ocean currents and tides. The potential sources of water recharge in the study area includes surface precipitation (rainfall), recharges from the creeks and Atlantic Ocean Inflow. Discharge sources include Seaward water movement at low-tide and Evapo-transpiration [18].

2.3. Soil Conditions

The soil of Ayetoro has a dark brown colouration due to high organic matter, minerals present and the poor drainage conditions referred to as “Hydromorphic soil”. (Merriam-Webster described it as soil that developed in the presence of excess moisture which tends to suppress aerobic factors). Also, the muddy nature and colour of the soil in Ayetoro coastline is as a result of the low action of the wave and currents of the Atlantic Ocean, which deposit much mud on the shelf than sands forming the mud beach (Figure 4 and 5). The older sand ridge complexes develop brown and orange sand soils while the more recent one near the coast bear light to dark grey sand soils. Where there are depressions on the ridge complexes, the soils can be described as poorly drained light grey sands. The swamps flats are characterized by swampy ‘organic’ soils which in the major part consists of decomposed and partly decomposed matter, while areas affected by tides bear saline soils [13].

Figure 3. Sampled location Map of Ayetoro, Ilaje (Idowu, 2019)

Figure 4. Image of Mudcracks at Ayetoro (Idowu, 2019)

2.4. Geological Setting

The study areas (Ilaje and Ayetoro) are underlain by the easternmost segment of the extensive Dahomey Basin. The Dahomey basin constitutes offshore basins from South-eastern part of Ghana, through Togo and Benin Republic and then South-western Nigeria. Okitipupa Ridge, a sub-surface basement separates the Dahomey basin and the Niger Delta [1] and according to Omosuyi et al. (2008) [19], it is underlain by Coastal Plain Sands or the Benin formation which constitute the major shallow hydro-geologic units in the area. Within the coastal plain sands and coastal alluvium, the aquifer units identified are predominantly sands with high porosity and permeability. The aquifer system is a multi-storey type. Maximum of four units have been delineated within the coastal alluvium or coastal plain sands, as such rated as high ground-water potential. The Sedimentary formation of Dahomey basin outcrop in an arcuate belt, is roughly parallel to the ancient coastline. The continental sediments that were deposited is in a series of rapidly subsiding, fault-controlled depressions on the Basement complex which are progressively overlain by finer detrital sandstones, silt stones and shales of transitional nature. In the onshore, cretaceous strata are about 200m thick [24]. A non-fossiliferous basal sequences rests on the Precambrian basements. This is succeeded by coal cycles, clays and marls which contain fossiliferous shales towards the top. Agagu et al., (1985) [3] dated this as being pre- Albian to Maastrichtian. However, the study area is generally composed Albian to Maastrichtian. However, the study area is generally composed of mudstone and shale (Figure 5).

3. Method of Study

3.1. Sample Collection

The stream sediments were systematically collected at a sampling density of 100m interval and were put in an aluminium foil to prevent contamination and kept in a poly-ethene bag. Alongside, standard field observations (the depth of water, geographical coordinates, nature of stream sediment in terms of colour and texture, and human activities around the sampling points) were recorded to assist in carrying out a meaningful and reasonable data interpretation at the end of the exercise. Afterwards, the samples were taken to the laboratory for further processing before they were prepared for physical and chemical analysis. It was found necessary to place the samples under cold storage to halt biological activity and to prevent any chemical transformation in the sediments before digestion.

Figure 5. Image of the Ayetoro water-way (Idowu,2019)

Figure 6. Geological setting of the study area (Idowu, 2019)

3.2. Sample Preparation/Pre-treatment

The samples were pre-treated using standard procedures [7]. They were completely dissolved using heavy metals dissolution method (Wet oxidation of samples), which involves the destruction of the organic matter in the samples using Trioxonitrate V acid HNO3(aq.) followed by Perchloric HClO₄ (60%) and hydrochloric acids (HCl). The sample treatment and analysis were carried out at TEMSOL CONSULTS LTD., 7, Alfonso Road, Shasha, Ibadan.

3.3. Sample Digestion

The sediments samples were air-dried naturally, grounded and sieved to particle size of <2 µm. 2g of samples each were measured into the digestion flask. 10 ml of 2:1 by volume of Nitric-Perchloric acid was added to the sample and digested until dense white fumes appeared which took about 1 hour 30 minutes. The digest was allowed to cool and some quantity of distilled water added to the digest. The solution was then filtered into a 50 ml volumetric flask and diluted to fill the volume of the flask.

3.4. Metal Analysis

Metals were analysed using Model 210 VGP of the Buck Scientific Atomic Absorption Spectrophotometer series with air-acetylene gas mixture as oxidant. Extracts from the above digestion were aspirated and the equipment calibrated for each element. The results were recorded as mg/l of solution and were converted to mg/kg of sample using the volume of sample taken as a denominator of the digest volume (50 ml). A blank control sample was also treated as above as part of quality control measures. The Calculations involved;

mg.kg-1 sample = Digest concentration × D.F.

Digest concentration = Analyte reading on AAS

Where, the volume of digest is the Final volume of digested or extracted sample, Aliquot is the ratio of sample to distilled water (when diluted further), weight of sample is the weight of sample taken for digestion or extraction and D.F. is the Dilution factor.

3.5. Statistical Analysis

Mean: The mean was calculated using Equation (1):

[picture] | (1)

Median: is defined as the midpoint value of all sets of values. It is expressed in Equation (2) as:

[picture] | (2)

Where, n is the Number of observation and M is the Median Position arranged in the ascending or descending order.

Standard Deviation: It is given by the formula in Equation (3) as:

[picture] | (3)

Where, ∑ is the summation, is the Mean, is the individual data in the data sets, S= Standard Deviation and N is the Total number of observations.

3.6. Pollution Assessment Indicators

Correlation Coefficient: It was used to determine the strength of relationship among the reported trace elements in the sample. A software statistical tool called “R 3.1.2”, was used to compute the analysis.

Enrichment Factor: EF was used to assess the extent of influence from anthropogenic inputs, as such increasing EF represent rising contribution from anthropogenic sources. EF value of nearly one denotes the metals that are naturally derived, while EF values greater than one indicates elements of anthropogenic origin. EF was calculated by the ratio of Metal concentration to Reference material concentration in the sample divided by the ratio of the Metal concentration in reference background environment to Reference metal concentration in background environment.

[picture] | (4)

Where, Cn sample is the metal concentration in sample, Cref sample is the reference material concentration in sample, Bn background is the metal concentration in reference (background) environment and Bref background is the reference metal concentration in reference (background) environment. There are six levels of enrichment; EF < 2 (deficiency to minimal enrichment), 2 < EF < 5 (moderate enrichment), 5 < EF < 20 (significant enrichment), 20 <EF< 40 (very high enrichment), EF > 40 (extremely high enrichment).

Polluted Load Index (PLI) and Contamination Factor (CF): PLI invented by Tomlinson, et al. (1980) [22] was calculated using the heavy metal data and metal concentration of the world shale average [25] as the background value. Due to the absence of any background values of elements from the study area, the mean shale standards of heavy metals described by Turekian and Wedepohl (1961) [23] were considered as geochemical reference concentration in the present work. The PLI was obtained as a function of Concentration Factor (CF) of each metal with respect to the background value in the sediment [5]. The PLI represents the number of times by which the metal content in the sediment exceeds the background concentration, and gives a summative indication of the overall level of heavy metal toxicity in a particular sample. It was evaluated by applying the following equation:

[picture] | (5)

Where, Cmetal = Concentration of the metal in the sample, Cbackground = Concentration of metal in the background, CFmetal= Contamination Factor of the metal, n= number of metals and CF₁, CF₂,... CFn are the Contamination factor of each metal. When the PLI value is greater than unity, then it is polluted, but when less than unity, it is considered unpolluted.

Principal Component Analysis/ Factor Analysis: “R 3.1.2” software statistical application tool was used to analyse the data for component analysis.

4. Result and Discussion

4.1. Descriptive Statistics

The mean concentration of heavy metals in sediments of the study area showed variations across the sites studied with least values observed at the SS13 (Dogun) and the highest at SS15 (Eyinmore) (Figure 7). These high values at SS15 (Eyinmore) can be attributed to anthropogenic activities (Human settlement and dense market that leads to massive disposal of sewage waste and other harmful substances), and at other locations they are due to the presence of engineering workshop, petrol stations, dense settlements etc. The range are as follows: Fe 15313.05 - 38399.11 mg/kg, Cu 16.73-112.59 mg/kg, Zn 28.81-125.59 mg/kg, Cd 0.05-22.75 mg/kg, Pb 17.94-165.57 mg/kg, Ni 3.75-17.96 mg/kg. The concentration of Fe (26966.19±7322.65 mg/kg) was higher than other metals examined, this was followed by those of Pb, Zn and Cu, Ni while Cd had the least value. The variation of the concentration of metals across the location shows very similar trends in terms of correlation (Figure 7). Table 1 gives the descriptive statistics of the Heavy metals across all the sampled location.

Figure 7. Variation plots of individual heavy metals across the sampled locations

Figure 8. Box Plot of Heavy Metals and their mean concentration across sampled locations

Table 1. Descriptive Statistics of the Heavy metals and their concentration

Table 2. Correlation Matrix showing the inter-relationship between heavy metals

4.2. Correlation Coefficient

Correlation coefficients reveal the interrelationships between elements. Table 2 above revealed that the Correlation Coefficient ranges from 0.478 (for Fe and Cd) to 0.948 (for Fe and Ni). Correlation coefficient in Table 2 larger than 0.5 showed that there is positive correlation between the two metals and those less than 0.5 indicates inverse or negative correlation between the variables (metals). Pb-Cu shows a high level of relationship with no significant difference at p-value < 0.05, this indicates that that the sources are similar (anthropogenic sources such as Engineering workshop, Petrol station etc.); Cd-Pb and Cd-Ni shows positive correlation (the higher the concentration of Cd in the sediment the more the concentration of the other metals) with correlation significant at p-value <0.05 indicating their common source as majorly anthropogenic. There is positive correlation of Ni-Fe, Ni-Zn, Ni-Pb, Pb-Fe, Pb-Zn, Zn-Fe, Zn-Cu and Cu-Fe with significant difference at p-value < 0.01, these shows similar origin and revealed that elements with positive correlation are abundant in the geochemical system while those with negative correlation are depleted [8].

4.3. Enrichment Factor

In order to know the possible natural or anthropogenic input and impact in sediments, enrichment factor (EF) was computed. The Enrichment Factor values ranges from 0.11 at SS12 (Lepe) to 84.33 at SS15 (Eyin-more). According to Table 3, most of the heavy metals have minimal to deficiency level of pollution as a result across the sample stations, except Pb that is moderately enriched to significantly enriched with its possible source for enrichment to natural mineralization in form of sporadic sulphide occurrences. The source of the high Pb enrichment of the stream sediments is uncertain. Cd was known to have extremely high enrichment at SS15 (Eyin-more) this can be due to dense human settlement, petrol station and also carpentry works based on observations during field work. The average Enrichment Factor values indicates that Cd and Pb has significant enrichment (7.67 and 5.71 respectively), while Cu, Ni, Zn have deficiency to minimal enrichment (1.31, 0.17, 1.02 respectively). Cd and Pb is significantly enriched in all locations compared to the other heavy metals, which could be as a result of oil pollution from exploitation, improper waste disposal and industrial effluents. Fe was not included in the EF column (Table 3), because it serves as the normalizing element due to its high enrichment as a result of its high concentration in the sediment sample.

Table 3. Enrichment factor across all the sampled Location

4.4. Contamination Factor (CF) and Pollution Load Index (PLI)

Table 4. Geo-accumulation Index result across all the sampled location

Table 5. Contamination Factor and Pollution Load Index across all the sampled Location

The contamination levels of the heavy metals in the coastal sediments were evaluated by comparing present contaminations with background levels using the Muller scale for Igeo. The Igeo of the heavy metals in sediments is already presented in Table 4. The values of the Igeo values are as follow: Fe (-2.21 to -0.88), Cu (-2.01 to 0.74), Zn (-2.31 to -0.18), Cd (-3.17 to 5.66), Pb (-0.74 to 2.46), Ni (-4.77 to -2.51) and it is lowest at Dogun (-4.77). In this study, most parameters (Fe, Cu, Zn and Ni) showed its Geo-accumulation index value to be less than unity (1) across all the samples location, which likely indicates that these areas are unpolluted according to Muller (1981) [16] Cd and Pb has Igeo value greater than 1, indicating that sediments collected from various location are contaminated with these metals. SS15 (Eyimore) is shown to be very strongly polluted with Cd and Pb and moderately polluted at SS1 (Ayetoro), SS2 (Idi-Ogba), SS3 (Ero) and SS6 (Okun-Harama) respectively. This could be attributed to the high level of pollution from industrial machine exhausts and oil wastes from engineering works and spillages from oil creeks. Calculated values of the pollution indices are presented in Table 5. The values for the Contamination Factor (CF) ranged from 0.055 to 75.833, Cd generally had the highest across all the sampled locations and Ni had the least across the sampled locations. Ni also had the least at SS13 (Dogun) and Cd had the highest at SS15 (Eyin-more).

4.5. Principal Component Analysis

Table 6 presents the result of the factor analysis. The first factor is dominated by Fe-Zn-Pb-Ni metal association. This accounted for 53.59% of the total variance and indicated the type of mineralization common in the studied area. The second factor con-sists of Cu-Zn-Cd metal association which are the indicator elements to the type of mineralization which accounted for 40.416% of the total variance, while the third factor which consist of no metals although small amount of % total variance (1.23%), indicated weathering and dispersed elements within the geochemical system either by metasomatic process, metamorphism or dissolution. The presence of zinc in the first and second factors is an indication of sphalerite deposits leading to massive sulphide mineralization in the studied area.

Table 6. Factor Analysis Matrix of the Heavy Metals

From the Scree plot (Figure 8), It is seen that the first three components are high above (carrying more information of the environment of deposition) and from the third factor it is almost relatively flat meaning that each successive factor or components accounts for smaller portion of the total variance as such less information. Figure 9, Figure 10 & Figure 11 presents the distribution patterns of Cu, Cd and Pb across the sampled locations with the peaks at Eyimore (SS15) location having the highest concentrations of these metals. The scattered plot matrices of the heavy metals (Figure 14) revealed the geochemical associations of these metals in relation to their sampling sites. The dendograms (Figure 15) revealed six cluster groups (6 & 9, 1 & 2, 3, 7 & 8, 12 & 13, 10, 4 & 5, 11 & 4) which represented the geo-chemical attributes/behaviour of the heavy metals with respect to their sampling sites. The 6 principal components analysis (Figure 16) showed that components 1 and 2 are very important in terms of the mineral associations while the remaining ones are insignificant which is also displayed in Figure 15 & Figure 16. However, some heavy metals that were found in higher concentrations (Fe, Cd, Zn, and Cu) have dangerous effects on the ecosystem, organisms present and human that feed on these organisms. Ingesting very high levels of Cadmium, severely irritates the stomach leading to vomiting and death. Long-term exposure to lower levels leads to a build-up, fragile bones and possibly kidney disease. Pollution of water by these trace metals leads to depletion of resources that are present (such as Coral reefs, Salt marsh etc.), reduction in the utilization of the water for purposes like Irrigation, drinking etc.

Figure 9. Scree plot of Variance against component number

Figure 10. Copper concentration variation across the sampled location

Figure 11. Cadmium Concentration variation across the sampled location

Figure 12. Lead Concentration Variation across the sampled location

Figure 13. Clus Plot graph showing clusters of data using R statistical package

Figure 14. Scatter plot matrix of the heavy metals parameter using R programming software

Figure 15. Cluster diagram (Dendogram) of the sampled location using the R statistical software

Figure 16. Principal Component Analysis chart of the six components (element)

Figure 17. PCA graph showing the Heavy Metals

5. Conclusion

Heavy metal contaminations and pollution assessment of the coastal sediments in Ayetoro and environs has been carried out. A study of the occurrence, distribution and level of pollution of six heavy metals such as Fe, Cu, Zn, Cd, Ni, Pb, in the bottom sediments of the studied area revealed that the sequential dominance of these metals as Fe> Pb>Zn>Cu>Ni>Cd. Mean concentration of heavy metals showed variations across the sites studied with least values observed at the SS13 (Dogun) and the highest value at SS15 (Eyinmore). These high values at SS15 (Eyinmore) can be attributed to anthropogenic activities such as human settlements, exploration, exploitation activities, market density in the area leading to massive and daily disposal of sewage wastes and other harmful substances. Enrichment factor (EF) and Geo-accumulation index (Igeo) revealed that all the locations are moderately enriched with Cd and Pb as a result of human influences from sewage disposal, industrial effluents, Cd was known to have extremely high enrichment at SS15 (Eyin-more) which was linked to anthropogenic sources as mentioned above. Cd and Pb have Igeo values greater than 1, showing that the respective location is contaminated with the metals from geogenic sources while SS15 (Eyimore) is shown to be very strongly polluted with Cd and Pb. This could be as a result of the use of fertilizers, pesticides and industrial effluents etc. PLI values of 1.06, 1.10 and 2.76 indicate that SS1, SS6 and SS16 have high level of heavy metal toxicity, while other locations remained unpolluted. Cadmium (Cd) is a radioactive element which is very poisonous when consumed by human as it can leads to brain damage, severe bleeding, and acute genetic disorders such as mutations, and death from consumption of fishes (tilapia and catfishes). In addition, the study area is suspected for Fe-Zn-Pb-Ni mineralization based on the results from the Principal Component Analysis (PCA). The mineral associations discovered confirmed sphalerite deposits leading to massive sulphide mineralization in the studied area. Finally, the Coastal area of Ayetoro should be given more attention in terms Environmental Safety enforcement by the Government. There should be strict regulations to control the dumping of chemical contaminants and other waste into the water, with enforcement of penalties imposed on defaulters.

Acknowledgements

I hereby acknowledge my project students from the Department of Marine Science and Technology (2019), The Federal University of Technology, Akure who worked assiduously with me to achieve success on this research. You are all wonderful Technical Partners to work with, and I appreciate you all for your valuable suggestions and contributions to the success of this research.

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