Trace elements characterization of soils and rocks in Agricultural areas of Labunwa, Near Idanre, Southwestern Nigeria


 Trace elements (TE) concentrations of subsoil and the underlying parent rocks of Labunwa – Odele area were determined in other to ascertain the enrichment level, distribution and sources of these TEs in the subsoil in the study area. Twenty-one (21) subsoil (at depth of 30 -100 cm) and thirteen (13) rock samples were collected, pulverised and digested using aqua regia for soil samples and near total digestion of HClO4, HF, HCl and HNO3of different proportions for the rocks. The samples were analysed using Inductively Coupled Plasma- Mass Spectrometry, (ICP-MS). The mean TE concentrations in ppm for subsoil showed Cu (40.0), Pb, (24.2), Zn (56.3), As (0.9) and U (2.7) among other elements as against the mean concentrations of granite gneiss (GGN) with Cu (22.9), Pb (61.4), Zn (64.6), As (1.0), U (2.6) and Pegmatite, (PGM) Cu(128.4), Pb(17.0), Zn(108.8), As (1.1), U (1.3) among other TEs. The relatively low concentrations of the TEs in the subsoil compared to the underlying parent rocks suggests that TEs in the subsoil may have been influenced by geogenic factors, such as weathering of the underlying rocks. TEs source apportionments in the subsoil using Bivariant plots, correlation coefficient, Bi-polar and dendogram analyses showed that these TEs are essentially from the underlying GGN and PGM in the area. Pollution status indices, I-geo, Contamination factor and PLI showed that the study area is practically unpolluted. This suggests that locations with relatively higher concentrations of some TEs are probably due to mineralisation and since most of the subsoil TEs are significantly lower in concentrations compared to the underlying bedrock, the area is safe for agricultural activities.

2017). And such relative enrichment of these trace elements that are present in the agricultural input might be of hazardous status when they exceed permissible limit in the geomedia Agricultural soil are critical assets that need to be monitored, particularly with respect to the chemical status, because there is the possibility of mobility of such trace elements into the plant and other living things that interact with the soil, hence the need for continuous monitoring.
The works of Owens et al., (2016); Li et al., (2019), showed the use of Cluster analysis, Principal Component Analysis and other related methods to infer potential sources from geochemical characteristics of sediments and soils. This assisted in knowing the source contribution and compositions of the analysed geochemical data. Odukoya and Akande(2015), carried out pollution status assessment of major, trace and rare earth elements (Fe, Al, Ca, Na, Mg, K, P, Ti, Co, Mn, U, Th, Sr, V, La, Cr, Ba, Sc, Ga, Cs, Nb, Rb, Y, Ce, Mo, Pb, Zn, As, Cd, Sb, Sn and Zr), using Inductively Coupled Plasma -Mass Spectroscopy (ICP-MS). The environmental risk assessment was quanti ed using geo-accumulation index (Igeo), Pollution Load Index (PLI) and Contamination Factor (CF). It was observed that all the samples were within the class of low to medium contamination risk range, with the exception of samples from Owode Onirin stream chatchment, which fell within very high to extremely high risk. Several published works have similarly used inference statistical methods in assessing soils and sediments' elemental enrichment status, whether the geomedia are from geogenic or otherwise (Grba el al., 2015;Udosen et al., 2016;Sako et al., 2018; Melvin et al., 2020). They concluded that the trace element contents of the geo media (soil, sediments and water) were mainly controlled by geochemical processes, particularly by weathering rather than anthropogenic effect. They also found out that there is little or no signi cant health risk to the exposed population. From the forgoing, it becomes very important that such an agricultural soil needed to be continuously monitored.
The aim of this research is to determine the trace element concentration and distribution in the subsoil of Labunwa -Odole and its environs as well as evaluate the health risk, if any, that are associated with the concentration level of these selected trace elements in the study area.

Study Area
Field survey was carried out in the agrarian (Agricultural farmland) area of cocoa, cassava, yam tuber and other cash crops. The communities in the study area include Omiliyan, Labunwa, Owomofewa, Akinde, Olisaga, Ago-Gabriel and Odole among other hamlets ( Figure 1). The study area is easily accessible from Oda and Idanre towns and lies within the tropical rainforest of the southwerstern part of Nigeria. The area is humid, with temperature varying between 21.1 to 22.3

Geology of the Study Area
Labunwa and environs are underlain by the Precambrian Basement Complex of Southwestern Nigeria. These Precambrian rocks are regionally sub-divided into four major rock types as a result of tectono-stratigraphic basis (Hockey et al., 1963;Oyawoye 1976;McCurry, 1976;Olarewaju 1988;Rahaman 1988). These sub-divisions are Migmatite -Gneiss -Quartzite Complex, the Schist belt, the Older Granites and the Granitoids, which are emplaced as minor felsic and ma c intrusive bodies (Ajibade et al., 1987, Ajibade et al., 2008, Adekoya 1991. In the study area, two rock types were mappedin the course of the eld exercise. The two rock types are Granite Gneiss, which dominate over 90% of the study area as well as the pegmatite. The pegmatite are mainly exposed along the stream channels ( Figure 2).The dominate felsic minerals include quartz, alkaline (K) feldspar and plagioclase feldspar, while the ma c minerals include biotite, hornblend and muscovite mica. Accessory mineral include rutile, nepheline and opaque minerals.

Methodology
Twenty -one (21) composite subsoils samples were collected from the B -horizon at depth that ranged between 30cm -100cm. To obtained the composite samples, three (3) sub samples were collected from each of the grids that had been drawn of the topographic sheet prior to sample collection. The three sub-samples were then mixed together to obtained the composite sample ( Figure 1). The soil sampling exercise was conducted at the peak of dry season, precisely in February, 2019. Collection was done with the aid of hand auger and care was taken to ensure that samples were not contaminated. This was achieved by carefully washing the hand auger with detergent, properly rinsed and drying it after each samples collection. The collected samples are, thereafter, carefully put in a well-labelled sample bag, the coordinates of the location and other necessary observations recorded in the eld notebook. Similarly, at every sample point, a larger diameter cutting head was employed in order to rst remove the overburden, shrubs and topsoil and then replaced with a narrower diameter to collect the subsoil. In the same vein, thirty-one (31) representative rock samples were also collected within the study area. These rock samples were collected based on the lithology of the study areas as presented by Awosusi et al., 2019. Both the soil and rock samples were properly labelled upon sampling, in a bag and transported to the laboratory for sample preparation.
The soil samples were air dried at room temperature for a period of eight (8) days. The dried samples were, subsequently, pulverized and sieved using 053um mesh fraction. Furthermore, the sieved samples were digested using modi ed partial digestion method, (Aqua regia). The digestion process involves gradual input of 5ml nitric acid (mesh Suprapur of 65%), with the addition of 2ml hydrochloric acid (HCL) (merch suprapur 36 o C) and 10ml of pure water of 18mΩ/cm speci c resistivity) in ultraclean tube. The samples were heated at temperature of 95 o C for two (2) hours, using microwave oven. At the end of heating, the samples were decanted in volumetric ask of 50ml size. Then, the solution were extracted using disposable syringe ltered Procedures for quality control and assurances were carried out before and in between the analysis of the samples. These were done using certi ed reference materials, dublicate samples as well as blank samples, following the laboratory (ACME) scienti c protocol ( Table 1). The geochemical results of the quality control data, 20% of the total soil samples, were analysed and the result showed very low standard deviation of 10% in between samples analysed (Table 1). Similarly, the minimum detection limit (MDL), analysed samples as showed in Table 1, indicated signi cantly high sensitivity values which suggest that the equipment was highly sensitive and was satisfactory for the determination of the selected trace elements.  From the equation, Cn means the concentration of trace element in the subsoil in ppm, Bn represents the background concentration (in ppm), which in this case, the average granite gneiss elemental concentration were used as the background concentrations. 1.5 is a constant, which is used as a factor to minimize variation in the litho materials. Under this evaluation, classi cation that ranges from 0 to 5, as stated below, have been adopted to represent the relative pollution status of each element in every location.

Uncontaminated (Igeo≤ 0)
Uncontaminated to moderately contaminated (0 < Igeo≤ 1) Moderately contaminated (1 < Igeo≤ 2) Moderately to heavily contaminated (2 < Igeo≤ 3) Heavily contaminated (3 < Igeo≤ 4) Heavily to extremely contaminated (4 < Igeo≤ 5) Extremely contaminated (Igeo> 5) In the case of the contamination factor (CF), whichis a quanti cation of the degree of contamination relative to either average crustal composition of a metal or to the measured background value from geologically similar and uncontaminated area (Ladigbolu and Balogun, 2011).This was also used to assess the relative pollution status of the studied subsoil. The

Results And Discussions
The distributions of the analysed trace elements (Cu, Pb, Zn, Ni, Co, Mn, As, U, Th, Sr, Cd, V, La, Cr, Ba, Sc, and Se) in the subsoil of the study area were found to vary in concentrations (in ppm) from one sample location to the other. The concentrations of Cu in the subsoil ranged from 9.26ppm, as found in location IDS16, to 76.28ppm as found in location IDS12. The average (mean) concentration of Cu was 40.00 ppm, with a standard deviation of 20. 50 other analysed elements were also observed in the subsoil samples ( Table 2). The average concentrations of some of the trace elements in the subsoil were found to be lower than the average concentrations of both the granite gneiss and pegmatite. Such elements include: As, Sr and Ba.The concentrations of these elements in the subsoildecrease in the following order: Mn>Ba>La>Zn>V>Cu>Cr>Cr>Pb>Co>Sr>Th>Ni>Sc>U>Se>As>Cd.
The mean value of As in the subsoil was 0.9 ppm, which is slightly higher than that in the granite gneiss 1.0 ppm and pegmatite  (Table 2).
A Comparative analysis of the trace elements in the subsoils and the two rock types (granite gneiss and pegmatite) underlying the study area, were also carried out using the boxplots in Figures 3 (a-q). From the plots, higher concentrations of Ba was found in both the pegmatite and the granite gneiss compare to thatin the subsoil. Similar trend were recorded in As, Cd, Sr and Zn.
However, different enrichment patterns were observed in Co, Cr, Cu, Mn, Ni, Sc, and V. In these elements, the concentrations in pegmatite were relatively higher compared to the subsoil and the concentrations of these elements were much lower in the granite gneiss. It was also observed that La, Pb, Th and U were found to be higher in concentration in the granite gneiss than in the subsoil. Since the study area is essentially underlain by granite gneiss, covering about 90% of the rock within the study area, it could be inferred that the rock (granite gneiss) may have contributed greatly in the enrichment of the elements in the subsoil through effect of weathering and erosion in the formation the soil in the study area.

Interelemental relationship
The reative association of the trace elements in the geomedia, (subsoil, granite gneiss and pegmatite) were evaluated, using Pearson correlation cooe cient (Bivariant plots) in Figure 4  The correlation matric of the trace elements in the subsoil showed varying degree of correlation (Table 3). From the correlation coe cient ( r ), it was observed that it ranges from negative correlation of -0.4, between Th and Cu, to very strong correlation of 0.9, between Cd and Mn. Relatively fair to strong correlation were found between Mn/Cu (0.7), As/Pb (0.7), Mn/Zn (0.6), Co/Ni The subsoil data were further subjected to Principal Component Anaysis (PCA) with varimax rotation. From the results, a total of ve factors with eigen value greater than 1.0 and accounting for 85.74% of the data variability were extracted and considered appropriate ( Table 4)   The mean concentration of the trace elements in the subsoil, granite gneiss and pegmatite and the mean concentration of some trace elements in soils of published researched works, particularly in agricultural and urban soils in Nigeria are presented in Table 5. Also included in the table are  Lanka (Jayawardana et al., 2013). And the mean Pb concentration, from this study, is signi cantly lower compared to the data from other soils in Egypt, Sri Lanka, among other areas of comparison (Table 5). Similarly, the mean Zn concentration, in subsoil of this study, is found to be signi cantly lower compared to the data from most of the areas of comparison except in Cerrado soils, Brazil (Marques, et al., 2004).
The mean concentrations of the other elements in the subsoil, from this study, are comparatively lower than the concentrations from most of the selected areas of comparison (Table 5). This suggests that that the sources of these elements are essentially geogenic rather than anthropogenic.  The results of the Igeo index for some selected high priority trace elements are presented in Table 5. These elements include Cu, Pb, Zn, Ni, Co, Mn, As, Th, Sr, Cd, V, U, La and Cr. From the results, it was observed that elements such as Pb, Th, Sr, Cd, As U and La, practically showed negative Igeo values which suggests that the subsoil are practically unpolluted with respect to these elements. Cu Igeo values fall within the range of "unpolluted" in more than 60% of the studied locations, while about 30% of the locations are uncontaminated to moderately contaminated. The remaining 10% of the sample locations are moderately contaminated. Mn Igeo values were found to range from uncontaminated to moderately contaminated. However, locations that were uncontaminated are found to be signi cantly (about 60%) higher than the sample locations (about 40%) that were moderately contaminated. Similar trend were observed for V and Cr, with much of the sample locations exhibiting uncontaminated to moderately uncontaminated. Generally, it was observed that the Igeo index values of the selected trace elements in the subsoil samples were essentially uncontaminated.
Similarly, the results for the Contamination Factor (CF), are presented in Table 6. From the result, as earlier explained in the methodology, it was observed that Cu in the subsoil recorded low to moderate contamination, which ranged from 0 to < 3. Pb, Zn, Ni, U, Th, La and Sr showed essentially low contamination of (CF <1). However, Co, Mn and Cr showed relatively higher CF values of >3 but < 6, suggesting considerable contamination in many of the locations sampled. The high CF values of Mn, Co and Cr may not be unconnected with the Mn-Oxides presence in the in-situ weathered lateritic soils from the granite gneiss that essentially underlain the study area. It could also be due to the scavenging action of Mn-oxides on these elements in the secondary environment. The result of the calculated Pollution Load Index, (PLI), as presented in Table 6, showed most of the sampled locations are not polluted except in locations 15, 18, 19 and 21 where their PLI is higher than 1. This may probably be attributed to mineralisation rather than pollution.

Conclusion
Trace element concentrations of subsoil and rocks (Granite Gneiss and Pegmatite) that underlain Labunwa-Odole and environs have been determined, with a view to ascertaining the relative concentration, distribution and sources of the metals in the study area since the area is economically an agrarian terrain. The concentrations of these elements decreased in the following order: Mn>Ba>La>Zn>V>Cu>Cr>Pb>Co>Sr>Th>Ni>Sc>U>Se>As>Cd. The trace elements were found to be relatively low in concentration.
The average concentration of the trace elements in the subsoil were found to be lower than the average shale (earth crust) concentration except for Pb, Co, Mn, Th and Se, which showed slightly higher concentrations. Similar lower concentrations were observed when compared with the results from other authors. Furthermore, it was observed that the trace element concentrations in the subsoil were largely lower than the concentrations in the underlying crystalline rock, suggesting that the enrichment of these trace elements in the subsoil were in uenced by the weathering of the rocks in the study area. Locations with relatively higher concentrations of these trace elements suggest possible mineralisation.
Results of the pollution status quanti cations such as the Igeo, Contamination Factors and Pollution Load Index showed that the trace elements ranged from uncontaminated to moderately contaminated. Correlation and clustering analyses point to a geogenic rather than anthropogenic source for the trace elements. Figure 1 Samples location map of the study area.

Declarations
Page 20/23      Bi-Polar plot for the selected trace elements.

Figure 6
Dendogram plot the analysed trace elements and sample location, using Average Linkage (Between Groups)