J. Nig. Soc. Phys. Sci. 4 (2022) 887 Journal of the Nigerian Society of Physical Sciences Assessment of Heavy Metal Pollution Status in Surface Soil of a Nigerian University M. A. Lalaa,∗, S. Kawua, O. A. Adesinaa, J. A. Sonibareb aDepartment of Chemical and Petroleum Engineering, Afe Babalola University, Ado-Ekiti, Nigeria bDepartment of Chemical Engineering Obafemi Awolowo University, Nigeria Abstract The problem of urban soil contamination with heavy metals due to rapid urbanization and industrialization has been a major concern in recent years. A university can be considered as a product of industrialization and urbanization which is associated with different activities that may induce heavy metals pollution into the environment. Therefore, this research work assessed the contamination level of chromium (Cr), copper (Cu), lead (Pb), zinc (Zn) and manganese (Mn) in surface soils of Afe-Babalola university (ABUAD) using various indices. Soil samples were taken from ten (10) different functional sites in the university. These samples were taken to the laboratory and analyzed for chromium (Cr), copper (Cu), lead (Pb), zinc (Zn) and manganese (Mn) using standard method. The mean concentrations of copper (Cu), chromium (Cr) and lead (Pb) were up to 0.75, 0.66 and 0.36 mg/g respectively, while manganese (Mn) and zinc (Zn) were 1.37 and 0.49 mg/g respectively. The average concentration of manganese (Mn) was comparable to its corresponding natural background value, but the average concentration of chromium (Cr), copper (Cu), zinc (Zn) and lead (Pb) were higher. They were approximately of the ratio 1:7, 1:2, 1:3 and 1:2 respectively compared to their corresponding natural background value. The multivariate statistical analyses indicated that vehicles, power generating sets, petrol station, machine workshops, production plants and emissions from outdoor roasted food spots were the major sources of heavy metals contamination on the universitys’ soil. The results from contamination indices and assessment showed that the contamination level of soils within the university can generally be classified as moderately contaminated. Therefore, periodic assessment of the sources and associated ecological risks of the heavy metals is highly recommended. This is to enable decision-makers to effectively manage the environment in the manner that will preserve public and ecosystem health. DOI:10.46481/jnsps.2022.887 Keywords: Contamination indices, Ecological risk assessment, Multivariate techniques, Afe-Babalola University Article History : Received: 23 June 2022 Received in revised form: 21 July 2022 Accepted for publication: 21 July 2022 Published: 15 August 2022 c© 2022 The Author(s). Published by the Nigerian Society of Physical Sciences under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0). Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Communicated by: M. Orosun 1. Introduction Heavy metals are relatively high density (usually 3.50 to 7.00 g cm−3) metallic or metalloid elements that are capable of ∗Corresponding author tel. no: +2348163280469 Email address: lalam@abuad.edu.ng (M. A. Lala) inducing toxicity to humans and the environment at some lev- els of exposure [1-2]. These heavy metals include cadmium (Cd), mercury (Hg), arsenic (As), chromium (Cr), zinc (Zn), nickel (Ni), lead (Pb), copper (Cu) etc. They are widely present in the crust of the earth and are not degradable in nature [3]. Heavy metals can be considered as trace elements because of their trace quantity in the environmental. The bioavailability 1 Lala et al. / J. Nig. Soc. Phys. Sci. 4 (2022) 887 2 of heavy metals is usually influenced by physical factors (i.e temperature, adsorption and phase association), biological fac- tors (i.e biochemical adaptation, physiological adaptation and species characteristics) and chemical factors. The chemical fac- tor affects the formation of more ions in the course of their re- actions [1-6]. Sources of heavy metals pollution can generally be classi- fied as natural and anthropogenic or manmade. The crust of the earth naturally contains heavy metals, but human or an- thropogenic activities have been recognized as the major source of the pollution [1]. Considering the natural courses of heavy metal pollution, weathering and volcanic eruptions have been identified as parts of the main contributors [1, 7, 8]. Envi- ronmental pollution through anthropogenic activities includes agricultural and domestic use of compounds containing metals, mining operations and smelting operations. Industrial activities such as burning of coal in power plants and processing of met- als in refineries are also major sources of manmade pollution. Moreover, petroleum combustions, textiles, plastics, microelec- tronics, paper processing and wood preservation also contribute immensely to heavy metals level in the environment [1]. In some years back, series of studies have been carried out on the assessment urban soils for heavy metals contamination [9-11]. This is because soil is the main geochemical reservoir for all heavy metal pollutants discharged into the environment. Heavy metals are being deposited on soil which is the most im- portant component of the biosphere through vehicular and other combustion engines emissions. Careless waste disposals and oil spillage in auto-mechanic workshops, industrial production, energy generation, construction activities, coal and fuel com- bustion, as well as indiscriminate use of pesticides and fertiliz- ers on farmlands also induce heavy metals into the environment [12-15]. In addition, study indicated that atmospheric deposi- tion which occurs either by dry or wet deposition represents another major contributor of heavy metals into the topsoil in urbanized areas [16]. The most commonly found metals on soils of contaminated sites include zinc (Zn), arsenic (As), chromium (Cr), lead (Pb), cadmium (Cd), mercury (Hg), copper (Cu) and nickel (Ni). They do not undergo chemical or microbial degradation as ap- plicable to organic pollutants which oxidized easily by micro- bial actions [1, 17]. Prolonged exposure to cadmium (Cd) and lead (Pb) even at low concentrations could cause lung dam- age, cancer, kidney disease, and nervous disorder. This is most common with lead (Pb). Chromium (Cr) which exists in dif- ferent valence states can cause gastrointestinal, lung and nasal irritation, small intestines and stomach ulcer, decreased sperm counts and dermatitis. Nickel (Ni) also causes cancer, dermati- tis and lung inflammation. Copper (Cu) is associated with car- diomyopathy and lung irritation, and the major reported side effect of copper (Cu) and zinc (Zn) on health are vomiting, abdominal pain, respiratory system irritation and nausea [18]. Other heavy metals also pose great adverse effects to humans, animals and plants. Soils contamination in different urban sector may vary de- pending on the activities being carried out on them. Hence, assessment of urban soils for heavy metals contamination is highly important [19-20]. In recent years, studies have been conducted on the contamination assessment of heavy metals in soil samples from auto-mechanic workshops [21-22], dust from paved and unpaved roadside [12, 18], soil samples from devel- oping communities [11, 13] and many more. In the present study, assessment of heavy metals in surface soils of a Nigerian university was considered. This assessment is important because a university can be characterized by many other activities that can induce heavy metals contaminations into the environment apart from the normal academic activi- ties. Machines workshop which comprises of welding section, automobile section, lathe machine section and other machine tools sections are prime sources of trace metals contamination in university environment. Emissions from power generating sets and the maintenance of these sets are also major contrib- utors to heavy metal pollution in universities where electric power generating sets are installed as alternative power sup- ply. Other contributors to heavy metals pollution in a university environment include the activities from; automobile transport pools [23], building construction sites, university petrol station, and university central works department. Despite the significance of the discussed activities to heavy metals contamination level within a university, little or no work has been done on the assessment of heavy metals in university environment. Therefore, this research work aimed at assessing the contamination level of Mn, Pb, Cr, Cu and Zn in surface soils of ABUAD, and the specific objectives are to; (1) estab- lish the concentrations of the selected metals in surface soil of ABUAD, (2) identify the source and contributions of the se- lected metals to the contamination level of ABUAD soils, and (3) evaluate the contamination and risk level of the metals us- ing enrichment factor (EF), geo-accumulation index (Igeo), po- tential ecological risk index (RI), pollution index (PI) and in- tegrated pollution load index (IPI). This is to detect areas that need special attention and to suggest appropriate control mea- sures. 2. Materials and methods 2.1. Study area Afe Babalola University (ABUAD) was considered for the current research work. ABAUD is located in Ado-Ekiti, Ekiti State, southwestern Nigeria (Fig. 1) The citadel of learning is located between latitude 07◦35’59”and 36’50”N, and longitude 05◦18’0”and 18’45”E. The geographical area is characterized by relatively low relief with dome-shaped isolated hills and in- serbergs. The institution has over 8,500 students across all the colleges in the university and workforce of about 1000 staff. The university community consist of many strategic places such as; residential apartments for staff and students, academic and administrative buildings, research centre, planetarium, petrol station, supermarkets, bakery, water production plant, restau- rants, banks, ATM points, the university works department, sports pavilion, college of engineering central workshop and guest house. 2 Lala et al. / J. Nig. Soc. Phys. Sci. 4 (2022) 887 3 Figure 1. Study area (a) Map of Nigeria (b) Map of Ekiti state showing ABAUD (c) Sampling locations within ABUAD 2.2. Soil sampling Twenty four (24) soil samples taken at a depth of about 0 to15 cm of the earth surface were collected using a standard soil auger [24] from ten (10) different main functional sites in ABUAD. Two (2) control samples were also taken from an un- developed site within ABUAD. This is between the university premises and the university farm. Samples were collected in duplicates from each site except site 9 where 4 samples were collected. Four (4) samples were collected from site 9 because the site comprises of more activities. As shown in Table 1, the sampling sites were considered based on different activities that can induce heavy metal contamination into the environment. To avoid further contamination other than the ones from the sam- pling site, collected soil samples were kept in clean nylon and taken directly to laboratory for analysis. 2.3. Sample preparation and analysis Debris and all other foreign materials were manually re- moved from the soil samples, afterwards the samples were dried and reduced to about 1.18 mm soil particle size. To determine the selected metals concentration, 1 g from each dried samples were digested in standard Erlenmeyer flask using 12 mL aqua- regia solution. The solution was prepared at a ratio of 1:3 of HNO3 to HCl [11, 21]. The beaker was covered and the con- tents were heated for 2 hr using medium hot plate heat [11, 21]. After heating, the mixture was left to cool down naturally and 3 Lala et al. / J. Nig. Soc. Phys. Sci. 4 (2022) 887 4 subsequently filtered using a Whatman No. 42 filter paper. The filtrate was diluted to 50 mL with de-ionized distilled water [21, 25]. These solutions were further analyzed for the selected met- als concentration using AA320N atomic absorption spectropho- tometer. To minimize error, all soil samples were analysed in triplicate. During the analysis, standards and blanks were run to ensure 95% reliability of the machine [11]. 2.4. Descriptive statistics analysis The concentration and distribution of the selected metals in ABUAD soil samples were investigated using statistical anal- ysis. The quantified data where analysed using Microsoft Ex- cel software to obtain mean, standard deviation, standard error, sample variation, minimum and maximum values. Also, prin- cipal component analysis (PCA) was carried out with the aid of XLSTAT software. This was used for source identification and contributions of the selected metals to the contamination level of ABUAD soils. 2.5. Contamination and risk assessment Contamination and risk assessment levels for this study were analysed using the following indices; 1. Enrichment factor (EF) The enrichment factor (EF) is a relatively straightforward and simple tool used for evaluating the extent of soils contamination and to compare the contamination of dif- ferent environmental media. It involves a universal method for calculating degree of soil enrichment by dividing the ratio of a particular metal and normalizing element by the ratio of the same metals found in a baseline and normal- izing element [13, 26, 27]. This can be computed using Equation 1. EF = (Trace metal/Fe)S oil sample (Trace metal/Fe)Natural background (1) where (Trace metal/Fe)Soil sample= ratio of heavy metal to Fe in the soil sample taken from the selected site, and (Trace metal/Fe)Natural background= ratio of heavy metal to Fe in the soil sample taken from the control site. Similar to Ololade [22], the normalizer used for this work was Fe. This is because Nigeria soils are rich in Fe [28- 29], and also due to its conservative nature during diagen- esis [30]. For the background values, the average concen- trations of metals detected in control site were used ac- cording to the approach given by Benhaddya and Hadjel [13]. EF values of unity or very close to unity shows that the heavy metal originated from natural sources. Values not up to 1.0 signify depletion or mobilization of trace metals, and values more than 1.0 implies that the trace metal is from an anthropogenic source [22, 31]. Val- ues greater than 1.0 are further interpreted and classified into different categories according to Birth [32], these in- clude; no enrichment if EF is < 1, minor enrichment if EF is < 3, moderate enrichment if EF is from 3 to 5, mod- erate severe enrichment if EF is from 5 to 10, severe en- richment if EF if from 10 to 25, very severe enrichment if EF if from 25 to 50, and extremely severe enrichment if EF is > 50. 2. Geo-accumulation index (Igeo) Igeo index estimates contamination level by comparing present and the preindustrial concentrations level [13]. In this study, Igeo was also used to evaluate the contami- nation level of ABAUD soils by employing Equation 2 proposed by Muller [33]. Igeo = log2 ( Cm 1.5 x Cb ) (2) Cm and Cb = trace metals concentration in soil samples and natural background respectively. The constant value 1.5 is a feasible alteration reference value to reduce the effect of possible variation in the background value. Lev- els of contamination are classified as; unpolluted for Igeo ≤ 0, unpolluted to moderately polluted for Igeo between (0–1), moderately polluted for Igeo between (1–2), mod- erately to strongly polluted for Igeo between (2–3), strongly polluted for Igeo between (3–4), strongly to very strongly polluted for Igeo between (4–5) and very strongly pol- luted for Igeo = 5. 3. Potential ecological risk index (RI) This risk index (RI) was used to evaluate the ecological risk of trace metal contamination in soils by considering metals toxicity and the response to the environment. This is given by Equations 3, 4 and 5, and was originally given by Hakanson in 1980 [13, 34]. RI = ∑ Ei (3) Ei = Ti ∗ fi (4) fi = Ci/Bi (5) Ei is the potential ecological risk factor, fi is the pollu- tion factor for metals, Ci is the concentration of metals in soil, Bi is the natural background value of metals and Ti is metal toxic factor. As given by Duodu et al.,[35]; the value of Ti for Mn and Zn = 1, Cr = 2, & Cu and Pb =5 [34, 35]. The four (4) categories of RI used in this study are; RI ≤ 50 for low contamination, 50 < RI ≤ 100 for moderated contamination, 100 < RI ≤ 200 for consider- able contamination, and RI > 200 for high contamination. 4. Pollution index (PI) and integrated pollution load in- dex (IPI) These important indexes assess the contamination level of heavy metals in soils for each metal and total metals under consideration respectively. According to Chen et al, 2005 [15], PI is evaluated as the ratio of the concen- tration of each metal to the background value of the cor- responding metal. This is given in Equation 6, where Cm is the measured concentration of each heavy metal, and Cb is the corresponding background value which is taken in this study as the mean concentrations of the cor- responding heavy metal in unaffected soils (control site). 4 Lala et al. / J. Nig. Soc. Phys. Sci. 4 (2022) 887 5 Table 1. Sampling site and the associated activities Site Activity AB1 Mainly residential staff quarters AB2 Installed and functioning university central power generating set AB3 Installed and functioning staff quarter’s power generating set AB4 College of Social & management sciences/college of engineering transport pool AB5 Senate building transport pool and new building construction site AB6 College of engineering central workshop which comprises of welding section, automobile section, lathe machine section and other machine tools sections AB7 University central works department which comprises of welding section, auto-mechanic’s section, vulcanizing section, plumbing sec- tion, etc. AB8 University filling station AB9 Various business activities such as restaurant and cafeteria, supermar- ket, printing press, pure water factory, barbecue and other outdoor roasted food spots AB10 Barbecue fish, meat, fried yam and other outdoor roasted food spots AB11 Control site not shown on the Map The contamination level for each metal can be catego- rized as; low, medium and high contamination when PI ≤ 1, 1 < PI ≤ 3, and PI > 3 respectively [13, 15]. PI = Cm Cb (6) IPI as a criterion for evaluating soil pollution can be esti- mated as the mean PI of all estimated heavy metals. It can be categorized as; extremely high pollution level, high pollution level, moderate pollution level and low pollu- tion level when IPI > 5, 2 < IPI ≤ 5, 1 < IPI ≤ 2 and IPI ≤ 1 respectively. 3. Results and discussion Descriptive statistics of Cr, Cu, Zn, Pb and Mn detected in the soil of the studied university are given in Table 3. The Table also presents World Health Organization (WHO) and Standard Guidelines in Europe limits for trace metals in soils [36]. Table 2 presents the mean values for all the sampling sites. Minimum and maximum concentration of Cr, Cu, Zn, Pb and Mn were 0.2 & 1.75, 0.39 & 1.11, 0.02 & 0.70, 0.03 & 9.40, and 0.09 & 1.03 mg/g respectively, and their mean concentrations were 0.75, 0.66, 0.36, 1.37, and 0.49 respectively. The mean concen- tration of the considered heavy metals in the university soil fol- low the trend of Pb > Cr > Cu > Mn > Zn. The average concen- tration of Zn (0.36 mg/g) was found to be slightly higher than the permissible limit while Mn (0.49 mg/g) was below the limit. Average concentration of Cr (0.75 mg/g), Cu (0.66 mg/g), and Pb (1.37 mg/g) were found to be more than the limit. This may be attributed to the effects from different human activities or the high nature of the corresponding natural background value [11, 36]. Considering the average concentration of heavy metals and their corresponding natural background value, Mn concentra- tions was comparable, where Cr, Cu, Zn and Pb concentration were more than the natural background value. They were ap- proximately of the ratio 1:7, 1:2, 1:3 and 1:2 respectively. The standard deviation and standard error for Cu, Zn, Cr and Mn were high while value of Pb was very high. This showed that the concentration of the heavy metals varied greatly across the university and this may be attributed to non-uniform dispersion in the soil [11, 37]. Cr and Pb showed high sample variation and this indicated high human influence on the concentrations [11, 38]. Furthermore, the mean concentration of metals reported in this study was generally higher than those detected in soils from some urban and industrialized areas such as Hassi Messaoud in Algeria; Bangkok in Thailand; Madrid in Spain; Hong Kong in China etc. Concentration of Cu, Pb and Zn in Hassi Messaoud (0.01317, 0.13097 and 0.061 mg/g) [11], Bangkok (0.0417, 0.0478 and 0.118 mg/g) [39], Madrid (0.072, 0.161 and 0.21 mg/g) [40] and Hong Kong (0.0233, 0.0946 and 0.125) [41] were low com- pared to 0.66, 1.37 and 0.36 mg/g for this study. This may be as a result of the high natural background value of metals in the soil of the present study area [11]. Also, this may be asso- ciated with the nature of the activities taken place in ABUAD. The university has automobile workshop and machines work- shop which are constantly in use for training purposed. Thus, generating related heavy metals contamination. Moreover, comparing results from the present study with the assessment of metal contamination in sediment samples col- lected from Lagos dockyard harbour by Basheeru et al [42], the contamination level of lagoon sediment with lead and cop- per is higher compared to the contamination level of ABUAD soils. In another work carried out by some researchers on estu- ary sediments from Olonkoro river, Oyo state, Nigeria [43], it was found that the concentration level of Zn, Cu, Zn, and Mn were also higher. This is because different industrial and do- mestic effluent are been discharged into the harbor and the river 5 Lala et al. / J. Nig. Soc. Phys. Sci. 4 (2022) 887 6 Table 2. Average values of selected trace metals at each sampling site Sampling point Heavy metal concentrations (mg/g) Cr Cu Zn Pb Mn AB1 0.73+0.04 0.70+0.01 0.13+0.03 2.65+0.15 0.84+0.05 AB2 0.42+0.22 0.92+0.19 0.24+0.23 2.02+0.38 0.63+0.21 AB3 1.33+0.42 0.58+0.06 0.28+0.10 1.02+0.58 0.38+0.16 AB4 0.31+0.07 0.42+0.03 0.45+0.26 5.26+4.13 0.76+0.14 AB5 0.72+0.02 0.68+0.29 0.28+0.09 0.38+0.09 0.29+0.04 AB6 0.65+0.05 0.48+0.04 0.41+0.07 0.06+0.04 0.19+0.01 AB7 0.77+0.57 0.74+0.18 0.19+0.05 0.23+0.05 0.41+0.32 AB8 0.74+0.38 0.65+0.13 0.52+0.02 1.13+0.38 0.49+0.01 AB9 0.77+0.23 0.59+0.07 0.42+0.20 0.49+0.15 0.65+0.29 AB10 1.05+0.07 0.94+0.05 0.63+0.05 1.28+0.05 0.10+0.01 Control site 0.32+0.22 0.46+0.12 0.12+0.00 1.12+0.36 0.41+0.01 Limits 0.100 0.100 0.300 0.100 2.000 Table 3. Descriptive statistical analysis of selected trace metals in ABUAD soil S/N Data analysis Concentrations (mg/g) Cr Cu Zn Pb Mn 1 Mean 0.75 0.66 0.36 1.37 0.49 2 Minimum 0.20 0.39 0.02 0.03 0.09 3 Maximum 1.75 1.11 0.70 9.40 1.03 4 SE 0.08 0.04 0.04 0.42 0.06 5 SD 0.38 0.21 0.21 1.97 0.30 6 SV 0.15 0.04 0.04 3.88 0.09 Control value 0.32 0.46 0.12 1.12 0.41 Permissible limit 0.10 0.10 0.30 0.10 2.00 SV sample variation, SD standard deviation, SE standard error thereby contributing to their higher heavy metal level. 3.1. Heavy metal contents in different sampling sites As given in Table 2, the average concentrations of Cu and Zn in different functional areas were more than their corre- sponding natural background value except Cu detected in site AB4. This is similar to the result obtained for soils in Hassi Messaoud, Algeria [11]. The average concentrations of Cr from different sites were also higher compared to their natural back- ground value except for site AB4 which was lower, and site AB2 which was comparable to the background value. Also, the average concentrations of Mn were comparable to the natu- ral background value in sites AB3 and AB7, lower in sites AB5, AB6 and AB10, and higher in all other sampling sites. Pb mean concentrations were below the natural value except for the res- idential area (AB1), the university central power generating set area (AB2), transport pool (AB4) and site AB10. The study area is characterized by high automobiles and power generating sets, and the trace metals such as Mn, Pb, Cu, Cr and Zn selected for consideration in the present study are reported to be present as additives in lubricants and gaso- line [22, 44]. Also, Pb, Cu and Zn are reported to be present in vehicular emissions, tires, wires, alloys, brake parts, etc. [18, 45-52]. Copper (Cu) present in soils from all sampling sites were higher than the natural background value (0.46 mg/g) except site AB4 which is comparable to the background value. The average concentrations ranged from 0.42 mg/g in site AB4 to 0.94 mg/g in site AB10. These were all higher than the per- missible limit (0.1 mg/g) and may be attributed to the higher natural background value. Also, it is notable that electrical and electronic parts of automobile wastes and alloys from corrod- ing metal parts that have possibly leached into the soil of these various sites can be attributed to the high Cu present [53]. Average values of Pb in soils from sampling site AB1 (2.65 mg/g), AB2 (2.02 mg/g), AB4 (5.26 mg/g) and AB10 (1.28 mg/g) were notably higher compared to the corresponding back- ground value (1.12 mg/g). This suggested that combustion en- gine emissions, spill waste oils and expired motor batteries from the high number of automobiles that cluster site AB1, AB4 and AB2 can be responsible for the high Pb concentration in these areas. This is similar to the result obtained for a study carried out by a group of researchers in Ilorin, Nigeria [54]. In the study, Pb concentration was higher compared to Cu and Cd. Higher Pb level in the study was suggested to have been influ- enced by traffic volume and exhaust from motor vehicles. The mean Zn content in all soils from different sites ranged from 0.13 mg/g in site AB1 to 0.63 mg/g in site AB10. These were all greater than the natural background value (0.12 mg/g). 6 Lala et al. / J. Nig. Soc. Phys. Sci. 4 (2022) 887 7 Also, average values from sites AB4, AB6, AB8, AB9 and AB10 were more than the given limit. This indicated that the activities from the different functional areas such as automo- biles, machines workshops, petrol station and others are respon- sible for the high Zn content. Cr concentrations at different sites ranged from 0.31 mg/g in site AB4 to 1.33 mg/g in site AB3. The values were all higher than the permissible limit of Cr and were also more than the natural value (0.32 mg/g) except site AB4 which is compara- ble to the background value. The low level of Cr in site AB4 suggested that Cr emissions were not much from the transport pool since the vehicles were always packed without any emis- sion during the working hours and also the pool is a paved area, while high Cr concentration in other areas indicated the effects of anthropogenic activities in such areas. Mn detected in all sampling sites was lower in concentra- tion compared to its permissible limit. However some areas like AB1, AB2, AB4, AB8 and AB9 shows higher Mn content compared to the natural background value. This indicated that activities from automobiles, machines workshops, power gen- erators and petrol station in these areas were responsible for the high Mn content. 3.2. Source identification Principal component analysis (PCA), a multivariate recep- tor model analysis is applicable for contamination sources iden- tification [55-56]. XLSTAT, a statistical software for Microsoft Excel was used in the present study for the source identifica- tion and contributions of the selected metals to the contamina- tion level of ABUAD soils. Typical PCA score plot will have variables with the similar source located close to each other, while those with divergent sources will be far apart [57]. Fig- ure 2 shows the PCA variable plot with a cumulative variance of 75.66% where factor 1 (F1) accounts for 45.60% and factor 2 (F2) 30.06% of the total variance. Variables that are close to each other and far from the centre as shown in Figure 2 are con- sidered to be significantly positively correlated. Also, variables located on opposite sides are significantly negatively correlated and those located orthogonally are considered not correlated. Also, Figure 2 shows that there is proximity between sam- ples taken from the same site, such as samples taken within sites AB4, AB5, AB6, AB8 and AB10. This inferred that the contaminations within these sites were from the same source. There is low proximity for samples taken within sites AB3 and AB7 which implies that the contaminations on these sites may be from different sources. This is evident from the composi- tion of the areas. Site AB7 comprises of welding workshop, auto-mechanic workshop, vulcanizing workshop and plumber workshop, and site AB3 which has functional power generat- ing set installed on it is not too far from site AB7. Four samples were taken from site AB9 where some have proximity and some do not. This is because the site has various business activities and production plants such as restaurants and cafeterias, super- markets, printing press, pure water factory, barbecue and other outdoor roasted food spots. Therefore the result on the PCA variable plot implies that site with similar human activity has a single source of heavy Figure 2. Variable plot for PCA Figure 3. Observation plot of PCA indicating the positions of Cr, Cu, Pb, Zn and Mn metals while sites with various human activities have different sources of heavy metal contaminations. The PCA observation plot given in Figure 3 shows no cluster between the five se- lected heavy metals. This indicates that the heavy metals con- 7 Lala et al. / J. Nig. Soc. Phys. Sci. 4 (2022) 887 8 tamination originated from more than a single source, and these include automobiles, generators, petrol station, machine work- shops, central works departments, production plants and other business activities. 3.3. Pollution assessment 1. Enrichment factors (EF) Enrichment factors (EFs) of Cu, Cr, Pb, Zn and Mn were considered to assess ABUAD soils contamination level (Fig. 4). The average EF of Cu (0.89), Pb (0.76) and Mn (0.73) were found to be less than one (1), while Cr (1.47) and Zn (1.82) were found slightly greater than one (1). This inferred no enrichment for Cu, Pb and Mn, and minor enrichment for Cr and Zn. Cr enrichment factor ranges from 0.56 to 3.12, Cu from 0.59 to 1.63, Zn from 0.67 to 4.34, Pb from 0.04 to 3.07 and Mn from 0.11 to 2.00. This result shows no enrichment or moderate enrichment for Cr, no enrichment or minor enrichment for Cu, no enrichment or moderate enrichment for Zn, no enrichment or moderate enrichment for Pb and no en- richment or minor enrichment for Mn. Site AB9 which comprises various business centres and production plants has Zn (4.34) as the metal with the highest enrichment. 2. Geo-accumulation index (Igeo) Igeo index was considered to estimate the ABUAD soils contamination level by comparing the preindustrial and present concentrations of heavy metals [13]. Figure 5 shows that the Igeo of all the selected metals in ABUAD soils does not exceed moderately polluted on an average level. Average Igeo of Cu (-0.07), Pb (-0.29) and Mn (- 0.35) indicated unpolluted while Cr (0.65) and Zn (0.97) indicated moderately polluted. The highest Igeo value obtained in the present study is for Zn (1.77). This was detected on site AB10 which majorly comprises of Bar- becue fish, meat, fried yam and other open roasted food spots. The findings from Igeo are in agreement with the EF values showing that the sampled environment is not highly contaminated. 3. Potential ecological risk index (RI) Ecological risk of the selected trace metal in ABUAD soils was assessed. Table 4 gives the risk index for the contamination caused by Cr, Cu, Pb, Zn and Mn in all sampled ABUAD soils as low contamination. This indi- cated that ABUAD soils may not be too sensitive to heavy metals contamination and the contamination level posed a low potential ecological risk. This is also in agreement with EI and Igeo assessments, showing that the sampled environment has a low level of contamination. 4. Pollution index (PI) and integrated pollution load in- dex (IPI) Contamination level of ABUAD soils was also assessed using pollution index (PI) and integrated pollution load index (IPI). The summarized results are presented in Ta- ble 5. PI of Cr ranged from 0.99 to 4.18 and showed low contamination to high contamination. The given mean PI of 2.36 indicated medium Cr contamination of ABUAD Figure 4. Enrichment factors for metals Figure 5. Geo-accumulation index (Igeo) soil. The highest PI of Cr was detected on site AB4 and this inferred possible contamination from gasoline and lubricant leakages from vehicles that dominated the area. A similar trend as noticed for Cr was also seen in Zn and Pb. The highest PI of 5.12 for Zn and 4.72 for Pb were detected on site AB10 and AB4 respectively and indi- cated high contamination. The high content of Zn and Pb in sites AB10 and AB4 respectively may be linked to the effect of activities in these areas. PI of Cu and Mn showed a similar trend. Their PI ranged from low contamination to medium contamination, and informa- tion on their average PI indicated medium contamination of ABUAD soils. Considering the IPI assessment, the mean value of 1.83 indicated a moderate pollution level of ABUAD soils. Signals were also given that sites AB4 and AB10 have high pollution levels. This is similar to the PI assessment of some heavy metals in these same locations. 8 Lala et al. / J. Nig. Soc. Phys. Sci. 4 (2022) 887 9 Table 4. Potential ecological risk indexes for heavy metals in ABUAD soils Sampling point Ei RI Pollution degree Cr Cu Zn Pb Mn AB1 4.59 7.59 1.07 11.89 2.02 27.15 Low AB2 2.63 9.97 1.99 9.03 1.52 25.14 Low AB3 8.36 6.24 2.26 4.58 0.91 22.36 Low AB4 1.98 4.53 3.64 23.58 1.84 35.56 Low AB5 4.54 7.33 2.26 1.68 0.70 16.51 Low AB6 4.09 5.24 3.33 0.29 0.46 13.40 Low AB7 4.81 8.02 1.55 1.05 0.98 16.41 Low AB8 4.68 7.02 4.24 5.07 1.18 22.18 Low AB9 4.81 6.36 3.39 2.21 1.56 18.33 Low AB10 6.62 10.18 5.12 5.72 0.23 27.86 Low Table 5. PI and IPI of heavy metals in ABUAD soil Heavy metal PI IPI Min Max Mean Min Max Mean Cr 0.99 4.18 2.36 Cu 0.91 2.04 1.45 Zn 1.07 5.12 2.88 1.35 2.42 1.83 Pb 0.06 4.72 1.30 Mn 0.23 2.02 1.14 4. Conclusion Various assessment methods and tools were used to evaluate trace metals contamination levels of ABUAD soil. Twenty four (24) soil samples taken at a depth of about 0 to15 cm of the earth surface were collected using a standard soil auger from ten (10) different main functional sites, and were analyzed for Cu, Cr, Pb, Mn and Zn. Control samples were taken from an undeveloped area within ABUAD. These were also analyzed and served as natural background to the corresponding heavy metals collected from the different functional areas within the university. The minimum and maximum concentration of Cr, Cu, Zn, Pb and Mn were 0.2 and 1.75, 0.39 and 1.11, 0.02 and 0.70, 0.03 and 9.40, and 0.09 and 1.03 mg/g respectively, and the mean concentrations were 0.75, 0.66, 0.36, 1.37, and 0.49 mg/g respectively. Mn average concentration in ABUAD soil was comparable to natural background value; however Cr, Cu, Zn and Pb were higher than their corresponding background value and approximately of the ratio 1:7, 1:2, 1:3 and 1:2 re- spectively. The multivariate statistical analyses indicated that staff and administrative vehicles, power generating sets, petrol station, machine workshops, central works department, production plants and various outdoor roasted food spots activities were the main sources of metal contamination. The results of EF, Igeo, RI, PI and IPI showed that the contamination level of ABUAD soil can be generally classified as low or moderately contaminated. Also, according to some of the indices, contamination attributed to Zn and Pb were found to be slightly high in sites AB4, AB9 and AB10. This can be linked to possible contamination from gasoline and lubricant leakages from vehicles that dominated site AB4, and various outdoor roasted food spots together with the production plants located in site AB10 and AB9 respec- tively. The present study considered a university which is a com- munity that is usually associated with a high number of peo- ple. Contamination of university soils by trace metals is of great risks and hazards to the immediate ecosystem if not prop- erly handled. Exposure to heavy metals is usually by; der- mal contact with suspended dust and soil particles and inhala- tion/ingestion absorption pathways. Therefore, periodic assess- ment of the sources and associated ecological risks of the heavy metals is highly recommended. This is to enable decision- makers to effectively manage the environment in the manner that will preserve public and ecosystem health. Acknowledgments We thank the referees for the positive enlightening com- ments and suggestions, which have greatly helped us in making improvements to this paper. References [1] P. B. Tchounwou, C. G. Yedjou, A. K. Patlolla & D. J. Sutton, “Heavy metals toxicity and the environment”, NIH-RCMI Center for Environ- mental Health, College of Science, Engineering and Technology, EXS. 101 (2014) 133, https://dx.doi.org/10.1007/978-3-7643-8340-4 6. 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