Appraising the impact of automobile mechanic workshop activities on the soil’s heavy metals contamination level in Isoko Community, Niger Delta region of Nigeria

doi:10.21203/rs.3.rs-3304408/v1

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Appraising the impact of automobile mechanic workshop activities on the soil’s heavy metals contamination level in Isoko Community, Niger Delta region of Nigeria

https://doi.org/10.21203/rs.3.rs-3304408/v1

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There is increasing concern on environmental pollution caused by anthropogenic actions. This research was aimed at evaluating the effect of leachates from vehicle mechanic workshops, on the soil’s heavy metals pollution level. A total of 20 soil samples (10 topsoil and 10 subsoil) were collected from 9 active clusters of automobile mechanic workshops, and a reference site. Eight heavy metals – cadmium “Cd”, chromium “Cr”, copper “Cu, iron “Fe”, lead “Pb”, manganese “Mn”, nickel “Ni” and zinc “Zn”- concentration were measured in the soil samples in accordance with ASTM International standard. Thereafter these pollution indices – contamination factor (CF), single pollution index (SPI) and pollution load index (PLI) were used to evaluate the degree of heavy metals pollution in the region’s soil. The results revealed that the mean Cd, Cr, Cu, Fe, Pb, Mn, Ni and Zn concentration in the topsoil samples was 0.172 mg/kg, 0.36 mg/kg, 0.64 mg/kg, 159.40 mg/kg, 0.415 mg/kg, 1.39 mg/kg, 0.745 mg/kg and 2.184 mg/kg respectively. While the Cd, Cr, Cu, Fe, Pb, Mn, Ni and Zn content in the subsoil was 0.139 mg/kg, 0.274 mg/kg, 0.462 mg/kg, 138.90 mg/kg, 0.349 mg/kg, 1.144 mg/kg, 0.586 mg/kg and 1.793 mg/kg respectively. Furthermore, the pollution indices results indicated that the soil had low level of heavy metals contamination, and can be considered safe for plants and animals. Accumulation of toxic metals in the soil is a major environmental threat; therefore there is need to monitor the activities of automobile mechanics in Nigeria by environmental protection agencies.

Heavy metals

pollution indices

soil health

spatial distribution

vehicle mechanic

Land management has become a major concern to environmentalist, as the soil usually acts as a natural storage medium for both harmful and harmless substances (Darma et al. 2022). Soil pollution typically results from the discharge of harmful materials into the soil either through anthropogenic actions or atmospheric deposition. Some of the anthropogenic actions that are liable for land pollution are organic and inorganic oil spill, effluents from solid wastes, leachates from decomposing agricultural materials and agro-chemicals, metals mining activities, discharge from vehicle maintenance workshop and industrial waste discharge. Though there are several pollution forms, land and water are considered to be the most common types in many ecosystems. According to Zhang et al. (2018), human induced actions usually produce numerous toxic substances which can cause serious harm to the soil, plants and animals. Uguru et al. (2021) stated that the geotechnical and mechanical properties of soil are greatly influenced by heavy metals concentration levels and their distribution pattern.

Heavy metals (manganese “Mn”, copper “Cu”, zinc “Zn”, lead “Pb”, cadmium “Cd”, and chromium “Cr”) accumulation in the environment is major constituent of soil pollution, which can be linked directly to effluent discharge from vehicle maintenance workshops. These heavy elements have persistent nature; thus, they can easily accumulate in the ecosystems, which could be harmful to humans, other living organisms, and the entire environment (Udousoro et al., 2010; Adelekan and Abegunde, 2011). Additionally, Ekeocha et al. (2017) started that these heavy metals pollution is not limited to the soil, but contribute massively to air and water pollution; thus its accumulation in the environment should be constantly monitored. The occurrence of heavy metals in wastes leachate is responsible for the pollution of soil and water bodies. The accumulation level of heavy metals in the soil is a factor of the concentration of heavy metals in the leachate discharged into the environment, the prevailing environmental condition and the soils’ physical characteristics (Ghosh et al., 2017; Vongdala et al., 2019). Vongdala et al. (2019) stated that the heavy metal pollution rate in the environment is directly proportional to the concentration of the heavy metal in the leachate; while high soil moisture content tends to facilitate the leaching rate of the heavy metal in the soil.

Rapid population growth has led to speedy industrialization and anthropogenic pollution are liable for several complications to human and environmental health; thus, creating serious imbalance in the ecological resources. According to Adewoyin et al. (2013), human actions are the major causes of environmental pollution, which interred negatively with the ecosystems activities, leading to severe environmental degradation and human health impediments. Although several studies have been conducted on the effect of automobile maintenance workshop (Ipeaiyeda and Dawodu, 2008; Adelekan and Abegunde, 2011; Rabe et al., 2018), there is still information dearth on the impact of emissions from small clusters artisan’s workshop on the land resources in Nigeria, particularly the Isoko area of Delta State. Therefore, this study is aimed at assessing the impact of leachates from artisan’s vehicle mechanic workshops on the soil quality (heavy metals pollution), and spatial distribution of the heavy metals in Ozoro municipal area of Nigeria.

2.1 Study area

This study was carried out at Ozoro (latitude 5^o31ʹ11.99ʺ to 5^o34ʹ9.29ʺ N, and longitude 6^o11ʹ58.19 ʺ to 6^o15ʹ33.12ʺ E), a major district of Nigeria with a population of about 100,000 people (Uguru et al., 2020). Ozoro experiences high rainfall – about 1800 mm per annual - with biomodal pattern, and mean temperature of approximately 29⁰C. The region vegetation is mainly the topical forest type, and alluvial topsoil with moderate infiltration rate (Eboibi et al., 2018).

Resulting from lack of proper regional planning, there are numerous colonies of artisans’ vehicle maintenance workshops in the community. Most of these workshops are sited close to open drainages and residential buildings; and wastes generated by these artisans are discarded untreated into the environment. All the auto-mechanic workshops visited lack basic social amenities and safety facilities; and were littered with unserviceable vehicles at various deplorable stages (Figurer 1). There are 15 legally registered vehicle mechanic shops, which spread uniformly across Ozoro municipal area.

2.2 Sample collection

Soil samples were taken from 10 major vehicle mechanic workshops. At each workshop, two samples – topsoil (0–20 cm) and subsoil (20–50 cm) were collected. To effectively evaluate the impact of the discharges from these workshops on the environment, another point (with co-ordinates − 5⁰33ʹ44.41ʺ N and 6⁰14ʹ57.13ʺ E) about 2 km from the sampled locations was chosen as the reference (control) point. The control area was from free from artisans’ activities, has natural vegetation and has no recorded history of oil spills. The geographical location of the sampling points was determined through the use of a Global Positioning System (GPS). The satellite image of the sampling locations is presented in Fig. 2. In each soil profile, three soil samples were collected. Each soil sample was poured into a black polyethylene, and bag immediately transported to the laboratory of the Delta State University of Science and Technology Ozoro, for further analysis.

2.3 Determination of the heavy metals in the soil samples

In the laboratory, the soil samples were dried under ambient temperature 26 ± 4⁰C for 14 days. Thereafter, the dried soil was crushed with a laboratory mortar and pestle, and sieved in a 2 mm gauge nylon sieve (Hussein et al., 2021). The sieved soil was then digested with two acids (H₂SO4, HNO₃) mixture, at a temperature of 90⁰C in a water bath until a clear solution was achieved (Cao et al., 2010). The solution was thereafter filtered into a measuring beaker, and diluted with distilled water to a volume of 100 mL. Then the heavy metal (Cd, Cr, Cr, Fe, Pb, Mn, Ni and Zn) concentration level in each digested soil sample was measured by using the Atomic Absorption Spectrometer (AAS).

2.4 Soil heavy metal pollution evaluation

Contamination factor (CF)

This pollution index was used to access heavy metals contamination degree in the soil. It is calculated through the expression presented in Eq. 1.

\(CF= \frac{{C}_{c}}{{C}_{x}}\) 1

Where Cc = concentration of the heavy metal at the spatial location, and Cx = heavy metal concentration at the reference point.

Single pollution index (SPI)

The PI is used to further confirm the pollution level of an investigated contaminated area. PI is calculated through the formula shown in Eq. 2 (Hu et al. 2017).

\(PI= \frac{{C}_{n}}{{G}_{B}}\) 2

Where Cn = heavy metal concentration in the polluted soil, and GB = threshold value of the metal.

Pollution Loading Index (PLI)

The PLI was used to access the environmental deterioration caused by the heavy metals pollution, as it is expressed in the formula presented in Eq. 3.

\(PLI= \sqrt[n]{{PI}_{1}\times {PI}_{2}\times \dots \times {PI}_{n}}\) 3

This is one of the indices used for the assessment of the degree of contamination in soil; the PLI is used also to provide an easy way to prove the deterioration of the accumulation of heavy metals. (Varol 2011)

Pollution load index (PL1) is also connected to the modified degree of contamination (MDC).

For the total assessment of the degree of contamination in soil, and is used to determine the deterioration state of the soil with respect to the accumulation of heavy metals. And contribute to an evaluation of the total HMs contamination (Kokwlska et al, 2018).

According to the relevant litratures, various models or methods have been adopted in determining the level of contamination in the soil and groundwater.

The interpretation of the pollution indices values as explained by Chen et al. (2015).

Contamination factor

CF < 1 low contamination factor

1 > CF > 3 Indicates moderate contamination factor

3 > CF > 6 Indicates considerable contamination factor

6 > CF Indicates very high contamination factor

Single pollution Index

≤ 1.0 Safety

1.0 < SPI ≤ 2.0 Slight pollution

2.0 < SPI ≤ 3.0 Mild pollution

3.0 < SPI ≤ 5.0 Moderate pollution

SPI > 5.0 Severe pollution

Pollution load index

PLI < 0 No pollution

0 > PLI > 1 Indicate low degree of pollution

1 > PLI > 2 Indicates moderate degree of pollution

2 > PLI > 4 Indicates high degree of pollution

4 > PLI > 8 Indicates very high degree of pollution

8 > PLI > 16 Indicates extremely high degree of pollution

2.5 Data analysis

All the data collected from the laboratory tests were analyzed using Microsoft Excel for Windows (Version 2010). Then the spatial distribution pattern of the heavy metals was determined through the application of the ArcGIS 10.6 software, as described by Liang et al. (2019).

3.1 Heavy metals concentration

The results of the heavy metals accumulation level in the topsoil and sub soil are presented in Table 1. It was observed that the Cd concentration in the topsoil ranged from 0.144 mg/kg to 0.199 mg/kg with mean of 0.172 mg/kg; while in the subsoil the Cd level ranges from 0.102 mg/kg to 0.163 mg/kg (mean ~ 0.139 mg/kg). The topsoil Cr content varied from 0.224 mg/kg to 0.558 mg/kg, and average value of 0.36 mg/kg; while in the subsoil, the Cr concentration varied from 0.123 mg/kg to 0.462 mg/kg (mean ~ 0.274 mg/kg). Also, the Cu content in the topsoil varied from 0.445 mg/kg to 0.832 mg/kg (mean ~ 0.64 mg/kg); while the Cu level in the subsoil lies between 0.315 mg/kg and 0.595 mg/kg (mean ~ 0.462 mg/kg). The topsoil Fe concentration varied between 121.60 mg/kg and 343.50 mg/kg (average ~ 159.40); while the Fe level in the subsoil ranged from 114.80 mg/kg − 253.10 mg/kg (average ~ 138.90 mg/kg). Additionally, the Pb content of the topsoil lies between 0.316 mg/kg and 0.591 mg/kg (mean 0.415 mg/kg); and the subsoil Pb concentration varied from 0.258 mg/kg − 0.522 mg/kg (mean ~ 0.349 mg/kg). It was detected that the topsoil Mn content ranged between 1.004 mg/kg and 1.994 mg/kg (mean ~ 1.378 mg/kg); and the subsoil Mn concentration varied from 0.885 mg/kg − 1.518 mg/kg (average ~ 1.144 mg/kg). Furthermore, the results shows that the Ni content of the topsoil varied from 0.445 mg/kg − 1.121 mg/kg (mean ~ 0.745 mg/kg), and in the subsoil the Ni level lies between 0.395 mg/kg and 1.005 mg/kg (mean ~ 0.586 mg/kg). Then as for Zn, its concentration in the topsoil ranged from 1.877 mg/kg − 2.553 mg/kg (average ~ 2.184 mg/kg); and its content in the subsoil varied between 1.158 mg/kg and 2.112 mg/kg (mean ~ 1.793 mg/kg). These results are in conformity with Onianwa and Fakayoda (2000) reports which stated that automobile activities caused substantial increment in Zn, Cd, Pb and Ni concentration in the soil

The results further depicted that the concentration level of the metals at the topsoil was higher than the metals accumulation level recorded at the subsoil. This situation could be possibly caused by the higher concentration and amount of leachates the topsoil received, when compared to the subsoil. Mohammed and Abdu (2014) and Darma et al. (2022) reported similar situation of vertical variation of heavy metals concentration in soil samples collected from gold mines areas. Likewise, Ipeaiyeda and Dawodu (2008) stated that concentration of Zn, Cr and Ni declined unevenly as the soil depth increased from 0 m to 0.5 m. According to Adewumi (2020), the lower heavy metals concentration usually obtained at greater soil depth could be attributed to excessive leaching of these elements from this soil stratum.

Generally, Fe had the maximum concentration among all the heavy metals investigated, in the topsoil (159.40 mg/kg) and subsoil (138.90 mg/kg) respectively; while Cd had the minimum concentration among all the heavy metals investigated, in the topsoil (0.172 mg/kg) and subsoil (0.139 mg/kg) respectively. Interestingly, the concentration of the eight (8) heavy metals evaluated at the mechanic workshop’s topsoil and subsoil, were higher when compared to the values obtained at the reference point. This signifies that the effluent discharge from the waste generated by the artisans have significant effect on the soil’s heavy metals concentration. Similar results were obtained by Adelekan and Abegunde (2011), where the Cd, Cu, Pb, Cr and Ni concentration levels in soil samples collected from the vicinity of vehicle maintenance workshops, were considerably higher than the results corded at the reference site.

Table 1

Heavy metal accumulation level in the soil
Soil sample		Cd	Cr	Cu	Fe	Pb	Mn	Ni	Zn
Top soil	Minimum	0.144	0.224	0.445	121.60	0.316	1.004	0.445	1.877
	Maximum	0.199	0.558	0.832	343.50	0.591	1.994	1.121	2.553
	Mean	0.172	0.36	0.64	159.40	0.415	1.378	0.745	2.184
	Std Deviation	0.021	0.128	0.123	70.051	0.096	0.363	0.207	0.232
Control		0.05	0.12	0.30	118	0.25	0.88	0.29	1.30
Sub soil	Minimum	0.102	0.123	0.315	114.80	0.258	0.885	0.395	1.158
	Maximum	0.163	0.462	0.595	253.10	0.522	1.518	1.005	2.112
	Mean	0.139	0.274	0.462	138.90	0.349	1.144	0.586	1.793
	Std Deviation	0.021	0.125	0.103	43.791	0.088	0.235	0.197	0.314
Control		0.03	0.12	0.30	118	0.35	0.88	0.30	1.30
	WHO (1996)	0.8		36	30,000	85	2000	35	50

3.2 Spatial Distribution of the heavy metals in the soil

Cadmium spatial distribution

Figures 3a and 3b show the Cd distribution pattern in the soil. The variation map (Fig. 3a) shows that the degree of topsoil Cd concentration at the central part of the study area, opposed the concentration at north eastern part of the area. The highest Topsoil Cd concentration was observed at the North-eastern part of the community, while the lowest topsoil Cd level was recorded at the South-Western and North-central parts of the studied region. It was noted in the variation map that the northern part of the community tends to have higher Cd accumulation than the southern region of the community. This was contrary to the spatial distribution of Cd concentration in the subsoil. As shown in Fig. 3b, the northern region of the study area tends to have higher Cd accumulation, than the southern part of the community. Also, Fig. 3b revealed that the central part of the studied region experiences both high and low accumulation of Cd in the subsoil. It was also noted that the North-western part of the region, had moderate level of Cd concentration, which is similar to the topsoil Cd concentration level in the North-western part of the region.

Chromium spatial distribution

The spatial distribution of Cr in the topsoil and subsoil are presented in Figs. 4a and 4b. In Fig. 4b, topsoil Cr concentration increased non-evenly from the central part of the area to the boundaries of the area. The maximum topsoil Cr concentration was detected at the north eastern part of the area. Regarding the subsoil, the degree of accumulation of Cr, declined non-linearly from the eastern part to the western part of the area. Figure 4b depicted that the lowest subsoil Cr accumulation (0.224 mg/kg) was witnessed at the south-western part of the study area; while the north-eastern and south-eastern parts of the area recorded the maximum Cr concentration of 0.558 mg/kg. It was observed from the maps that the topsoil Cr distribution is similar to Cd topsoil distribution, which portrayed that both metals pollution might emitted from the same source.

Copper spatial distribution

Figures 5a and 5b revealed the spatial variation map of Cu accumulation level in the topsoil and subsoil. The topsoil (Fig. 5a) had bimodal Cu concentration – one maximum point located at the south-eastern part and the other located at the north eastern part of the area. Generally, the topsoil Cu concentration declined non-uniformly from the north-eastern part of the studied area to the south-western part if the studied region. Furthermore, the map depicted that the north-western and south-south parts of the studied region had average Cu topsoil concentration.

Regarding the subsoil (Fig. 5b), the map revealed that the highest Cu accumulation (0.595 mg/kg) was recorded at the north-central part of the area, while the lowest Cu accumulation was observed at the far north-eastern and the middle of the south-western parts of the community. Remarkably, most of the community’s subsoil has moderate Cu accumulation. The lower Cu concentration recorded at the edges of the community, could be linked to the remediation effects of the grasses growing in these parts. According to Chibuike and Obiora (2014), plants and decomposing organic materials have the ability of degrading the metals concentration in the environment (soil, air and water); hence, greatly assisting in clearing the contaminated ecosystems, and replenish the soil biochemical properties.

p> Iron spatial variation

The spatial of Fe concentration distribution in the community’s top sand sub soils are presented in Figs. 6a and 6b. The topsoil Fe variation map reveals that Fe was heavily concentrated (343.50 mg/kg) in northern part topsoil, while central part of the community recorded the least Fe concentration of 121.60 mg/kg. Figure 6a portrayed that the top soil Fe concentration declined non-linearly from the northern part of the community to the southern part of the community; though the north central part had overlapping Fe concentration. Similar to the topsoil Fe distribution pattern, the subsoil Fe concentration variation (Fig. 5b) revealed that the maximum Fe concentration was recorded at the north-eastern part of the area, while the lowest subsoil Fe content (114.80 mg/kg) was noted at the north central part of the studied area. This shows that the Fe level in the subsoil increased in a non-uniform pattern from the central part of the area to the boundaries.

Lead spatial distribution

The spatial distribution maps of Pb accumulation in the top and sub soils are presented in Figs. 7a and 7b. Figure 7a shows that Pb was visibly present in high concentration in the topsoil at the central part of the study area; while the community north-eastern part topsoil had the highest Pb concentration. The distribution of Pb across the community topsoil is similar to the pattern followed by Fe, when the concentration of the heavy metal increased non-linearly from the central to the edges of the area investigated in this research. Regarding the Pb concentration distribution in the subsoil (Fig. 7b), it was noted the variation followed similar trend as the topsoil Fe distribution. The lowest subsoil Pb content appeared at the north-central part of the area, which increased uniformly to the edges of the studied region.

Manganese spatial variation

The spatial variation of Mn concentration level in the topsoil and subsoil is presented in Figs. 8a and 8b. It was noted that the topsoil Mn concentration widely across the area (Fig. 8a); but the concentration generally decreased non-linearly from the southern part of the studied area to the northern part of the area investigated. The maximum and minimum Mn concentration was both recorded at the central part of the area. Apart from the central part of the investigated area, high accumulation of Mn was recoded in two other locations – one at the far north eastern part of the area, and the point was located at the south western part of the area. Likewise, the subsoil (Fig. 8b) Mn concentration distribution pattern was similar the variation observed in the topsoil. The Mn concentration was scanty in the northern region subsoil, while the south-eastern region of the area recorded high Mn accumulation.

Nickel spatial distribution

The spatial distribution map of Ni concentration in the top and sub soils are presented in Figs. 9a and 9b. As portrayed by the results, the highest Ni content in the top and sub soils was at the south eastern part of the study area. It was observed that large proportion of the topsoil has fairly high Ni concentration; whereas as the soil depth increases to 50 cm, the concentration of this region declined considerably. Traces of Ni were present in the soil in considerable amount at the middle part of the study area, irrespective of the sampling location.

Zinc distribution

The distribution maps (Figs. 10a and 10b) revealed that the topsoil Zn concentration varied widely from the central part of the study area to the edges of the area. Interestingly, maximum and minimum Zn concentration was detected at two spots in the topsoil, which is unique from the subsoil. Furthermore, Fig. 10b revealed the study area was largely covered with moderate Zn concentration. Similar results were reported by Ipeaiyeda and Dawodu (2008), where the Zn concentration around the auto-mechanic workshops varied widely, as the soil profile depth increased from 0 cm to 50 cm.

Similar patterns of uneven distribution of soil metals concentration were observed by Atikpo and Ihimekpen (2018) and Uguru et al. (2021) for other geographical regions. In contrast, the heavy metals concentration recorded in this study were far lower than the Pb concentration level obtained by the previous authors (Uguru et al., 2021; Atikpo and Ihimekpen, 2018). The uneven variation observed among the eight metals investigated in this research, can be linked to remediation effect, the soil moisture content, pH and organic materials content (Rakesh et al., 2013).

3.3 Evaluation of the soil quality

The Heavy Metals Contamination Factor

The results of the heavy metals contamination factor are given in Table 2. As shown in Table 2, Cd recorded the highest CF values both in the topsoil and subsoil; while Fe and Pb had the lowest CF value in the topsoil and subsoil respectively. It was detected that the heavy metals follows this pattern of contamination Fe < Mn < Pb < Zn < Cu < Ni < Cr < Cd in the topsoil; while in the subsoil the CF followed this inclining trend Pb < Fe < Mn < Zn < Cu < Ni < Cr < Cd. Judging the pollution of the area’s soil based on the CF, the topsoil had moderate contamination of Cu, Fe, Pb, Mn, Ni and Zn, and considerable contamination of Cd and Cr. Then the subsoil had moderate pollution degree of Cr, Cu, Fe, Pb, Mn, Ni and Zn, and considerable pollution degree of Cd. Generally, it was noted that CF of the metals declined with increase in the soil profile; this is an indication that the subsoil is less contaminated than the topsoil. This is similar to the observations of Darma et al. (2022), during an investigation of the effect of gold mines leachates on the soil mass; when the pollution degree declined significantly with an increase in the soil depth.

Table 2

The heavy metals contamination factor
	Cd	Cr	Cu	Fe	Pb	Mn	Ni	Zn
Topsoil	3.44	3.00	2.13	1.35	1.66	1.57	2.57	1.68
Subsoil	4.63	2.28	1.54	1.18	1.00	1.30	1.95	1.38

Single pollution index

The individual pollution levels of the heavy metals among the 10 studied points are presented in Tables 3 and 4. The maximum topsoil cadmium SPI value (0.249) was located at Location C, while the lowest topsoil cadmium SPI result (0.18) was recorded at Location B. It was observed that the Cd pollution at all the sampling points was at moderate degree of pollution. Regarding the subsoil, the maximum SPI was located at Location D and the minimum SPI was observed in spatial Point B. The SPI results revealed that regardless of the sampling location, the Cd pollution at the topsoil and subsoil was at the safety level of pollution. Regarding the Cr pollution, the maximum topsoil chromium SPI value was located at Point C, while Point E had the lowest SPI value. The study findings revealed that Cr pollution at Points A, C, D and G had moderate level of Cr contamination; while Points B, E, F. H and I topsoil had mild degree of Cr pollution. With respect to the subsoil, the highest Cr SPI vale waste recorded at Point D; while Point A recorded the lowest Cr SPI value. In terms of the subsoil Cr pollution level, it can being seen form the findings (Fig. 4) that Locations C, D and G had moderate degree of Cr pollution; Locations F and H had mild level of Cr pollution; and Locations A, B, E and I had slight degree of Cr soil pollution.

Regarding the Copper pollution, the SPI values depicted that at the topsoil, the maximum and minimum SPI values were located at Points G and D respectively; while in the subsoil, the highest and lowest SFI values were detected at Locations I and H respectively. Additionally, the SPI results portrayed that Cu contamination of the area was at the safety pollution degree. It was observed that the iron SPI values was evenly distributed both in the topsoil and subsoil (the values lies between 0.004 and 0.005) across the study area, apart from Location I that recorded very high SFI values in the top and sub soil. From Tables 4 and 5, it can be realized that Fe pollution of the area topsoil and subsoil was within the safety pollution level. Similarly, the SFI values for Pb revealed that Location B had the highest pollution degree both in the topsoil and subsoil. It was also noted from the results that Pb pollution level in the soil (both top and subsoil) was at the safety pollution degree. The topsoil Mn and nickel SFI values ranged from 0.0005 to 0.001 and 0.0177 to 0.0263 respectively; and the SFI values recorded in the subsoil Mn and Ni pollution varied from 0.0004 to 0.0007 and 0.0113 to 0.0287 respectively. This is an indication that the Mn and Ni pollution level in the study area soil was within the safety degree of pollution. In addition, in the topsoil, the highest zinc SPI value (0.0511) was located at spatial Point D, and Location G had the minimum topsoil Zn SPI value of 0.0375. In the subsoil, the maximum and minimum Zn SFI values were 0.0422 at Point D and 0.232 at Point A. The range of SFI values obtain for Zn revealed that, the area had safety level of Zn pollution.

Table 3

Topsoil SPI values
Metal	Point A	Point B	Point C	Point D	Point E	Point F	Point G	Point H	Point I
Cd	0.243	0.191	0.249	0.233	0.191	0.18	0.241	0.206	0.198
Cr	3.775	1.925	4.650	4.300	1.875	2.600	3.383	2.642	1.867
Cu	0.017	0.016	0.019	0.02	0.015	0.016	0.023	0.012	0.022
Fe	0.0043	0.0051	0.0050	0.0050	0.0041	0.0042	0.0044	0.0043	0.0115
Pb	0.0064	0.0070	0.0051	0.0037	0.0037	0.0048	0.0042	0.0042	0.0049
Mn	0.0006	0.0008	0.0005	0.0009	0.0006	0.001	0.0005	0.0007	0.0005
Ni	0.0263	0.0127	0.0177	0.0225	0.0232	0.032	0.0178	0.0157	0.0235
Zn	0.0409	0.0438	0.0446	0.0511	0.0423	0.0397	0.0375	0.0509	0.0423

Table 4

Subsoil SPI values
Metal	Point A	Point B	Point C	Point D	Point E	Point F	Point G	Point H	Point I
Cd	0.179	0.128	0.185	0.204	0.18	0.153	0.189	0.199	0.144
Cr	1.025	1.617	3.625	3.850	1.208	2.350	3.075	2.258	1.525
Cu	0.011	0.009	0.013	0.016	0.012	0.012	0.017	0.009	0.016
Fe	0.0040	0.0046	0.0046	0.0044	0.0039	0.0039	0.0040	0.0038	0.0084
Pb	0.0050	0.0061	0.0049	0.0031	0.0030	0.0042	0.0034	0.0036	0.0037
Mn	0.0006	0.0006	0.0005	0.0007	0.0005	0.0008	0.0004	0.0006	0.0005
Ni	0.0229	0.0117	0.0151	0.0147	0.0151	0.0287	0.0141	0.0113	0.0171
Zn	0.0232	0.0381	0.0407	0.0422	0.0359	0.0312	0.0316	0.0422	0.0377

Pollution load index (PLI)

The soil heavy metals PLI results are presented in Table 5. It was revealed in Table 5 that irrespective of the sampling depth, Mn had the lowest PLI value while Cr had the highest PLI value. The topsoil PLI followed this increasing pattern Mn < Pb < Fe < Cu < Ni < Zn < Cd < Cr; while the subsoil PLI took this increasing trend Mn < Pb < Fe < Cu < Ni < Zn < Cd < Cr. Based on the pollution level of the toxic elements in the soil, the PLI values depicted that there was low level of Mn, Pb, Fe, Cu, Ni, Zn and Cd pollution in the soil; while Cr contamination was at moderate degree of pollution. Continued accumulation of heavy metals in the soil can result in greater toxic metals uptake by plants, and contamination of the water bodies. This may significantly increase the menaces, associated with heavy metals poisoning in the affected regions (Darma et al. 2022).

Table 5

Pollution load index values for soil
Metal	Top Soil	Subsoil
Cd	0.213	0.172
Cr	2.835	2.069
Cu	0.018	0.012
Fe	0.005	0.004
Pb	0.005	0.004
Mn	0.001	0.001
Ni	0.021	0.016
Zn	0.043	0.035

The aim of this research was to access the impact of automobile mechanic activities on heavy metals pollution of the environment. Results of the soil samples sampled from the vicinity of mechanic workshops had higher heavy metals concentration, when compared to the results recorded at the reference point. The high concentration of Cd, Cu, Cr, Pb, Fe, Mn, Ni and Zn and Cu in the topsoil and subsoil show that soil quality had been compromised, by the effluent discharge for the vehicle mechanic workshops. It was observed from the findings that the concentrations of the eight heavy metals investigated in the top and sub soils were within the permissible limits approved by WHO and Nigeria Department of Petroleum Resources (DPR). Based on the SPI and PLI values, the area soil can be considered as safe for human plants and animals. Accumulation of toxic metals in the soil is a major threat to the inhabitants of Ozoro metropolis, as these metals are lethal to human when consumed in large quantity. Therefore, there is urgency for environmental protection agencies, to regulate the activities of automobile maintenance workshops in Nigeria.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

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No competing interests reported.

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Appraising the impact of automobile mechanic workshop activities on the soil’s heavy metals contamination level in Isoko Community, Niger Delta region of Nigeria

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Abstract

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1. Introduction

2. Materials and Methods

2.1 Study area

2.2 Sample collection

2.3 Determination of the heavy metals in the soil samples

2.4 Soil heavy metal pollution evaluation

2.5 Data analysis

3. Results and Discussion

3.1 Heavy metals concentration

3.2 Spatial Distribution of the heavy metals in the soil

3.3 Evaluation of the soil quality

4. Conclusion

Declarations

Conflicts of Interest

References

Additional Declarations

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