Ecological risk assessment of heavy metal-contaminated soils of selected villages in Zamfara State, Nigeria

Abstract

The incidence of heavy metal contamination in Zamfara State, northern Nigeria, due to artisanal mining in some villages has resulted in the pollution of a vast area of land and water. This study evaluated the extent of environmental risks caused by heavy metals. It involved five (5) villages (Bagega, Dareta, Sunke, Tunga, and Abare) where mining activities were taking place and Anka town with no record of mining activities served as control. In each of the five villages, three sites (3) were identified as a mining site, processing site, and village making a total of sixteen (16) sites. Bulked soil samples were collected in triplicate and analyzed for iron, lead, cadmium, chromium, zinc, and nickel using flame atomic absorption spectrophotometry. Measured concentrations of the heavy metals in soils were then used to calculate the pollution and ecological risk pose by heavy metals. Their concentrations were in the order Fe > Pb > Cr > Zn > Cd > Ni, with Pb and Cd having a concentration higher than permissible levels for soils and accounted for 98.64% of the total potential ecological risk. Also, all the different pollution indices examined showed that all the sites were polluted with Cd, and all the processing sites were polluted with Pb. This reveals that processing sites pose more risk to heavy metal contamination. Correlation analysis showed a highly significant (p < 0.001) positive correlation between Pb and Zn, Cr and Ni, and a significant (p < 0.01) positive correlation between Fe and Pb, Zn and Cr. The principal component analysis suggested that Pb, Zn, Cr, and Ni likely originated from the same source, i.e., mining activities, and Fe and Cd originated from the abundant parent material in the study area.

Introduction

Heavy metal persistence and toxicity present a devastating environmental problem in our world today. The heavy metals are accumulated in our environment as a result of natural and anthropogenic activities from illegal mining and intense mineral exploration in mining areas. This results in the production of a large amount of waste material, leading to the release of toxic elements to the environment [44] particularly heavy metals [4]. This illegal and intense mineral exploration produces substantial waste material accumulating on tailings and heaps [38], and without proper management, the minerals on the heaps and tailing serve as the source of contaminants, which are often washed out by water and can eventually pollute the environment [34, 35]. Besides, the degree and extent of heavy metal contamination are determined by the geochemical characteristics of both the ore and the bedrock [29].

Soils are a rich ecosystem, consisting of both living and non-living matter with varying levels of interaction between them. It is also a critical component due to its ability to accumulate pollutants produced by natural and anthropogenic activities such as from agriculture, industry, mining and vehicular movement. Different processes interact together to aid the movements of heavy metals in soil, and this includes processes of biological, chemical, and physical nature [57]. These polluted soils serve as the source of dispersal of heavy metals in the environment and may enter the food chain and food web [25]. The biggest problems of the heavy metals are persistent and non-degradable, their presence in soil is stable and long-term [36], and these pose risks to public health and the environment [61].

Incidence of heavy metal contamination in Zamfara State, Nigeria, in 2010 [32] captured a lot of attention, and many kinds of research have been carried out to assess the levels of the heavy metals in the affected areas [4, 40, 44, 47, 48]. However, to the best of our knowledge, little or no study has been carried out or reported on the ecological risk of these contaminated areas. Long-term, low-level exposure to common pollutants like heavy metals is detrimental to health [11]; therefore, there is the need to assess the levels of this pollutant not only in contaminated soils but also in the soils of our environments, to provide information on the level of risks for proper management. This research was therefore design to determine the status and assess the ecological risk posed by heavy metal pollution in arable lands in the selected villages of Zamfara State, Nigeria.

Materials and methods

Study area, soil samples collection and preparation

The soil samples for the study were collected from six (6) locations, i.e., Abare, Sunke, Tungar Kudaku (Tunga), Bagega, Dareta, and Anka town (Fig. 1, Table 1), all from Anka Local Government of Zamfara State, Nigeria. According to Jurgen et al. [32], Abare and Sunke are confirmed heavy metal-contaminated area, Bagega is suspected, and Dareta is a remediated area. Anka with no record of heavy metal contamination served as our control.

Fig. 1
figure1

Maps showing Nigeria, Zamfara State and the sampling locations

Table 1 Coordinates and altitudes of the soil sampling sites

The soil samples were sampled from six (6) different villages/locations. In each of the locations, apart from Anka town (i.e., control site), sampling was done from the processing site, mining site, and the villages, while only one sample was collected from Anka. At each sampling site, five subsamples were randomly collected at depth of 0–30 cm to make a composite sample. A total of sixteen (16) sampling sites were obtained as shown in Table 1. Each soil sample was placed inside a polythene bag. The samples were taken to the laboratory, spread, and air-dried, some portions were used for the chemical and physical analyses, while the remaining were stored at room temperature and used for heavy metal analysis.

Routine soil analysis

The soil samples were dried and sieved through a 2.0 mm sieve. Total nitrogen, organic carbon, available phosphorus, exchangeable cations, exchangeable acidity, effective cation exchange capacity, soil pH, and electrical conductivity were carried out on the 2.0 mm soil samples.

The pH and conductivity meters were used to measure the pH and electrical conductivity, respectively, in the soil suspension (1:2.5 w/v dilutions) [31]. Organic carbon was determined by Walkley and Black method [41]. The hydrometer method was used for the determination of particle size distribution [24]. Total nitrogen was determined using the Kjeldahl method [13], and available phosphorus by Bray 1 extraction method [16], exchangeable cation by extraction with 1 N NH4OAc solution [49], exchangeable acidity by leaching the soil sample with 1 N KCl solution [7] and effective cation exchange capacity by summation method.

Determination of total heavy metal concentration

The air-dried soil sample was finely ground in stainless steel, 1 g of each sample was placed in a conical flask, and a mixture of concentrated HNO3:HClO4:HF in the ratio 3:1:3 was added [45]. The mixtures were then heated to 800C for 3 h. The digests were filtered into a 100-ml standard plastic bottle and made to 100 ml with deionized water.

The heavy metal concentrations in the samples were measured using flame atomic absorption spectrophotometry (Varian model-AA240FS) in the Ahmadu Bello University Multi-User Laboratory. The heavy metals determined include: iron (Fe), cadmium (Cd), lead (Pb), chromium (Cr) zinc (Zn), and nickel (Ni).

Determination of pollution indices

Pollution indices are very useful in processing, analyzing, and conveying raw environmental information to the public and decision-makers [18]. Geoaccumulation index, contamination factor, pollution load index, and enrichment factor were the indices used to measure the extent of heavy metal pollution, while the ecological risk index was used to assess the ecological risk associated with the heavy metals’ pollution in the study area.

Enrichment factor (EF)

The enrichment factor is the index used to determine the amount of metal added to soil compared to the average occurrence of that metal in the Earth's crust [37]. It was calculated based on Eq. (1) using Fe as a reference element due to its abundance in soil [46].

$${\text{EF}} = \frac{{\left( {\frac{Msample}{{{\text{Re}} sample}}} \right)}}{{\left( {\frac{Mref}{{{\text{Re}} ref}}} \right) }}$$
(1)

where EF is enrichment factor, Msample and Resample are the concentrations of the metal and the reference metal, respectively, in the contaminated soil and Mref and Reref are concentrations of the metal and the reference metal in the reference soil, respectively [2, 3, 5].

Five contamination categories are classified based on enrichment factors [55]. These include: < 2, deficient to minimal enrichment; 2 < 5, moderate enrichment; 5 < 20, significant enrichment; 20 < 40, very high enrichment; and ≥ 40, extremely high enrichment.

Geoaccumulation index (Igeo)

An index of geoaccumulation was used to define and determine metal contamination in the soils. This was done, by comparing current concentrations with pre-contamination levels. It was computed using Eq. (2) [43].

$${\text{I}}_{{{\text{geo}}}} = \log_{2} \left[ {\frac{Cn}{{1.5 Bn}}} \right]$$
(2)

Cn stands for measured concentration of the examined metal n in the soil and Bn stands for reference value or geochemical background concentration of the metal n (mg/kg) in the soil. Factor 1.5 was used to take into account the possible variations in background values for a given metal in the environment and the small anthropogenic influences [2, 3, 30].

Seven classes of geoaccumulation index (Igeo) were identified [17]; these are: ≤ 0 as Class 0 , i.e., unpolluted; 0.1–1.0 as Class 1, i.e., unpolluted to moderately polluted; 1.1–2.0 as Class 2, i.e., moderately polluted; 2.1–3.0 as Class 3, i.e., moderately to strongly polluted; 3.1–4.0 as Class 4, i.e., strongly polluted; 4.1–5.0 as Class 5, i.e., strongly to extremely polluted; and > 5 as Class 6, i.e., extremely polluted.

Contamination factor (CF)

The contamination factor is an index used to define the contamination or pollution range of a certain metal. It was calculated by employing the model set by [33].

$${\text{CF}} = \frac{{{\text{Concentration of the metal in the soil}} }}{{{\text{Target }}\left( {{\text{Background}}} \right){\text{Value}}}}$$
(3)

The background/target value is a reference value for the maximum allowable concentration of metals in the Nigerian soil [19]. Values less than one define the contamination range, while values greater than one define the pollution range.

Ten contamination categories are recognized based on contamination factor (CF) [33], and these are: < 0.1 very slight contamination; 0.10–0.25, slight contamination; 0.26–0.5, moderate contamination; 0.51–0.75, severe contamination; 0.76–1.00, very severe contamination; 1.1–2.0, slight pollution; 2.1–4.0, moderate pollution; 4.1–8.0, severe pollution; 8.1–16.0, very severe pollution; and > 16 excessive pollution.

The pollution load index (PLI)

This is the geometric mean of CFs of the heavy metals under study, proposed by Tomlinson et al. [56]. It gives an estimate of the combined metal contamination status and the necessary action that should be taken. It was computed using Eq. (4).

$${\text{PLI}} = \left( {{\text{CF}}1 \times {\text{CF}}2 \times {\text{CF}}3 \times {\text{CF}}4 \ldots \ldots \times {\text{CF}}n} \right)^{{{1 \mathord{\left/ {\vphantom {1 {\text{n}}}} \right. \kern-\nulldelimiterspace} {\text{n}}}}}$$
(4)

where n stands for the number of metals studied and CF is the contamination factor calculated from Eq. (3).

The value of PLI was divided into four groups [58], i.e., < 1 – no pollution, 1.0 < 2—moderate pollution, 2.0 < 3—heavy pollution, and ≥ 3.0—extreme pollution.

Ecological risk factor (ErF)

This is an index that quantitatively expresses the potential ecological risk associated with a given single contaminant [26], calculated as:

$${\text{ErF}} = {\text{Tr}}^{i} \times {\text{CF}}^{i}$$
(5)

where Tri is toxic response factor of a metal (Pb = 5, Zn = 1, Cd = 30, Cr = 2, Ni = 5) and CFi is the contamination factor.

Five terminologies are used to define ecological risks based on Hakanson [26]. These are < 40, low potential ecological risk; 40 < 80, moderate potential ecological risk; 80 < 160, considerable potential ecological risk; 160 < 320, high potential ecological risk; and ≥ 320, very high ecological risk.

Potential ecological risk index (RI)

This index is the sum of all the ecological risk factors of the metals under study, taking into account the cumulative effects of the metals under study [26]. It is calculated thus:

$${\text{RI}} = \left( {{\text{ErF}}1 + {\text{ErF}}2 + {\text{ErF}}3 \ldots + {\text{ErF}}n} \right)$$
(6)

where ErF is the ecological risk factor and n is the number of elements studied. The following terminologies have been used for the potential ecological risk index [26]: < 150, low ecological risk; 150 < 300, moderate ecological risk; 300 < 600, considerable ecological risk; and ≥ 600, very high ecological risk.

Statistical analyses

Each soil sample collected was made into triplicate before analysis, and the data collected were analyzed using SAS 9.0 [53] and Microsoft Excel (version 2016), where there are significant differences, and Duncan multiple range technique (DMRT) tests were used to separate the means. Correlation analysis was employed to compare relationships between variables. Principal component (PC) analysis was done on the variables to check the possible factors that contribute toward the metal concentrations and source apportionment. The selection of the number of significant principal components was based on varimax orthogonal rotation with Kaiser normalization at eigenvalues greater than 1.

Results and discussion

Physical and chemical properties of the experimental soil

The physical and chemical properties of the experimental soils are shown in Table 2. According to the USDA soil classification system, the textural classes of the soils at the plowing depth were majorly sandy loam, few are loam, and only one falls under silt loam. The presence of loam in all the soils indicates that the soils of the region are suitable for agriculture, as most crops thrive best on loam textured soils [15]. The pH (H2O) values recorded for these soils ranged from 6.2 to 7.7, 18.75% fall under slightly acidic, 68.75% under neutral, and 12.5% are slightly alkaline [42]. The values are in agreement with those reported by Raji et al. [51] in some soils of the Nigerian savanna and are within the optimum pH range for most plants’ growth. Electrical conductivity ranged from 0.10 to 0.35 dSm−1; these indicate that no salt/salinity problem would be encountered in the soils [28]. The cation exchange capacity recorded for the soil units ranged from 3.97 to 14.89 cmol(+)kg−1, and these according to the ratings of Hazelton and Murphy [27] ranged from low to moderate which indicates that the soils would have low to moderate nutrient retention capacity [14]. Organic carbon ranged from 0.20 to 1.22 gkg−1, these can be classified as very low (≤ 2%) based on Sigarf et al. [54] ratings, and this could be due to the lower amount of organic matter because of lower vegetation. The available phosphorus ranges from 1.58 to 17.68 mg/kg and is rated low to medium according to the rating of the Federal Ministry of Agriculture and Natural Resources of Nigeria [21]. Total nitrogen content of all the soils ranged from 0.7 to 2.8 gkg−1 and rated very low to low according to Sigarf et al. [54]. This could be due to lower organic matter contents of the soil [12], and this indicates nitrogen deficiency in the soils, which is typical of savanna soils.

Table 2 Experimental soil physical and chemical parameters

Amounts of heavy metals in the soils

The spatial distribution of heavy metals studied in the soils from all the study locations is depicted in Table 3. The average concentrations of the heavy metals varied significantly (p < 0.001) and decreased in the following order Fe > Pb > Cr > Zn > Cd > Ni. Iron (Fe) has the highest average concentration compared with other metals studied. These agree with many reports indicating natural soils containing a significant amount of Fe [2, 3, 6, 9, 20]. From the coefficient of variation of Fe (0.316), it suggests that less variability exists in the different sites, which reflects the homogenous spatial distribution of Fe in the area. These reveal that a high concentration of Fe in the soils cannot be conclusively attributed to mining alone, but other sources of Fe must be put into consideration. Besides, Fe has been reported to be the most abundant heavy metal in Nigerian soil [10]. The average Pb concentrations from all the processing sites of the study locations exceeded the international threshold of 300 mg/kg for Pb in arable soils [1], and they also exceeded the maximum allowable concentration of 85 mg/kg in the Nigerian soils as set by Department of Petroleum Resources of Nigeria [19]. The Pb concentration of Anka (control site) together with most of the mining sites and the villages is low. Only the Bagega mining site has a considerable amount of Pb (449.8 mg/kg), and this may be due to some element of grinding of the metal ores taking place around the mining sites. Therefore, this is a clear indication of Pb contamination from the processing of the metal ores.

Table 3 Mean concentrations of heavy metals in soils from all the study locations of Anka Local Government, Zamfara State (mg/kg)

Cadmium concentrations in all the study sites are greater than the maximum allowable concentration of 0.8 mg/kg in the Nigerian soils as set by the Department of Petroleum Resources of Nigeria [19]. Only Anka (control site) with a concentration of 1.2 mg/kg has a value less than the international threshold of Cd (1.4–19.5 mg/kg) as set by different countries [1]. This shows that the soils of all the study locations apart from Anka (control site) are contaminated with Cd. This agrees with the study of Mohammed and Abdu [40] of Dareta soils, Salisu et al. [52] of Bagega soils, and Abdu and Yusuf [4] of Abare soils. Zinc and Ni concentrations in all the study sites are less than the maximum allowable concentration of 140 mg/kg and 35 mg/kg, respectively, in the Nigerian soils, as set by the Department of Petroleum Resources of Nigeria [19]. They also have concentrations less than the international threshold of Zn (200–1400 mg/kg) and Ni (50–210 mg/kg), respectively, in arable soil set by different countries [1]. Although the concentrations are less than the maximum allowable concentrations, the significant differences (p < 0.001) observed between the locations indicate that mining activities have a great influence on the variations, as Anka (control site) have the lowest concentrations of Zn and Ni, and statistically lower than all the mining and processing sites of the study locations. All the Cr concentrations except Anka, Abare village, and Abare mining site, exceeded the 6.4 mg/kg set as a threshold by the UK, but are less than the other international threshold values set by other countries [1]. Statistical analysis result reveals a significant difference (p < 0.0001) between the sites and locations, with Anka (control site) having a value less than all the international threshold and less than the maximum allowable concentration formulated by DPR, and statistically lower than all other locations. This indicates that mining activities may have a contribution to the Cr contaminations.

Correlation and principal component analysis

To elucidate the relationship that exists between the heavy metals under study, and to identify the potential sources of the heavy metals’ pollution, principal component analysis and correlation analysis were carried out. Table 4 shows that 3 principal components (PCs) account for 87% of the total variation. PC1 explained 58% of the total variation and mainly included Ni, Cr, Zn, and Pb, whose variance values were, 0.917, 0.807, 0.850, and 0.798, respectively. PC2 explained 17% of the total variation and mainly included Fe and Cd with a variance value of 0.669 and 0.564, respectively. PC3 explained 13% of the total variation and mainly included Fe, with a variance value of 0.581. The correlation matrix indicates there is a significant positive correlation between Pb, Zn, Cr, and Ni; Zn with Cr and Ni; and Cr with Ni; and also between Fe, Pb, Zn, and Cr (Table 4).

Table 4 Principal component analysis (PCA) and correlation coefficients of heavy metals in Anka soils

The principal component analysis result was following those of the correlation analysis. These significant correlations that exist between many of the heavy metals may suggest their common origin [22, 39, 50]. Thus, Pb, Zn, Cr, and Ni likely originated from the same sources, i.e., mining activities, since it is the dominant anthropogenic activity taking place in the study area. The sources of Fe and Cd with the same principal component may likely be from the parent material of the area, as Anka (control site) has also recorded a significant amount of Cd, and for Fe, as reported earlier is the most abundant element in Nigerian soil [10].

Pollution assessment of heavy metals in the soils

Enrichment of heavy metals in soil

The accumulation of heavy metals in the soil of the study area was evaluated using the enrichment factor (Table 5). Lead enrichment evaluation shows that three sites (Bagega mining, Bagega processing, and Dareta processing) have extremely high enrichment, four sites (Sunke processing, Tunga processing, Abare processing, and Abare village) have very high enrichment, while the remaining nine sites including Anka (control site) have a deficient to minimal enrichment. It was observed that all the processing sites (Table 5) fell under very high enrichment to extremely high enrichment of Pb. This gives a clear indication that the processing of the metal ores was the major anthropogenic activities leading to the accumulation of Pb in the study areas. This is to say by grinding the ore, the Pb compounds are exposed to the air, and hence, they can be transported through the processes of physical, chemical, and biological nature [57] to different locations to cause accumulation. It was also observed for Cd that two sites (Dareta village and Anka mining) have very high enrichment, two sites (Sunke mining and Abare village) have moderate enrichment, and all the remaining twelve sites including Anka (control site) have significant enrichment of Cd. Since Anka (control site) also has a significant enrichment of Cd, we cannot conclude generally that the accumulation of Cd is due to mining activities alone, but other sources of Cd must be taken into consideration. Mohammed and Abdu [40] confirmed that the enrichment of Cd in the area was due to anthropogenic activities in which mining is inclusive. For Zn, Cr, and Ni, all the sites have a deficiency to minimal enrichment of the three metals, except Bagega mining sites that have moderate enrichment of Cr (Table 5). This indicates that mining activities did not impact any significant accumulation of Zn, Cr, and Ni with the natural background levels in the study areas.

Table 5 Enrichment factor of the heavy metals in soils from all the study locations in Anka Local Government, Zamfara State

Geoaccumulation (Igeo) of heavy metals in soils

The calculated Igeo for the soils of this study ranged from -16.31 to 4.22 for Pb, 1.46 to 2.29 for Cd, − 16.31 to − 0.17 for Cr, − 2.70 to − 0.75 for Fe, − 18.71 to − 1.56 for Zn, and − 18.22 to − 3.62 for Ni (Table 6). This revealed that all the sites studied in respect to Cr, Zn, Fe, and Ni fell into class 0 (unpolluted), while Pb ranged from class 0 (unpolluted) to class 5 (strongly to extremely polluted), and Cd ranged from class 2 (moderately polluted) to class 3 (moderately to strongly polluted). Like the result of the enrichment factor (Table 5) Igeo confirms that all the processing sites were strongly to extremely polluted with Pb, and all the study sites were moderately polluted with Cd. This also confirms that the processing of the metal ores is the major anthropogenic activity leading to the pollution of the study areas with Pb. However, the reference values used for assessing soil heavy metals vary greatly. Some used the pre-industrial reference level, the average crust level, background level, average content of shale heavy metals, etc. [26, 59]. For this study, average content of shale heavy metals was used. The reference values could lead to a discrepancy in assessment, but still [40] used the background level as the reference in one of the study locations and observed that Pb was strongly/extremely polluted, Cd was extremely polluted and Zn is unpolluted. This confirms that despite the different reference values used, the study locations were polluted with Pb and Cd.

Table 6 Geoaccumulation index of heavy metals in soils from all the study locations of Anka Local Government, Zamfara State

Pollution load indices and contamination assessment of heavy metals in the soils

The soil contamination assessment was based on contamination factor (Table 7) calculated for each heavy metal and each study site using the values from standard table formulated by the Department of Petroleum Resources of Nigeria [19] as target/background reference value for Nigerian soil. Based on the values of the contamination factor calculated, the soils were generally classified as very slightly contaminated with Zn, Ni, and Cr. All the processing sites were moderate to severely polluted with Pb and Fe. And all the sites were slight to moderately polluted with Cd. It was also observed that very slight contamination was recorded for Pb in Anka (control site), Bagega village, Dareta village, Sunke village, and Tunga village. The pollution of the area with Pb and Cd is evident to be from the mining activities, while Fe is based on the abundance of the element in the earth crust as reported by Amusan et al. [10]. These results also confirm that mining activities led to pollution of the study areas with heavy metals, as several researchers have earlier reported that the Nigerian savanna soils are generally non-polluted [2, 3, 8, 51].

Table 7 Contamination factor of heavy metals in soils from all the study locations of Anka Local Government, Zamfara State

The pollution load index value (Fig. 1, maps showing Nigeria, Zamfara State, and the sampling locations, Fig. 2) indicates that there is no pollution load in all the study sites (PLI < 1) apart from Bagega mining, Sunke processing, and Tunga processing that have moderate pollution. There is increasing potential for rising pollution levels in virtually all the study sites apart from the control site (Anka town), this called for remediation and control of illegal mining in all the study sites.

Fig. 2
figure2

Pollution load index of the heavy metals in soils from all the study locations of Anka Local Government, Zamfara State

Ecological risk assessment of heavy metals in the soils

The ecological risk assessment results are summarized in Table 8. It was found that ecological risk factors for Pb, Cr, Zn, and Ni were below 40, thus indicating low potential ecological risk. Cadmium was all within the moderate potential ecological risk. To quantify the overall potential ecological risk of observed metals in the study sites, the risk index (RI) was calculated as the sum of all the five risk factors (Fig. 3). Risk index could characterize the sensitivity of the local ecosystem to the toxic metals and represent ecological risk result from the overall contamination. The contribution to the overall potentially ecological risk shows that Cd contributed 84.25% and Pb contributed 14.39% of the total potentially ecological risk, this means that the two metals combined account for 98.64% of the total risk. This result is similar to what was reported by Fan et al. [23] in contaminated soil of three mining areas in Central China in which Cd accounted for almost 99.77% of the total risk. Wu et al. [60] also reported a similar result where Cd accounted for 70.6% of the total risk. The different pollution indices examined in this study (EF, Igeo, CF, and ErF) showed that all sites were polluted with Cd, and all the processing sites were polluted with Pb and are the main constraint to ecological risk.

Table 8 Ecological risk factor of the heavy metals in soils from all the study locations of Anka Local Government, Zamfara State
Fig. 3
figure3

Potential ecological risk index of the heavy metals in soils from all the study locations of Anka Local Government, Zamfara State

Conclusion and recommendation

In conclusion, the principal component analysis suggested that Pb, Zn, Cr, and Ni with the same principal component likely originated from the same source, i.e., mining activities, and Fe and Cd also with the same principal component originated from the abundant parent material in the study area. The results of this research revealed that processing sites pose more risk to heavy metal contamination as compared to mining sites and the farmlands around the villages, this is due to the grinding of the metal ores that releases the metals into the environment. It also revealed that Pb and Cd have the highest enrichment with most of the values greater than the maximum allowable limits set by different countries, and they virtually accounted (98.64%) of all the total potential ecological risk in the study areas. This quantitative evidence demonstrates the critical need to put in place mining regulations to protect the environment and residents, especially children, from heavy metal pollution in the area, and remediation of the contaminated areas is highly recommended.

Availability of data and materials

Data sharing applies to this article as data sets were generated and analyzed during the current study.

References

  1. 1.

    Abdu N (2010) Availability, transfer and balances of heavy metals in urban agriculture of West Africa. Kassel University Press GmbH, London

    Google Scholar 

  2. 2.

    Abdu N, Abdulkadir A, Agbenin JO, Buerkert A (2011) Vertical distribution of heavy metals in wastewater-irrigated vegetable garden soils of three West African cities. Nutr Cycl Agroecosyst 89(3):387–397

    Article  Google Scholar 

  3. 3.

    Abdu N, Agbenin J, Buerkert A (2011) Geochemical assessment, distribution, and dynamics of trace elements in urban agricultural soils under long-term wastewater irrigation in Kano, northern Nigeria. J Plant Nutr Soil Sci 174(3):447–458

    Article  Google Scholar 

  4. 4.

    Abdu N, Yusuf A (2013) Human health risk characterization of lead pollution in contaminated farmlands of Abare village, Zamfara State, Nigeria. Afr J Environ Sci Technol 7(9):911–916

    Google Scholar 

  5. 5.

    Abrahim G, Parker R (2008) Assessment of heavy metal enrichment factors and the degree of contamination in marine sediments from Tamaki Estuary, Auckland. NZ Environ Monit Assess 136(1–3):227–238

    Google Scholar 

  6. 6.

    Ademoroti C (1996) Environmental chemistry and toxicology. Foludex Press Ltd, Ibadan, pp 22–23

    Google Scholar 

  7. 7.

    Agbenin J (1995) Laboratory manual for soil and plant analysis (Selected methods and data analysis). Faculty of Agriculture/Institute of Agricultural Research, ABU Zaria, pp 7–71

    Google Scholar 

  8. 8.

    Agbenin JO, Felix-Henningsen P (2001) The status and dynamics of some trace elements in a savanna soil under long-term cultivation. Sci Total Environ 277(1–3):57–68

    Article  Google Scholar 

  9. 9.

    Aluko O, Sridhar M, Oluwande P (2003) Characterization of leachates from a municipal solid waste landfill site in Ibadan. Niger J Environ Health Res 2(1):32–37

    Google Scholar 

  10. 10.

    Amusan A, Ige D, Olawale R (2005) Characteristics of soils and crops’ uptake of metals in municipal waste dump sites in Nigeria. J Hum Ecol 17(3):167–171

    Article  Google Scholar 

  11. 11.

    Arora S, Jain C, Lokhande R (2017) Review of heavy metal contamination in soil. Int J Environ Sci Nat Resour 3(1.10):19080

    Google Scholar 

  12. 12.

    Asmamaw M, Haile A, Abera G (2018) Characterization and classification of salt affected soils and irrigation water in Tendaho sugarcane production farm, North-Eastern Rift Valley of Ethiopia. Afr J Agric Res 13(9):403–411

    Article  Google Scholar 

  13. 13.

    Bradstreet RB (1954) Kjeldahl method for organic nitrogen. Anal Chem 26(1):185–187

    Article  Google Scholar 

  14. 14.

    Brady N, Weil R (2002) The Nature and properties of soils. Prentince Hall, New Jersey

    Google Scholar 

  15. 15.

    Brady NC, Weil RR (2016) The nature and properties of soils. Pearson, London

    Google Scholar 

  16. 16.

    Bray RH, Kurtz L (1945) Determination of total, organic, and available forms of phosphorus in soils. Soil Sci 59(1):39–46

    Article  Google Scholar 

  17. 17.

    Buccolieri A, Buccolieri G, Cardellicchio N, Dell’Atti A, Di Leo A, Maci A (2006) Heavy metals in marine sediments of Taranto Gulf (Ionian Sea, southern Italy). Mar Chem 99(1–4):227–235

    Article  Google Scholar 

  18. 18.

    Caeiro S, Costa MH, Ramos T, Fernandes F, Silveira N, Coimbra A, Medeiros G, Painho M (2005) Assessing heavy metal contamination in Sado Estuary sediment: an index analysis approach. Ecol Ind 5(2):151–169

    Article  Google Scholar 

  19. 19.

    DPR (2002) Environmental guidelines and standards for the petroleum industry in Nigeria (revised Ed.)

  20. 20.

    Eddy N, Odoemelem S, Mbaba A (2006) Elemental composition of soil in some dumpsites. J Envr Agric Food Chem 5(3):1349–1365

    Google Scholar 

  21. 21.

    Enwezor W, Ohiri A, Opuwaribo E, Udo E (1990) Literature review on soil fertility investigations in Nigeria. Federal Ministry of Agriculture and Natural Resources, Lagos. P, p 281

    Google Scholar 

  22. 22.

    Facchinelli A, Sacchi E, Mallen L (2001) Multivariate statistical and GIS-based approach to identify heavy metal sources in soils. Environ Pollut 114(3):313–324

    Article  Google Scholar 

  23. 23.

    Fan Y, Zhu T, Li M, He J, Huang R (2017) Heavy metal contamination in soil and brown rice and human health risk assessment near three mining areas in central China. J Healthc Eng. https://doi.org/10.1155/2017/4124302

  24. 24.

    Gee GW, Or D (2002) 2.4 Particle-size analysis. Methods Soil Anal Part 4(598):255–293

    Google Scholar 

  25. 25.

    Gholizadeh A, Borůvka L, Saberioon MM, Kozák J, Vašát R, Němeček K (2015) Comparing different data preprocessing methods for monitoring soil heavy metals based on soil spectral features. Soil Water Res 10(4):218–227

    Article  Google Scholar 

  26. 26.

    Hakanson L (1980) An ecological risk index for aquatic pollution control. Sedimentol Approach Water Res 14(8):975–1001

    Google Scholar 

  27. 27.

    Hazelton P, Murphy B (2016) Interpreting soil test results: what do all the numbers mean? CSIRO publishing, Clayton

    Google Scholar 

  28. 28.

    HIDE J (1954). Diagnosis and Improvement of Saline and Alkali Soils. US Salinity Laboratory Staff; LA Richards, Ed. US Dept. of Agriculture, Washington, DC, rev. ed., 1954. vii+ 160 pp. Illus. $2.(Order from Supt. of Documents, GPO, Washington 25, DC. pp 0036–8075

  29. 29.

    Iavazzo P, Adamo P, Boni M, Hillier S, Zampella M (2012) Mineralogy and chemical forms of lead and zinc in abandoned mine wastes and soils: an example from Morocco. J Geochem Explor 113:56–67

    Article  Google Scholar 

  30. 30.

    Ihedioha J, Ukoha P, Ekere N (2017) Ecological and human health risk assessment of heavy metal contamination in soil of a municipal solid waste dump in Uyo. Niger Environ Geochemist Health 39(3):497–515

    Article  Google Scholar 

  31. 31.

    IITA (1982) Automated and semi-automated methods for soil and plant analysis. International Institute of Tropical Agriculture, Ibadan

    Google Scholar 

  32. 32.

    Jurgen B, Matthew C, Gert-Jan K, Edith P, Ramon R. (2010) Lead pollution and poisoning crisis environmental emergency response mission Zamfara State, Nigeria

  33. 33.

    Lacatusu R (2000) Appraising levels of soil contamination and pollution with heavy metals. European Soil Bureau 4:93–102

    Google Scholar 

  34. 34.

    Li Z, Ma Z, van der Kuijp TJ, Yuan Z, Huang L (2014) A review of soil heavy metal pollution from mines in China: pollution and health risk assessment. Sci Total Environ 468:843–853

    Article  Google Scholar 

  35. 35.

    Liakopoulos A, Lemiere B, Michael K, Crouzet C, Laperche V, Romaidis I, Drougas I, Lassin A (2010) Environmental impacts of unmanaged solid waste at a former base metal mining and ore processing site (Kirki, Greece). Waste Manage Res 28(11):996–1009

    Article  Google Scholar 

  36. 36.

    Lizárraga-Mendiola L, González-Sandoval M, Durán-Domínguez M, Márquez-Herrera C (2009) Geochemical behavior of heavy metals in a Zn–Pb–Cu mining area in the State of Mexico (central Mexico). Environ Monit Assess 155(1–4):355

    Article  Google Scholar 

  37. 37.

    Loska K, Wiechuła D, Pelczar J (2005) Application of enrichment factor to assessment of zinc enrichment/depletion in farming soils. Commun Soil Sci Plant Anal 36(9–10):1117–1128

    Article  Google Scholar 

  38. 38.

    Ma L, Sun J, Yang Z, Wang L (2015) Heavy metal contamination of agricultural soils affected by mining activities around the Ganxi River in Chenzhou. Southern China Environ Monit Assess 187(12):731

    Article  Google Scholar 

  39. 39.

    Micó C, Recatalá L, Peris M, Sánchez J (2006) Assessing heavy metal sources in agricultural soils of an European Mediterranean area by multivariate analysis. Chemosphere 65(5):863–872

    Article  Google Scholar 

  40. 40.

    Mohammed I, Abdu N (2014) Horizontal and vertical distribution of lead, cadmium, and zinc in farmlands around a lead-contaminated goldmine in Zamfara, Northern Nigeria. Arch Environ Contam Toxicol 66(2):295–302

    Article  Google Scholar 

  41. 41.

    Nelson DW, Sommers LE (1996) Total carbon, organic carbon, and organic matter. Methods Soil Anal Part3 Chem Methods 9:961–1010

    Google Scholar 

  42. 42.

    NRCS U (1993) Soil survey division staff soil survey manual Soil conservation service. US Department of Agriculture Handbook, Washington

    Google Scholar 

  43. 43.

    Ntekim E, Ekwere S, Ukpong E (1993) Heavy metal distribution in sediments from Calabar River, southeastern Nigeria. Environ Geol 21(4):237–241

    Article  Google Scholar 

  44. 44.

    Nuhu AA, Sallau M, Majiya M (2014) Heavy metal pollution: the environmental impact of artisanal gold mining on Bagega village of Zamfara State, Nigeria. Res J Pharm Biol Chem Sci 5(6):306–313

    Google Scholar 

  45. 45.

    Nwajei G, Gagophien P (2000) Distribution of heavy metals in sediments of Lagos Lagoon. Pak J Sci Ind Res 43(6):338–340

    Google Scholar 

  46. 46.

    Okuo J, Iyasele J (2007) A study of heavy metals composition of total suspended particulate matter around industrial complexes in Edo state, Nigeria. J Chem Soc Nigeria 32(1):32–37

    Google Scholar 

  47. 47.

    Oladipo M, Njinga RL, Elele U, Salisu A (2014) Heavy metal contaminations of drinking water sources due to illegal gold mining activities in Zamfara state-Nigeria. J Chem Biochem 2(1):31–44

    Google Scholar 

  48. 48.

    Orisakwe O, Oladipo O, Ajaezi G, Udowelle N (2017) Horizontal and vertical distribution of heavy metals in farm produce and livestock around lead-contaminated goldmine in Dareta and Abare, Zamfara State, Northern Nigeria. J Environ Public Health 2017:3506949

    Article  Google Scholar 

  49. 49.

    Page AL, Miller RH, Keeney DR (1982) Methods of soil analysis. Part 2. Chemical and microbiological properties. Agronomy, No. 9. Soil Science Society of America, Madison, WI, p 1159

  50. 50.

    Qu C-S, Ma Z-W, Yang J, Liu Y, Bi J, Huang L (2012) Human exposure pathways of heavy metals in a lead-zinc mining area, Jiangsu Province. China PloS one 7(11):e46793

    Article  Google Scholar 

  51. 51.

    Raji B, Jimba W, Alagbe S (2015) The distribution and geochemical assessment of trace elements from the semi-arid to sub-humid savanna of Nigeria. Environ Earth Sci 73(7):3555–3564

    Article  Google Scholar 

  52. 52.

    Salisu K, Yusuf M, Ahmed M, Mohammed M, Umar I (2016) Analysis of the distribution of heavy metals in the soils of Bagega mining area Zamfara state, Nigeria. Bayero J Pure Appl Sci 9(1):150–159

    Article  Google Scholar 

  53. 53.

    SAS (2002) Statistical Analysis System (SAS) Version 9.0. Users guide Inst. Cary, N. C.

  54. 54.

    Sigarf TA, Desanier N, Cabigat JC, Abayao EH (2003) Soil fertility limitations of Ifugao rice terraces. Philipp J Crop Sci 28(1):39–48

    Google Scholar 

  55. 55.

    Sutherland R (2000) Bed sediment-associated trace metals in an urban stream, Oahu. Hawaii Environ Geol 39(6):611–627

    Article  Google Scholar 

  56. 56.

    Tomlinson D, Wilson J, Harris C, Jeffrey D (1980) Problems in the assessment of heavy-metal levels in estuaries and the formation of a pollution index. Helgoländer meeresuntersuchungen 33(1):566

    Article  Google Scholar 

  57. 57.

    Violante A, Huang PM, Gadd GM (2008) Biophysico-chemical processes of heavy metals and metalloids in soil environments. Wiley Online Library, New Jersey

    Google Scholar 

  58. 58.

    Wang X, He M, Xie J, Xi J, Lu X (2010) Heavy metal pollution of the world largest antimony mine-affected agricultural soils in Hunan province (China). J Soils Sediments 10(5):827–837

    Article  Google Scholar 

  59. 59.

    Wedepohl KH (1995) The composition of the continental crust. Geochim Cosmochim Acta 59(7):1217–1232

    Article  Google Scholar 

  60. 60.

    Wu Y, Yang J, Zhou X, Lei M, Gao D, Qiao P, Du G (2015) Risk assessment of heavy metal contamination in farmland soil in Du’an Autonomous County of Guangxi Zhuang autonomous region, China. Huan jing ke xue= Huanjing kexue 36(8):2964–2971

    Google Scholar 

  61. 61.

    Zhu N, Qiao J, Yan T (2019) Jan 15). Arsenic immobilization through regulated ferrolysis in paddy field amendment with bismuth impregnated biochar. Sci Total Environ 648:993–1001. https://doi.org/10.1016/j.scitotenv.2018.08.200

    Article  Google Scholar 

Download references

Acknowledgement

The authors wish to thank the Department of Soil Science, Ahmadu Bello University, for providing the enabling environment for the conduct of the research.

Author information

Affiliations

Authors

Contributions

Sharhabil comes up with the idea and designed the research, carried out the studies, and wrote the manuscript. Nafiu and Fatima studied the analysis of soil samples and carried out the studies of other sections. Sharhabil and Nafiu generated all the figures and tables in the manuscript and draft the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Sharhabil Musa Yahaya.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Yahaya, S.M., Abubakar, F. & Abdu, N. Ecological risk assessment of heavy metal-contaminated soils of selected villages in Zamfara State, Nigeria. SN Appl. Sci. 3, 168 (2021). https://doi.org/10.1007/s42452-021-04175-6

Download citation

Keywords

  • Contaminated soils
  • Ecological risk assessment
  • Heavy metals
  • Zamfara State
  • Nigeria