Heavy Metal Concentrations and Ecological and Human Health Risks in Soils Around Osubi and Aladja Waste Dumpsites, Delta State, Nigeria

materials and blanks were included in each analytical batch as part of the quality assurance and quality control (QA/QC) procedures. Contact with metallic surfaces was avoided during sample handling to minimise the possibility of contamination. Determination of Physical Properties of Soil Selected physical properties of the soil, including moisture content, particle-size characteristics, bulk density, porosity, specific gravity and consistency limits, were determined to characterise the soils from the Osubi and Aladja dumpsites and the control site. Standard laboratory procedures based on ASTM D2216 and ASTM D422 were adopted, and tests were performed in triplicate where applicable to improve reproducibility. Moisture content was determined by the oven-drying method. Approximately 30 g of fresh soil was weighed into a clean, pre-weighed moisture can and dried in a hot-air oven at 105 °C ± 5 °C for 24 hours, or until a constant weight was obtained. After cooling in a desiccator, the dry mass was recorded. Moisture content was calculated as the mass of water lost relative to the mass of dry soil, expressed as a percentage. Particle-size analysis was performed using a combination of dry sieving and hydrometer methods. A 500 g oven-dried soil sample was mechanically sieved through a nest of sieves ranging from 4.75 mm to 75 μm. For the fraction passing the 75 μm sieve, 50 g was dispersed in sodium hexametaphosphate solution and analysed by hydrometer at specified time intervals. The proportions of sand, silt and clay were determined, and the results were plotted on a particle-size distribution curve and classified using the USDA soil-texture classification system. Bulk density was determined using the core-cutter method. An undisturbed soil core was collected using a cylindrical cutter of known volume. The core was trimmed, weighed and oven-dried to determine its dry mass. Bulk density was calculated as dry soil mass per unit volume. Porosity and void ratio were subsequently calculated from bulk density and specific gravity using standard equations. The specific gravity of the soil solids was determined using the pycnometer method. A known mass of oven-dried soil was placed in a calibrated pycnometer and filled with distilled water. The masses of the pycnometer containing the soil and water, and the pycnometer containing water alone, were recorded. Specific gravity was calculated from the mass of soil solids and the equivalent volume of water. For the fine-grained fraction, the liquid limit was determined using the Casagrande apparatus, while the plastic limit was determined by rolling soil into threads of approximately 3 mm diameter until the threads crumbled. The plasticity index was calculated as the difference between the liquid limit and plastic limit. Plate 3.2 shows the researcher during laboratory air-drying of the samples. IIARD International Journal of Geography & Environmental Management Results Metal concentrations Nickel and arsenic recorded the highest mean concentrations in the soil samples, while cadmium had the lowest. Across the 14 samples, the mean concentrations followed the order Ni (0.043 mg/kg) > As (0.041 mg/kg) > Pb (0.034 mg/kg) > Cr (0.017 mg/kg) > Cu (0.016 mg/kg) > Cd (0.0005 mg/kg). Cadmium was below the detection limit in eight of the 14 samples. Lead showed the greatest variability, with a standard deviation of 0.042 mg/kg and concentrations ranging from not detected to 0.154 mg/kg at Osubi L2 topsoil. Table 3. Heavy metal concentrations (mg/kg) in soils Site / location / depth Cu Cr Cd Pb As Ni Osubi L1, topsoil 0.0079 0.0069 ND 0.0260 0.0227 0.0200 Osubi L2, topsoil 0.0261 0.0074 ND 0.1543 0.0253 0.0230 Osubi L3, topsoil 0.0251 0.0052 ND 0.0870 0.0923 0.0220 Osubi L4, topsoil 0.0099 0.0063 ND 0.0233 0.0285 0.0300 Osubi L1, subsoil 0.0105 0.0035 ND 0.0201 0.0162 0.0303 Osubi L5, subsoil 0.0213 0.0082 0.0006 0.0251 0.0223 0.0602 Aladja L1, topsoil 0.0244 0.0489 0.0009 0.0242 0.0244 0.0722 Aladja L2, topsoil 0.0069 0.0124 ND ND 0.0246 0.0200 Aladja L6, topsoil 0.0164 0.0138 ND 0.0079 0.0733 0.0922 Aladja L1, subsoil 0.0325 0.0599 0.0008 0.0239 0.0233 0.0632 Aladja L2, subsoil 0.0027 0.0097 ND ND 0.0902 0.0233 Aladja L6, subsoil 0.0204 0.0148 0.0014 0.0067 0.0324 0.0723 Control, topsoil 0.0080 0.0188 ND 0.0092 0.0222 0.0500 Control, subsoil 0.0128 0.0213 0.0028 0.0670 0.0822 0.0234 Mean (n = 14) 0.0161 0.0169 0.0005 0.0339 0.0414 0.0430 SD 0.0090 0.0168 0.0008 0.0424 0.0288 0.0246 Average shale (Turekian & Wedepohl, 1961) 45 90 0.3 20 13 68 ND = not detected. The two dumpsites showed distinct metal profiles (Table 4). Mean chromium concentration at Aladja (0.0266 mg/kg) was approximately four times the Osubi value (0.0062 mg/kg), while mean nickel was almost twice as high at Aladja (0.0572 mg/kg) as at Osubi (0.0309 mg/kg). In contrast, mean lead was substantially higher at Osubi (0.0560 mg/kg) than at Aladja (0.0105 mg/kg). Copper concentrations were similar at the two sites. Across the dumpsite samples, lead was higher in topsoil than subsoil, whereas chromium, cadmium and nickel were slightly higher in subsoil. The two control samples did not consistently show lower concentrations than the dumpsite samples; the control subsoil contributed to relatively high arsenic, lead and cadmium values. IIARD International Journal of Geography & Environmental Management Table 4. Mean metal concentrations (mg/kg) by site and depth Group N Cu Cr Cd Pb As Ni Osubi dumpsite 6 0.0168 0.0062 0.0001 0.0560 0.0346 0.0309 Aladja dumpsite 6 0.0172 0.0266 0.0005 0.0105 0.0447 0.0572 Control 2 0.0104 0.0200 0.0014 0.0381 0.0522 0.0367 Dumpsite topsoil 7 0.0167 0.0144 0.0001 0.0461 0.0416 0.0399 Dumpsite subsoil 5 0.0175 0.0192 0.0006 0.0152 0.0369 0.0499 Geo-accumulation index All calculated Igeo values were negative, ranging from −7.33 to −15.24 (Table 5). On the basis of the adopted classification, the soils fall within Class 0 (practically uncontaminated) for the six metals. The least negative values were recorded for cadmium in the control subsoil (−7.33), lead at Osubi L2 topsoil (−7.60), and arsenic at Osubi L3 topsoil (−7.72) and Aladja L2 subsoil (−7.76). Table 5. Geo-accumulation index of metals in soils Site / location / depth Cu Cr Cd Pb As Ni Osubi L1, topsoil −13.06 −14.26 BDL −10.17 −9.75 −12.32 Osubi L2, topsoil −11.34 −14.16 BDL −7.60 −9.59 −12.11 Osubi L3, topsoil −11.39 −14.66 BDL −8.43 −7.72 −12.18 Osubi L4, topsoil −12.74 −14.39 BDL −10.33 −9.42 −11.73 Osubi L1, subsoil −12.65 −15.24 BDL −10.54 −10.23 −11.72 Osubi L5, subsoil −11.63 −14.01 −9.55 −10.22 −9.77 −10.73 Aladja L1, topsoil −11.43 −11.43 −8.97 −10.28 −9.64 −10.46 Aladja L2, topsoil −13.26 −13.41 BDL BDL −9.63 −12.32 Aladja L6, topsoil −12.01 −13.26 BDL −11.89 −8.06 −10.11 Aladja L1, subsoil −11.02 −11.14 −9.14 −10.29 −9.71 −10.66 Aladja L2, subsoil −14.61 −13.76 BDL BDL −7.76 −12.10 Aladja L6, subsoil −11.69 −13.16 −8.33 −12.13 −9.23 −10.46 Control, topsoil −13.04 −12.81 BDL −11.67 −9.78 −10.99 Control, subsoil −12.36 −12.63 −7.33 −8.81 −7.89 −12.09 BDL = metal below detection limit; Igeo not calculated. Contamination factor, pollution load and ecological risk The other contamination and ecological-risk indices also indicated low levels of contamination (Table 6). The CF values were all well below 1, with the highest recorded for arsenic at Aladja (3.4 × 10−3). The degree of contamination ranged from 0.0067 to 0.0116, while the modified degree of contamination ranged from 0.0011 to 0.0019. PLI values were below 0.001, and the potential ecological risk index (RI) ranged from 0.055 at Osubi to 0.194 at the control site, remaining within the low-risk category. Cadmium and arsenic made the largest relative contributions to ecological risk because of their higher toxic-response factors. IIARD International Journal of Geography & Environmental Management Table 6. Contamination factor (CF), ecological risk factor (Er) and combined indices Index Osubi Aladja All dumpsite Control CF Cu 3.7 × 10−4 3.8 × 10−4 3.8 × 10−4 2.3 × 10−4 CF Cr 6.9 × 10−5 3.0 × 10−4 1.8 × 10−4 2.2 × 10−4 CF Cd 3.3 × 10−4 1.7 × 10−3 1.0 × 10−3 4.7 × 10−3 CF Pb 2.8 × 10−3 5.2 × 10−4 1.7 × 10−3 1.9 × 10−3 CF As 2.7 × 10−3 3.4 × 10−3 3.0 × 10−3 4.0 × 10−3 CF Ni 4.5 × 10−4 8.4 × 10−4 6.5 × 10−4 5.4 × 10−4 Degree of contamination 0.0067 0.0072 0.0069 0.0116 Modified degree of contamination 0.0011 0.0012 0.0012 0.0019 Pollution load index 5.5 × 10−4 8.2 × 10−4 7.8 × 10−4 1.0 × 10−3 Er Cd 0.010 0.052 0.031 0.141 Er As 0.027 0.034 0.030 0.040 Potential ecological risk index (RI) 0.055 0.095 0.075 0.194 Class Low Low Low Low Correlation between metals Copper and chromium were the only metal pair showing a statistically significant positive correlation (r = 0.534, p = 0.049; Table 7). Positive but non-significant relationships were observed for Cr–Ni (r = 0.480), Cu–Pb (r = 0.472), Cu–Ni (r = 0.432) and Cr–Cd (r = 0.378). Lead and nickel showed a weak negative correlation (r = −0.377), which is consistent with the different spatial patterns observed at Osubi and Aladja. Arsenic did not show a clear relationship with the other metals. Table 7. Pearson correlation matrix of metals in soils (n = 14) Metal Cu Cr Cd Pb As Ni Cu 1 Cr 0.534* 1 Cd 0.219 0.378 1 Pb 0.472 −0.153 0.073 1 As −0.111 −0.183 0.198 0.130 1 Ni 0.432 0.480 0.149 −0.377 −0.133 1 *Significant at p < 0.05 (two-tailed). Human health risk Based on the measured concentrations, estimated health risks associated with soil contact were low for both adults and children (Tables 8 and 9). The total hazard index was 3.8 × 10−4 for adults and 2.1 × 10−3 for children, both well below the reference value of 1. Arsenic contributed the largest share of the total HI in both groups. The children's HI was approximately six times the adult value, reflecting the greater relative exposure associated IIARD International Journal of Geography & Environmental Management with soil ingestion during childhood. The total estimated lifetime cancer risk was 3.3 × 10−8 for adults and 7.8 × 10−8 for children, both below the stated negligible-risk level of 10−6. Table 8. Hazard quotients (HQ) and hazard index (HI) from soil (mean of all samples) Metal Adult HQ ing. Adult HQ derm. Adult HI Child HQ ing. Child HQ derm. Child HI Cu 5.5 × 10−7 2.1 × 10−8 5.7 × 10−7 5.1 × 10−6 1.7 × 10−8 5.2 × 10−6 Cr 7.7 × 10−6 4.4 × 10−6 1.2 × 10−5 7.2 × 10−5 3.5 × 10−6 7.6 × 10−5 Cd 6.4 × 10−7 7.3 × 10−7 1.4 × 10−6 5.9 × 10−6 5.8 × 10−7 6.5 × 10−6 Pb 1.3 × 10−5 1.0 × 10−6 1.4 × 10−5 1.2 × 10−4 8.1 × 10−7 1.3 × 10−4 As 1.9 × 10−4 1.6 × 10−4 3.5 × 10−4 1.8 × 10−3 1.3 × 10−4 1.9 × 10−3 Ni 3.0 × 10−6 1.2 × 10−7 3.1 × 10−6 2.8 × 10−5 1.0 × 10−7 2.8 × 10−5 Total 3.8 × 10−4 2.1 × 10−3 ing. = ingestion; derm. = dermal contact. HI < 1 means no significant non-cancer risk. Table 9. Lifetime cancer risk from soil ingestion Metal Adult Child Cr 4.0 × 10−9 9.3 × 10−9 Cd 8.3 × 10−11 1.9 × 10−10 Pb 1.4 × 10−10 3.2 × 10−10 As 2.9 × 10−8 6.8 × 10−8 Total 3.3 × 10−8 7.8 × 10−8 LCR < 1 × 10−6 is considered negligible. Discussion The metal concentrations measured in this study were low in absolute terms and considerably lower than values reported in several other dumpsite and landfill studies. Rezapour et al. (2018), for example, reported 35–67 mg/kg copper and 54–95 mg/kg lead in soils affected by landfill leachate, while Ahmad et al. (2021) reported 73.8 mg/kg copper and 57.9 mg/kg chromium in soils near a landfill in Punjab, Pakistan. Beinabaj et al. (2023) reported 0.86 mg/kg copper and 1.02 mg/kg lead in soils around a Tehran landfill. The mean concentrations measured in the present study are substantially lower than those reported in these investigations. Several factors may help explain the relatively low concentrations observed. The dumpsites appear to receive predominantly municipal household waste, while the surrounding soils are sandy and relatively well drained. High rainfall in the Niger Delta may promote downward movement of dissolved constituents rather than their retention in surface soil (Abam & Nwankwoala, 2020). Sandy soils also generally provide fewer clay and organic surfaces for strong metal retention than finer-grained soils (Alloway, 2013). However, these factors do not fully explain the magnitude of the reported concentrations. All samples, including the control, were well below the average shale values used for comparison (Turekian & Wedepohl, 1961). This raises an important analytical consideration: incomplete digestion, recovery effects or a unit-conversion issue could potentially contribute to the unusually low absolute values. The concentrations should therefore be interpreted cautiously, IIARD International Journal of Geography & Environmental Management particularly when comparing them with regional background values. The relative differences among sites, depths and metals remain useful for identifying patterns within the present dataset, but the absolute concentrations would benefit from confirmation through independent analytical quality checks. Different signatures at the two dumps The two sites showed different metal profiles that are broadly consistent with their surrounding land-use settings. Aladja recorded higher chromium and nickel concentrations. Both elements are associated with steel production and alloy manufacture, and steel slag, dust and mill scale from industrial activities may contribute metals to the local waste stream (Natalia et al., 2015). Osubi, in contrast, recorded higher lead concentrations. Its proximity to a vehicle and machinery repair area provides plausible sources such as spent lead-acid batteries, used lubricating oils and old paint (Wuana & Okieimen, 2011). These source interpretations should, however, be regarded as plausible explanations rather than confirmed source apportionment. Lead concentrations were approximately three times higher in dumpsite topsoil than in subsoil. Lead commonly has a strong affinity for organic matter and iron oxides and can therefore be retained near the soil surface (Alloway, 2013). The relatively high value at Osubi L2 topsoil (0.154 mg/kg) may represent a localized input rather than a uniform condition across the site. Chromium, nickel and cadmium were slightly higher in the subsoil, suggesting that some downward redistribution may occur; however, the present dataset does not by itself establish the mechanisms responsible for vertical movement. What the correlations suggest The significant positive relationship between copper and chromium suggests that the two metals may have a common source or may respond similarly to the same soil processes. The weaker positive relationships involving chromium and nickel are also consistent with some degree of shared source or behavior. The weak negative relationship between lead and nickel largely reflects the contrasting site patterns, with lead higher at Osubi and nickel higher at Aladja. Arsenic showed no clear correlation with the other metals, indicating that its distribution may be controlled by a different source or by different geochemical processes. Correlation alone, however, cannot establish a definitive source. Pollution indices The pollution indices consistently indicated low measured contamination and low ecological risk. Igeo values were strongly negative, while CF, Cdeg, mCd, PLI and RI remained within their lowest categories. Other studies using similar indices have reported considerably higher contamination levels. For example, Chonokhuu et al. (2019) reported PLI values of 0.94–1.83 in urban soils in Mongolia, while Ahmad et al. (2021) reported Igeo values corresponding to moderate to heavy contamination around a landfill in Pakistan. It is important to recognize that these indices depend on the measured concentrations and selected background values. Consequently, the indices support the low values observed in this dataset but do not provide an independent check on the analytical measurements. Cadmium and arsenic contributed relatively more to the calculated ecological risk because their toxic-response factors are higher than those assigned to several of the other metals considered (Håkanson, 1980; Ali et al., 2019). Their contribution therefore reflects both their measured concentrations and the weighting built into the ecological-risk methodology. Human health risk Using the measured concentrations, estimated soil-exposure risks were low for both adults IIARD International Journal of Geography & Environmental Management and children. The children's HI was about six times the adult value, which is consistent with the greater relative exposure of children to soil through ingestion and their lower body weight (Chonokhuu et al., 2019). Arsenic was the principal contributor to both non-carcinogenic and carcinogenic risk estimates. Because the risk calculations are directly dependent on the measured concentrations, confirmation of the unusually low analytical values would strengthen confidence in the resulting risk estimates. Conclusion The soils sampled at the Osubi and Aladja dumpsites contained low measured concentrations of copper, chromium, cadmium, lead, arsenic and nickel. The geo-accumulation, contamination, pollution-load and ecological-risk indices consistently classified the soils within their lowest reported categories, while the estimated non-carcinogenic and carcinogenic risks were below the stated reference levels for both adults and children. The two dumpsites nevertheless showed different metal patterns: chromium and nickel were higher at Aladja, while lead was higher at Osubi. Lead was more concentrated in topsoil, and copper and chromium showed a significant positive correlation. Overall, the results indicate low measured contamination at the time of sampling, but continued monitoring remains necessary because waste inputs, rainfall and site conditions can change the distribution of metals over time. Recommendations i. The Delta State Ministry of Environment should establish a routine monitoring program for physicochemical properties and heavy metals in soils around active dumpsites. Monitoring should be repeated at defined intervals to identify changes in contaminant concentrations throughout the operational life of the sites. ii. Open dumping should progressively be replaced with engineered landfill facilities designed with appropriate liners and leachate-collection and management systems to reduce the release and accumulation of contaminants in surrounding soils. iii. Source separation of municipal waste should be strengthened to reduce the amount of potentially hazardous materials entering dumpsites. Recycling, reuse and material-recovery programmes should also be expanded to reduce the volume of waste requiring final disposal. iv. Agricultural activities and children's play should be discouraged on and immediately around active dumpsites, particularly in areas where localised lead enrichment has been identified. v. Environmental regulatory agencies, including the relevant state environmental authorities and the Delta State Waste Management Board , should strengthen inspection, monitoring and enforcement of applicable waste-management requirements and environmental standards. vi. Local governments and community organisations should sustain public-awareness programmes on proper waste disposal, environmental sanitation, groundwater protection and the potential environmental and health consequences of indiscriminate dumping. IIARD International Journal of Geography & Environmental Management References Abam, T. K. S., & Nwankwoala, H. O. (2020). Hydrogeology of eastern Niger Delta: A review. Journal of Water Resource and Protection, 12(9), 741–777. https://doi.org/10.4236/jwarp.2020.129045 Abrahim, G. M. S., & Parker, R. J. (2008). Assessment of heavy metal enrichment factors and the degree of contamination in marine sediments from Tamaki Estuary, Auckland, New Zealand. Environmental Monitoring and Assessment, 136(1), 227–238. https://doi.org/10.1007/s10661-007-9678-2 Ahmad, W., Alharthy, R. D., Zubair, M., Ahmed, M., Hameed, A., & Rafique, S. (2021). Toxic and heavy metals contamination assessment in soil and water to evaluate human health risk. Scientific Reports, 11(1), 17006. https://doi.org/10.1038/s41598-021- 94616-4 Ali, H., Khan, E., & Ilahi, I. (2019). Environmental chemistry and ecotoxicology of hazardous heavy metals: Environmental persistence, toxicity, and bioaccumulation. Journal of Chemistry, 2019, 6730305. https://doi.org/10.1155/2019/6730305 Alloway, B. J. (2013). Heavy metals in soils: Trace metals and metalloids in soils and their bioavailability (3rd ed.). Springer. Anikwe, M. A. N., & Nwobodo, K. C. A. (2002). Long-term effect of municipal waste disposal on soil properties and productivity of sites used for urban agriculture in Abakaliki, Nigeria. Bioresource Technology, 83(3), 241–250. https://doi.org/10.1016/S0960-8524(01)00154-7 Beinabaj, S. M. H., Heydariyan, H., Aleii, H. M., & Hosseinzadeh, A. (2023). Concentration of heavy metals in leachate, soil, and plants in Tehran's landfill: Investigation of the effect of landfill age on the intensity of pollution. Heliyon, 9(1), e13017. https://doi.org/10.1016/j.heliyon.2023.e13017 Chonokhuu, S., Batbold, C., Chuluunpurev, B., Battsengel, E., Dorjsuren, B., & Byambaa, B. (2019). Contamination and health risk assessment of heavy metals in the soil of major cities in Mongolia. International Journal of Environmental Research and Public Health, 16(14), 2552. https://doi.org/10.3390/ijerph16142552 Ekwok, S. E., Eldosouky, A. M., Akpan, A. E., & Henaish, M. A. (2024). Delineation of deep-seated crustal structures from magnetic data in the southeastern part of the Niger Delta basin, Nigeria. Frontiers in Earth Science, 12, 1347892. https://doi.org/10.3389/feart.2024.1347892 Essien, J. P., Inam, E. D., Ikpe, D. I., Udofia, G. E., & Benson, N. U. (2019). Ecotoxicological status and risk assessment of heavy metals in municipal solid wastes dumpsite impacted soil in Nigeria. Environmental Nanotechnology, Monitoring & Management, 11, 100215. https://doi.org/10.1016/j.enmm.2019.100215 Håkanson, L. (1980). An ecological risk index for aquatic pollution control: A sedimentological approach. Water Research, 14(8), 975–1001. https://doi.org/10.1016/0043-1354 (80)90143-8 Kjeldsen, P., Barlaz, M. A., Rooker, A. P., Baun, A., Ledin, A., & Christensen, T. H. (2002). Present and long-term composition of MSW landfill leachate: A review. Critical Reviews in Environmental Science and Technology, 32(4), 297–336. https://doi.org/10.1080/10643380290813462 Müller, G. (1969). Index of geoaccumulation in sediments of the Rhine River. GeoJournal, 2(3), 108–118. Natalia, C. C. L., Edwin, A. V., & Marcelo, B. M. (2015). Management of solid wastes from steel making and galvanizing processes: A brief review. Resources, Conservation and Recycling, 102, 49–57. IIARD International Journal of Geography & Environmental Management NPC. (2006). 2006 population and housing census of the Federal Republic of Nigeria. National Population Commission. Okumoko, D. P., & Izeze, E. O. (2020). Heavy metal contamination in selected dumpsites of Osubi, Warri, western Niger Delta, Nigeria. International Journal of Innovative Research and Development, 9(4). https://doi.org/10.24940/ijird/2020/v9/i4/JAN20090 Omoboriowo, A. O. (2018). Assessment of heavy metals contamination in soil due to leachate migration from open dumpsites in Agbor area. Pacific International Journal, 1(4), 199–204. Rezapour, S., Samadi, A., Kalavrouziotis, I. K., & Ghaemian, N. (2018). Impact of the uncontrolled leakage of leachate from a municipal solid waste landfill on soil in a cultivated-calcareous environment. Waste Management, 82, 51–61. https://doi.org/10.1016/j.wasman.2018.10.013 Salminen, R. (Ed.). (2005). Geochemical atlas of Europe. Part 1: Background information, methodology and maps. Geological Survey of Finland. Tomlinson, D. L., Wilson, J. G., Harris, C. R., & Jeffrey, D. W. (1980). Problems in the assessment of heavy-metal levels in estuaries and the formation of a pollution index. Helgoländer Meeresuntersuchungen, 33(1–4), 566–575. Turekian, K. K., & Wedepohl, K. H. (1961). Distribution of the elements in some major units of the earth's c.ust. Geological Society of America Bulletin, 72(2), 175–192. USEPA (1989). United State Environmental Protection. Risk assessment guidance for Superfund, Volume I: Human health evaluation manual (Part A) (EPA/540/1-89/002). United States Environmental Protection Agency. USEPA (2004). United State Environmental Protection, Risk assessment guidance for Superfund, Volume I: Human health evaluation manual (Part E, supplemental guidance for dermal risk assessment) (EPA/540/R/99/005). United States Environmental Protection Agency. Wuana, R. A., & Okieimen, F. E. (2011). Heavy metals in contaminated soils: A review of sources, chemistry, risks and best available strategies for remediation. ISRN Ecology, 2011, 402647. https://doi.org/10.5402/2011/402647