Comparison of ultrasonic, hotplate and microwave assisted digestion methods for the assessment of metals in agricultural soil: Environmental contamination and human health risk

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Naicker, P. N. Mahlambi, MM Mahlambi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4001090/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study presents the comparison of microwave assisted, hotplate and ultrasonic digestion methods for the analysis of metals in agricultural soils prior to ICP-OES determination. The percentage recoveries for all methods were within the acceptable range of 70–120% indicating that they can all be used for accurate determination of the target metals. However, hotplate can be recommended as it does not use too high pressure and temperature which can degrade analytes and it is easily accessible. On the hand, microwave require expensive instrument and thus its accessibility may be limited in other laboratories while ultrasonic is susceptible to underestimation of sample concentration due to incomplete digestion especially for complex samples as it uses lower temperatures. The metal concentrations obtained ranged from 0.60–256.4 mg/kg, however, all the metals were below the maximum permissible limits in soil except for Cr. The contamination factor and geo-accumulation index showed that the soil samples were mainly contaminated with Cu. The human health risk assessed indicated that dermal contact was the major exposure pathway in adults and children and children were more susceptible to non-carcinogenic risks. Although metal contamination in this study was not severe, consideration and monitoring of potential pollution hazards and human health risks in the future around these agricultural soils are required. Agricultural soil heavy metals digestion human health risk 1. Introduction The presence of heavy metals in agricultural soils can be naturally or due to unnatural/anthropogenic sources. The natural sources consist of atmospheric emissions, circulation of continental dust and weathering metal-enriched rocks (Naveedullah et al., 2013 ). In agricultural soils, the anthropogenic sources comprised of metal-enriched sewage sludges, irrigation water from wastewater treatment plants (WWTPs), livestock manure, application metal-based pesticides, municipal wastes, and other agricultural activities etc. The heavy metal contamination in agricultural soils proves to be concerning since they can accumulate in crops through soil, posing a significant threat to human health (Naveedullah et al., 2013 ). Agricultural soil is a complex environmental matrix consisting of organic matter, organic and inorganic compounds, which requires laborious sample pre-treatment. Sample digestion is one of the time-limiting steps in sample preparation. There are several sample digestions methods that can be employed to destroy the sample matrix (Kazi et al., 2008 ). Microwave, hotplate and ultrasonic assisted are used digestion methods in metal determination (Sastre et al., 2002 ), however, these digestion methods have their associated advantages and drawbacks. The microwave method is the most used digestion method, however, as it requires an expensive instrument, its availability can be limited. The hotplate and ultrasonic bath can be used as cheaper alternatives however being open systems, sample contamination, loss of volatile analytes and emission of acid fumes and incomplete dissolution can hinder their applicability. Once the digestion is completed, the samples can be analyzed using spectroscopic techniques such as inductively coupled plasma – optical emission or mass spectrometry in order to quantify the metal concentrations (Sastre et al., 2002 ). Once the metals are quantified, the contamination studies can be conducted using specifically the heavy metal concentrations to assess their contamination levels since they are persistent and toxic (Mussa et al. , 2020). In the estimation of heavy metal contamination due to anthropogenic activities. the contamination factor, geo-accumulation index can be calculated using mathematical expressions which include the metal and their respective baseline concentrations. The idea of background concentration is intended to provide an indication of natural heavy metal range prior to any contamination by human activity (Herselman et al., 2005 ). In addition, the potential ecological risk index can be calculated in order to assess the severity and risk levels of heavy metal contamination (Muzerengi, 2017 ). The human health risks can be calculated and assessed according to the non – carcinogenic and carcinogenic risk in adults and children where three main exposure pathways in humans are studied. These pathways included soil ingestion, dermal contact and air inhalation. The hazard quotient (HQ) and carcinogenic risks (CR) are evaluated on the basis of heavy metal presence in agricultural soil. The aim of this study was therefore to compare ultrasonic, hotplate and microwave digestion methods for metal determination in agricultural soils in KwaZulu-Nata. Also, to assess their environmental contamination level and potential ecological risk as well as and human health risk of heavy metals in the soil. There are fewer studies have been conducted in African countries on the occurrence and ecological risk assessment of heavy metals in agricultural soils. These include a study done in agricultural soils from Malawi, Southern Africa which indicated that metals were from anthropogenic and geogenic sources (Mussa et al. , 2020). Mussa and co-worker suggested that even though their study showed that the metals posses low to moderate ecological risk, actions to manage and control them need to be enforced to avoid their detrimental effects. Also, Muzerengi ( 2017 ) assessed heavy metal toxicity where the enrichment factor, contamination factor and geo-accumulation was calculated on soils near a Gold mine in Limpopo, South Africa. However, to the best of our knowledge the assessment of heavy metal concentration was done for the first time in the selected agricultural soils. In addition, no work has been conducted on the ecological risk and human health risk associated with heavy metals in KwaZulu-Natal agricultural soils. 2. Experimental 2.1 Study area and sample collection This study was conducted in the KwaZulu-Natal Province in South Africa (Pietermaritzburg city). Pietermaritzburg is the provincial capital city with an estimated population of 900 000 residents. Soils were sampled at five sampling sites which are agricultural lands (Curry Post, Cedara, Gilboa Farm, Richmond and Umgeni Valley). Portions of surface soil samples (0–10 cm depth) were randomly collected at different points around each site using Dutch auger (Reliance laboratory, Germany) and combined to make a representative sample of each site. The samples were stored in polyethylene containers and then transported to the laboratory where they were air dried in a fumehood for removal of excess moisture. They were then crushed and grinded using a clean and dry mortar and pestle followed by sieving through a 400 µm sieve to fineness prior to acid digestion. 2.2 Reagents, reference materials and standards The Purelab ultrapure water (18.2 MΩ.cm) was used in the preparation of all calibration standards and to clean all glassware along with dilute nitric acid. The 55% Nitric acid used in the preservation and digestion processes of the samples, 1000 mg/L ICP Multi-element standard and ULTRASPEC® Multi-Element Aqueous CRM in 5% nitric acid were purchased from Sigma Aldrich (Johannesburg, South Africa). The standard reference material of trace elements was employed to evaluate the accuracy of the method employed for determination of metals in agricultural soil samples. 2.3 Instrumentation The 720-ES ICP-OES instrument purchased from Varian (Johannesburg, South Africa) was used for determination of metals. The instrument was operated at a frequency of 40MHz, RF power of 1.00kW, a pneumatic concentric nebulizer was used at a flowrate of 0.75 L/min and an inert carrier gas (Argon) pumped at a rate of 15 rpm. The Multiwave 5000 microwave digester from Anton Paar (Johannesburg, South Africa). The heating plate and ultrasonic bath from Science Tech (Durban, South Africa) were used for digestion of the agricultural soil samples. A centrifuge purchased Shalom Laboratory (Durban, South Africa) was employed for the separation of extract from the soil. 2.4 Sample preparation 2.4.1 Microwave-assisted acid digestion The microwave assisted acid digestion method was adopted from the United States Environmental Protection Agency (US EPA 3051A). A 0.500g soil sample was mixed with 10 mL of HNO 3 in a microwave vessel which was then sealed and placed into the microwave system. The microwave digestion was conducted at 175 ± 5℃ in 5.5 ± 0.25 min and remained at 175 ± 5℃ for 4.5 min and the total digestion time was 10 min which was followed by cooling of the vessels to the initial temperature. After cooling, the contents were filtered using Whatman 70mm filter paper, centrifuged at 2000 rpm and allowed to settle. The filtrate was decanted into a 100 mL volumetric flask and filled to the mark with ultrapure water and analysed ICP-OES. 2.4.2 Hotplate assisted digestion The hotplate assisted digestion commonly classified as a wet digestion process was adopted from the United States Environmental Protection Agency (US EPA 3050B). A 0.500g of soil was mixed with 5 mL HNO 3 in a 100 mL beaker to form a slurry, it was then covered with a watch glass and placed onto the hotplate where it was heated at 95 ± 5 ℃ for 15 minutes without boiling. The contents were allowed to cool and a further 5 mL HNO 3 was added and placed on the hotplate at the same temperature which generated brown fumes indicating oxidation process. Once the brown fumes began to disappear, the watch glass was removed, and the contents were allowed to evaporate to approximately 5 mL. The total digestion time was 60 minutes. Upon the digestion completion, the samples were cooled, filtered and centrifuged at 2000 rpm. The filtrate was transferred into a 100 mL volumetric flask and filled up to the mark with ultrapure water and analysed by ICP-OES. 2.4.3 Ultrasonic-assisted acid digestion For the ultrasonic-assisted acid digestion method, a 0.500g of the soil sample was placed in a 100 mL Erlenmeyer flask followed by addition of 5 mL HNO 3 . The flask along with the sample-acid mixture was placed in an ultrasonic bath at a temperature of 80°C for 22.5 minutes. This was followed by addition of another 5 mL and further ultrasonicated for 22.5 minutes to make a total digestion time of 45 minutes. The flask was left to cool for 5 minutes and the digestate were filtered (Whatman 70mm) and centrifuged at 2000–3000 rpm and allowed to settle. Thereafter the filtrate was transferred into a 100 mL volumetric flask and made up to the mark with ultrapure water and analysed with ICP-OES. 2.5 Validation of the analytical method for the determination of metals in agricultural soil The ultrasonic, hotplate, microwave assisted digestion followed by ICP-OES analytical methods were validated in terms of linearity and percentage recovery test. The linearity was assessed over a concentration range of 0.05-10 mg/L. The accuracy of all digestion methods was assessed as percentage recoveries by spiking the soil samples with a mixture of the metals of interest to make a final concentration of 0.50 mg/kg. The spiked samples were then digested using hotplate, ultrasonic and microwave assisted method followed by analysis with ICP-OES, and the percentage recoveries were calculated. 2.6 Statistical analysis Statistical t-tests were conducted to investigate any differences in the mean percentage recoveries for all three digestion methods with a level of significance set at p < 0.05 assuming unequal variances. The metal concentrations were assessed using metal correlation coefficients to identify the common and potential sources. 2.7 Environmental and human health risk assessment of agricultural soil The qualitative assessment of agricultural soil was used to evaluate the environmental contamination was based on the calculation and classification of the contamination factor, pollution load, geo-accumulation, potential ecological risk indices. 2.7.1 Contamination factor (CF) and pollution load index (PLI) Contamination factor (CF) is a representation of the impact of trace heavy metals in the examined soil and is calculated in Eq. 1 . $$CF=\frac{{C}_{n}}{{C}_{ref}}$$ 1 where C n refers to the examined metal concentration in the studied soil and C ref is the background concentration of the examined metal in the soil. The pollution load index ( PLI ) represents the amount of times by which the metal content exceeds the natural background concentration and provides an indication of the overall metal toxicity in the studied sample. The pollution load index considers the contamination factor and number of metals at the sampling site in order to appropriately assess the degree of contamination using Eq. 2 , (Muzerengi, 2017 ). $$PLI={({CF}_{1}\times {CF}_{2}\times {CF}_{3}\times \dots \dots \times {CF}_{n})}^{\raisebox{1ex}{$1$}\!\left/ \!\raisebox{-1ex}{$n$}\right.}$$ 2 where n is the number of metals, in this study ( n = 6). PLI 1indicates deterioration of soil at the site. 2.7.2 Index of geo-accumulation (I GEO ) Geo-accumulation index ( I GEO ) were defined by Muller in 1969 in order to assess the contamination of soil. It is calculated using the background and sample metal concentration in a mathematical relationship shown in Eq. 3 $${I}_{GEO}={\text{log}}_{2}\left(\frac{{C}_{n}}{1.5\times {B}_{n}}\right)$$ 3 Where, C n is the estimated concentration of each element in soil, B n is the background concentration of the metal. The constant 1.5 is used to account for the natural variation and effect of small anthropogenic sources in the soil sample. The soil quality is determined by the I GEO values and classified into grades presented in Table 1 (Choi & Jeon, 2018 ) . Table 1 Classification grades of geo-accumulation index Grade Value Soil quality 0 I GEO ≪0 Practically uncontaminated 1 0 < I GEO <1 Uncontaminated to moderately contaminated 2 1 < I GEO <2 Moderately contaminated 3 2 < I GEO <3 Moderately to heavily contaminated 4 3 < I GEO <4 Heavily contaminated 5 4 < I GEO <5 Heavily to extremely contaminated 6 5 < I GEO Extremely contaminated 2.7.3 Potential Ecological Risk Index (PERI) The potential ecological risk index was proposed by Hakanson in 1980. It assesses the potential damage caused by heavy metal contamination which combines the assessment of ecological risk and environmental toxicity. The PERI is calculated using equations 4 – 6 . $$E{C}_{f}^{i}= \raisebox{1ex}{${C}_{D}^{i}$}\!\left/ \!\raisebox{-1ex}{${C}_{R}^{i}$}\right.$$ 4 $${E}_{R}^{i}= {T}_{R}^{i} \times {C}_{f}^{i}$$ 5 $$RI= {\sum }_{i-1}^{m}{E}_{R}^{i}$$ 6 Where, \({C}_{D}^{i}\) refers to the metal concentration in the soil sample, \({C}_{R}^{i}\) is the background concentration of the metal. \({C}_{f}^{i}\) is the contamination level of a single element, \({E}_{R}^{i}\) is the biological hazard of a single metal, RI is the overall biological hazard and \({T}_{R}^{i}\) is the biological toxicity weight of a single metal (Zn = 1, Cd = 30, Cr = 2, Pb, Ni, Co, Cu = 5). The RI values then classifies the risk levels of pollution as presented in Table 2 . Table 2 Classification of potential ecological risk index (PERI) as biological toxicity \({\varvec{E}}_{\varvec{R}}^{\varvec{i}}\) Pollution degree RI Risk level Risk Degree \({\varvec{E}}_{\varvec{R}}^{\varvec{i}}\) < 30 Slight RI < 40 A Slight 30 ≤ \({\varvec{E}}_{\varvec{R}}^{\varvec{i}}\) < 60 Medium 40 ≤ RI < 80 B Medium 60 ≤ \({\varvec{E}}_{\varvec{R}}^{\varvec{i}}\) < 120 Strong 80 ≤ RI < 160 C Strong 120 ≤ \({\varvec{E}}_{\varvec{R}}^{\varvec{i}}\) < 240 Very strong 160 ≤ RI < 320 D Very strong 240 ≤ \({\varvec{E}}_{\varvec{R}}^{\varvec{i}}\) Extremely strong 320 ≤ RI - - 2.7.4 Human health risk assessment Health risk assessment bridges the gap between the level of heavy metal contamination in the environment with a possibility of toxic effects in humans. The non-carcinogenic and carcinogenic risks are assessed by quantifying the hazard quotient (HQ) and cancer risk (CR) for the exposure of heavy metals. There are three exposure pathways considered for agricultural soil, these include soil ingestion (directly consumed or via consumption of agricultural produce), dermal contact and inhalation through soil vapour (Jiang et al., 2016 ). The average daily intake (ADD) is calculated for the non-carcinogenic risk for all three exposure pathways using Eq. 7 – 9 and thereafter the hazard quotient component is obtained by dividing the ADD for each heavy metal by their corresponding reference dosage (RfD) value (Eq. 10 ) in adults (18 + years) and children (1–17 years). The lifetime average potential daily dose (LADD) for carcinogens are calculated (Eq. 11 – 13 ) are multiplied by their respective cancer slope factor (SF) to calculate the cancer risk for each pathway (Eq. 14 ). Non-carcinogenic risk : $${ADD}_{ing}=\frac{C\times {IR}_{s}\times EF\times ED}{BW\times AT} \times {10}^{-6}$$ 7 $${ADD}_{dermal}=\frac{C\times SA\times AF\times ABS\times EF\times ED}{BW\times AT}$$ 8 $${ADD}_{inh}=\frac{C\times {IR}_{i}\times EF\times ED}{PEF\times BW\times AT}$$ 9 $$HQ=\sum \frac{{ADD}_{x}}{{RfD}_{x}}$$ 10 Carcinogenic risk : $${LADD}_{ing}=\frac{C\times {IR}_{s}\times EF\times ED}{BW\times LT} \times {10}^{-6}$$ 11 $${LADD}_{dermal}=\frac{C\times SA\times AF\times ABS\times EF\times ED}{BW\times LT}$$ 12 $${LADD}_{inh}=\frac{C\times {IR}_{i}\times EF\times ED}{PEF\times BW\times LT}$$ 13 $$CR=\sum \left({LADD}_{x}\times {SF}_{x}\right)$$ 14 The abbreviations and numerical parameters for the health risk assessment calculations are presented in Table S1 . Table S2 presented the reference dosage and slope factor obtained from literature for the calculation of the hazard quotient and cancer risk respectively. 3. Results and discussion 3.1 Validation of analytical method The calibration data along with the optimum wavelengths and maximum permissible limits (MRL values) for the metals analysed, are presented in Table 3 . The spectral interferences have been minimized by the selection of optimum wavelengths. The correlation coefficient for all metal analytes were greater than 0.99 which indicated a good degree of linearity. The recoveries ranging from 74–112% were obtained indicating good accuracy of the proposed methods. Statistical t-tests were conducted revealed that there is no significant difference between the mean recoveries for all the three digestion methods, since the p-values were found to be above 0.05. The p-values were p < 0.89 for microwave versus hotplate, p < 0.72 for microwave versus ultrasonic and p < 0.65 for hotplate versus ultrasonic digestion methods (Table S3). Table 3 Validation of analytical instrument Metal analyte Wavelength (nm) %Recoveries R 2 Micro HP Ultra Barium (Ba) 455.403 96 98 95 0.9998 Cobalt (Co) 228.615 84 81 85 0.9999 Chromium (Cr) 267.716 94 102 83 0.9995 Copper (Cu) 324.754 90 94 112 0.9999 Cadmium (Cd) 226.502 79 74 78 0.9999 Gallium (Ga) 287.423 100 101 99 0.9995 Lithium (Li) 670.783 98 86 83 0.9993 Nickel (Ni) 231.604 84 88 83 0.9999 Lead (Pb) 220.353 84 74 75 0.9997 Strontium (Sr) 407.771 81 82 97 0.9980 Thallium (Tl) 190.807 74 75 86 0.9995 Zinc (Zn) 213.857 78 81 83 0.9999 Micr – microwave assisted digestion, HP – hotplate digestion, Ultra – ultrasonic digestion 3.3 Metal concentrations in agricultural soils The average metal concentrations decreased in the following order: Ga > Cr > Ba > Cu > Ni > Zn > Sr > Co > Pb > Li (Table 4 ). The Cd and Tl concentrations were undetected at all sampling sites similarly to a study conducted on agricultural soil near Lake Chilwa in Malawi, Southern Africa, where Cd was also found to be undetected using the ICP-OES instrument (Mussa et al. , 2020) The Ga concentrations were the highest in all samples (27.9–256.4 mg/kg) with the highest concentration in Cedara. This is a concern since Ga is considered one of the emerging contaminants which are non-essential and potentially toxic in living organisms since they are susceptible to soil contamination (Liu et al., 2021 ). The concentration of Ga in Taiwan soils was found to range from < 3 to 70 mg/kg which is lower than the values obtained in this study (Liu et al., 2021 ). However, a maximum concentration of 437 mg/kg was reported from Poland soil collected near a zinc refinery plant which is higher than the maximum concentration observed in this study (Poledniok et al., 2012 ). The Ga occurs naturally in highly weathered soils and is said to vary with different soil types (Liu et al., 2021 ). The Ba concentrations ranged between 18.1–117.1 mg/kg, even though there are no defined maximum permissible limit assigned for Ba presence in soil, Ba concentrations of 200 mg/kg can be moderately toxic while concentrations of 500 mg/kg are considered toxic for plant life Pais et al., ( 1998 ). At Umgeni, Ba concentrations were found to be relatively high compared to the other sampling sites and despite it being lower than 200 mg/kg, Ba bioaccumulation in plants, specifically in edible plants can result in it transfer via the food chain (Ong et al., 2013 ). The Co, Ni, Pb and Zn were found to be below their respective permissible limits in all soil samples. In a study conducted by Mussa and co-workers, Ni, Pb and Zn maximum concentrations were 43.18, 16.81 and 99.21 mg/kg, respectively, which are relatively higher than the maximum concentrations obtained in this study (27.5, 3,3 and 36.7 mg/kg, respectively). The possible sources for higher concentrations of these heavy metals could be the application of fertilizers, pesticides (lead and zinc arsenate used in vegetable gardens) and manure. However, the low concentrations obtained for Co and Zn suggests that they may be from natural sources such as parent material of soils and lithogenic sources (Mussa et al. , 2020). Umgeni was found to be the most polluted since most metal concentrations observed were higher compared to the other sites. The Cr and Cu were above their maximum permissible limits. The possible sources of Cr and Cu in these agricultural soils could be due to their presence of farmyard manure, fertilizer or treated sludge as well as wastewater effluent possibly used for irrigation. These heavy metals can accumulate in the soil and migrate into crops via plant-root respiration (Mussa et al. , 2020). In general, the concentrations observed from the microwave and hotplate assisted digestion methods were comparable. These results suggest that even though the microwave is a widely used digestion method since it is a closed system process preventing loss of volatile analytes and sample contamination, the hotplate method can be used as a cheaper and accessible alternative (Sastre et al., 2002 ). The ultrasonic underestimated the concentrations which could be due to the temperature restriction of the ultrasonic bath causing low desorption and degradation of the sample matrix, ultimately resulting in incomplete digestion (Kazi et al. , 2009). Table 4 Average concentration (mg/kg) of metals in soil samples using the hotplate, ultrasonic and microwave assisted digestion methods (n = 3), and maximum allowable levels (MRL) Metal Curry Post Cedara Gilboa Farm Richmond Umgeni MRL mg/kg (WHO, 2001) Micro HP Ultra Micro HP Ultra Micro HP Ultra Micro HP Ultra Micro HP Ultra Ba 28.8 26.3 18.6 55.1 51.5 25.7 18.1 29.5 26.4 62.0 59.5 30.9 117.1 108.9 84.9 - Co 4.4 3.1 nd 11.4 10.5 1.6 9.9 17.5 12.4 4.1 4.0 nd 16.8 15.5 11.0 40 Cr 148.8 152.7 61.5 127.7 134.0 45.4 80.6 139.7 45.7 76.3 85.9 39.6 108.8 114.1 29.3 100.0 Cu 33.6 32.7 14.0 29.8 29.4 7.0 37.2 61.2 41.8 20.3 20.9 5.4 45.5 45.5 18.9 36 Cd nd nd nd Nd nd nd nd nd nd nd nd nd nd nd nd 0.8 Ga 246.5 218.0 49.8 256.4 240.5 65.1 139.0 226.8 81.2 185.4 178.2 35.5 158.7 157.9 27.9 - Li 1.3 0.6 nd 1.1 0.5 nd nd nd nd 1.1 0.6 nd 1.1 1.0 nd - Ni 13.8 15.7 5.9 20.6 21.7 4.5 18.3 27.5 12.8 12.1 14.8 7.0 32.5 34.1 15.6 35 Pb nd nd 2.1 nd 2.7 3.3 nd 1.4 3.0 2.8 nd 2.9 nd nd nd 85 Sr nd nd nd nd nd nd nd nd nd 2.1 1.9 nd 23.8 23.1 18.5 - Tl nd nd nd nd nd nd nd nd nd nd nd nd nd nd nd - Zn 12.8 12.4 2.1 13.5 12.3 nd 18.7 20.7 5.2 9.0 8.9 nd 36.7 35.8 12.8 100 nd – not detected 3.4 Contamination factor and geo-accumulation index The contamination factor and pollution load indexes for each site were calculated and presented in Table 5 . The contamination factors (CF) ranged from 0.41–2.12. 0.82–9.27 and 0.30–2.27 for Cr, Cu and Ni respectively, whilst the geo-accumulation index ranged from − 1.30–0.35, -0.61–1.82 and − 1.61–0.42 for Cr, Cu and Ni respectively. Based on CF values, the soil was contaminated with the studied heavy metals in the following order: Cu > Cr > Ni > Co > Pb > Zn. In a study conducted by Muzerengi ( 2017 ) on soil from the Limpopo Province, the CF value for Zn was also found to be the lowest where its presence can be derived predominantly due to natural processes or geogenic sources (Muzerengi, 2017 ) The pollution load index and geo-accumulation index were found to be greater than 1 in Gilboa farm and Umgeni which resulted in environmental concerns due to heavy metal contamination. The PLI at Curry Post and Richmond was found to be less than 1 which revealed that the sites were free from heavy metals contamination with negative geo-accumulation indices ( I GEO « 0 ) which is categorized as grade zero indicating that the soil quality is practically uncontaminated. The CF values for Cr and Ni were greater than 2 at Curry post and Umgeni indicating moderate contamination since these studied metals exceeded their respective background concentrations. It was also observed than no heavy metals in all sampling locations exceeded an CF values greater than 20. The highest CF value was obtained for Cu (9.27) at Gilboa farm suggesting significant contamination. Pollution of Cu can be due to agricultural activities since Cu is used in fertilizers for crop production in the forms of copper sulphate and copper oxide (Alengebawy et al., 2021 ). 3.5 Potential ecological risk index (PERI) The potential ecological risk index ( PERI) was calculated and presented in Table 6 . It reflected the general situation of pollution caused by the simultaneous presence of the six heavy metals. The RI values were classified in the slight risk level at Curry Post, Cedara and Richmond with ( RI < 40 ), while at Gilboa Farm and Umgeni, the RI values were in the medium risk level with 40 ≤ RI < 80. Soils contaminated by heavy metals can result in serious ecological risks and can negatively impact human health due to various forms of interaction (agriculture, livestock, etc.) where highly toxic heavy metals can enter via the food chain. Excessive accumulation of heavy metals in agricultural soils can affect the quality and safety of food and further increase the risk of serious diseases (cancer, kidney, liver damage, etc.), as well as impact the surrounding ecosystems (Santos-Francés et al., 2017 ). Although the pollution of metal was localized in a specific point, consideration of potential biological risks and steady monitoring are required. Table 5 Enrichment factor and geo-accumulation index for agricultural soil (n = 3) Metal Index Curry Post Cedara Gilboa Farm Richmond Umgeni Micro HP Ultra Micro HP Ultra Micro HP Ultra Micro HP Ultra Micro HP Ultra Co CF 0.22 0.16 - 0.57 0.53 0.08 0.50 0.88 0.62 0.21 0.20 - 0.84 0.78 0.55 I GEO -1.96 -2.27 - -0.97 -1.05 -2.93 -1.11 -0.54 -0.88 -1.99 -2.01 - -0.58 -0.66 -1.00 Cr CF 2.07 2.12 0.86 1.78 1.86 0.63 1.12 1.94 0.64 1.06 1.19 0.55 1.15 1.59 0.41 I GEO 0.32 0.35 -0.56 0.17 0.22 -0.87 -0.29 0.26 -0.86 -0.35 -0.23 -1.00 0.01 0.06 -1.30 Cu CF 5.09 4.95 2.12 4.52 4.45 1.06 5.64 9.27 6.33 3.08 3.17 0.82 6.89 6.89 2.86 I GEO 1.22 1.19 0.35 1.10 1.09 -0.35 1.32 1.82 1.44 0.72 0.75 -0.61 1.53 1.53 0.65 Ni CF 0.92 1.05 0.39 1.37 1.45 0.30 1.22 1.83 0.85 0.81 0.99 0.47 2.17 2.27 1.04 I GEO -0.49 -0.36 -1.34 -0.09 -0.04 -1.61 -0.21 0.20 -0.56 -0.62 -0.42 -1.17 0.37 0.42 -0.37 Pb CF - - 0.32 - 0.41 0.50 - 0.21 0.45 0.42 - 0.44 - - 0.21 I GEO - - -1.55 - -1.30 -1.10 - -1.96 -1.19 -1.26 - -1.23 - - -1.96 Zn CF 0.28 0.27 0.05 0.30 0.27 - 0.41 0.46 0.12 0.20 0.20 - 0.81 0.79 0.28 I GEO -1.67 -1.70 -3.47 -1.61 -1.71 - -1.29 -1.19 -2.57 -2.02 -2.03 - -0.61 -0.64 -1.67 PLI 0.90 0.86 0.40 1.13 0.94 0.38 1.10 1.19 0.69 0.60 0.68 0.55 1.73 1.72 0.59 Table 6 Potential ecological risk index for soil samples (n = 3) Metal Index Curry Post Cedara Gilboa Farm Richmond Umgeni Micro HP Ultra Micro HP Ultra Micro HP Ultra Micro HP Ultra Micro HP Ultra Co EC f 0.22 0.16 - 0.57 0.53 0.08 0.50 0.88 0.62 0.21 0.20 - 0.84 0.78 0.55 E R 1.10 0.78 - 2.85 2.63 0.40 2.48 4.38 3.10 1.03 1.00 - 4.20 3.88 2.75 Cr EC f 2.07 2.12 0.86 1.78 1.86 0.63 1.12 1.94 0.64 1.06 1.19 0.55 1.15 1.59 0.41 E R 4.14 4.25 1.71 3.55 3.73 1.26 2.24 3.89 1.27 2.12 2.39 1.10 3.03 3.17 0.82 Cu EC f 5.09 4.95 2.12 4.52 4.45 1.06 5.64 9.27 6.33 3.08 3.17 0.82 6.89 6.89 2.86 E R 25.5 24.8 10.6 22.6 22.3 5.3 28.2 46.4 31.7 15.4 15.8 4.1 34.5 34.5 14.3 Ni EC f 0.92 1.05 0.39 1.37 1.45 0.30 1.22 1.83 0.85 0.81 0.99 0.47 2.17 2.27 1.04 E R 4.60 5.23 1.97 6.87 7.23 1.50 6.10 9.17 4.27 4.03 4.93 2.33 10.8 11.4 5.20 Pb EC f - - 0.32 - 0.41 0.50 - 0.21 0.45 0.42 - 0.44 - - 0.21 E R - - 1.59 - 2.05 2.50 - 1.06 2.27 2.12 - 2.20 - - 1.06 Zn EC f 0.28 0.27 0.05 0.30 0.27 - 0.41 0.46 0.12 0.20 0.20 - 0.81 0.79 0.28 E R 0.28 0.27 0.05 0.30 0.27 - 0.41 0.46 0.12 0.20 0.20 - 0.81 0.79 0.28 RI 35.6 35.3 15.9 36.2 38.2 11.0 39.4 65.4 42.7 21.9 24.3 9.73 53.3 53.7 24.4 3.6 Metal correlation The heavy metal correlation was assessed for the microwave method since it is seen as the most common and widely used digestion method as a representation of the metal concentrations observed at each soil sample. A relative correlation was expressed as a number from − 1 to + 1 with 1 indicating a strong positive and − 1 indicating a strong negative relation. Also, to observe these results more clearly and easier, a heating map was used to express correlation degree using red being close to + 1 and blue being close to -1 (Table 7 ). The correlation coefficients demonstrated that Zn displayed a synergistic (strongly positive) relationship with Co, Cu and Ni thus owing to the possibility of a common source of these metals. The highly correlated heavy metals may potentially originate from the same source, specifically the use of agrochemicals such as manure, inorganic fertilizers and pesticides (Mussa et al. , 2020). The Cr displayed a strong negative (antagonistic) relationship with Co and Zn with R 2 values of -0.006 and − 0.015 respectively, which indicated that their concentrations are lower compared to Cr and potentially originated from natural sources. Table 7: Heavy metal correlation in soil samples by statistical analysis using concentration from microwave digestion 3.7 Human health risk assessment Five heavy metals (Cr, Cu, Ni, Pb and Zn) were considered in the assessment of human health risk as a result of their toxicity. The estimations of non-carcinogenic and carcinogenic health risks for the studied heavy metals in agricultural soil were calculated for adults (18 + years) and children (1–17 years) through the three major exposure pathways (Tables 8 and 9 ). The total hazard index (THI) values for adults and children were 1.63 and 8.69, respectively. Since the values were found to be greater than 1, it was deduced that people may experience non-carcinogenic effects however, children are more prone when compared to adults. The HQ values followed the following order for the studied heavy metals: Cr > Ni > Cu > Pb > Zn. Amongst the all the heavy metals, Cr in children had HQ values that exceeded 1. It was observed that the exposure pathways in both adults and children for the heavy metals decreased in the following order: dermal contact > soil ingestion > air inhalation. Dermal contact was the major exposure pathway in both adults and children where the contribution by dermal contact accounted for approximately 96.2% and 96.3% of their total hazard index respectively. Generally, children will experience higher non-carcinogenic risk when compared to adults hence, they are more prone to environmental contaminants. In a study conducted by Jiang et al., ( 2015 ), a similar observation was made, and this was found the physiological and behavioural characteristics such as high respiration rates per unit body weight and hand-to-mouth activities of children resulted in higher non-carcinogenic risks. The carcinogenic risk was estimated for Cr, Ni and Pb since Cu and Zn are not considered as carcinogenic. Only two out of three pathways were considered since the slope factor for dermal contact was not available. The carcinogenic risk estimation of Ni and Pb was through only one pathway, inhalation and ingestion respectively. The total carcinogenic risk (TCR) values were 2.71E-05 and 3.54E-05 for adults and children respectively (Table 9 ). Soil ingestion was the major pathway between the two considered. As per Fryer et al., ( 2006 ) study, the maximum tolerable risk of 1.00E-4 was higher than the calculated carcinogenic risks for both adults and children while children showed higher carcinogenic risks similarly to the non-carcinogenic trend. In the current study, the CR values for all examined heavy metals for both adults and children below the stipulated maximum tolerable risk in the range of 1.00E-6–1.00E-4 thus posing no significant health effect. The human health risk evaluated and the calculated HQ and CR values for hotplate and ultrasonic assisted digestion are presented in Tables S4 – S7. The trends were consistent with that observed using the microwave assisted digestion methods. Even though, no serious public health risk was identified in the study area, consistent estimation of human health risks is required. Table 8 Estimation of non-carcinogenic (Hazard quotient, HQ) from heavy metals in agricultural soil using microwave assisted digestion Adults (Aged 18+) Children (Aged 1–17) Heavy metal Sample locations Soil ingestion Dermal contact Air inhalation Total pathways Soil ingestion Dermal contact Air inhalation Total pathways Cr Curry Post 1.51E-02 4.30E-01 9.32E-04 4.46E-01 8.20E-02 2.30E + 00 9.61E-04 2.38E + 00 Cedara 1.30E-02 3.69E-01 8.00E-04 3.83E-01 7.04E-02 1.97E + 00 8.25E-04 2.04E + 00 Gilboa 8.18E-03 2.33E-01 5.05E-04 2.42E-01 4.44E-02 1.24E + 00 5.21E-04 1.28E + 00 Richmond 7.74E-03 2.21E-01 4.78E-04 2.29E-01 4.20E-02 1.18E + 00 4.93E-04 1.22E + 00 Umgeni 1.10E-02 3.15E-01 6.81E-04 3.27E-01 6.00E-02 1.68E + 00 7.03E-04 1.74E + 00 Cu Curry Post 2.56E-04 4.86E-05 - 3.05E-04 1.39E-03 2.59E-04 - 1.65E-03 Cedara 2.27E-04 4.31E-05 - 2.70E-04 1.23E-03 2.30E-04 - 1.46E-03 Gilboa 2.83E-04 5.38E-05 - 3.37E-04 1.54E-03 2.87E-04 - 1.83E-03 Richmond 1.54E-04 2.94E-05 - 1.83E-04 8.39E-04 1.57E-04 - 9.96E-04 Umgeni 3.46E-04 6.58E-05 - 4.12E-04 1.88E-03 3.51E-04 - 2.23E-03 Ni Curry Post 2.10E-04 4.43E-05 2.75E-05 2.82E-04 1.14E-03 2.37E-04 2.83E-05 1.41E-03 Cedara 3.14E-04 6.62E-05 4.10E-05 4.21E-04 1.70E-03 3.53E-04 4.23E-05 2.10E-03 Gilboa 2.79E-04 5.88E-05 3.64E-05 3.74E-04 1.51E-03 3.14E-04 3.76E-05 1.86E-03 Richmond 1.84E-04 3.89E-05 2.41E-05 2.47E-04 1.00E-03 2.07E-04 2.48E-05 1.23E-03 Umgeni 4.95E-04 1.04E-04 6.47E-05 6.64E-04 2.69E-03 5.57E-04 6.67E-05 3.31E-03 Pb Curry Post ND ND - 0.00E + 00 ND ND - 0.00E + 00 Cedara ND ND - 0.00E + 00 ND ND - 0.00E + 00 Gilboa ND ND - 0.00E + 00 ND ND - 0.00E + 00 Richmond 2.44E-04 9.25E-05 - 3.37E-04 1.32E-03 4.94E-04 - 1.81E-03 Umgeni ND ND - 0.00E + 00 ND ND - 0.00E + 00 Zn Curry Post 1.30E-05 3.70E-06 - 1.67E-05 7.05E-05 1.98E-05 - 9.03E-05 Cedara 1.37E-05 3.90E-06 - 1.76E-05 7.44E-05 2.08E-05 - 9.52E-05 Gilboa 1.90E-05 5.41E-06 - 2.44E-05 1.03E-04 2.89E-05 - 1.32E-04 Richmond 9.13E-06 2.60E-06 - 1.17E-05 4.96E-05 1.39E-05 - 6.35E-05 Umgeni 3.72E-05 1.06E-05 - 4.78E-05 2.02E-04 5.66E-05 - 2.59E-04 Total metals 5.81E-02 1.57E + 00 3.59E-03 1.63E + 00 3.16E-01 8.37E + 00 3.70E-03 8.69E + 00 Table 9 Estimation of carcinogenic (CR) from heavy metals in agricultural soil using microwave assisted digestion Adults (Aged 18+) Children (Aged 1–17) Heavy metal Sample locations Soil ingestion Dermal contact Air inhalation Total pathways Soil ingestion Dermal contact Air inhalation Total pathways Cr Curry Post 7,10E-06 - 3,51E-07 7,45E-06 9,63E-06 - 9,05E-08 9,72E-06 Cedara 6,09E-06 - 3,01E-07 6,39E-06 8,27E-06 - 7,76E-08 8,35E-06 Gilboa 3,84E-06 - 1,90E-07 4,03E-06 5,22E-06 - 4,90E-08 5,27E-06 Richmond 3,64E-06 - 1,80E-07 3,82E-06 4,94E-06 - 4,64E-08 4,99E-06 Umgeni 5,19E-06 - 2,56E-07 5,45E-06 7,04E-06 - 6,61E-08 7,11E-06 Ni Curry Post - - 6,35E-10 6,35E-10 - - 1,64E-10 1,64E-10 Cedara - - 9,48E-10 9,48E-10 - - 2,44E-10 2,44E-10 Gilboa - - 8,42E-10 8,42E-10 - - 2,17E-10 2,17E-10 Richmond - - 5,57E-10 5,57E-10 - - 1,44E-10 1,44E-10 Umgeni - - 1,50E-09 1,50E-09 - - 3,86E-10 3,86E-10 Pb Curry Post ND - - 0,00E + 00 ND - - 0,00E + 00 Cedara ND - - 0,00E + 00 ND - - 0,00E + 00 Gilboa ND - - 0,00E + 00 ND - - 0,00E + 00 Richmond 2,27E-09 - - 2,27E-09 3,08E-09 - - 3,08E-09 Umgeni ND - - 0,00E + 00 ND - - 0,00E + 00 Total metals 2,59E-05 - 1,28E-06 2,71E-05 3,51E-05 - 3,31E-07 3,54E-05 4. Conclusion The hotplate, ultrasonic and microwave assisted methods followed by ICP-OES were applied for metal determination in agricultural soil samples from different areas of KwaZulu-Natal. The percentage recoveries were all within the acceptable range of 70–120% indicating good accuracy for all methods. The metal concentrations decreased in the following order: Ga > Cr > Ba > Cu > Ni > Zn > Sr > Co > Pb > Li. The Ba and Cr were the two most abundant metals in all samples while Cd was undetected in all samples. The Co, Ni, Pb and Zn were found to be below whilst Cr and Zn were above their respective permissible limits in all soil samples. Umgeni soil was found to be the most polluted since most metals had higher concentrations than other sampling locations. Microwave and hotplate assisted digestion revealed similar metal concentrations while ultrasonic assisted digestion underestimated the concentrations. Despite the hotplate method being an open system method, it proved to be the most suitable substitute for microwave assisted digestion compared to the ultrasonic method. This is due to convenience, accessibility and being a cost-effective method, which does not require expensive instrumentation as opposed to the microwave method. Umgeni and Gilboa Farm were the two most contaminated sites as per the calculated contamination factor, pollution load, geo-accumulation, and potential ecological risk indices. The metal correlation revealed that Zn along with Co, Cu and Ni can possibly originate from the same source due to their synergistic relationship. The human health risk assessment revealed that the exposure pathways for non-carcinogenic risk decreased in the following order: dermal contact > soil ingestion > air inhalation. Conclusively, it was observed that children experienced higher non-carcinogenic risk as opposed to adults since the THQ values were greater than 1. The CR values were below the maximum tolerable limit range of 1.00E-6–1.00E-4, presenting no serious health risk. Although, heavy metal contamination was not severe at the selected sampling locations, the need for continuous assessment is required since these soils are used for agricultural activity. Declarations Discloser Statement The authors declare that there are no competing interests to declare. There are also no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding Declaration This work was sponsored by the National Research Foundation (NRF) of South Africa under Thuthuka Research Grant (Grant number: 121869). Author Contribution Precious Mahlambi, Mphilisi Mahlambi and Kavisha Naicker conceptualized and formulated the research study.Kavisha Naicker and Precious Mahlambi developed the method of sampling and analyses of the samples. Kavisha Naicker did the formal analysis and investigation of the research problem. Kavisha Naicker wrote the main manuscript including all figures, diagrams and statistical analysis.Precious Mahlambi and Mphilisi Mahlambi reviewed and edited the manuscript. Precious Mahlambi acquired funding for the project.Precious Mahlambi and Mphilisi Mahlambi supervised the project. Acknowledgements The authors would like to thank the University of KwaZulu Natal for providing facilities to carry out this research work. Data availability All data produced from this work has been included in the paper or presented as supplementary document. References Alengebawy, A., Abdelkhalek, S., Qureshi, S., & Wang, M. (2021). Heavy Metals and Pesticides Toxicity in Agricultural Soil and Plants: Ecological Risks and Human Health Implications. Toxics, 9, 1-33. https://doi.org/10.3390/toxics/9030042 Choi, J., & Jeon, S. (2018). A Geo-statistical Assessment of Heavy Metal Pollution n the Soil Around a Ship Building Yard in Busan, Korea. Journal of the Korean Society of Marine and Environmental Safety, 24 , 907-915. https://doi.org/10.7837/kosomes.2018.24.7.907 Fryer, M., Collins, C., Ferrier, H., Colvile, R., & Nieuwenhuijsen, M. (2006). Human exposure modelling for chemical risk assessment: a review of current approach and research and policy impications. Environmental Science and Policy, 9, 261-274. https://10.1016/j.envsci.2005.11.011 Herselman, J., Steyn, C., & Fey, M. (2005). Baseline concentration of Cd, Co, Cr, Cu, Pb, Ni and Zn in surface soils of South Africa. South African Journal of Science, 10, 509-512. https://hdl.handle.net/10019.1/9660 Jiang, Y., Chao, S., Liu, J., Yang, Y., Chen, Y., Zhang, A., & Cao, H. (2016). Source apportionment and health risk assessment of heavy metals in soil for a township in Jiangsu Province, China. Chemosphere 168, 1658-1668. https://dx.doi.org/10.1016/j.chemosphere/2016/11.088 Jiang, Y., Zeng, X., Fan, X., Chao, S., Zhu, M., Cao, H. (2015). Levels of arsenic pollution in daily foodstuffs and soils and its associated human health risk in a town in Jiangsu Province, China. Ecotoxicology and Environmental Safety, 122, 198-204. https://dx.doi.org/10.1016/j.ecoenv Kazi. T.. Jamali. M.. Arian. M.. Afridi. J. N.. Sarfraz. R.. & Ansari. R. (2008). Evaluation of an ultrasonic acid digestion procedure for total heavy metals. Journal of Hazardous Materials, 161, 1391-1398. https://dx.doi.org/10.1016/j.jhazmat.2008.04.103 Liu, Y., Shaheen, S., Rinklebe, J., & Hseu, Z. (2021). Pedogeochemical distribution of gallium, indium and thallium, their potential availability and associated risk in highly-weathered soil profiles of Taiwan. Environmental Research, 197 , 110994. https://doi.org/10.1016/j.envres.2021.110994 Mussa, C., Biswick, T., Changadeya, W., Mapoma, H., & Junginger, A. (2010). Occurrence and ecological risk assessment of heavy metals in agricultural soils of Lake Chilwa catchment in Malawi, Southern Africa. SN Applied Sciences, 2, 1-8. https://doi.org/10.1007/s42452-020-03718-7 Muzerengi, C. (2017). Enrichment and Geoaccumulation of Pb, Zn, As, Cd and Cr in soils near New Union Gold Mine, Limpopo Province. Mine Water and Circular Economy , 720-727. https://www.imwa.info/docs/imwa_2017/IMWA2017_Muzerengi_720.pdf Naveedullah, H, M. Z., Yu, C., Shen, H., Duan, D., Shen, C., Lou, L., & Chen, Y. (2013). Risk assessment of heavy metals pollution in agricultural soils of siling reservoir watershed in Zhejiang Province, China. BioMed Research International, 2013, 590306. https://doi.org/10.1155/2013/590306 Ong, G., Yap. C., Mahmood, M., Tan. S., & Hamzah, S. (2013). Barium Levels in Soils and Centella asiatica. Tropical Life Science Research, 24, 55-70. PMID: 24575242; PMCID: PMC3799414. Pais, I., Benton, J., & Jones, Jr. (1998). The handbook of trace elements. Boca Raton: St Lucie Press. 27, 223. https://doi.org/10.2134/jeq1998.00472425002700040041 Poledniok, J., Kita, A., & Zerzucha, P. (2012). Spectrophotometric and Inductively Coupled Plasma–Optical Emission Spectroscopy Determination of Gallium in Natural Soils and Soils Polluted by Industry: Relationships between Elements. Communinications in Soil Science and Plant Analysis, 43, 1121-1135. https://doi.org/10.1080/2012/662561 Santos-Francés, F., Martínez-Graña, A., Rojo, P., & Sánchez, A. (2017). Geochemical Background and Baseline Values Determination and Spatial Distribution of Heavy Metal Pollution in Soils of the Andes Mountain Range (Cajamarca-Huancavelica, Peru). International Journal of Environmental Research and Public Health, 14, 1-22. https://doi.org/10.3390/ijerph14080859 Sastre, J., Sahuquillo, A., Vidal, M., & Rauret, G. (2002). Determination of Cd. Cu. Pb and Zn in environmental samples: microwave-assisted total digestion versus aqua regia and nitric acid extraction. Analytica Chimica Acta, 462, 59-72 https://doi.org/10.1016/S0003-2670(02)00307-0 World Health Organization (WHO). (2001). Geneva: World Health Organization. http://www.inchem.org/documents/ehc/ehc221.htm (accessed 9 October 2021). Additional Declarations No competing interests reported. Supplementary Files EnvironmentalMonitoringandAssessmentsupportingdoc.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Introduction","content":"\u003cp\u003eThe presence of heavy metals in agricultural soils can be naturally or due to unnatural/anthropogenic sources. The natural sources consist of atmospheric emissions, circulation of continental dust and weathering metal-enriched rocks (Naveedullah et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In agricultural soils, the anthropogenic sources comprised of metal-enriched sewage sludges, irrigation water from wastewater treatment plants (WWTPs), livestock manure, application metal-based pesticides, municipal wastes, and other agricultural activities etc. The heavy metal contamination in agricultural soils proves to be concerning since they can accumulate in crops through soil, posing a significant threat to human health (Naveedullah et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAgricultural soil is a complex environmental matrix consisting of organic matter, organic and inorganic compounds, which requires laborious sample pre-treatment. Sample digestion is one of the time-limiting steps in sample preparation. There are several sample digestions methods that can be employed to destroy the sample matrix (Kazi et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Microwave, hotplate and ultrasonic assisted are used digestion methods in metal determination (Sastre et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), however, these digestion methods have their associated advantages and drawbacks. The microwave method is the most used digestion method, however, as it requires an expensive instrument, its availability can be limited. The hotplate and ultrasonic bath can be used as cheaper alternatives however being open systems, sample contamination, loss of volatile analytes and emission of acid fumes and incomplete dissolution can hinder their applicability. Once the digestion is completed, the samples can be analyzed using spectroscopic techniques such as inductively coupled plasma \u0026ndash; optical emission or mass spectrometry in order to quantify the metal concentrations (Sastre et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Once the metals are quantified, the contamination studies can be conducted using specifically the heavy metal concentrations to assess their contamination levels since they are persistent and toxic (Mussa \u003cem\u003eet al.\u003c/em\u003e, 2020).\u003c/p\u003e \u003cp\u003eIn the estimation of heavy metal contamination due to anthropogenic activities. the contamination factor, geo-accumulation index can be calculated using mathematical expressions which include the metal and their respective baseline concentrations. The idea of background concentration is intended to provide an indication of natural heavy metal range prior to any contamination by human activity (Herselman et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). In addition, the potential ecological risk index can be calculated in order to assess the severity and risk levels of heavy metal contamination (Muzerengi, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The human health risks can be calculated and assessed according to the non \u0026ndash; carcinogenic and carcinogenic risk in adults and children where three main exposure pathways in humans are studied. These pathways included soil ingestion, dermal contact and air inhalation. The hazard quotient (HQ) and carcinogenic risks (CR) are evaluated on the basis of heavy metal presence in agricultural soil.\u003c/p\u003e \u003cp\u003eThe aim of this study was therefore to compare ultrasonic, hotplate and microwave digestion methods for metal determination in agricultural soils in KwaZulu-Nata. Also, to assess their environmental contamination level and potential ecological risk as well as and human health risk of heavy metals in the soil. There are fewer studies have been conducted in African countries on the occurrence and ecological risk assessment of heavy metals in agricultural soils. These include a study done in agricultural soils from Malawi, Southern Africa which indicated that metals were from anthropogenic and geogenic sources (Mussa \u003cem\u003eet al.\u003c/em\u003e, 2020). Mussa and co-worker suggested that even though their study showed that the metals posses low to moderate ecological risk, actions to manage and control them need to be enforced to avoid their detrimental effects. Also, Muzerengi (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) assessed heavy metal toxicity where the enrichment factor, contamination factor and geo-accumulation was calculated on soils near a Gold mine in Limpopo, South Africa. However, to the best of our knowledge the assessment of heavy metal concentration was done for the first time in the selected agricultural soils. In addition, no work has been conducted on the ecological risk and human health risk associated with heavy metals in KwaZulu-Natal agricultural soils.\u003c/p\u003e"},{"header":"2. Experimental","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study area and sample collection\u003c/h2\u003e \u003cp\u003eThis study was conducted in the KwaZulu-Natal Province in South Africa (Pietermaritzburg city). Pietermaritzburg is the provincial capital city with an estimated population of 900 000 residents. Soils were sampled at five sampling sites which are agricultural lands (Curry Post, Cedara, Gilboa Farm, Richmond and Umgeni Valley). Portions of surface soil samples (0\u0026ndash;10 cm depth) were randomly collected at different points around each site using Dutch auger (Reliance laboratory, Germany) and combined to make a representative sample of each site. The samples were stored in polyethylene containers and then transported to the laboratory where they were air dried in a fumehood for removal of excess moisture. They were then crushed and grinded using a clean and dry mortar and pestle followed by sieving through a 400 \u0026micro;m sieve to fineness prior to acid digestion.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Reagents, reference materials and standards\u003c/h2\u003e \u003cp\u003eThe Purelab ultrapure water (18.2 MΩ.cm) was used in the preparation of all calibration standards and to clean all glassware along with dilute nitric acid. The 55% Nitric acid used in the preservation and digestion processes of the samples, 1000 mg/L ICP Multi-element standard and ULTRASPEC\u0026reg; Multi-Element Aqueous CRM in 5% nitric acid were purchased from Sigma Aldrich (Johannesburg, South Africa). The standard reference material of trace elements was employed to evaluate the accuracy of the method employed for determination of metals in agricultural soil samples.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Instrumentation\u003c/h2\u003e \u003cp\u003eThe 720-ES ICP-OES instrument purchased from Varian (Johannesburg, South Africa) was used for determination of metals. The instrument was operated at a frequency of 40MHz, RF power of 1.00kW, a pneumatic concentric nebulizer was used at a flowrate of 0.75 L/min and an inert carrier gas (Argon) pumped at a rate of 15 rpm. The Multiwave 5000 microwave digester from Anton Paar (Johannesburg, South Africa). The heating plate and ultrasonic bath from Science Tech (Durban, South Africa) were used for digestion of the agricultural soil samples. A centrifuge purchased Shalom Laboratory (Durban, South Africa) was employed for the separation of extract from the soil.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Sample preparation\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.4.1 Microwave-assisted acid digestion\u003c/h2\u003e \u003cp\u003eThe microwave assisted acid digestion method was adopted from the United States Environmental Protection Agency (US EPA 3051A). A 0.500g soil sample was mixed with 10 mL of HNO\u003csub\u003e3\u003c/sub\u003e in a microwave vessel which was then sealed and placed into the microwave system. The microwave digestion was conducted at 175\u0026thinsp;\u0026plusmn;\u0026thinsp;5℃ in 5.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25 min and remained at 175\u0026thinsp;\u0026plusmn;\u0026thinsp;5℃ for 4.5 min and the total digestion time was 10 min which was followed by cooling of the vessels to the initial temperature. After cooling, the contents were filtered using Whatman 70mm filter paper, centrifuged at 2000 rpm and allowed to settle. The filtrate was decanted into a 100 mL volumetric flask and filled to the mark with ultrapure water and analysed ICP-OES.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.4.2 Hotplate assisted digestion\u003c/h2\u003e \u003cp\u003eThe hotplate assisted digestion commonly classified as a wet digestion process was adopted from the United States Environmental Protection Agency (US EPA 3050B). A 0.500g of soil was mixed with 5 mL HNO\u003csub\u003e3\u003c/sub\u003e in a 100 mL beaker to form a slurry, it was then covered with a watch glass and placed onto the hotplate where it was heated at 95\u0026thinsp;\u0026plusmn;\u0026thinsp;5 ℃ for 15 minutes without boiling. The contents were allowed to cool and a further 5 mL HNO\u003csub\u003e3\u003c/sub\u003e was added and placed on the hotplate at the same temperature which generated brown fumes indicating oxidation process. Once the brown fumes began to disappear, the watch glass was removed, and the contents were allowed to evaporate to approximately 5 mL. The total digestion time was 60 minutes. Upon the digestion completion, the samples were cooled, filtered and centrifuged at 2000 rpm. The filtrate was transferred into a 100 mL volumetric flask and filled up to the mark with ultrapure water and analysed by ICP-OES.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.4.3 Ultrasonic-assisted acid digestion\u003c/h2\u003e \u003cp\u003eFor the ultrasonic-assisted acid digestion method, a 0.500g of the soil sample was placed in a 100 mL Erlenmeyer flask followed by addition of 5 mL HNO\u003csub\u003e3\u003c/sub\u003e. The flask along with the sample-acid mixture was placed in an ultrasonic bath at a temperature of 80\u0026deg;C for 22.5 minutes. This was followed by addition of another 5 mL and further ultrasonicated for 22.5 minutes to make a total digestion time of 45 minutes. The flask was left to cool for 5 minutes and the digestate were filtered (Whatman 70mm) and centrifuged at 2000\u0026ndash;3000 rpm and allowed to settle. Thereafter the filtrate was transferred into a 100 mL volumetric flask and made up to the mark with ultrapure water and analysed with ICP-OES.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Validation of the analytical method for the determination of metals in agricultural soil\u003c/h2\u003e \u003cp\u003eThe ultrasonic, hotplate, microwave assisted digestion followed by ICP-OES analytical methods were validated in terms of linearity and percentage recovery test. The linearity was assessed over a concentration range of 0.05-10 mg/L. The accuracy of all digestion methods was assessed as percentage recoveries by spiking the soil samples with a mixture of the metals of interest to make a final concentration of 0.50 mg/kg. The spiked samples were then digested using hotplate, ultrasonic and microwave assisted method followed by analysis with ICP-OES, and the percentage recoveries were calculated.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Statistical analysis\u003c/h2\u003e \u003cp\u003eStatistical t-tests were conducted to investigate any differences in the mean percentage recoveries for all three digestion methods with a level of significance set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 assuming unequal variances. The metal concentrations were assessed using metal correlation coefficients to identify the common and potential sources.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Environmental and human health risk assessment of agricultural soil\u003c/h2\u003e \u003cp\u003eThe qualitative assessment of agricultural soil was used to evaluate the environmental contamination was based on the calculation and classification of the contamination factor, pollution load, geo-accumulation, potential ecological risk indices.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e2.7.1 Contamination factor (CF) and pollution load index (PLI)\u003c/h2\u003e \u003cp\u003eContamination factor (CF) is a representation of the impact of trace heavy metals in the examined soil and is calculated in Eq.\u0026nbsp;\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$CF=\\frac{{C}_{n}}{{C}_{ref}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e refers to the examined metal concentration in the studied soil and \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003eref\u003c/em\u003e\u003c/sub\u003e is the background concentration of the examined metal in the soil.\u003c/p\u003e \u003cp\u003eThe pollution load index (\u003cem\u003ePLI\u003c/em\u003e) represents the amount of times by which the metal content exceeds the natural background concentration and provides an indication of the overall metal toxicity in the studied sample. The pollution load index considers the contamination factor and number of metals at the sampling site in order to appropriately assess the degree of contamination using Eq.\u0026nbsp;\u003cspan refid=\"Equ2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, (Muzerengi, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$PLI={({CF}_{1}\\times {CF}_{2}\\times {CF}_{3}\\times \\dots \\dots \\times {CF}_{n})}^{\\raisebox{1ex}{$1$}\\!\\left/ \\!\\raisebox{-1ex}{$n$}\\right.}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cem\u003en\u003c/em\u003e is the number of metals, in this study (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6). \u003cem\u003ePLI\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;1 indicates that the site is free from contamination, \u003cem\u003ePLI\u0026thinsp;=\u003c/em\u003e\u0026thinsp;1 implies that contamination is at background level and lastly \u003cem\u003ePLI\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;1indicates deterioration of soil at the site.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e2.7.2 Index of geo-accumulation (I\u003csub\u003eGEO\u003c/sub\u003e)\u003c/h2\u003e \u003cp\u003eGeo-accumulation index (\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e) were defined by Muller in 1969 in order to assess the contamination of soil. It is calculated using the background and sample metal concentration in a mathematical relationship shown in Eq.\u0026nbsp;\u003cspan refid=\"Equ3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$${I}_{GEO}={\\text{log}}_{2}\\left(\\frac{{C}_{n}}{1.5\\times {B}_{n}}\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere, \u003cem\u003eC\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e is the estimated concentration of each element in soil, \u003cem\u003eB\u003c/em\u003e\u003csub\u003e\u003cem\u003en\u003c/em\u003e\u003c/sub\u003e is the background concentration of the metal. The constant 1.5 is used to account for the natural variation and effect of small anthropogenic sources in the soil sample. The soil quality is determined by the \u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e values and classified into grades presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(Choi \u0026amp; Jeon, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2018\u003c/span\u003e\u003cem\u003e)\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification grades of geo-accumulation index\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSoil quality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e ≪0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePractically uncontaminated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e \u0026lt;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUncontaminated to moderately contaminated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e \u0026lt;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerately contaminated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e \u0026lt;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModerately to heavily contaminated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e \u0026lt;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHeavily contaminated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e \u0026lt;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHeavily to extremely contaminated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u0026thinsp;\u0026lt;\u0026thinsp;\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eExtremely contaminated\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e2.7.3 Potential Ecological Risk Index (PERI)\u003c/h2\u003e \u003cp\u003eThe potential ecological risk index was proposed by Hakanson in 1980. It assesses the potential damage caused by heavy metal contamination which combines the assessment of ecological risk and environmental toxicity. The PERI is calculated using equations \u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Equ6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$E{C}_{f}^{i}= \\raisebox{1ex}{${C}_{D}^{i}$}\\!\\left/ \\!\\raisebox{-1ex}{${C}_{R}^{i}$}\\right.$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$${E}_{R}^{i}= {T}_{R}^{i} \\times {C}_{f}^{i}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$$RI= {\\sum }_{i-1}^{m}{E}_{R}^{i}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({C}_{D}^{i}\\)\u003c/span\u003e\u003c/span\u003e refers to the metal concentration in the soil sample, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({C}_{R}^{i}\\)\u003c/span\u003e\u003c/span\u003e is the background concentration of the metal. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({C}_{f}^{i}\\)\u003c/span\u003e\u003c/span\u003e is the contamination level of a single element, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({E}_{R}^{i}\\)\u003c/span\u003e\u003c/span\u003e is the biological hazard of a single metal, RI is the overall biological hazard and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({T}_{R}^{i}\\)\u003c/span\u003e\u003c/span\u003e is the biological toxicity weight of a single metal (Zn\u0026thinsp;=\u0026thinsp;1, Cd\u0026thinsp;=\u0026thinsp;30, Cr\u0026thinsp;=\u0026thinsp;2, Pb, Ni, Co, Cu\u0026thinsp;=\u0026thinsp;5). The RI values then classifies the risk levels of pollution as presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification of potential ecological risk index (PERI) as biological toxicity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{E}}_{\\varvec{R}}^{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePollution degree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRisk level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRisk Degree\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{E}}_{\\varvec{R}}^{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e \u0026lt; 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSlight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eRI\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSlight\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30 \u0026le;\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{E}}_{\\varvec{R}}^{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e\u0026lt; 60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u0026thinsp;\u0026le;\u0026thinsp;\u003cem\u003eRI\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60 \u0026le; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{E}}_{\\varvec{R}}^{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e \u0026lt; 120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80\u0026thinsp;\u0026le;\u0026thinsp;\u003cem\u003eRI\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStrong\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e120 \u0026le; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{E}}_{\\varvec{R}}^{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e \u0026lt; 240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery strong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160\u0026thinsp;\u0026le;\u0026thinsp;\u003cem\u003eRI\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVery strong\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e240 \u0026le; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{E}}_{\\varvec{R}}^{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExtremely strong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e320\u0026thinsp;\u0026le;\u0026thinsp;\u003cem\u003eRI\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e2.7.4 Human health risk assessment\u003c/h2\u003e \u003cp\u003eHealth risk assessment bridges the gap between the level of heavy metal contamination in the environment with a possibility of toxic effects in humans. The non-carcinogenic and carcinogenic risks are assessed by quantifying the hazard quotient (HQ) and cancer risk (CR) for the exposure of heavy metals. There are three exposure pathways considered for agricultural soil, these include soil ingestion (directly consumed or via consumption of agricultural produce), dermal contact and inhalation through soil vapour (Jiang et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The average daily intake (ADD) is calculated for the non-carcinogenic risk for all three exposure pathways using Eq.\u0026nbsp;\u003cspan refid=\"Equ7\" class=\"InternalRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Equ9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and thereafter the hazard quotient component is obtained by dividing the ADD for each heavy metal by their corresponding reference dosage (RfD) value (Eq.\u0026nbsp;\u003cspan refid=\"Equ10\" class=\"InternalRef\"\u003e10\u003c/span\u003e) in adults (18\u0026thinsp;+\u0026thinsp;years) and children (1\u0026ndash;17 years). The lifetime average potential daily dose (LADD) for carcinogens are calculated (Eq.\u0026nbsp;\u003cspan refid=\"Equ11\" class=\"InternalRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Equ13\" class=\"InternalRef\"\u003e13\u003c/span\u003e) are multiplied by their respective cancer slope factor (SF) to calculate the cancer risk for each pathway (Eq.\u0026nbsp;\u003cspan refid=\"Equ14\" class=\"InternalRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eNon-carcinogenic risk\u003c/em\u003e:\u003cdiv id=\"Equ7\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ7\" name=\"EquationSource\"\u003e\n$${ADD}_{ing}=\\frac{C\\times {IR}_{s}\\times EF\\times ED}{BW\\times AT} \\times {10}^{-6}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e7\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ8\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ8\" name=\"EquationSource\"\u003e\n$${ADD}_{dermal}=\\frac{C\\times SA\\times AF\\times ABS\\times EF\\times ED}{BW\\times AT}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e8\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ9\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ9\" name=\"EquationSource\"\u003e\n$${ADD}_{inh}=\\frac{C\\times {IR}_{i}\\times EF\\times ED}{PEF\\times BW\\times AT}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e9\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ10\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ10\" name=\"EquationSource\"\u003e\n$$HQ=\\sum \\frac{{ADD}_{x}}{{RfD}_{x}}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e10\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eCarcinogenic risk\u003c/em\u003e:\u003cdiv id=\"Equ11\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ11\" name=\"EquationSource\"\u003e\n$${LADD}_{ing}=\\frac{C\\times {IR}_{s}\\times EF\\times ED}{BW\\times LT} \\times {10}^{-6}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e11\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ12\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ12\" name=\"EquationSource\"\u003e\n$${LADD}_{dermal}=\\frac{C\\times SA\\times AF\\times ABS\\times EF\\times ED}{BW\\times LT}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e12\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ13\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ13\" name=\"EquationSource\"\u003e\n$${LADD}_{inh}=\\frac{C\\times {IR}_{i}\\times EF\\times ED}{PEF\\times BW\\times LT}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e13\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ14\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ14\" name=\"EquationSource\"\u003e\n$$CR=\\sum \\left({LADD}_{x}\\times {SF}_{x}\\right)$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e14\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe abbreviations and numerical parameters for the health risk assessment calculations are presented in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Table S2 presented the reference dosage and slope factor obtained from literature for the calculation of the hazard quotient and cancer risk respectively.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Validation of analytical method\u003c/h2\u003e \u003cp\u003eThe calibration data along with the optimum wavelengths and maximum permissible limits (MRL values) for the metals analysed, are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The spectral interferences have been minimized by the selection of optimum wavelengths. The correlation coefficient for all metal analytes were greater than 0.99 which indicated a good degree of linearity. The recoveries ranging from 74\u0026ndash;112% were obtained indicating good accuracy of the proposed methods.\u003c/p\u003e \u003cp\u003eStatistical t-tests were conducted revealed that there is no significant difference between the mean recoveries for all the three digestion methods, since the p-values were found to be above 0.05. The p-values were p\u0026thinsp;\u0026lt;\u0026thinsp;0.89 for microwave versus hotplate, p\u0026thinsp;\u0026lt;\u0026thinsp;0.72 for microwave versus ultrasonic and p\u0026thinsp;\u0026lt;\u0026thinsp;0.65 for hotplate versus ultrasonic digestion methods (Table S3).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eValidation of analytical instrument\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMetal analyte\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWavelength (nm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e%Recoveries\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eMicro\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eHP\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eUltra\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBarium (Ba)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e455.403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9998\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCobalt (Co)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e228.615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChromium (Cr)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e267.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9995\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCopper (Cu)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e324.754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCadmium (Cd)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e226.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGallium (Ga)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e287.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9995\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLithium (Li)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e670.783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9993\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNickel (Ni)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e231.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLead (Pb)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e220.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9997\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStrontium (Sr)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e407.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9980\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThallium (Tl)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e190.807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9995\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZinc (Zn)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e213.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eMicr \u0026ndash; microwave assisted digestion, HP \u0026ndash; hotplate digestion, Ultra \u0026ndash; ultrasonic digestion\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Metal concentrations in agricultural soils\u003c/h2\u003e \u003cp\u003eThe average metal concentrations decreased in the following order: Ga\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Ba\u0026thinsp;\u0026gt;\u0026thinsp;Cu\u0026thinsp;\u0026gt;\u0026thinsp;Ni\u0026thinsp;\u0026gt;\u0026thinsp;Zn\u0026thinsp;\u0026gt;\u0026thinsp;Sr\u0026thinsp;\u0026gt;\u0026thinsp;Co\u0026thinsp;\u0026gt;\u0026thinsp;Pb\u0026thinsp;\u0026gt;\u0026thinsp;Li (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The Cd and Tl concentrations were undetected at all sampling sites similarly to a study conducted on agricultural soil near Lake Chilwa in Malawi, Southern Africa, where Cd was also found to be undetected using the ICP-OES instrument (Mussa \u003cem\u003eet al.\u003c/em\u003e, 2020)\u003c/p\u003e \u003cp\u003eThe Ga concentrations were the highest in all samples (27.9\u0026ndash;256.4 mg/kg) with the highest concentration in Cedara. This is a concern since Ga is considered one of the emerging contaminants which are non-essential and potentially toxic in living organisms since they are susceptible to soil contamination (Liu et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The concentration of Ga in Taiwan soils was found to range from \u0026lt;\u0026thinsp;3 to 70 mg/kg which is lower than the values obtained in this study (Liu et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, a maximum concentration of 437 mg/kg was reported from Poland soil collected near a zinc refinery plant which is higher than the maximum concentration observed in this study (Poledniok et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The Ga occurs naturally in highly weathered soils and is said to vary with different soil types (Liu et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Ba concentrations ranged between 18.1\u0026ndash;117.1 mg/kg, even though there are no defined maximum permissible limit assigned for Ba presence in soil, Ba concentrations of 200 mg/kg can be moderately toxic while concentrations of 500 mg/kg are considered toxic for plant life Pais et al., (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). At Umgeni, Ba concentrations were found to be relatively high compared to the other sampling sites and despite it being lower than 200 mg/kg, Ba bioaccumulation in plants, specifically in edible plants can result in it transfer via the food chain (Ong et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Co, Ni, Pb and Zn were found to be below their respective permissible limits in all soil samples. In a study conducted by Mussa and co-workers, Ni, Pb and Zn maximum concentrations were 43.18, 16.81 and 99.21 mg/kg, respectively, which are relatively higher than the maximum concentrations obtained in this study (27.5, 3,3 and 36.7 mg/kg, respectively). The possible sources for higher concentrations of these heavy metals could be the application of fertilizers, pesticides (lead and zinc arsenate used in vegetable gardens) and manure. However, the low concentrations obtained for Co and Zn suggests that they may be from natural sources such as parent material of soils and lithogenic sources (Mussa \u003cem\u003eet al.\u003c/em\u003e, 2020).\u003c/p\u003e \u003cp\u003eUmgeni was found to be the most polluted since most metal concentrations observed were higher compared to the other sites. The Cr and Cu were above their maximum permissible limits. The possible sources of Cr and Cu in these agricultural soils could be due to their presence of farmyard manure, fertilizer or treated sludge as well as wastewater effluent possibly used for irrigation. These heavy metals can accumulate in the soil and migrate into crops via plant-root respiration (Mussa \u003cem\u003eet al.\u003c/em\u003e, 2020).\u003c/p\u003e \u003cp\u003eIn general, the concentrations observed from the microwave and hotplate assisted digestion methods were comparable. These results suggest that even though the microwave is a widely used digestion method since it is a closed system process preventing loss of volatile analytes and sample contamination, the hotplate method can be used as a cheaper and accessible alternative (Sastre et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). The ultrasonic underestimated the concentrations which could be due to the temperature restriction of the ultrasonic bath causing low desorption and degradation of the sample matrix, ultimately resulting in incomplete digestion (Kazi \u003cem\u003eet al.\u003c/em\u003e, 2009).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAverage concentration (mg/kg) of metals in soil samples using the hotplate, ultrasonic and microwave assisted digestion methods (n\u0026thinsp;=\u0026thinsp;3), and maximum allowable levels (MRL)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"17\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMetal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCurry Post\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eCedara\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eGilboa Farm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e \u003cp\u003eRichmond\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c16\" namest=\"c14\"\u003e \u003cp\u003eUmgeni\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMRL mg/kg\u003c/p\u003e \u003cp\u003e(WHO, 2001)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e 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align=\"left\" colname=\"c2\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e 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\u003cp\u003e15.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e14.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e32.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e34.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003end\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e36.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e35.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"17\"\u003end \u0026ndash; not detected\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Contamination factor and geo-accumulation index\u003c/h2\u003e \u003cp\u003eThe contamination factor and pollution load indexes for each site were calculated and presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The contamination factors (CF) ranged from 0.41\u0026ndash;2.12. 0.82\u0026ndash;9.27 and 0.30\u0026ndash;2.27 for Cr, Cu and Ni respectively, whilst the geo-accumulation index ranged from \u0026minus;\u0026thinsp;1.30\u0026ndash;0.35, -0.61\u0026ndash;1.82 and \u0026minus;\u0026thinsp;1.61\u0026ndash;0.42 for Cr, Cu and Ni respectively. Based on CF values, the soil was contaminated with the studied heavy metals in the following order: Cu\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Ni\u0026thinsp;\u0026gt;\u0026thinsp;Co\u0026thinsp;\u0026gt;\u0026thinsp;Pb\u0026thinsp;\u0026gt;\u0026thinsp;Zn. In a study conducted by Muzerengi (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) on soil from the Limpopo Province, the CF value for Zn was also found to be the lowest where its presence can be derived predominantly due to natural processes or geogenic sources (Muzerengi, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe pollution load index and geo-accumulation index were found to be greater than 1 in Gilboa farm and Umgeni which resulted in environmental concerns due to heavy metal contamination. The PLI at Curry Post and Richmond was found to be less than 1 which revealed that the sites were free from heavy metals contamination with negative geo-accumulation indices (\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e \u003cem\u003e\u0026laquo; 0\u003c/em\u003e) which is categorized as grade zero indicating that the soil quality is practically uncontaminated.\u003c/p\u003e \u003cp\u003eThe CF values for Cr and Ni were greater than 2 at Curry post and Umgeni indicating moderate contamination since these studied metals exceeded their respective background concentrations. It was also observed than no heavy metals in all sampling locations exceeded an CF values greater than 20. The highest CF value was obtained for Cu (9.27) at Gilboa farm suggesting significant contamination. Pollution of Cu can be due to agricultural activities since Cu is used in fertilizers for crop production in the forms of copper sulphate and copper oxide (Alengebawy et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Potential ecological risk index (PERI)\u003c/h2\u003e \u003cp\u003eThe potential ecological risk index (\u003cem\u003ePERI)\u003c/em\u003e was calculated and presented in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. It reflected the general situation of pollution caused by the simultaneous presence of the six heavy metals. The RI values were classified in the slight risk level at Curry Post, Cedara and Richmond with (\u003cem\u003eRI\u0026thinsp;\u0026lt;\u0026thinsp;40\u003c/em\u003e), while at Gilboa Farm and Umgeni, the RI values were in the medium risk level with 40\u0026thinsp;\u0026le;\u0026thinsp;\u003cem\u003eRI\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;80. Soils contaminated by heavy metals can result in serious ecological risks and can negatively impact human health due to various forms of interaction (agriculture, livestock, etc.) where highly toxic heavy metals can enter via the food chain. Excessive accumulation of heavy metals in agricultural soils can affect the quality and safety of food and further increase the risk of serious diseases (cancer, kidney, liver damage, etc.), as well as impact the surrounding ecosystems (Santos-Franc\u0026eacute;s et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Although the pollution of metal was localized in a specific point, consideration of potential biological risks and steady monitoring are required.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEnrichment factor and geo-accumulation index for agricultural soil (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"17\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMetal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIndex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eCurry Post\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eCedara\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003eGilboa Farm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c14\" namest=\"c12\"\u003e \u003cp\u003eRichmond\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c17\" namest=\"c15\"\u003e \u003cp\u003eUmgeni\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-1.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-2.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e-1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCr\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e-1.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCu\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e9.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e6.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eNi\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e2.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e-0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePb\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-1.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e-1.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eZn\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eI\u003c/em\u003e\u003csub\u003e\u003cem\u003eGEO\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e-1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e-2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e-2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e-1.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePLI\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePotential ecological risk index for soil samples (n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"17\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMetal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIndex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eCurry Post\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eCedara\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003eGilboa Farm\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c14\" namest=\"c12\"\u003e \u003cp\u003eRichmond\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c17\" namest=\"c15\"\u003e \u003cp\u003eUmgeni\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cem\u003eMicro\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cem\u003eHP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c17\"\u003e \u003cp\u003e\u003cem\u003eUltra\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCo\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEC\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eE\u003c/em\u003e\u003csup\u003e\u003cem\u003eR\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e4.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCr\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEC\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eE\u003c/em\u003e\u003csup\u003e\u003cem\u003eR\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eCu\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEC\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e9.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e6.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e6.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eE\u003c/em\u003e\u003csup\u003e\u003cem\u003eR\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e46.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e34.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e34.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eNi\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEC\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e2.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eE\u003c/em\u003e\u003csup\u003e\u003cem\u003eR\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e9.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e4.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e4.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e10.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e5.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003ePb\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEC\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eE\u003c/em\u003e\u003csup\u003e\u003cem\u003eR\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eZn\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEC\u003c/em\u003e\u003csub\u003e\u003cem\u003ef\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eE\u003c/em\u003e\u003csup\u003e\u003cem\u003eR\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eRI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e35.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e35.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e15.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e36.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e38.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e11.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e39.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e65.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e42.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e21.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003e24.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e9.73\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003e53.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003e53.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c17\"\u003e \u003cp\u003e\u003cb\u003e24.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Metal correlation\u003c/h2\u003e \u003cp\u003eThe heavy metal correlation was assessed for the microwave method since it is seen as the most common and widely used digestion method as a representation of the metal concentrations observed at each soil sample. A relative correlation was expressed as a number from \u0026minus;\u0026thinsp;1 to +\u0026thinsp;1 with 1 indicating a strong positive and \u0026minus;\u0026thinsp;1 indicating a strong negative relation. Also, to observe these results more clearly and easier, a heating map was used to express correlation degree using red being close to +\u0026thinsp;1 and blue being close to -1 (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The correlation coefficients demonstrated that Zn displayed a synergistic (strongly positive) relationship with Co, Cu and Ni thus owing to the possibility of a common source of these metals. The highly correlated heavy metals may potentially originate from the same source, specifically the use of agrochemicals such as manure, inorganic fertilizers and pesticides (Mussa \u003cem\u003eet al.\u003c/em\u003e, 2020). The Cr displayed a strong negative (antagonistic) relationship with Co and Zn with R\u003csup\u003e2\u003c/sup\u003e values of -0.006 and \u0026minus;\u0026thinsp;0.015 respectively, which indicated that their concentrations are lower compared to Cr and potentially originated from natural sources.\u003c/p\u003e \n\u003cp\u003eTable 7: Heavy metal correlation in soil samples by statistical analysis using concentration from microwave digestion\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" width=\"617\" height=\"239\"\u003e\u003c/p\u003e\n \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Human health risk assessment\u003c/h2\u003e \u003cp\u003eFive heavy metals (Cr, Cu, Ni, Pb and Zn) were considered in the assessment of human health risk as a result of their toxicity. The estimations of non-carcinogenic and carcinogenic health risks for the studied heavy metals in agricultural soil were calculated for adults (18\u0026thinsp;+\u0026thinsp;years) and children (1\u0026ndash;17 years) through the three major exposure pathways (Tables\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and \u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe total hazard index (THI) values for adults and children were 1.63 and 8.69, respectively. Since the values were found to be greater than 1, it was deduced that people may experience non-carcinogenic effects however, children are more prone when compared to adults. The HQ values followed the following order for the studied heavy metals: Cr\u0026thinsp;\u0026gt;\u0026thinsp;Ni\u0026thinsp;\u0026gt;\u0026thinsp;Cu\u0026thinsp;\u0026gt;\u0026thinsp;Pb\u0026thinsp;\u0026gt;\u0026thinsp;Zn. Amongst the all the heavy metals, Cr in children had HQ values that exceeded 1. It was observed that the exposure pathways in both adults and children for the heavy metals decreased in the following order: dermal contact\u0026thinsp;\u0026gt;\u0026thinsp;soil ingestion\u0026thinsp;\u0026gt;\u0026thinsp;air inhalation. Dermal contact was the major exposure pathway in both adults and children where the contribution by dermal contact accounted for approximately 96.2% and 96.3% of their total hazard index respectively. Generally, children will experience higher non-carcinogenic risk when compared to adults hence, they are more prone to environmental contaminants. In a study conducted by Jiang et al., (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), a similar observation was made, and this was found the physiological and behavioural characteristics such as high respiration rates per unit body weight and hand-to-mouth activities of children resulted in higher non-carcinogenic risks.\u003c/p\u003e \u003cp\u003eThe carcinogenic risk was estimated for Cr, Ni and Pb since Cu and Zn are not considered as carcinogenic. Only two out of three pathways were considered since the slope factor for dermal contact was not available. The carcinogenic risk estimation of Ni and Pb was through only one pathway, inhalation and ingestion respectively. The total carcinogenic risk (TCR) values were 2.71E-05 and 3.54E-05 for adults and children respectively (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Soil ingestion was the major pathway between the two considered. As per Fryer et al., (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) study, the maximum tolerable risk of 1.00E-4 was higher than the calculated carcinogenic risks for both adults and children while children showed higher carcinogenic risks similarly to the non-carcinogenic trend. In the current study, the CR values for all examined heavy metals for both adults and children below the stipulated maximum tolerable risk in the range of 1.00E-6\u0026ndash;1.00E-4 thus posing no significant health effect. The human health risk evaluated and the calculated HQ and CR values for hotplate and ultrasonic assisted digestion are presented in Tables S4 \u0026ndash; S7. The trends were consistent with that observed using the microwave assisted digestion methods. Even though, no serious public health risk was identified in the study area, consistent estimation of human health risks is required.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimation of non-carcinogenic (Hazard quotient, HQ) from heavy metals in agricultural soil using microwave assisted digestion\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eAdults (Aged 18+)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003eChildren (Aged 1\u0026ndash;17)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy metal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSample locations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSoil ingestion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eDermal contact\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eAir inhalation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eTotal pathways\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eSoil ingestion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eDermal contact\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eAir inhalation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eTotal pathways\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCurry Post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.51E-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.30E-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.32E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.46E-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.20E-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.30E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9.61E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.38E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCedara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.30E-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.69E-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.00E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.83E-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.04E-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.97E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8.25E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.04E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGilboa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.18E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.33E-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.05E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.42E-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.44E-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.24E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.21E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.28E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRichmond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.74E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.21E-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.78E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.29E-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.20E-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.18E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.93E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.22E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUmgeni\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10E-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.15E-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.81E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.27E-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.00E-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.68E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.03E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.74E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCurry Post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.56E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.86E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.05E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.39E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.59E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.65E-03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCedara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.27E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.31E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.70E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.23E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.30E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.46E-03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGilboa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.83E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.38E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.37E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.54E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.87E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.83E-03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRichmond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.54E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.94E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.83E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.39E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.57E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.96E-04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUmgeni\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.46E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.58E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.12E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.88E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.51E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.23E-03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCurry Post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.10E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.43E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.75E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.82E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.14E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.37E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.83E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.41E-03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCedara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.14E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.62E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.10E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.21E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.70E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.53E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.23E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.10E-03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGilboa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.79E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.88E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.64E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.74E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.51E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.14E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.76E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.86E-03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRichmond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.84E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.89E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.41E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.47E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.07E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.48E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.23E-03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUmgeni\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.95E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.04E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.47E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.64E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.69E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.57E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.67E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.31E-03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCurry Post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCedara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGilboa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRichmond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.44E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.25E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.37E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.32E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.94E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.81E-03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUmgeni\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCurry Post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.30E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.70E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.67E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.05E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.98E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.03E-05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCedara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.37E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.90E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.76E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.44E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.08E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9.52E-05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGilboa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.90E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.41E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.44E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.03E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.89E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.32E-04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRichmond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.13E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.60E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.17E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.96E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.39E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.35E-05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUmgeni\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.72E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.78E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.02E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.66E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.59E-04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal metals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.81E-02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.57E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.59E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.63E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.16E-01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.37E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.70E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8.69E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimation of carcinogenic (CR) from heavy metals in agricultural soil using microwave assisted digestion\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eAdults (Aged 18+)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c10\" namest=\"c7\"\u003e \u003cp\u003eChildren (Aged 1\u0026ndash;17)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy metal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSample locations\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSoil ingestion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eDermal contact\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eAir inhalation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eTotal pathways\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eSoil ingestion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eDermal contact\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eAir inhalation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eTotal pathways\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eCr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCurry Post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7,10E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,51E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,45E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9,63E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e9,05E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9,72E-06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCedara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,09E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,01E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,39E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8,27E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7,76E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8,35E-06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGilboa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,84E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,90E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,03E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,22E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4,90E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5,27E-06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRichmond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,64E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,80E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,82E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4,94E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4,64E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4,99E-06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUmgeni\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,19E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,56E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,45E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7,04E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6,61E-08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7,11E-06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCurry Post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,35E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,35E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1,64E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1,64E-10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCedara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9,48E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,48E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2,44E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2,44E-10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGilboa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,42E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8,42E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2,17E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2,17E-10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRichmond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,57E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5,57E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1,44E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1,44E-10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUmgeni\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,50E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,50E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3,86E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3,86E-10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ePb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCurry Post\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0,00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCedara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0,00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGilboa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0,00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRichmond\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,27E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,27E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,08E-09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3,08E-09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUmgeni\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0,00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0,00E\u0026thinsp;+\u0026thinsp;00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal metals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,59E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,28E-06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,71E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3,51E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3,31E-07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3,54E-05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eThe hotplate, ultrasonic and microwave assisted methods followed by ICP-OES were applied for metal determination in agricultural soil samples from different areas of KwaZulu-Natal. The percentage recoveries were all within the acceptable range of 70\u0026ndash;120% indicating good accuracy for all methods. The metal concentrations decreased in the following order: Ga\u0026thinsp;\u0026gt;\u0026thinsp;Cr\u0026thinsp;\u0026gt;\u0026thinsp;Ba\u0026thinsp;\u0026gt;\u0026thinsp;Cu\u0026thinsp;\u0026gt;\u0026thinsp;Ni\u0026thinsp;\u0026gt;\u0026thinsp;Zn\u0026thinsp;\u0026gt;\u0026thinsp;Sr\u0026thinsp;\u0026gt;\u0026thinsp;Co\u0026thinsp;\u0026gt;\u0026thinsp;Pb\u0026thinsp;\u0026gt;\u0026thinsp;Li. The Ba and Cr were the two most abundant metals in all samples while Cd was undetected in all samples. The Co, Ni, Pb and Zn were found to be below whilst Cr and Zn were above their respective permissible limits in all soil samples. Umgeni soil was found to be the most polluted since most metals had higher concentrations than other sampling locations. Microwave and hotplate assisted digestion revealed similar metal concentrations while ultrasonic assisted digestion underestimated the concentrations. Despite the hotplate method being an open system method, it proved to be the most suitable substitute for microwave assisted digestion compared to the ultrasonic method. This is due to convenience, accessibility and being a cost-effective method, which does not require expensive instrumentation as opposed to the microwave method. Umgeni and Gilboa Farm were the two most contaminated sites as per the calculated contamination factor, pollution load, geo-accumulation, and potential ecological risk indices.\u003c/p\u003e \u003cp\u003eThe metal correlation revealed that Zn along with Co, Cu and Ni can possibly originate from the same source due to their synergistic relationship. The human health risk assessment revealed that the exposure pathways for non-carcinogenic risk decreased in the following order: dermal contact\u0026thinsp;\u0026gt;\u0026thinsp;soil ingestion\u0026thinsp;\u0026gt;\u0026thinsp;air inhalation. Conclusively, it was observed that children experienced higher non-carcinogenic risk as opposed to adults since the THQ values were greater than 1. The CR values were below the maximum tolerable limit range of 1.00E-6\u0026ndash;1.00E-4, presenting no serious health risk. Although, heavy metal contamination was not severe at the selected sampling locations, the need for continuous assessment is required since these soils are used for agricultural activity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eDiscloser Statement\u003c/h2\u003e \u003cp\u003eThe authors declare that there are no competing interests to declare. There are also no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was sponsored by the National Research Foundation (NRF) of South Africa under Thuthuka Research Grant (Grant number: 121869).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003ePrecious Mahlambi, Mphilisi Mahlambi and Kavisha Naicker conceptualized and formulated the research study.Kavisha Naicker and Precious Mahlambi developed the method of sampling and analyses of the samples. Kavisha Naicker did the formal analysis and investigation of the research problem. Kavisha Naicker wrote the main manuscript including all figures, diagrams and statistical analysis.Precious Mahlambi and Mphilisi Mahlambi reviewed and edited the manuscript. Precious Mahlambi acquired funding for the project.Precious Mahlambi and Mphilisi Mahlambi supervised the project.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors would like to thank the University of KwaZulu Natal for providing facilities to carry out this research work.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eAll data produced from this work has been included in the paper or presented as supplementary document.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlengebawy, A., Abdelkhalek, S., Qureshi, S., \u0026amp; Wang, M. (2021). Heavy Metals and Pesticides Toxicity in Agricultural Soil and Plants: Ecological Risks and Human Health Implications. \u003cem\u003eToxics, 9, \u003c/em\u003e1-33. https://doi.org/10.3390/toxics/9030042 \u003c/li\u003e\n\u003cli\u003eChoi, J., \u0026amp; Jeon, S. (2018). A Geo-statistical Assessment of Heavy Metal Pollution n the Soil Around a Ship Building Yard in Busan, Korea. \u003cem\u003eJournal of the Korean Society of Marine and Environmental Safety, 24\u003c/em\u003e, 907-915. https://doi.org/10.7837/kosomes.2018.24.7.907 \u003c/li\u003e\n\u003cli\u003eFryer, M., Collins, C., Ferrier, H., Colvile, R., \u0026amp; Nieuwenhuijsen, M. (2006). Human exposure modelling for chemical risk assessment: a review of current approach and research and policy impications. \u003cem\u003eEnvironmental Science and Policy, 9,\u003c/em\u003e 261-274. https://10.1016/j.envsci.2005.11.011\u003c/li\u003e\n\u003cli\u003eHerselman, J., Steyn, C., \u0026amp; Fey, M. (2005). Baseline concentration of Cd, Co, Cr, Cu, Pb, Ni and Zn in surface soils of South Africa. \u003cem\u003eSouth African Journal of Science, 10,\u003c/em\u003e 509-512. https://hdl.handle.net/10019.1/9660\u003c/li\u003e\n\u003cli\u003eJiang, Y., Chao, S., Liu, J., Yang, Y., Chen, Y., Zhang, A., \u0026amp; Cao, H. (2016). Source apportionment and health risk assessment of heavy metals in soil for a township in Jiangsu Province, China. \u003cem\u003eChemosphere 168,\u003c/em\u003e 1658-1668. https://dx.doi.org/10.1016/j.chemosphere/2016/11.088 \u003c/li\u003e\n\u003cli\u003eJiang, Y., Zeng, X., Fan, X., Chao, S., Zhu, M., Cao, H. (2015). Levels of arsenic pollution in daily foodstuffs and soils and its associated human health risk in a town in Jiangsu Province, China. \u003cem\u003eEcotoxicology and Environmental Safety, 122,\u003c/em\u003e 198-204. https://dx.doi.org/10.1016/j.ecoenv\u003c/li\u003e\n\u003cli\u003eKazi. T.. Jamali. M.. Arian. M.. Afridi. J. N.. Sarfraz. R.. \u0026amp; Ansari. R. (2008). Evaluation of an ultrasonic acid digestion procedure for total heavy metals. \u003cem\u003eJournal of Hazardous Materials, 161,\u003c/em\u003e 1391-1398. https://dx.doi.org/10.1016/j.jhazmat.2008.04.103 \u003c/li\u003e\n\u003cli\u003eLiu, Y., Shaheen, S., Rinklebe, J., \u0026amp; Hseu, Z. (2021). Pedogeochemical distribution of gallium, indium and thallium, their potential availability and associated risk in highly-weathered soil profiles of Taiwan. \u003cem\u003eEnvironmental Research, 197\u003c/em\u003e, 110994. https://doi.org/10.1016/j.envres.2021.110994 \u003c/li\u003e\n\u003cli\u003eMussa, C., Biswick, T., Changadeya, W., Mapoma, H., \u0026amp; Junginger, A. (2010). Occurrence and ecological risk assessment of heavy metals in agricultural soils of Lake Chilwa catchment in Malawi, Southern Africa. \u003cem\u003eSN Applied Sciences, 2,\u003c/em\u003e 1-8. https://doi.org/10.1007/s42452-020-03718-7 \u003c/li\u003e\n\u003cli\u003eMuzerengi, C. 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The handbook of trace elements. \u003cem\u003eBoca Raton: St Lucie Press.\u003c/em\u003e\u003cem\u003e \u003c/em\u003e\u003cem\u003e27,\u003c/em\u003e 223. https://doi.org/10.2134/jeq1998.00472425002700040041\u003c/li\u003e\n\u003cli\u003ePoledniok, J., Kita, A., \u0026amp; Zerzucha, P. (2012). Spectrophotometric and Inductively Coupled Plasma\u0026ndash;Optical Emission Spectroscopy Determination of Gallium in Natural Soils and Soils Polluted by Industry: Relationships between Elements. \u003cem\u003eCommuninications in Soil Science and Plant Analysis, 43,\u003c/em\u003e 1121-1135. https://doi.org/10.1080/2012/662561 \u003c/li\u003e\n\u003cli\u003eSantos-Franc\u0026eacute;s, F., Mart\u0026iacute;nez-Gra\u0026ntilde;a, A., Rojo, P., \u0026amp; S\u0026aacute;nchez, A. (2017). Geochemical Background and Baseline Values Determination and Spatial Distribution of Heavy Metal Pollution in Soils of the Andes Mountain Range (Cajamarca-Huancavelica, Peru). \u003cem\u003eInternational Journal of Environmental Research and Public Health, 14,\u003c/em\u003e 1-22. https://doi.org/10.3390/ijerph14080859\u003c/li\u003e\n\u003cli\u003eSastre, J., Sahuquillo, A., Vidal, M., \u0026amp; Rauret, G. (2002). Determination of Cd. Cu. Pb and Zn in environmental samples: microwave-assisted total digestion versus aqua regia and nitric acid extraction. \u003cem\u003eAnalytica Chimica Acta, 462,\u003c/em\u003e 59-72 https://doi.org/10.1016/S0003-2670(02)00307-0\u003c/li\u003e\n\u003cli\u003eWorld Health Organization (WHO). (2001). Geneva: World Health Organization. http://www.inchem.org/documents/ehc/ehc221.htm (accessed 9 October 2021).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Agricultural soil, heavy metals, digestion, human health risk","lastPublishedDoi":"10.21203/rs.3.rs-4001090/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4001090/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study presents the comparison of microwave assisted, hotplate and ultrasonic digestion methods for the analysis of metals in agricultural soils prior to ICP-OES determination. The percentage recoveries for all methods were within the acceptable range of 70\u0026ndash;120% indicating that they can all be used for accurate determination of the target metals. However, hotplate can be recommended as it does not use too high pressure and temperature which can degrade analytes and it is easily accessible. On the hand, microwave require expensive instrument and thus its accessibility may be limited in other laboratories while ultrasonic is susceptible to underestimation of sample concentration due to incomplete digestion especially for complex samples as it uses lower temperatures. The metal concentrations obtained ranged from 0.60\u0026ndash;256.4 mg/kg, however, all the metals were below the maximum permissible limits in soil except for Cr. The contamination factor and geo-accumulation index showed that the soil samples were mainly contaminated with Cu. The human health risk assessed indicated that dermal contact was the major exposure pathway in adults and children and children were more susceptible to non-carcinogenic risks. Although metal contamination in this study was not severe, consideration and monitoring of potential pollution hazards and human health risks in the future around these agricultural soils are required.\u003c/p\u003e","manuscriptTitle":"Comparison of ultrasonic, hotplate and microwave assisted digestion methods for the assessment of metals in agricultural soil: Environmental contamination and human health risk","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-01 15:28:53","doi":"10.21203/rs.3.rs-4001090/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9f980c17-1923-42fb-8e49-cc4cfba5ad4c","owner":[],"postedDate":"April 1st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-21T15:23:36+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-01 15:28:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4001090","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4001090","identity":"rs-4001090","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}